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District-level Assessment of the Ecohydrological Resilience to Hydroclimatic Disturbances and its Controlling Factors in India
Abstract
The carbon and water cycles play an important role in ecosystem functioning and are linked to each other through different physical and biological processes. The hydroclimatic disturbances such as droughts affect both hydrological as well as the ecological processes. Increasing hydroclimatic disturbances under climate change will adversely affect the ecohydrological processes and hence, the assessment of the ecohydrological resilience and its controlling factors is important for the sustainability of the ecosystems. In this study, an assessment of the resilience of terrestrial ecosystems in India to hydroclimatic disturbances was carried out at the district (i.e. administrative division) scale. Ecosystem water use efficiency (WUEe), defined as the ratio of net primary productivity (NPP) to evapotranspiration, was used as an indicator of ecosystem functioning or its response to hydroclimatic disturbances. We found a large spatial variation in WUEe in India at district scale, which was significantly higher in lower Himalayan regions compared to rest of the country. Increasing trend in WUEe was found for central parts of the country. The resilience was measured in terms of the ratio of the WUEe under the dry conditions and the mean WUEe, which indicates the ability to absorb hydroclimatic disturbance. Out of 634 districts considered for this study, only 241 (38%) districts were found resilient to dry conditions, whereas a significant reduction in WUEe was observed for some of the districts. The resilience at district scale indicates the cross-biomes response of ecosystems. In general, the forest dominated districts had higher resilience compared to districts dominated by other biome types. Also, districts having temperate climate were found having higher resilience. Out of 30 states and union territories (UTs) only 10 states had more 50% resilient area. The results of this study highlight the need for better ecosystem management policies in the country.
... Quantifying changes in EHIs helps accurately assess the ecosystem behavior and responses to disturbances (Wei et al., 2019). WUE e is a primary and widely used EHI for assessing the TE response to hydroclimatic alterations (Sharma and Goyal, 2018;Yang et al., 2016). It quantifies the amount of carbon assimilated as biomass per unit amount of water utilized by TE (El Masri et al., 2019). ...
... Kundu et al. (2017) used NDVI based RUE e index for monitoring vegetation degradation in Rajasthan and found that 35% of the total area has been highly degraded. Sharma and Goyal (2018) examined the ecosystem resilience to hydroclimatic disturbances using WUE e as an indicator and found that most regions are not resilient to climate disturbances. Peddinti et al. (2020) quantified patterns of WUE e and its drivers in citrus orchids of central India using the eddy covariance (EC) technique and Landsat images. ...
... Where NPP is the net primary productivity (g C/m 2 ), and ET is evapotranspiration (mm). This formula is used for WUE e, assuming that ET is a water loss of an ecosystem, and it has been used extensively in previous studies (Sharma and Goyal, 2018;Zhang et al., 2016). ...
The carbon, water, and energy cycles play an important role in the terrestrial ecosystem's functioning. Climate change and hydroclimatic disturbances are primary factors that influence these cycles, yet little is known about the major ecohydrological indicators (EHIs) that characterize these cycles. In addition, it is essential to analyze spatiotemporal variations and driving factors of EHIs to comprehend how well terrestrial ecosystems can preserve their structure and function in the face of hydroclimatic perturbations. We assessed the three important EHIs, namely water use efficiency (WUEe), rain use efficiency (RUEe), and light use efficiency (LUEe), as well as their controlling factors, in India from 2002 to 2017 at various spatial scales (major river basins, climatic zones, and land cover types). In general, high EHI values were found in high productivity ecosystems (e.g., forest ecosystems) compared to low productivity ecosystems (e.g., cropland and grassland ecosystems). WUEe and LUEe have similar characteristics and were higher in mountain, tropical wet, and tropical wet-dry zones, whereas lower in arid zones. RUEe shows distinct spatial characteristics with higher values in semi-arid zones and lower values in arid zones. The drivers investigated in this study include CO2 concentrations, evapotranspiration (ET), humidity, leaf area index (LAI), normalized difference vegetation index (NDVI), precipitation (PRECIP), soil moisture (SM), solar radiation (SR), temperature (TEMP), vapor pressure deficit (VPD), and wind speed (WS). All three EHIs were found sensitive to TEMP and SR at a national scale, whereas CO2 was a significant driver in arid ecosystems. Other controlling factors (e.g., VPD, SM, and humidity) also played a significant role at smaller spatial scales. Further, this study finds that undisturbed ecosystems (only climate influenced) have slightly higher values of EHIs compared to disturbed (climate-human influenced) ecosystems. Based on the results, in future, it can be expected that an increase in the incident SR and TEMP will decrease the EHIs in India. This study helps understand the coupling of water, carbon, and energy cycles, and the findings from this research can be a reference for ecosystem conservation and restoration.
... Terrestrial net primary productivity (NPP), defined as the net photosynthetic accumulation of carbon, plays a vital role in the energy and carbon cycles at global and ecosystem scales (Jinguo et al., 2006). It is one of the most extensively used indicators of ecosystem carbon uptake and other ecosystem services such as food production, fuel, and timber products (Hao et al., 2016;Huang et al., 2017;Sharma and Goyal, 2018). Climate change, soil geochemical properties, ecosystem attributes, and human activities are the primary factors influencing NPP (Yuan et al., 2021a). ...
... In India, few attempts have been made to assess terrestrial ecosystems productivity (Bala et al., 2013;Banger et al., 2015;Bish and Bhatt, 2011;Gholkar et al., 2014;Jha et al., 2019a;Nayak et al., 2015Nayak et al., , 2013Sharma and Goyal, 2018). Bala et al. (2013) analyzed the spatiotemporal trend and controlling factors of NPP modeled using Advanced Very High-Resolution Radiometer (AVHRR) data. ...
... The estimated NEP has undergone substantial inter-annual variations due to climate variability. Sharma and Goyal (2018) assessed the resilience of terrestrial ecosystems to droughts in India using ecosystem water use efficiency (WUE e ) as an indicator. The study shows that forest-dominated districts had higher resilience when compared to other ecosystems. ...
Climate change and anthropogenic activities have altered the terrestrial ecosystem dynamics around the globe. Due to the complex ecosystem-atmosphere interactions at different scales, these impacts are difficult to quantify and are poorly understood, especially in developing countries with limited ground-based observations. This study analyzed the impact of climatic changes and anthropogenic activities on ecosystem net primary productivity (NPP) in India using remote sensing-based observations, correlation analysis, and Residual Trend analysis (RESTREND). Using different climate variables such as precipitation, temperature, and solar radiation, along with Land Use and Land Cover (LULC) and NPP maps, we first classified the ecosystems (ES) into two categories: natural ecosystems – influenced only by climate change (ESc), covering about 19.7% of the area, and human-influenced ecosystems – influenced by both climate change and anthropogenic activities (ESc+a), covering about 80.3% of the area. RESTREND analysis was performed on both ESc and ESc+a to analyze the relative contributions of climate change and human activities to changes in NPP. The correlation analysis between NPP and climate variables suggested that precipitation was the dominant control of NPP in about 72% area, whereas temperature and solar radiation controlled NPP in Himalayan and forest-dominated regions, respectively. The human-influenced ecosystems (ESc+a) experienced an increasing trend in NPP, whereas natural ecosystems (ESc) experienced a decreasing trend, particularly in forest-dominated regions. Overall, NPP increased in the country during the study duration. The contributions of climatic changes and anthropogenic activities varied spatially and temporally. In general, climatic factors enhanced the NPP, whereas human activities contributed to a slight decline in NPP. These findings improve our understanding of how ecosystems in India are influenced by climate change and anthropogenic activities in recent decades. The results from this study will aid in identifying ecological hotspots and key drivers for better ecosystem management strategies.
... Also, the magnitude of the precipitation varies in the spatio-temporal domains. In extreme precipitation conditions, these changes may cause droughts and floods (Goyal and Sharma, 2017;Gupta and Jain, 2018;Sharma and Goyal, 2018). The assessment of precipitation extremes is necessary to mitigate ill effects of such disastrous conditions. ...
... Climate change has shown strongest negative impacts on the India's water resource systems, especially in last two or three decades (Jain, 2019). Many regions in India have been confronted with severe extreme events such as droughts and floods (Gupta and Jain, 2018;Sharma and Goyal, 2018;. Several studies utilizing global climate models (GCMs) have shown that the magnitude of precipitation extremes will be enhanced in the 21st century (Mishra et al., 2019;Singh and Goyal, 2016;IPCC, Palazzi et al., 2014). ...
... Several studies utilizing global climate models (GCMs) have shown that the magnitude of precipitation extremes will be enhanced in the 21st century (Mishra et al., 2019;Singh and Goyal, 2016;IPCC, Palazzi et al., 2014). In the recent past, Indian Himalayan regions faced several cloud-burst and flash flood events (Mishra et al., 2019), whereas extreme high-intensity precipitation events had occurred in different parts of India (Gupta and Jain, 2018;Sharma and Goyal, 2018;Gupta and Jain, 2019). A major challenge associated with flash floods and cloudburst events is the forecasting and accurate prediction of these extreme events, which require a real-time highresolution precipitation dataset and that is limited especially in Himalayan regions (Koutsouris et al., 2016;Xiaosheng, 2019a, 2019b). ...
The availability of global satellite‐based precipitation datasets provides an asset to accomplish precipitation dependent analysis where gauge based precipitation datasets are not available or limited. In this study, we have taken three most popular and globally accepted satellite‐based daily gridded (0.25°×0.25°) precipitation datasets such as Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Satellite Soil Moisture to Rain (SM2RAIN‐ASCAT) and Tropical Rainfall Measuring Mission (TRMM now available as Global Precipitation Measurement (GPM)) for ten (10) years (2007‐2016) time‐series durations to test their reliability across India. The India Meteorological Department (IMD) observed daily gridded (0.25°×0.25°) precipitation data have been taken as reference data to compare the other three satellite‐based gridded precipitation datasets by developing standard extreme precipitation indices (SEPIs). The precipitation extremity has been tested in the wet season (June‐July‐August‐September) and throughout the year. We have also analyzed the extreme behavior of precipitation (in both upper and lower tails) using Quantile‐Quantile (Q‐Q) regression analysis after selecting 33 random precipitation grids across India. The overall analysis results showed that all satellite‐based datasets have significant spatial heterogeneity in estimating precipitation extremes accurately which varies across India. Among all satellite‐precipitation datasets, TRMM found closer to IMD than SM2RAIN‐ASCAT and CHIRPS. The frequency based SEPIs showed that CHIRPS, TRMM and SM2RAIN‐ASCAT have similarities to IMD precipitations. The intensity‐based SEPIs show that TRMM and CHIRPS have significant similarities with IMD precipitations. The wet season‐based analysis results showed that TRMM and CHIRPS are closer to IMD precipitations than SM2RAIN‐ASCAT satellite‐precipitations. Overall TRMM and CHIRPS datasets performed well across most regions in India, while SM2RAIN‐ASCAT dataset has performed poorly in India, especially for extreme precipitation cases. Q‐Q plots show that each satellite‐based precipitation dataset captured most of extreme cases in different quantile intervals with respect to IMD precipitation; however, SM2RAIN‐ASCAT has slightly under‐performed at many regions in India.
... WUE e depends on biotic factors (e.g., types of vegetation and leaf area index (LAI)) as well as abiotic factors (e.g., air temperature and precipitation) (Tong et al. 2014;Liu et al. 2015). It has been reported that energy-limited humid regions have higher WUE e than water-limited arid and semi-arid regions (Sharma and Goyal 2018;Zhao et al. 2020). This can be due to the lower availability of water in arid zones for the process of photosynthesis (Kim et al. 2021). ...
... The estimation of WUE e at a regional or global scales can be achieved using remote sensing datasets (Xia et al. 2015). Many studies have reported the spatial and temporal variations in WUE e over regional and global scales (Tang et al. 2014;Sharma and Goyal 2018;Zhao et al. 2020;Tesfaye et al. 2021). For example, the global distribution of WUE e was investigated by Tang et al. (2014) using ground-based eddy covariance (EC) measurements of GPP and remote sensing data, and they found higher WUE e in the forest ecosystem. ...
Ecosystem water use efficiency (WUEe), defined as the amount of carbon biomass produced to water loss, is an important ecohydrological index characterizing the relationship between the carbon and water cycles. Understanding the WUEe dynamics and its controlling factors is essential for ecosystem management and restoration. This study analyzed spatiotemporal variations and controlling factors of WUEe over major basins, climate zones, and land covers in India during 2002–2015 using remote sensing-based datasets. A substantial spatial variation in WUEe was observed in India across different spatial scales. WUEe was high in shrubland ecosystems, followed by forest, cropland, and grassland ecosystems. The country-average WUEe showed a significant increasing trend over the study duration. Eleven biotic and abiotic controlling factors were analyzed in this study, namely, CO2 concentration, evapotranspiration (ET), humidity, leaf area index (LAI), normalized difference vegetation index (NDVI), precipitation, soil moisture, solar radiation, temperature, vapor pressure deficit (VPD), and wind speed. Among these factors, solar radiation, CO2 concentration, and temperature were found most sensitive factors to WUEe at the country scale. Other factors, such as NDVI, soil moisture, and humidity play a significant role at local scales in some regions. The inland drains in Rajasthan and west-flowing rivers from Kutch to Saurashtra were found most sensitive to controlling factors than other basins. These findings provide important insights into ecosystem functioning and water use patterns across different scales in India and will be helpful for water resources and ecosystem management.
... In 2018, the Government of India has formulated Hydro-meteorological Data Dissemination Policy in 2018 which is to be implemented by Central Warehousing Corporation (CWC) and Central Ground Water Board (CGWB), the Ministry of Jal Shakti (Sharma and Goyal 2018). This policy supersedes previous related orders or guidelines of the Ministry of Water Resources, River Development and Ganga 24 S. Baidya and A. K. Gupta ...
... From late 1980s, the idea of sustainable development became the most important idea in the filed Standardization (ISO) issued its first standard protocol. Environmental Impact Assessment & Ecolabeling are other important steps towards saving the nature(Sharma and Goyal 2018;Shivam and Sarma 2017). The United Nations (UN) has provided platform, for all kinds of International Negotiations and agreement on the environmental issues and policy making. ...
Policies are the way of bringing change in the system and regulating the behaviour of the allied stakeholders. The idea of policies dates back to the ancient ages of Harappa Civilization 4500 years back. Since then numerous policies have been prepared for saving the nature and environment. United Nations (UN) has taken important roles in environment and climate change related policy intervention, starting from creating awareness to implementing strict laws within the countries. In India, keeping pace with Paris Agreement, several environmental policies have been prepared and implemented, but being a developing country, India is facing challenges in implementing the Nationally Determined Contributions due to economic shortfall. Mobilization of International finance is in need to implement many of India’s targeted Green Policies. India has numerous policies and guidelines to safeguard the natural setting and the environment but proper implementation is needed.
... The eWUE trend result was aggregated into different land cover types (CCI-LC) and Agroecological zones of the area of interest. Finally, the ecosystem resilience to drought was calculated using the dimensionless ecosystem resilience index (eRd) from the ratio of mean values of multi-annual eWUE to the annual eWUE of the driest year as initially defined by Sharma and Goyal [43] and further applied in other studies [44,45]. The driest year (2009) of high drought severity in the Horn of Africa was identified from the spatial and temporal patterns of the high-resolution annual SPEI images, this was also checked and matched with the EM-DAT record of drought [46]. ...
... The observed increasing trend of eWUE in the grassland might be attributed to the growing intensity and fluctuations of precipitation, water stress and drought conditions. Several studies indicated that different vegetation types tend to increase in eWUE due to water stress conditions [45,50]. ...
Understanding the response of vegetation and ecosystem resilience to climate variability and drought conditions is essential for ecosystem planning and management. In this study, we assessed the vegetation changes and ecosystem resilience in the Horn of Africa (HOA) since 2000 and detected their drivers based mainly on analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS) products. We found that the annual and seasonal trends of NDVI (Normalized Difference Vegetation Index) generally increased during the last two decades over the Horn of Africa particularly in western parts of Ethiopia and Kenya. The weakest annual and seasonal NDVI trends were observed over the grassland cover and tropical arid agroecological zones. The NDVI variation negatively correlated with Land Surface Temperature (LST) and positively correlated with precipitation at a significant level (p < 0.05) account for 683,197 km2 and 533,385 km2 area, respectively. The ecosystem Water Use Efficiency (eWUE) showed overall increasing trends with larger values for the grassland biome. The precipitation had the most significant effect on eWUE variation compared to LST and annual SPEI (Standardized Evapotranspiration Index). There were about 54.9% of HOA resilient to drought disturbance, whereas 32.6% was completely not-resilient. The ecosystems in the humid agroecological zones, the cropland, and wetland were slightly not-resilient to severe drought conditions in the region. This study provides useful information for policy makers regarding ecosystem and dryland management in the context of climate change at both national and regional levels.
... More than 500 million people live in these drought-prone areas globally (Sheffield et al. 2004;Rathore 2004;Wilhite 2000). Indian economy too is periodically affected by drought as well, because 60% of it is sustained by the agricultural sector (Jha et al. 2019;Sharma and Goyal 2018). According to West Bengal too, a heavily dependent agrarian state faces major weather anomalies which includes delayed monsoons and prolonged breaks in monsoon resulting in drought-like situations. ...
... In the drought year 2008, Paschim/West and Purba/ East Medinipur districts were highly affected. Works by Bera and Bandyopadhyay (2017) and Sharma and Goyal (2018) also are supportive evidences of drought occurrences during these years. ...
This volume uses an innovative and interdisciplinary approach to assess various issues resulting from human-environment interactions in relation to sustainable development. The book encompasses theoretical and applied aspects, using both thematic and regional case studies from India, to highlight the impact of human-environment interactions at various spatio-temporal scales, with each study focusing on a particular anthropogenic issue, particularly in an Indian context. The book's three focal themes (e.g. habitat linkages, ekistics and social ecology, hazard and environmental management) elaborate the essential components of human-environment interactions with nature, its impact on the surrounding natural and social environments, and management techniques through research innovations. Readers will learn how maladjustments, disturbances and disasters are often inevitable byproducts of human-environment systems, and what conceptual and practical strategies can be applied towards sustainable coexistence. The book will be of interest to students, academics and policymakers engaged in environmental management, human-environment interactions and sustainable development.
... Indian economy too is periodically affected by drought as well, because 60% of it is sustained by the agricultural sector (Jha et al. 2019;Sharma and Goyal 2018). According to Chatterjee et al. 2016 West Bengal too, a heavily dependent agrarian state faces major weather anomalies which includes delayed monsoons and prolonged breaks in monsoon resulting in drought-like situations. ...
... In the drought year 2008, Paschim/West and Purba/ East Medinipur districts were highly affected. Works by Bera and Bandyopadhyay (2017) and Sharma and Goyal (2018) also are supportive evidences of drought occurrences during these years. ...
Climate variability has severe consequences on agricultural productivity. Studies related to drought monitoring using point data has not been widely successful. Remote sensing and GIS has proved to be a better alternative toward fast, accurate, and repetitive appraisal. This study focuses on the application of remote sensing and GIS for monitoring the spatiotemporal extent of agricultural drought over West Bengal, especially its western districts. Over the years, a large number of band rationing techniques and indices have evolved for assessment of crop condition, of which VCI (vegetation condition index) derived from NOAA-STAR has been used for this particular study. This vegetation index values were then compared with CHIRPS rainfall data based RAI (rainfall anomaly index) to identify impact of deficit rainfall on vegetation condition. This provided a better understanding for identifying the drought. Yield anomaly index (YAI) were also computed with the help of crop production data collected from district statistical handbooks in order to estimate the reduction in crop production as a result of drought. Using these indices, it was evident that during the study period of 1997–2017, the years 2000–2001 and 2010–2011 had experienced severe drought.
... More than 500 million people live in these drought-prone areas globally (Sheffield et al. 2004;Rathore 2004;Wilhite 2000). Indian economy too is periodically affected by drought as well, because 60% of it is sustained by the agricultural sector (Jha et al. 2019;Sharma and Goyal 2018). According to West Bengal too, a heavily dependent agrarian state faces major weather anomalies which includes delayed monsoons and prolonged breaks in monsoon resulting in drought-like situations. ...
... In the drought year 2008, Paschim/West and Purba/ East Medinipur districts were highly affected. Works by Bera and Bandyopadhyay (2017) and Sharma and Goyal (2018) also are supportive evidences of drought occurrences during these years. ...
The contemporary issues of environmental degradation, population growth, human settlements and growing need for livelihood security pose ever increasing risks and vulnerability to human development. The chapter intends to focus on such major themes to include: (a) habitat and environmental issues of human concerns, (b) ekistics and ecology of social environment and (c) hazards and environmental management for sustainable development. Management of environment, food security and poverty alleviation are the primary factors contributing to the complexity of natural resource management, which is very important for achieving sustainable development goals. The rural poor depend on agriculture or are otherwise dependent on natural resources for their basic life support systems. The livelihood and well-being of rural and urban people depend fundamentally on the opportunities available to them, and these opportunities are shaped substantially by their access to resources, which in turn depends on numerous underlying political, social and macro-economic factors, those are transforming with the current trends of globalization, migration, market integration, democratization and decentralization.
... Several models assess different climate change scenarios through outputs from general circulation models (GCMs). There is a need for different statistical methods and machine learning algorithms to increase the efficacy of GCMs estimates at a regional scale for various extreme events (Das and Umamahesh 2021;Sharma and Goyal 2018;Murari and Ghosh 2019). The studies for future variability of the events show the increase in frequency, severity, and longer duration across different world regions, including the Indian region, by 2100 (Cowan et al. 2014;Murari and Ghosh 2019). ...
Climate change and global warming surge the frequency and severity of extreme weather events like heatwaves, cyclones, floods, etc. This study assesses future heatwave events in four Indian cities, i.e., Srinagar, Jaipur, Guwahati, and Visakhapatnam. It uses CMIP 6 projections with four SSP scenarios, i.e., SSP 126, 245, 370, and 585. The yearly value of the heatwave magnitude index is used to classify the events in cities. The forthcoming forecast is distributed into three identical periods of 27 years each, i.e., near- (2020–2046), mid- (2047–2073), and long-term periods (2074–2100). The outcomes from the study showed that heatwave events would increase across the cities for all periods under SSP 370 and 585 scenarios. It is computed that 104 extreme events are probable to be observed across these four cities. This study highlights the importance of adaptive techniques in dealing with the negative implications of predicted heatwave weather events.
... Daily precipitation data are obtained from India Meteorological Department (IMD) 20 for the period from 1988 to 2011 at high spatial resolution (0.25° × 0.25°). This dataset incurs the ability to capture the spatial pattern of extreme and annual precipitation across India, and has been widely utilized in recent literature 35,61 . And, daily observed discharge data of 54 catchments are taken from India-WRIS (Water Resources Information System) portal (http:// www. ...
Climate change significantly impacts the global hydrological cycle, leading to pronounced shifts in hydroclimatic extremes such as increased duration, occurrence, and intensity. Despite these significant changes, our understanding of hydroclimatic risks and hydrological resilience remains limited, particularly at the catchment scale in peninsular India. This study aims to address this gap by examining hydroclimatic extremes and resilience in 54 peninsular catchments from 1988 to 2011. We initially assess extreme precipitation and discharge indices and estimate design return levels using non-stationary Generalized Extreme Value (GEV) models that use global climate modes (ENSO, IOD, and AMO) as covariates. Further, hydrological resilience is evaluated using a convex model that inputs simulated discharge from the best hydrological model among SVM, RVM, random forest, and a conceptual model (abcd). Our analysis shows that the spatial patterns of mean extreme precipitation indices (R1 and R5) mostly resemble with extreme discharge indices (Q1 and Q5). Additionally, all extreme indices, including R1, Q1, R5, and Q5, demonstrate non-stationary behavior, indicating the substantial influence of global climate modes on extreme precipitation and flooding across the catchments. Our results indicate that the random forest model outperforms the others. Furthermore, we find that 68.52% of the catchments exhibit low to moderate hydrological resilience. Our findings emphasize the importance of understanding hydroclimatic risks and catchment resilience for accurate climate change impact predictions and effective adaptation strategies.
... Overall, the local tropical Indian Ocean SST effect was observed mostly in the SIF anomalies across the central and northern Indian regions, where the land largely comprises rain-fed agricultural lands and forest ecosystems, the productivity of which fluctuates according to the monsoon rainfall [33,74]. Mostly an arid-semi-arid climatic condition persists in the ACZs of this region and, in some areas, shifts to sub-humid climates. ...
Sea surface temperature (SST) substantially influences the land climate conditions through the co-variability of multiple climate variables, which in turn affect the structural and functional characteristics of terrestrial vegetation. Our study explored the varying responses of vegetation photosynthesis in India to the SST variations in the tropical Indian Ocean during the summer monsoon. To characterise the terrestrial photosynthetic activity, we used solar-induced chlorophyll fluorescence (SIF). Our results demonstrated a significant negative SST-SIF relationship during the onset phase of the summer monsoon: the SIF anomalies in the northern and central Indian regions decrease when strong warm SST anomalies persist in the tropical Indian Ocean. Further, SIF anomalies increase with cold anomalies of SST. However, the negative SST anomalies in the tropical Indian Ocean are less impactful on SIF anomalies relative to the positive SST anomalies. The observed statistically significant SST–SIF link is feasible through atmospheric teleconnections. During monsoon onset, positive SST anomalies in the tropical Indian Ocean favour weakened monsoon flow, decreasing moisture transport from the ocean to the Indian mainland. The resultant water deficiency, along with the high air temperature, created a stress condition and reduced the photosynthetic rate, thus demonstrating negative SIF anomalies across India. Conversely, negative SST anomalies strengthened monsoon winds in the onset period and increased moisture availability across India. Negative air temperature anomalies also dampen water stress conditions and increased photosynthetic activity, resulting in positive SIF anomalies. The identified SST-SIF relationship would be beneficial to generate a simple framework that aids in the detection of the probable impact on vegetation growth across India associated with the rapidly varying climate conditions in the Indian Ocean.
... It was found that a machine learning technique based on random forest algorithm could economically estimate the atmospheric ratio of hydrogen balance sufficiently observed and the data needed to be manageable. Sharma and Goyal (2018) provided useful knowledge in assessing the resilience of land ecological system in India for water climatic turbulences in the district (i.e. the administrative unit). This article found significant atmospheric differences in Ecological Water Use (WUE) at the region level, which was complex in the Himalayan regions compared to other countries. ...
This paper examines the idea of Multi-Hazard Early Warning System (MH-EWS) from the perspective of its historical evolution, current relevance, feasibility, and challenges. It is argued that the contemporary efforts towards operationalization of such a system require a focus beyond hydro-meteorological hazards and overcoming considerable coordination challenges at various levels. Taking the case of India, this analysis shows that the existing mechanism favors hazard-specific warning and within that framework there exists scope for only limited scale of integration among different EWS components. However the recent initiatives aimed at development of people centered EWS and institutional deliberations for the multi-hazard platforms are ideal conditions to develop an effective disaster risk based EWS. Realization of this goal requires sustained political and institutional commitment, appropriate changes in policies and procedures and importantly participation of citizens and the promotion of inclusiveness as a key feature.KeywordsMulti-hazard EWSIndiaEarly warningHydro-meteorological hazardDisaster management
... Northeastern river basins have the largest forest cover among all river basins over India. In contrast, the Mahi and Sabarmati basins have the least WUE among all river basins, which is primarily due to the absence of forest areas (Sharma and Goyal, 2018b). It is interesting to note that the Mahi basin receives the lowest annual mean rainfall, whereas the Brahmaputra basin receives the highest annual mean rainfall (Fig. 2a), which indicates the dependence of water use efficiency over precipitation. ...
Rapid onset droughts, termed as “flash droughts”, cause short-term but serious threats to terrestrial ecosystems and influence carbon dynamics due to insufficient warning. To date, how the regional terrestrial carbon dynamics respond to flash droughts in India remains unknown. Since, India is highly dependent on its cropland and vegetation, identifying the influence of flash droughts on terrestrial ecosystem is important. Here we use MODIS remote sensing satellite sensor based gross primary productivity (GPP) and remote sensing-based soil moisture data to compute the response of ecosystems to flash droughts in India. From the investigation, it was observed that GPP responds to more than 95% of the flash droughts across India, with the highest response frequency occurring over Ganga basin and southern India while the lowest response across northeastern India. The discrepancies in the response frequencies are mainly attributed to different vegetation resilience conditions across different parts of the country. Moreover, the mean response time is about 10 to 19 days averaged over India, with the lowest and highest response time over Indus-Ganga basins and northeastern Indian river basins (including the Brahmaputra, Minor rivers draining into Myanmar basin (MRMB), and Barak basins), respectively. Severe reduction in water use efficiency (WUE) was observed for the Ganga river basin and some parts of southern India, which highlighted the non-resilient nature of ecosystem towards rapid soil moisture variations. The study facilitates the identification of flash drought hotspots in the country including the Indus basin, Southern river basins (Cauveri, EFRPCP, and EFRSCB basins), some parts of the Ganga basin, and the ability of an ecosystem to withstand such drastic conditions. These findings highlight the need to adopt essential drought mitigation measures to safeguard the sustainability of ecosystems.
... Precipitation is the major controlling meteorological factor of WUE by directly influencing ET and indirectly influencing the plant carbon uptake via regulating the soil moisture (Reichstein et al., 2002;Zhang et al., 2016). Previous studies on WUE variation to precipitation found that the energy-limited humid regions have a higher WUE than that in the water-limited semi-arid and arid climate zones (Sharma and Goyal, 2018;Zhao et al., 2020), which can be attributed to the lower water availability for the physical processes of GPP and ET (Kim et al., 2021). Soil moisture can strongly impact ecosystem WUE through water, carbon, and energy trade between the land surface and atmosphere (Humphrey et al., 2021) because soil moisture deficit has been verified to result in decreased photosynthesis and net primary productivity (Novick et al., 2016). ...
Groundwater influences the water and carbon cycle by supplying moisture to plants in the semi-arid and arid zones. However, little is known about the response of ecosystem water use efficiency (WUE) to climate change in different groundwater depth (GD) sections. Recent research has shown that plant photosynthesis and growth are closely related to GD via field experiments but the wider recognition of GD effect on regional-scale ecosystems has not been yet established. In this study, we test whether the GD has an impact on ecosystem WUE and its variability to climate change at the regional scale. Based on the observed data of nearly 3000 wells, meteorological data (precipitation and pan evaporation), and the 0.01°-resolution remote sensing datasets including gross primary production (GPP), evapotranspiration (ET), and normalized difference vegetation index (NDVI), we explored the spatio-temporal variations of WUE and its composites (i.e., GPP and ET), and their characteristics depending on GD under different aridity conditions and biomes across the Ordos Plateau, a semi-arid to arid area in northern China. Results show that WUE increases with decreasing GD due to water availability in the semi-arid lands where WUE variability is mainly regulated by biological processes (i.e., GPP), while WUE is insensitive to the changes in GD across the arid zone where the physical processes (i.e., ET) control WUE change. However, when drought happens the groundwater-independent vegetation in the arid zone can also utilize groundwater, characterized by lower reductions of GPP with decrease in GD. A dense vegetation condition (i.e., large NDVI) is more vulnerable to climatic disturbance over the semi-arid zone because it tends to decrease GPP and WUE, especially in the large GD regions. These findings have important implications for reasonable land use and groundwater management over the semi-arid and arid regions.
... Out of 30 states and nine Union Territories, only 10 states have 50% resilient areas. Out of 634 districts, only 241 districts (38%) were found to be resilient to dry conditions/ droughts (Sharma & Goyal 2018). ...
Several climate-smart agriculture (CSA) interventions are promoted by public, private and civil societies in India. However, there is a considerable variation among them. Therefore, to understand the different CSA interventions supported and prioritised by the public and
non-governmental organisations (NGOs) as well as their impacts at the farmer level, a case study was undertaken in Anantapur district,
as it is highly vulnerable to climate change risks due to the increase in temperature, delayed monsoon, erratic rainfall and frequent occurrence of droughts. A case study research method was followed to assess the CSA interventions promoted by Krishi Vigyan Kendra
(KVK), Department of Agriculture, Accion and Adarsha. The findings showed that KVK has focused its extension advisory services on the promotion of field crop (e.g. groundnut)-based CSA. The extension services of NGO-Accion were aimed at promoting horticulture, and Adarsha was prioritised promoting millet-based CSA interventions. Whereas the CSA priority of the department of agriculture was driven by the prevailing zero-budget natural farming project. However, interventions of KVK and NGOs were implemented on a limited scale. Therefore, the recommendations that emerged from the study will help the stakeholders to ensure convergence and foster synergy in implementing CSA interventions at scale. Some challenges faced during the research study were difficulties in the identification of the right stakeholders who were promoting CSA, also their technologies and services related to CSA. However, after a thorough discussion with the extension officers of Anantapur district, the stakeholders were identified and their CSA interventions were ascertained through focus group discussions and secondary data reviewed from magazines and other publications. Furthermore, the present study focused only on the CSA interventions promoted by two public sectors and two NGOs, and there is a wider scope for identifying more stakeholders, e.g. private sector, FPOs and entrepreneurs, and assessing their extent of involvement in the promotion of CSA and prioritisation.
... Overall, the SST effect was observed mostly in the plant productivity across the central and northern Indian regions, where the land largely comprises rain-fed agricultural lands and forest ecosystems, the NPP of which areas uctuates according to the monsoon rainfall 52,53 . Mostly an arid-semi arid climatic condition persists in the ACZs of this region and, in some areas, shifts to sub-humid climates. ...
This is a maiden attempt to explore the influence of sea surface temperature (SST) variations in the tropical Indian Ocean on the gross primary productivity (GPP) of the terrestrial vegetation of India during the summer monsoon. We studied the productivity of the vegetation across India using solar-induced chlorophyll fluorescence (SIF) as a proxy. Our results demonstrated a strong negative SST–SIF relationship: the productivity decreases (increases) when the SST of the tropical Indian Ocean is higher (lower) than normal. This SST–SIF coupling observed during June can be explained through the atmospheric teleconnections. Positive SST anomalies weaken the land–ocean thermal gradient during the monsoon onset period, reduce the monsoon flow, and hence decrease the moisture transport from the ocean to the Indian mainland. The resultant water stress, along with the high air temperature, leads to a reduction in the GPP. Conversely, negative SST anomalies strengthen the monsoon and increase the availability of moisture for photosynthesis. There is scope for improving regional GPP forecasting studies using the observed SST–SIF relationships.
... According to Tuong and Bouman (2003), 15 million ha irrigated rice areas of Asia may experience-Physical water scarcity and 22 million ha may face-economic water scarcity. At present India is facing a drought in 42% of land area, while 76.02% of Haryana's land area is drought-resilient (Sharma and Goyal, 2018). However, due to increasing global population, around 50% more food will be needed by 2030, with double that being needed by 2050 (Banwart, 2011). ...
The field experiments with thirty genotypes were conducted during June to October month of kharif, 2018 and kharif, 2019, to assess extent of variability under aerobic condition. The genotypes were sown under dry direct seeded condition using randomized block design (RBD) with three replications. Each genotype was sown in single row of 5 m length with spacing of 20 cm between rows and 15 cm between plants. Data recorded for 22 characters including different morphological and quality traits from 5 randomly selected plants of each replication and mean data used for analysis. ANOVA revealed that the mean sum of squares were highly significant difference for most of the traits. The value of PCV was higher than GCV for all the twenty-two characters. However, maximum GCV and PCV were observed for root dry weight plant-1 (31.44% and 32.17%) followed grain yield plant-1 (29.97% and 31.03%), root volume (28.62% and 29.20%), root fresh weight plant-1 (28.51% and 29.08%), biological yield plant-1 (21.86% 22.50%) and number of grains panicle-1 (20.55% and 21.37%). Rest of the traits showed moderate and low GCV and PCV. High heritability and genetic advance were recorded for the traits viz., leaf length, number of tillers plant-1, number of grains panicle-1, 1000 seed weight, root length, root volume, root fresh weight plant-1, root dry weight plant-1, kernel length-breadth ratio, grain yield plant-1, biological yield plant-1 and harvest index. The information regarding different variability will provide direction to select high yielding genotypes under aerobic condition.
... Currently, numerous studies have been conducted on the WUE at the regional scale using remote sensing technology products, such as GPP and ET products. Sharma and Goyal et al. revealed the characteristics of the spatial and temporal variation in the WUE at the district scale using moderate-resolution imaging spectroradiometer (MODIS) net primary productivity and ET data [15,16]. Tang et al. analyzed the characteristics of the global WUE and concluded that changes in land use were the main cause of the significant decline in the WUE using National Aeronautics and Space Administration (NASA) TERRA and AQUA MODIS-based estimates of the GPP and ET [17]. ...
Exploring the variations in the water use efficiency (WUE) is helpful in gaining an in-depth understanding of the regional carbon and water cycles on the Chinese Loess Plateau (CLP). Here, we employed the spatial variations in the WUE and the quantitative contributions of the influencing factors, including the precipitation (P), temperature (Temp), vapor pressure deficit (VPD), sunshine duration (SD), and leaf area index (LAI), with the drought index varying over the last two decades. Results showed that the multiyear average WUE decreased significantly as the drought index increased for all of the vegetation types. Per-pixel interannual variability of WUE trend was 0.024 gC•m −2 •mm −1 •yr −1. As the drought index increased, the WUE initially increased and then decreased for the forests, grassland, and shrubland, and their peaks occurred at drought index values of 2.60-3.10. Among the influencing factors, the WUE was predominantly controlled by the LAI, with an impact and relative contribution of 0.014 gC•m −2 •mm −1 •yr −1 and 58.3%, respectively. The P and SD contributed the least to the trend in WUE, and impact and relative contribution of both were 0.001 gC•m −2 •mm −1 •yr −1 and 4.17%. Our study also demonstrated that the LAI was the dominant factor affecting the WUE trends for grassland and the Yan River due to the structural parameters and geographical location. In addition, the impact and relative contribution of the residual factors on the WUE trend were 0.004 gC•m −2 •mm −1 •yr −1 and 16.7%. Our findings suggested that comprehensive effects such as micro-geomorphic changes and nitrogen deposition could not be ignored except for vegetation and climate change. This study will clarify the spatial and temporal evolution of WUE and its influence mechanism.
... The value of R d is classified into three categories: slightly non-resilient for 0.9 < R d < 1, moderately nonresilient for 0.8 < R d < 0.9 and severely non-resilient for R d < 0.8. (Sharma and Goyal, 2018a;2018b;Guo et al., 2019). Figure 2 shows the schematic diagram of the methodology. ...
There are limited literature on the impacts of drought on crop yields in warm regions such as southwest China. Drought vulnerability of four different crops (wheat, rice, maize and sugarcane) cultivated in three provinces (Sichuan, Guizhou and Yunnan) within southwest China were investigated in this study. It was based on the drought index of standardized precipitation evapotranspiration index (SPEI) for ‐3‐ and ‐6‐months timescales (SPEI‐3 and SPEI‐6). The correlation between the SPEI and the standardized yield residuals series (SYRS) index for the individual crops was estimated for the period from 1960 to 2018. The highest drought duration was recorded in the southern part of the study area especially in the Yunnan Province. For SPEI‐3, 60% of the total area was affected by drought mainly during the months from August to December for about 13 years (2005‐2018). In terms of SPEI‐6, the total affected area by the drought exceeded 80% during the timeframe from 2009 to 2013. Among the studied crops, winter wheat had the highest annual crop yield losses particularly in 2010 when the loss exceeded 50%. The results of this study have implications for agricultural management and climate policymaking in minimizing the influence of drought under the warming climate in southwest China. Further, it provides greater insight into crop–climate interactions and sustainable crop production.
... for hazard assessment. This dataset is extensively used in studies over the Indian region (Madhusoodhanan et al., 2017;Mishra et al., 2019;Sharma and Goyal, 2018). The monthly root-zone soil moisture data in m 3 /m 3 is obtained from Modern-Era Retrospective Analysis for Research and Application (MERRA-Land) with a spatial resolution of 1/2 • lat. ...
Long term drought management requires proper assessment and characterization of drought hazard, vulnerability and risk. This is particularly important for an agriculture-dependent, highly-populated, developing country such as India. However, the regulation of drought vulnerability and drought risk assessment in the country is mostly region-specific and ad-hoc, considering only a limited number of vulnerability indicators. In this study, a comprehensive, fine-resolution, country-wide drought risk assessment is carried out considering drought hazard in a multivariate framework, and using reliable drought vulnerability indicators that account for exposure, sensitivity and adaptive capacity. Further, multiple aggregation techniques including subjective, objective and comprehensive methods are employed for vulnerability assessment, and their performance assessed and compared. The Analytic Hierarchy Process (AHP)+Entropy and TOPSIS methods, which are comprehensive aggregation techniques are found to be better performing, TOPSIS being the most robust method. A bivariate choropleth map based on the TOPSIS-derived drought vulnerability shows regions of Punjab, Haryana, Uttar Pradesh and Tamil Nadu subjected to drought hazard-driven risk, while risk in other regions such as Rajasthan, parts of Central India, Orissa and parts of Maharashtra are driven more by drought vulnerability. Parts of Western Rajasthan, Vidharbha, North-East India, Chattisgarh, Tamil Nadu and Karnataka are under severe drought risk resulting from an interplay of hazard and vulnerability. Irrigation index, water body fraction, and groundwater availability are found to be the most significant indicators for assessing drought vulnerability in India. The above findings can aid decision makers and government bodies to plan region-specific line of action for building drought resilience.
... respectively. These estimates were lower than those obtained using models of mechanisms and observations at different sites worldwide, but were still within reasonable range of the results reported for tropical regions (Khalifa et al., 2018;Sharma and Goyal, 2018;Alemu et al., 2014). NPP in our study was consistent with previous reports Sharema and Goyal, 2018;Pan et al., 2015;Abdi et al., 2014), but was much lower than estimates from other studies in Ethiopia (Khalifa et al., 2018;Teferi et al., 2015). ...
Water use efficiency (WUE) measures the trade-off between carbon gain and water loss and is an important link between the carbon and water cycles. A better understanding of spatiotemporal variation in WUE and its controlling factors will help to improve ecosystem management for adapting to and mitigating the impacts of climatic change. We examined the spatiotemporal variations of WUE and its controlling factors for five bioclimatic zones and four land covers for 1982–2014 in the Tekeze River basin in northern Ethiopia. We quantified mean annual and seasonal net primary productivity (NPP), actual evapotranspiration (ETa), and WUE (NPP/ETa) during this period and found that each increased significantly. NPP, ETa, and therefore WUE varied spatially amongst the bioclimatic zones and land covers, but with different patterns. WUE was higher in semi-arid than humid zones. Spatiotemporal changes in temperature and precipitation could be important controls on NPP and ETa variations and therefore WUE. Mild and severe droughts in the southern regions of the basin decreased annual WUE, and moderate and extreme droughts slightly increased it, indicating that the measure of environmental rehabilitation implemented since the 1980s have increased NPP in these regions, despite the water stress caused by frequent droughts. The variability of WUE was primarily controlled by climatic change and human activity, the latter dominant since the 2000s. Ecological restoration and measures for conserving soil and water could substantially increase the vegetation productivity of this region, and be a viable management strategy to both adapt to and mitigate the impacts of climate change.
... Droughts in India have become more frequent in the last two decades (NRAA, 2009;Roy & Hirway, 2007). Over one-third of all the districts (241 of 634 districts) of India faced drought or drought-like conditions, of which at least 133 districts frequently faced drought almost every year (Sharma & Goyal, 2018). One-third of the country has experienced prolonged, widespread drought in recent decades (Mishra & Singh, 2010;Roy & Hirway, 2007). ...
The present study in the Rarh region (a region between Chota Nagpur Plateau and the Ganges Delta) of West Bengal analyses the impact of drought on the rural households in the eastern India villages and investigates the importance of temporary migration as a coping strategy in times of drought. As many as 82 of a total of 190 households were randomly selected for collection of data with the help of a structured household schedule. The study found that the propensity of male out-migration increased due to regular droughts in the region. Severe drought conditions coupled with crop failure made most marginal and small landholding households vulnerable to food insecurity due to poor adaptive capacity and resilience. The majority of the landholding farmers under such conditions resort to seasonal out-migration to sustain themselves. Temporary migration is a coping strategy for the survival of rural households during the drought periods.
... The satellite precipitation datasets is useful in estimation of crop yields, weather forecasting and assessment of climate extreme events (Sharma and Goyal, 2018). In this study the validity of the CHIRPS and TRMM datasets was testing using the station datasets of the Subernarekha basin for the period of 2000-2014 as shown in Fig. 4a and b, respectively. ...
The Water Accounting Plus (WA+) framework uses open access remote sensing and GIS data and hydrological model output. This framework uses Budyko hypothesis and thus makes use of ‘green’ water and ‘blue’ water accounting. We applied the WA+ framework to the Subarnarekha basin, India, to assess the total water consumptions and land productivity (LP) and water productivity (WP) for a period of 12 years from 2003 to 2014 by using satellite and open data sources. The total water consumptions in the basin for 2013–14 (wet year) and 2010–11 (dry year) are 27.1 BCM/year and 23.1 BCM/year, respectively. The LP in the basin is found to vary from 1575 to 2141 kg/ha/year (with an average of 1921 kg/ha/year) and 1315–2325 kg/ha/year (with an average of 1948 kg/ha/year) during the period of 2003-04 to 2013–14, respectively for rainfed and irrigated cereals. Similarly, the WP is found to vary from 0.34 to 0.49 kg/m³ (with an average of 0.42 kg/m³) and 0.38–0.69 kg/m³ (with an average of 0.59 kg/m³) during the period of 2003-04 to 2013–14, respectively for rainfed and irrigated cereals. This study shows that the WA+ framework can be successfully applied for analyzing water consumption patterns, land productivity and WP of irrigated and rainfed crops individually. The results are available in map form, it is easy to identify the places/farmers with low LP and WP and work with them to improves these. Such efforts will ultimately lead to efficient management of water resources in the basin and poverty alleviation.
... Longer return period prevails in the Western Ghats because it receives highest rainfall, one of the ecological rich region and presence of evergreen forest. Moreover, this regions is known to be resilient to hydroclimatic disturbances (Sharma and Goyal, 2018;Jha et al., 2019b). Whereas the basins in South India (Cauveri, EFRPCB and Krishna), Sabarmati, BB basins show smaller joint return period in case of meteorological drought. ...
Duration and severity are the two most important parameters used for drought characterization. In this study, we used a bivariate copula‐based approach to understand the joint dependence of drought duration and severity of three different drought types. Three types of bivariate copulas (Gumbel, Frank, and Plackett) are estimated for modeling and the best fit copula is selected over 1162 grid points (at a resolution of 0.5°×0.5°) of India. Further, the joint dependence of drought duration and severity are analyzed to infer important properties in terms of exceedance probability and return periods. Finally, conditional probability and conditional return periods of drought characteristics are also derived, which could be useful for proper planning and management of the water resource system. From the investigation, it is observed that drought events in the Western and Central India are longer and more severe whereas the ones in the south Indian river basins are more frequent but less severe. Moreover, similar results were also obtained for the conditional probability and conditional return periods. This study provides information regarding the severe and longer drought event hotspots all over the study area and thus helpful for the policymakers in developing effective drought prevention and mitigation strategies comprehensively at a national scale.
... Wang et al. (2014) indicated that climate extremes were more destructive to exotic tree species than to native ones. Sharma and Goyal (2018) found that forests were more resilient than other vegetation types in hydroclimatic disturbances in India. Although we found that T-ECIs had a greater impact on ecosystems than P-ECIs on an annual scale in SWC, the response and resilience of different vegetation types to climate extremes should be analyzed in the future to evaluate the sustainability of ecosystems as more extreme climate events occur in the region. ...
Due to global warming, climate extremes are increasing significantly, which is greatly impacting ecosystems dynamics. Identified as a key ecological area, southwest China (SWC) has experienced frequent extreme climatic events. Using daily meteorological data and Moderate-Resolution Imaging Spectroradiometer data, we analyzed the spatiotemporal variations of 21 extreme climate indices (ECIs) and 3 ecosystem metrics, namely, normalized difference vegetation index (NDVI), leaf area index (LAI), and gross primary production (GPP), as well as the responses of these metrics to ECIs during 2000–2018. Our results showed that the regionally averaged NDVI, LAI, and GPP increased significantly in this period with annual rates of 0.003, 0.04 m² m⁻², and 10.58 g C m⁻², respectively (P < 0.001). Cold-related ECIs and consecutive wet days decreased, while warm-related ECIs, heavy precipitation days, and extreme precipitation intensity displayed the opposite trend. The sums (22.48%, 12.98%, and 32.70%, respectively) of the relative contribution proportions of the sensitive temperature-related ECIs (T-ECIs) to NDVI, LAI, and GPP were higher than that those (14.60%, 12.75%, and 16.37%, respectively) of the sensitive precipitation-related ECIs (P-ECIs). Ecosystem metrics were significantly correlated with most ECIs with time lags of 2–3-month. The correlation coefficients between large-scale atmospheric circulation indices and T-ECIs were significant (P < 0.05). The Atlantic Multidecadal Oscillation had a greater influence on T-ECIs than any other large-scale climatic oscillations. Our study indicated that T-ECIs had a greater impact on ecosystems than P-ECIs in SWC and that more attention should be paid to increasingly heavy precipitation and extreme high temperatures in the region.
... Moreover, adverse consequences of extreme precipitation events are also evident in the country, around 268 flood events have been reported during 1950-2015 affecting 825 million people (Roxy et al., 2017). India is a climatologically diverse country having spatiotemporal variability in terms of temperature, precipitation, thereby the response to hydroclimatic disturbances for different regions are distinct (Sharma and Goyal, 2018;Singh et al., 2019). Therefore, both the case studies are presented at a national scale here. ...
The persistent extreme weather events (floods, droughts, heatwaves, etc.) are increasing the risks towards critical infrastructure (C.I). Therefore, it is essential to enhance the resilience of our C.I to withstand such events in the present and future. Here, a review of current and projected impacts of climate change is conducted on extreme events and on possible implications on C.I is carried out, which suggests that such events can have a severe impact on C.Is. Also, two studies on the behaviour of precipitation extremes and temporal evolution of drought across India are carried out, taking into account the corresponding impacts on C.Is. It indicated that northwestern , northeastern westernmost regions and western Ghats are highly susceptible to floods and northern, central-eastern, western, and central regions are prone towards co-occurrence of floods and droughts. Also, a case study on Kharif paddy yield forecasting using different machine learning (ML) models is carried out, where the random forest was found to be the most suitable model for yield prediction. Finally, we put forward a robust framework for risk assessment and improving the resilience of C.Is based upon the principles of flexibility, diversity , and industrial ecology, incorporating both short-term and long-term impacts of climate risk.
... In recent years, modeling simultaneously net primary productivity and evapotranspiration have been a subject of increasing interest because of the importance of terrestrial carbon and water cycle, which are tightly coupled through photosynthesis and evapotranspiration processes, in global climate change (Tian et al. 2010;Sharma and Goyal 2018;El Masri et al. 2019). As an important tool for understanding the scaling of carbon dioxide (CO 2 ) and water (H 2 O) exchange from leaf to canopy fluxes, coupled models of leaf stomatal conductance-photosynthesis-transpiration have been researched widely (Collatz et al. 1991;Tuzet et al. 2003;Müller et al. 2014). ...
Process-based coupled model of stomatal conductance–photosynthesis–transpiration was developed to estimate simultaneously stomatal conductance gsw, photosynthetic rate Pn, and transpiration rate Tr during leaf ontogeny. The modified Jarvis model was constructed by superposing the influence of leaf age LA on gsw in traditional Jarvis model. And the modified Farquhar model was constructed by incorporating the relationships of the LA with parameters in Farquhar model into traditional Farquhar model. The average and leaf-age-based coupled models were constructed, respectively, by combining traditional Farquhar and Penman–Monteith models with traditional Jarvis, and combining modified Farquhar and Penman–Monteith models with modified Jarvis. The results showed that the gsw, the maximum rate of carboxylation, maximum rate of electron transport, rate of triose phosphates utilization, and mitochondrial respiration rate varied in a positive skew pattern, while the mesophyll diffusion conductance decreased linearly with increase in LA. The average coupled model underestimated gsw, Pn, and Tr for young leaves and overestimated gsw, Pn, and Tr for old leaves. And the leaf-age-based coupled model generally perfected well in estimating gsw, Pn, and Tr for all leaves during leaf ontogeny. The study will provide basic information for either modeling leaf gsw, Pn, and Tr continuously, or upscaling them from leaf to canopy scale by considering the variation of LA within canopy.
... From past pandemics, it has been found that panic and quarantine regulations significantly impacted the economic growth and human development (Arndt and Lewis 2001;Bermejo 2004). However, it also affects agricultural activities due to decreased availability of agricultural industry workers, decreased demands for agricultural exports, impacts of longer lead times in supply, limited transportation and logistics services, decreased supply capacity, stringent market protocols, reduced average annual precipitation (Goyal and OJha (2012); Goyal and Ojha (2014); Sharma and Goyal (2018)) and globally the increase biosecurity regulations. Burgui (2020) and Sar et al. (2010) found that an outbreak of contagious diseases will result in malnutrition and hunger due to significant impact on agricultural related activities. ...
Global pandemics, epidemics, and disease outbreaks have plagued humanity for ages. However, the scale and spread of pandemics and epidemics increased drastically in recent history. Currently, COVID-19 pandemic (respiratory illness) caused by SARS-CoV-2 virus ravaging fright around the world. The infectious nature of the disease affected the global and local economies and societies. Nations are forced to implement precautionary measure such as restriction of mobility to stop the spread of disease, which vastly affecting the major economic sectors including food and agricultural industry. The precautionary measures such as travel restrictions disrupt the food production, distribution, and supply chain network. The impact is widely seen on livestock and aquaculture farming, which threatens the food security and calls for immediate policy interventions from the government. This chapter investigates the challenges posed by COVID-19 pandemic on agricultural sector and food industry in India and determine the possible mitigation measures. The study presented the recommendation to call for government support in strengthen policies to boost agricultural sector activities to achieve transitions towards food security during and post-pandemic period.
... Attempts have been made to quantify the resilience of components of an ecohydrological system (King, Franz, and Caylor, 2012;Ridolfi, D'Odorico, and Laio, 2006;Sharma and Goyal, 2018) but no tangible metric of resilience exists for understanding an ecohydrological system as a whole. Computing resilience of an eco-hydrological system and delineating their points of no recovery, if they exist, using networks would be an exciting extension of this study. ...
The Himalayan ecosystem is a global biodiversity hotspot and a vital component of the global water cycle. However, the studies characterizing the ecohydrological processes of the Himalayas are still limited. Looking at a system as a network, having nonlinear couplings, can give us better insights into its dynamics. Here, using an information-theoretic approach on the variables, Precipitation (P), Temperature (T), Enhanced Vegetation Index (EVI), Latent Heat Flux (LH), Sensible Heat Flux (SH), Wind Speed (WS), Incoming Shortwave Radiation (SWL), and Relative Humidity (Q), we represent the ecohydrological processes of the Himalayas in the form of networks for three seasons: summer (MAM), monsoon (JJASO), and winters (NDJF). The networks have two types of links between variables: real-time and memory-driven. We show that the couplings between ecohydrological variables in the Western Himalaya are more memory dominant that the Eastern Himalaya. Precipitation interacts with vegetation in the Himalayas using both real-time associations as well as memory-based connections. The dominance of memory varies spatially and temporally. The Temperature, on the other hand, influences vegetation in near real-time, and it also has memory-based links in Central Himalaya and at the higher elevations of the Eastern Himalaya. We find that the real-time interactions (zero lagged connections) among ecohydrological variables are high during the monsoon as opposed to winters, which are dominated by memory-based associations. These findings provide the foundation for further analysis of the trajectory of Himalayan ecohydrological systems under natural and human-induced climate stresses.
... Anthropogenic forces such as the fossil fuel, land-use changes, and quick industrialization are considered to be the main reasons for the increased GHGs in the atmosphere [3]. Especially in the high mountainous basins, global warming triggers the melting of snow, increase in rainfall rather than snowfall, depletion of glaciers [4], change in evaporation and cloud formation, all of which ultimately altering the hydrological conditions of that region [5] and also increasing the threat of extreme events (flood and drought) around the globe [6]. Investigating the trends of the past hydro-climatic parameters can play a vital role in future impact estimation [7]. ...
Climate change is one of the major threats to humanity in recent times. It has a significant potential to disturb the water cycle which additionally accelerates many problems i.e. water availability, agriculture yields, damage to the ecosystem, etc. That is why it is important to understand the climatic changes in the rural and agrarian-based basin. Therefore, the focus of this study was to detect the changes in the climatic indices and parameters in the Kunhar river basin, Pakistan. Box and whisker plots, RClimDex tool, Mann Kendall test, and Inverse distance weighted (IDW) were used to observe the basic statistics, variations in the climatic indices, trends of climatic parameters, and their significance and spatial distribution of the climatic parameters respectively, over the Kunhar River basin. For the baseline period (1979-2014), it was found that the maximum and minimum temperatures were increasing significantly. However, precipitation, wind speed, and relative humidity were decreasing significantly. Changes in the climatic parameters were more significant in the lower half of the basin than the upper. Changes in the seasonal flow were more significant than annual. Runoff was increasing at the rate of 0.415 m 3 s-1 per spring season and decreasing at the rate of 0.415 m 3 s-1 per summer season, which is a clear indication of peak shift in the backward direction. These changes affect the agriculture yields, water availability, and ecosystem of the basin.
In 2015 the beginning of the Indian Smart Cities’ mission was one of the significant steps taken by the Indian government to make the urban environment resilient to climate change impact and extreme weather events like drought, floods, heatwaves, etc. This study computes the urban drought risk for Indian smart cities before the beginning of the Indian smart cities mission. This study considers three decadal variability (1982–2013) in meteorological, hydrological, vegetation, and soil moisture parameters for inducing water scarcity and drought conditions in urban regions. Hazards associated with urban drought-inducing parameters variability, vulnerability, and exposure of Indian smart cities were used to compute the Urban drought risk. The research investigations revealed the maximum urban drought risk for Bangalore, Chennai, and Surat cities. Northwest, West Central, and South Peninsular urban regions have higher risk among all the urban regions of India. Indian smart cities mission can be used to make Indian cities resilient to urban drought risk and increase their sustainability. The present research aligned with several national and international agreements by providing an urban drought risk rank for Indian cities, making them less vulnerable to extreme weather events and improving their resilience to climate change.
The ecosystem water use efficiency (WUE), a crucial indicator of how climate change will affect terrestrial ecosystems, depicts the coupling of the carbon gain and water loss in terrestrial ecosystems. In this study, the spatiotemporal variations in the WUE and its responses to drought in the Lancang–Mekong River Basin (LMRB) from 1982 to 2018 were investigated using the gross primary productivity (GPP) and evapotranspiration (ET) data acquired from the Global Land Surface Satellite (GLASS) products. The analyses revealed that: (1) the mean yearly WUE for the LMRB was 1.63 g C kg ⁻¹ H 2 O, with comparatively higher values in forests and warm temperate climatic types. The interaction of temperature and leaf area index was the main factor affecting the spatial distribution of WUE. The yearly WUE for the entire region exhibited a decreasing trend with a rate of −0.0009 g C kg ⁻¹ H 2 O·yr ⁻¹ , and the spatially significantly decreasing area accounted for 41.67% of the total area. (2) The annual WUE was positively correlated with drought in the humid regions, accounting for 66.55% of the total area, while a negative relationship mainly occurred in the high-altitude cold region. (3) The ecosystem WUE lagged behind the drought by 3 months in most regions. The lag effect was more apparent in the grassland-dominated upstream region and the cropland-dominated Mekong Delta. (4) The resilience analysis revealed that the ecosystems in forests and temperate climate types were strongly resistant to drought, while the grassland and high-altitude regions with a dry and cold climate had relatively poor resilience. The results of this study shed light on how the WUE responds to drought across diverse land use types, climate types, and elevation gradients, uncovering fresh insights into the potential mechanisms behind the impact of drought on water and carbon cycles within ecosystems.
Terrestrial ecosystem water use efficiency (WUE) is an important indicator for coupling plant photosynthesis and transpiration, and is also a key factor linking the carbon and water cycles between the land and atmosphere. However, under the combination of climate change and human intervention, the change in WUE is still unclear, especially on the Tibetan Plateau (TP). Therefore, satellite remote sensing data and process-based terrestrial biosphere models (TBMs) are used in this study to investigate the spatiotemporal variations of WUE over the TP from 2001 to 2010. Then, the effects of land use and land cover change (LULCC) and CO2 fertilization on WUE from 1981–2010 are assessed using TBMs. Results show that climate change is the leading contributor to the change in WUE on the TP, and temperature is the most important factor. LULCC makes a negative contribution to WUE (−20.63%), which is greater than the positive contribution of CO2 fertilization (11.65%). In addition, CO2 fertilization can effectively improve ecosystem resilience on the TP. On the northwest plateau, the effects of LULCC and CO2 fertilization on WUE are more pronounced during the driest years than the annual average. These findings can help researchers understand the response of WUE to climate change and human activity and the coupling of the carbon and water cycles over the TP.
The meteorological phenomenon are the prime agents in causing extreme events in the arid and semi-arid areas. These are drought and famines, flood, sand and dust storms, etc. The response to the climate change varies with the deterioration of global climate warming. GIS, Remote Sensing and GPS are the modern tools which play significant role in the management of extreme events. These have proved their importance in the rapid assessment of the pre- and post-events through the spatio-temporal variabilities of terrain properties. Satellite images of varied resolution, provide a synoptic evaluation and offer valuable environmental details, for a vast range of scales. The most important methods currently in vogue are the conventional synoptic and numerical methods to monitor changes in the weather. Droughts mainly depends on precipitation, temperature and evaporation. The western part of Rajasthan, known as the Thar Desert, often experiences several consecutive years of droughts and famine cause various kinds of socio-economic and environmental hazards. The other important one is the sand and dust storms. Flash floods do occur to cause land degradation and damage crops. Application of Geospatial technologies in the management of the extreme events helps to reduce the risk as well as control the impact of such events. Further, the integration of weather data and GIS helps to quantitatively monitor storm impact. The present paper deals with the application of geospatial technologies in their prediction and management.
In the modern world of developments in geospatial data capture techniques, the data handling of geospatial data as big data is pivotal. The most of real world data is available in an unstructured form. While some of this data is stored in databases, much of the data is unstructured and temporal in nature. In this book chapter, we survey different forms of geospatial big data their characteristics, tools and techniques. We present case studies which are related to hydrology and meteorology department. A flood management and wind power generation using geospatial big data is explained in this chapter as an application of geospatial data. We discuss ten different features of geospatial big data.
This study attempted to reexamine the relationship between hydroclimate extreme and economic growth in India. Using primary and secondary information, this exploration was carried out at three levels - macro, meso, and micro. The study confirmed the negative impact of hydroclimatic extreme events on economic growth, highlighting different impact pathways.
Drought is a natural hazard, which has widespread, significant impacts on the world’s economy, environment, industries, and the community. This study includes a comprehensive discussion on drought types, drought indices, and the impact of droughts. Further, a case study is presented to investigate meteorological, hydrological, vegetation, and soil moisture drought over Central India during the period 1982–2013. Further, drought concurrence over Central India is also examined. Finally, drought adaptation and mitigation strategies were discussed. Examinations indicate that 82% of concurrent droughts include soil moisture drought as a major part over Central India. This study facilitates a comprehensive approach to better understand the dynamic characteristics of all major droughts and their complex interaction from various perspectives over Central India, and thus provides useful insights for policymakers to develop effective strategies for drought mitigation and sustainable ecosystem management.
Climate change is expected to have a significant impact on the hydrological cycle, which includes precipitation, evapotranspiration, and soil moisture. The most visible sign of climate change is change/increase in temperature. The evapotranspiration or crop water requirement is the most sensitive to temperature changes. Therefore, any temperature change will have a profound effect on the overall crop water requirement and in turn on the water resources of any area. The current study attempts to comprehend the likely impact of climate change on Rajasthan’s water resources. Reference evapotranspiration (ETo) was calculated using the Penman-Monteith equation and the sensitivity of ETo was examined by increasing the temperature from 1% to 3% while keeping other parameters constant. A temperature increase of 1% (≤0.42 °C based on Rajasthan’s normal maximum temperature) will augment the evapotranspiration demand by 11.7 mm on an annual basis. This will further add annual water demand of 718 mcm and 2245 mcm for the whole state based on net irrigated area and total cropped area respectively. The drought-prone region like Rajasthan is not blessed with worthy perennial river systems, so any surge in water demand requires watchful planning for future water resource development.
Drought is a frequently occurring hydrometeorological event, which is defined as a reduction in water availability in different hydrologic elements. Over the last century, the hydrologists around the world have put substantial efforts to improve the monitoring and prediction of droughts through the development of new drought indices and prediction models. However, the scarcity of site-based observations has constrained these efforts to date. Remote sensing has emerged as an alternative to supplement these observations and has enabled the progress in drought studies in data-scarce parts of the world. This chapter describes the applicability of remote sensing in evaluation and assessment of drought (i.e., meteorological, agricultural, and hydrological). We also discuss the limitations associated with remote sensing applications (resolution, continuity, and uncertainty) and future perspectives. Further, a case study on remote sensing application in assessment of drought impact on Net Primary Production (NPP) in India is also presented, which highlights the importance of remote sensing in providing information of ecohydrological variables that are difficult to monitor on ground.
In the recent years, the growing concern to understand the impact of climate variability on various aspects of human civilizations have led to developing an understanding of proxy response according to change in the environmental conditions. Among various climate-sensitive proxies (e.g., geochemistry, pollens, biomarkers, grain size, etc.), the stable isotopes are the crucial component that not only helps us to understand the climate variability in the past, but also provides a detailed understanding of past meteorological variables such as temperature and precipitation, and vegetation response with changing hydrological conditions. The present study is focusing on the application of stable isotopes (δ13C, δ18O, δ15N and δD) in order to understand the climate variability since Pleistocene to present day conditions and provide a significant insight towards understanding the role of external (solar forcings), and internal forcing factors (teleconnections, such as El-Niño Southern Oscillation – ENSO, North Atlantic Oscillation – NAO) influencing the centennial to millennial-scale climate variability. Further, using case studies from the south Asian region, we have highlighted several challenges such as the impact of post-depositional changes and moisture pathways associated with the isotopic studies. This understanding will further provide better insights of isotope behaviour in natural archives in spatially varied terrains which is essential to decipher the temporal evolution of climate.
Locating a piece of land for upcoming government project or choosing a correct piece of land for shifting an existing government project is indeed a difficult task. This task is difficult as the wrong decision in this regard may lead to increased financial stress and in worst case lead to project failure. To facilitate this decision making, spatial data infrastructure is used in this research, data model is also given for decision making. Here three map layers are created namely land use land cover map, temperature map and rainfall map. Detailed procedure to generate map is given for each map layer and final map is generated using weighted sum to find out most suitable location for upcoming project by using land use land cover along with meteorological data. Verification is done by using actual ground control points for above three parameters. Accuracy calculation is also done in order to find out accuracy of LULC classification. Finally, significance of this research to government agencies for effective decision making is given.
Drought is natural disaster which is characterized by intense and persistent shortage of precipitation. Drought monitoring plays an important role for the freshwater planning and management as well as for prediction of the onset and severity of droughts. The present study deals with the potential of using precipitation-based Standardized Precipitation Index to analyse the temporal pattern of drought in the Gulmarg area of Baramulla district of Jammu and Kashmir. Monthly precipitation data from 2010 to 2019 for Gulmarg region were used to compute Standardized Precipitation Index (SPI) values. The computation of SPI series was carried out for short, intermediate and for long time scales. The moderate drought occurred in 2013 and severe drought occurred in 2018. The intensity of these droughts was found to be moderate during three years from 2011-2013. The SPI values were less than (-)1.0 for these years on 6-month, 9-month and12-month time scales. The 12-month SPI value for these years were (-)1.05, (-)1.34, (-)1.49, respectively. The 12-month SPI values for 2018 was (-)1.56 which indicated severe drought. However, the SPI values suggest moderate dryness in place of acute dryness during the years of severe and extreme drought.
This chapter portrays that co-operatives be it agricultural or financial are instrument in building socio-hydrological resilience. This is due to the fact that co-operatives are deep rooted to solve societal problems in an inclusive way. The co-operatives are built under social responsibility and caring values which support them in the provision of strong social security to its members. This helps co-operatives to lessen adverse impact on the most disadvantaged groups, and this in turn promotes disaster risk reduction. Likewise, unity as another value of co-operatives enables them to play a philanthropic role after the occurrence of disaster. Co-operatives, being among strong institutions and very close to the communities, are positioned to create awareness for disaster response. Building social hydrological resilience in a more effective and sustainable manner requires comprehensive and all-inclusive approaches which in the one hand are among the pillars inherent in a co-operative ideology. It is also important to note that this does not mean other approaches of dealing with resilience such as engineering resilience and ecological resiliencies are less important. The two approaches are equally important but their success and sustainability will depend on socio-hydrological approach. Thus, it can be concluded that if co-operatives become more adaptive and sustainable mainly as a result of strong management, solid market advantageous, strong venture capital and good governance, they are likely to be resilient not only on financial aspects but also in many other aspects including socio-hydrological matters. This can be demonstrated by their abilities to have self-mobilisation and be able to fulfil the needs of their stakeholders.KeywordsSocio-hydrologicalResilienceCo-operativesFloodsTanzania
Mountain ecosystems regulate global terrestrial carbon dynamics and are sensitive to changes of extreme climate. To discuss extreme climate’s impact on productivity of vegetation by using the elevation change as a binding force can provide a new reference for carbon sink management of ecosystem in alpine regions. The CASA model and Rclimdex1.0 were used to calculate NPP and 16 climate extremes indices, respectively, from 1982 to 2019 in Yunnan. The response characteristics of regional NPP to climate extremes were calculated using unary regression analysis, correlation analysis, geographic detector, and relative importance analysis. The results are as follows: (1) The turning point of NPP for various vegetation types appeared in the late 1980s in Yunnan. (2) The correlation between extreme precipitation index and NPP is more dependent on elevation than on extreme temperature indices. (3) Extreme climate indices are more sensitive in middle and high-elevation areas. As a result, NPP of alpine vegetation increased by more than 10% after the turning point compared with that before the turning point. (4) In the elevation range Ⅰ-IV (76–4000 m), the proportion of double-factor increase on NPP was more than 30%, while in the range of 4000–5000 m, the proportion of double-factor increase on NPP was <10%. (5) The primary controlling factors of NPP in the elevation Ⅰ﹣III (76–3000 m) were R25mm, R10mm, and R10mm, respectively. The primary controlling factors of NPP increasing in the elevation IV﹣Ⅵ (4000–6000 m) were SU25, TR20, and FD0, respectively. This study provides new insights into the impact of extreme climate on regional NPP from the perspective of elevation, emphasizing the management of ecological environment in high-elevation regions which are sensitive to climate response.
Spatial and temporal analysis on the extreme rainfall events (ERE’s) across the districts that fall under Barak and its adjacent river basin during the monsoon months have been carried out. The analysis was carried out to understand the risks that arise as a result of changes in the frequency and intensity of EREs for developing adaptation strategies for the vulnerable districts. Indices such as days with rainfall more than 25 mm (R25), 20 mm (R20), and 10 mm (R10), consecutive dry day, consecutive wet days, highest 1-day precipitation have been computed for the earlier years (1901–1976) and the recent period (1977–2015). A comparison of the ERE’s across the two periods has also been carried out to analyze the plausible impact of climate change. Further, the study classifies the various districts into three regions (medium, high, and very high rainfall) and analyze the districts with significant changes in different EREs. Results indicate a significant increase in mean rainfall by 2507–4483 mm in various districts (South Garo Hills, West Khasi Hills, and East Khasi Hills) of high rainfall areas during the later period compared to the pre-1977 period. An increase in the number of days in R25 and R20 was noted in the district of Karimganj, Hailakandi, which may worsen the situation in these flood-prone areas. Senapati district, which falls under the medium-rainfall region, has had a significant increase in all the indices. Such districts that show a significant increase in most indices are further selected to illustrate the different impacts of ERE’s in terms of both risks and opportunities. Findings from the study would feed in the district action plan in developing climate change and adaptation policies to tackle the rapid or frequent occurrence of ERE’s in a different region of the basin.
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The persistent extreme weather events (floods, droughts, heatwaves, etc.) are increasing the risks towards critical infrastructure (C.I). Therefore, it is essential to enhance the resilience of our C.I to withstand such events in the present and future. Here, a review of current and projected impacts of climate change is conducted on extreme events and on possible implications on C.I is carried out, which suggests that such events can have a severe impact on C.Is. Also, two studies on the behaviour of precipitation extremes and temporal evolution of drought across India are carried out, taking into account the corresponding impacts on C.Is. It indicated that north-western, north-eastern westernmost regions and western Ghats are highly susceptible to floods and northern, central-eastern, western, and central regions are prone towards co-occurrence of floods and droughts. Also, a case study on Kharif paddy yield forecasting using different machine learning (ML) models is carried out, where the random forest was found to be the most suitable model for yield prediction. Finally, we put forward a robust framework for risk assessment and improving the resilience of C.Is based upon the principles of flexibility, diversity, and industrial ecology, incorporating both short-term and long-term impacts of climate risk.
The coronavirus disease 2019 (COVID 19) turned out to be one the most substantial global crisis in the recent times. Researchers all around the world are trying to understand the factors which influence and govern the occurrence and evolution of the pandemic. Earlier understanding of diseases generated by similar family of viruses suggest that climate factors do influence the growth of disease. Similarly, the risk of natural or manmade disaster depends on the vulnerability, exposure and capacity of the population. These factors in turn depend on the socio-economic status of the exposed population. During the past few years, it has been realized that India is highly vulnerable to climate change with the existing socio-economic condition. Given the severity of COVID 19 pandemic, it becomes necessary to investigate the role of climatic factors and socio-economic conditions in augmenting the risk of the disease. This chapter discusses the role of climatic and socio-economic conditions in increasing the risk of COVID 19 pandemic. We first discuss the dependence of climatic variables in augmenting the risk of the similar diseases. Then, the role of socio-economic status of the exposed population is investigated by previous studies. Further, the chapter incorporates a case study which explores the role of four climatic variables (pressure, relative humidity, temperature and wind speed) in governing the risk of COVID 19 in India. The hazard measure in terms of the occurrence of different percentiles of confirmed COVID 19 cases was calculated and then combined with the vulnerability and exposure indicators to estimate the risks. The case study is carried out using extreme value theory in a nonstationary setting to check and incorporate the dynamic nature of climate and COVID 19 dependence.
In recent decades, remote sensing and geographic information system (GIS) have emerged as important geospatial tools for monitoring the natural resources on earth and to understand the role of anthropogenic activities. The improvement in these tools (e.g. sensor technology, processing tools, algorithms, etc.) is widening the scope of remote sensing and GIS applications. These tools offer continuous observations throughout the earth, which is vital for ensuring the sustainable use of the world's resources. This chapter first introduces the concept of remote sensing and GIS, and then presents the various applications of remote sensing and GIS in earth observation and sustainable resource management. We conclude the chapter with a case study on examining the terrestrial ecosystem's resilience to hydroclimatic disturbances in northeast India. We also highlight the future scope of remote sensing and GIS applications in sustainability.
The impacts of concurrent droughts and heatwaves could be more serious compared to their individual occurrence. Meteorological drought condition is generally characterized by low rainfall, but impact of such an event is amplified with simultaneous occurrence of heatwaves. Positive feedback between these two extremes can worsen the rainfall deficit situation to serious soil moisture depletion due to enhanced evapotranspiration. In this study, the concurrence of meteorological droughts and heatwaves is investigated in India using Indian Meteorological Department (IMD) high resolution gridded data over a period of 60 years. Significant changes are observed in concurrent meteorological droughts and heatwaves defined at different percentile based thresholds and durations during the period 1981–2010 relative to the base period 1951–1980. There is substantial increase in the frequency of concurrent meteorological droughts and heatwaves across whole India. Statistically significant trends in the spatial extent of droughts are observed in Central Northeast India and West Central India; however, the spatial extent affected by concurrent droughts and heatwaves is increasing across whole India. Significant shifts are identified in the distribution of spatial extent of concurrent drought and heatwaves in India compared to the base period.
Socioeconomic challenges continue to mount for half a billion residents of central India because of a decline in the total rainfall and a concurrent rise in the magnitude and frequency of extreme rainfall events. Alongside a weakening monsoon circulation, the locally available moisture and the frequency of moisture-laden depressions from the Bay of Bengal have also declined. Here we show that despite these negative trends, there is a threefold increase in widespread extreme rain events over central India during 1950–2015. The rise in these events is due to an increasing variability of the low-level monsoon westerlies over the Arabian Sea, driving surges of moisture supply, leading to extreme rainfall episodes across the entire central subcontinent. The homogeneity of these severe weather events and their association with the ocean temperatures underscores the potential predictability of these events by two-to-three weeks, which offers hope in mitigating their catastrophic impact on life, agriculture and property.
Recent studies have shown an increasing trend in hydroclimatic disturbances like droughts, which are anticipated to become more frequent and intense under global warming and climate change. Droughts adversely affect the vegetation growth and crop yield, which enhances the risks to food security for a country like India with over 1.2 billion people to feed. Here, we compared the response of terrestrial net primary productivity (NPP) to hydroclimatic disturbances in India at different scales (i.e., at river basins, land covers, and climate types) to examine the ecosystems’ resilience to such adverse conditions. The ecosystem water use efficiency (WUEe: NPP/Evapotranspiration) is an effective indicator of ecosystem productivity, linking carbon (C) and water cycles. We found a significant difference (p < .05) in WUEe across India at different scales. The ecosystem resilience analysis indicated that most of the river basins were not resilient enough to hydroclimatic disturbances. Drastic reduction in WUEe under dry conditions was observed for some basins, which highlighted the cross-biome incapability to withstand such conditions. The ecosystem resilience at land cover and climate type scale did not completely relate to the basin-scale ecosystem resilience, which indicated that ecosystem resilience at basin scale is controlled by some other ecohydrological processes. Our results facilitate the identification of the most sensitive regions in the country for ecosystem management and climate policy making, and highlight the need for taking sufficient adaptation measures to ensure sustainability of ecosystems.
We calculated water use efficiency (WUE) using measures of gross primary production (GPP) and evapotranspiration (ET) from five years of continuous eddy covariance measurements (2009–2013) obtained over a primary subtropical evergreen broadleaved forest in southwestern China. Annual mean WUE exhibited a decreasing trend from 2009 to 2013, varying from ~2.28 to 2.68 g C kg H2O−1. The multiyear average WUE was 2.48 ± 0.17 (mean ± standard deviation) g C kg H2O−1. WUE increased greatly in the driest year (2009), due to a larger decline in ET than in GPP. At the diurnal scale, WUE in the wet season reached 5.1 g C kg H2O−1 in the early morning and 4.6 g C kg H2O−1 in the evening. WUE in the dry season reached 3.1 g C kg H2O−1 in the early morning and 2.7 g C kg H2O−1 in the evening. During the leaf emergence stage, the variation of WUE could be suitably explained by water-related variables (relative humidity (RH), soil water content at 100 cm (SWC_100)), solar radiation and the green index (Sgreen). These results revealed large variation in WUE at different time scales, highlighting the importance of individual site characteristics.
Partitioning of precipitation (P) into actual evapotranspiration (ET) and runoff affects a proxy for water availability (P-ET) on land surface. ET accounts for more than 60% of global precipitation and affects both water and energy cycles. We study the changes in precipitation, air temperature, ET, and P-ET in seven large basins under the RCP 2.6 and 8.5 scenarios for the projected future climate. While a majority of studied basins is projected to experience a warmer and wetter climate, uncertainty in precipitation projections remains large in comparison to the temperature projections. Due to high uncertainty in ET, uncertainties in fraction of precipitation that is evaporated (ET/P) and a proxy for available water (P-ET) are also large under the projected future climate. Our assessment showed that under the RCP 8.5 scenario, global climate models are major contributors to uncertainties in ET (P-ET) simulations in the four (six) basins, while uncertainty due to hydrological models is prevailing or comparable in the other three (one) basins. The simulated ET is projected to increase under the warmer and wetter future climates in all the basins and periods under both RCPs. Regarding P-ET, it is projected to increase in five out of seven basins in the End term (2071–2099) under the RCP 8.5 scenario. Precipitation elasticity and temperature sensitivity estimated for ET were found to be positive in all the basins under the RCP 8.5 scenario. In contrast, the temperature sensitivity estimated for (P-ET) was found to be negative for all the basins under the RCP 8.5 scenario, indicating the role of increased energy availability and limited soil moisture. Our results highlight the need for improvements in climate and hydrological models with better representation of soil, vegetation, and cold season processes to reduce uncertainties in the projected ET and P-ET.
Resilience thinking in relation to the environment has emerged as a lens of inquiry that serves a platform for interdisciplinary dialogue and collaboration. Resilience is about cultivating the capacity to sustain development in the face of expected and surprising change and diverse pathways of development and potential thresholds between them. The evolution of resilience thinking is coupled to social-ecological systems and a truly intertwined human-environment planet. Resilience as persistence, adaptability, and transformability of complex adaptive social-ecological systems is the focus, clarifying the dynamic and forward-looking nature of the concept. Resilience thinking emphasizes that social-ecological systems, from the individual, to community, to society as a whole, are embedded in the biosphere. The biosphere connection is an essential observation if sustainability is to be taken seriously. In the continuous advancement of resilience thinking there are efforts aimed at capturing resilience of social-ecological systems and finding ways for people and institutions to govern social-ecological dynamics for improved human well-being, at the local, across levels and scales, to the global. Consequently, in resilience thinking, development issues for human well-being, for people and planet, are framed in a context of understanding and governing complex social-ecological dynamics for sustainability as part of a dynamic biosphere.
This invited article is a republication of Folke, C. 2016. "Resilience" of the Oxford Research Encyclopedia of Environmental Science (http://dx.doi.org/10.1093/acrefore/9780199389414.013.8)
Several studies have documented that regional climate warming and the resulting increase in drought stress have triggered increased tree mortality in semi-arid forests with unavoidable impacts on regional and global carbon sequestration. Although climate warming is projected to continue into the future, studies examining long-term resilience of semi-arid forests against climate change are limited. In this study, long-term forest resilience was defined as the capacity of forest recruitment to compensate for losses from mortality. We observed an obvious change in long-term forest resilience along a local aridity gradient by reconstructing tree growth trend, disturbance history and investigating post-disturbance regeneration in semi-arid forests in southern Siberia. In our study, with increased severity of local aridity, forests became vulnerable to drought stress, and regeneration first accelerated and then ceased. Radial growth of trees during 1900-2012 was also relatively stable on the moderately arid site. Furthermore, we found that smaller forest patches always have relatively weaker resilience under the same climatic conditions. Our results imply a relatively higher resilience in arid timberline forest patches than in continuous forests; however, further climate warming and increased drought could possibly cause the disappearance of small forest patches around the arid treeline. This study sheds light on climate change adaptation and provides insight into managing vulnerable semi-arid forests. This article is protected by copyright. All rights reserved.
Long-term (1901-2012) changes in hydroclimatic variables in the 18 Indian sub-continental basins were examined with hydrology simulated using the Variable Infiltration Capacity (VIC) model. Change point analysis using the Sequential Mann-Kendall test showed two distinct periods (1901-1947 and 1948-2012) for the domain averaged monsoon season (June to September) precipitation. Hydrologic changes for the entire water budget were estimated for both periods. In the pre-1948 period, a majority of the river basins experienced increased monsoon season precipitation, evapotranspiration, and surface water availability (as defined by total runoff). Alternatively, in the post-1948 period, monsoon season precipitation declined in 11 of the 18 basins, with statistically significant trends in one (the Ganges basin), and most (15) basins experienced significant warming trends. Additionally, in the post-1948 period the mean monsoon season evapotranspiration (ET) and surface water availability declined in eight (with significant declines in four) basins. Our results indicate that changes in ET and surface water availability in the pre and post 1948 periods were largely driven by the changes in the monsoon season precipitation rather than air temperature, despite prominent warming after 1975. Coupled modes of variability of sea surface temperature (SST) and surface water availability indicated El Nino Southern Oscillation (ENSO) as the leading mode. The second mode was identified as the trend mode for surface water availability in the sub-continental river basins, which was largely driven by SST anomalies in the Indian and Atlantic Ocean regions. This indicates that surface water availability in India’s sub-continental basins may be affected in the future in response to changes in large scale climate variability.
Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland.
Drought characteristics for the Indian monsoon region are analyzed using two different datasets and standard precipitation index (SPI), standardized precipitation-evapotranspiration index (SPEI), Gaussian mixture model-based drought index (GMM-DI), and hidden Markov model-based drought index (HMM-DI) for the period 1901–2004. Drought trends and variability were analyzed for three epochs: 1901–1935, 1936–1971 and 1972–2004. Irrespective of the dataset and methodology used, the results indicate an increasing trend in drought severity and frequency during the recent decades (1972–2004). Droughts are becoming more regional and are showing a general shift to the agriculturally important coastal south-India, central Maharashtra, and Indo-Gangetic plains indicating higher food security and socioeconomic vulnerability in the region.
Climate change may pose profound implications for hydrologic processes in Indian sub-continental river basins. Using downscaled and bias corrected future climate projections and the Soil Water Assessment Tool (SWAT), we show that a majority of the Indian sub-continental river basins are projected to shift towards warmer and wetter climate in the future. During the monsoon (June to September) season, under the representative concentration pathways (RCP) 4.5 (8.5), the ensemble mean air temperature is projected to increase by more than 0.5 (0.8), 1.0 (2.0), and 1.5 (3.5) ºC in the Near (2010-2039), Mid (2040-2069), and End (2070-2099) term climate, respectively. Moreover, the sub-continental river basins may face an increase of 3-5ºC in the post-monsoon season under the projected future climate. While there is a large intermodel uncertainty, robust increases in precipitation are projected in many sub-continental river basins under the projected future climate especially in the Mid and End term climate. A sensitivity analysis for the Ganges and Godavari river basins shows that surface runoff is more sensitive to change in precipitation and temperature than that of evapotranspiration (ET). An intensification of the hydrologic cycle in the Indian sub-continental basins is evident in the projected future climate. For instance, for Mid and End term climate, ET is projected to increase up to 10% for the majority of the river basins under both RCP 4.5 and 8.5 scenarios. During the monsoon season, ensemble mean surface runoff is projected to increase more than 40% in 11 (15) basins under the RCP 4.5 (8.5) scenarios by the end of the 21st century. Moreover, streamflow is projected to increase more than 40% in 8 (9) basins during the monsoon season under the RCP 4.5 (8.5) scenarios. Results show that water availability in the sub-continental river basins is more sensitive towards changes in the monsoon season precipitation rather than air temperature. While in the majority of the sub-continental river basins, water availability is projected to increase, spatial and temporal (interannual) variability in the monsoon season precipitation under the projected future climate may play a significant role. Changes in the hydrologic processes under the projected future climate indicate that substantial efforts may be required to develop water management strategies in the Indian sub-continental river basins in the future.
The study discusses development of a new daily gridded rainfall data set (IMD4) at a high spatial resolution (0.25° × 0.25°, latitude × longitude) covering a longer period of 110 years (1901-2010) over the Indian main land. A comparison of IMD4 with 4 other existing daily gridded rainfall data sets of different spatial resolutions and time periods has also been discussed. For preparing the new gridded data, daily rainfall records from 6955 rain gauge stations in India were used, highest number of stations used by any studies so far for such a purpose. The gridded data set was developed after making quality control of basic rain-gauge stations. The comparison of IMD4 with other data sets suggested that the climatological and variability features of rainfall over India derived from IMD4 were comparable with the existing gridded daily rainfall data sets. In addition, the spatial rainfall distribution like heavy rainfall areas in the orographic regions of the west coast and over northeast, low rainfall in the lee ward side of the Western Ghats etc. were more realistic and better presented in IMD4 due to its higher spatial resolution and to the higher density of rainfall stations used for its development.
Water use efficiency (WUE; gross primary production [GPP]/evapotranspiration [ET]) estimates the tradeoff between carbon gain and water loss during photosynthesis and is an important link of the carbon and water cycles. Understanding the spatiotemporal patterns and drivers of WUE is helpful for projecting the responses of ecosystems to climate change. Here we examine the spatiotemporal patterns, trends, and drivers of WUE at the global scale from 2000 to 2013 using the gridded GPP and ET data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our results show that the global WUE has an average value of 1.70 g C/kg H2O with large spatial variability during the 14-year period. WUE exhibits large variability with latitude. WUE also varies much with elevation: it first remains relatively constant as the elevation varies from 0 to 1000 m and then decreases dramatically. WUE generally increases as precipitation and specific humidity increase; whereas it decreases after reaching maxima as temperature and solar radiation increases. In most land areas, the temporal trend of WUE is positively correlated with precipitation and specific humidity over the 14-year period; while it has a negative relationship with temperature and solar radiation related to global warming and dimming. On average, WUE shows an increasing trend of 0.0025 g C·kg-1 H2O·yr-1 globally. Our global-scale assessment of WUE has implications for improving our understanding of the linkages between the water and carbon cycles and for better projecting the responses of ecosystems to climate change.
Water use efficiency (WUE) measures the trade-off between carbon gain and water loss of terrestrial ecosystems, and better understanding its dynamics and controlling factors is essential for predicting ecosystem responses to climate change. We assessed the magnitude, spatial patterns, and trends of WUE of China's terrestrial ecosystems and its responses to drought using a process-based ecosystem model. During the period from 2000 to 2011, the national average annual WUE (net primary productivity (NPP)/evapotranspiration (ET)) of China was 0.79 g C kg(-1) H2O. Annual WUE decreased in the southern regions because of the decrease in NPP and the increase in ET and increased in most northern regions mainly because of the increase in NPP. Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. "Turning-points" were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE. The cumulative lagged effect of drought on monthly WUE varied by region. Our findings have implications for ecosystem management and climate policy making. WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity.
Great advances have been made in the last decade in quantifying and understanding the spatio-temporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available datasets predict the spatio-temporal patterns of GPP, identify the differences among datasets, and highlight the main advantages/disadvantages of each dataset. We compare GPP estimates for the historical period (1990–2009) from two observation-based datasets (MTE, MODIS) to coupled carbon–climate models and terrestrial carbon cycle models from the CMIP5 and TRENDY projects, and to a new hybrid dataset (CARBONES). Results show a large range in the mean global GPP estimates. The different datasets broadly agree on GPP seasonal cycle in terms of phasing, while there are still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based datasets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.
A better understanding of ecosystem water-use efficiency (WUE) will help us improve ecosystem management for mitigation as well as adaption to global hydrological change. Here, long-term flux tower observations of productivity and evapotranspiration allow us to detect a consistent latitudinal trend in WUE, rising from the subtropics to the northern high-latitudes. The trend peaks at approximately 51°N, and then declines toward higher latitudes. These ground-based observations are consistent with global-scale estimates of WUE. Global analysis of WUE reveals existence of strong regional variations that correspond to global climate patterns. The latitudinal trends of global WUE for Earth's major plant functional types reveal two peaks in the Northern Hemisphere not detected by ground-based measurements. One peak is located at 20° ~ 30°N and the other extends a little farther north than 51°N. Finally, long-term spatiotemporal trend analysis using satellite-based remote sensing data reveals that land-cover and land-use change in recent years has led to a decline in global WUE. Our study provides a new framework for global research on the interactions between carbon and water cycles as well as responses to natural and human impacts.
Using satellite observations of Normalized Difference Vegetation Index together with climate data from other sources in a terrestrial biosphere model, inter-annual variability of Net Primary Productivity (NPP) over India during 1981–2006 was studied. It is revealed that the variability is large over mixed shrub and grassland (MGL), moderate over cropland and small over the forest regions. Inter-annual variability of NPP exhibits strong positive coherence with the variability of precipitation, and weak coherence with the variability of temperature and solar radiation. Estimated linear growth rate of annual NPP is 0.005 Pg C Yr−2 which is equivalent to 8.5% over the country during past 25 years. This increase is primarily due to the enhancement of productivity over agricultural lands in the country. NPP has increased over most parts of the country during the early 15-year period (1981–1995) resulting in a 10% growth rate of national NPP budget. On the other hand, the NPP growth rate has been reduced to 2.5% during later 15 years period (1991–2005) owing to large decline of NPP over the Indo-Gangetic plains. Climate had a strong control on NPP growth rate during both the periods. Copyright © 2012 Royal Meteorological Society
Significance
Understanding the location of carbon sources and sinks is essential for accurately predicting future changes in atmospheric carbon dioxide and climate. Mid- to high-latitude terrestrial ecosystems are well known to be the principal carbon sink regions, yet less attention has been paid to the mid- to low-latitude ecosystems. In this study, long-term eddy covariance observations demonstrate that there is a high carbon dioxide uptake (net ecosystem productivity) by the mid- to low-latitude East Asian monsoon subtropical forests that were shaped by the uplift of the Tibetan Plateau. Increasing nitrogen deposition, a young forest age structure, and sufficient water and heat availability combined to contribute to this large carbon dioxide uptake.
Globalization, the process by which local social-ecological systems (SESs) are becoming linked in a global network, presents policy scientists and practitioners with unique and difficult challenges. Although local SESs can be extremely complex, when they become more tightly linked in the global system, complexity increases very rapidly as multi-scale and multi-level processes become more important. Here, we argue that addressing these multi-scale and multi-level challenges requires a collection of theories and models. We suggest that the conceptual domains of sustainability, resilience, and robustness provide a sufficiently rich collection of theories and models, but overlapping definitions and confusion about how these conceptual domains articulate with one another reduces their utility. We attempt to eliminate this confusion and illustrate how sustainability, resilience, and robustness can be used in tandem to address the multi-scale and multi-level challenges associated with global change.
Terrestrial plants remove CO2 from the atmosphere through photosynthesis, a process that is accompanied by the loss of water vapour from leaves. The ratio of water loss to carbon gain, or water-use efficiency, is a key characteristic of ecosystem function that is central to the global cycles of water, energy and carbon. Here we analyse direct, long-term measurements of whole-ecosystem carbon and water exchange. We find a substantial increase in water-use efficiency in temperate and boreal forests of the Northern Hemisphere over the past two decades. We systematically assess various competing hypotheses to explain this trend, and find that the observed increase is most consistent with a strong CO2 fertilization effect. The results suggest a partial closure of stomata-small pores on the leaf surface that regulate gas exchange-to maintain a near-constant concentration of CO2 inside the leaf even under continually increasing atmospheric CO2 levels. The observed increase in forest water-use efficiency is larger than that predicted by existing theory and 13 terrestrial biosphere models. The increase is associated with trends of increasing ecosystem-level photosynthesis and net carbon uptake, and decreasing evapotranspiration. Our findings suggest a shift in the carbon- and water-based economics of terrestrial vegetation, which may require a reassessment of the role of stomatal control in regulating interactions between forests and climate change, and a re-evaluation of coupled vegetation-climate models.
As part of the National Communication (NATCOM) project undertaken by the Ministry of Environment and Forests, Government of India, the present study has been taken up to quantify the impact of the climate change on the water resources of Indian river systems. The study uses the HadRM2 daily weather data to determine the spatio-temporal water availability in the river systems. A distributed hydrological model namely SWAT (Soil and Water Assessment Tool) has been used. Simulation over 12 river basins of the country has been made using 40 years (20 years belonging to control or present and 20 years for GHG (Green House Gas) or future climate scenario) of simulated weather data. The initial analysis has revealed that under the GHG scenario, severity of droughts and intensity of floods in various parts of the country may get deteriorated. Moreover, a general reduction in the quantity of the available runoff has been predicted under the GHG scenario. This paper presents the detailed analyses of two river basins predicted to be worst affected (one with respect to floods and the other with respect to droughts).
Until recently, continuous monitoring of global vegetation productivity has not been possible because of technological limitations.
This article introduces a new satellite-driven monitor of the global biosphere that regularly computes daily gross primary
production (GPP) and annual net primary production (NPP) at 1-kilometer (km) resolution over 109,782,756 km2 of vegetated land surface. We summarize the history of global NPP science, as well as the derivation of this calculation,
and current data production activity. The first data on NPP from the EOS (Earth Observing System) MODIS (Moderate Resolution
Imaging Spectroradiometer) sensor are presented with different types of validation. We offer examples of how this new type
of data set can serve ecological science, land management, and environmental policy. To enhance the use of these data by nonspecialists,
we are now producing monthly anomaly maps for GPP and annual NPP that compare the current value with an 18-year average value
for each pixel, clearly identifying regions where vegetation growth is higher or lower than normal.
Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975-1998), and drier, warmer conditions in the early twenty-first century (2000-2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUE(e): above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUE(e) in drier years that increased significantly with drought to a maximum WUE(e) across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought-that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUE(e) may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.
Water-use efficiency (WUE) has been recognized as an important characteristic of ecosystem productivity, which links carbon (C) and water cycling. However, little is known about how WUE responds to climate change at different scales. Here, we investigated WUE at leaf, canopy, and ecosystem levels under increased precipitation and warming from 2005 to 2008 in a temperate steppe in Northern China. We measured gross ecosystem productivity (GEP), net ecosystem CO2 exchange (NEE), evapotranspiration (ET), evaporation (E), canopy transpiration (Tc), as well as leaf photosynthesis (Pmax) and transpiration (Tl) of a dominant species to calculate canopy WUE (WUEc=GEP/T), ecosystem WUE (WUEgep=GEP/ET or WUEnee=NEE/ET) and leaf WUE (WUEl=Pmax/Tl). The results showed that increased precipitation stimulated WUEc, WUEgep and WUEnee by 17.1%, 10.2% and 12.6%, respectively, but decreased WUEl by 27.4%. Climate warming reduced canopy and ecosystem WUE over the 4 years but did not affect leaf level WUE. Across the 4 years and the measured plots, canopy and ecosystem WUE linearly increased, but leaf level WUE of the dominant species linearly decreased with increasing precipitation. The differential responses of canopy/ecosystem WUE and leaf WUE to climate change suggest that caution should be taken when upscaling WUE from leaf to larger scales. Our findings will also facilitate mechanistic understanding of the C–water relationships across different organism levels and in projecting the effects of climate warming and shifting precipitation regimes on productivity in arid and semiarid ecosystems.
Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of NPP over the surrounding landscape offer opportunities for validating the MODIS NPP and GPP products, but these flux measurements must be scaled over areas on the order of 25 km2 to make effective comparisons to the MODIS products. Here, we report results for such comparisons at 9 sites varying widely in biome type and land use. The sites included arctic tundra, boreal forest, temperate hardwood forest, temperate conifer forest, tropical rain forest, tallgrass prairie, desert grassland, and cropland. The ground-based NPP and GPP surfaces were generated by application of the Biome-BGC carbon cycle process model in a spatially-distributed mode. Model inputs of land cover and leaf area index were derived from Landsat data. The MODIS NPP and GPP products showed no overall bias. They tended to be overestimates at low productivity sites — often because of artificially high values of MODIS FPAR (fraction of photosynthetically active radiation absorbed by the canopy), a critical input to the MODIS GPP algorithm. In contrast, the MODIS products tended to be underestimates in high productivity sites — often a function of relatively low values for vegetation light use efficiency in the MODIS GPP algorithm. A global network of sites where both NPP and GPP are measured and scaled over the local landscape is needed to more comprehensively validate the MODIS NPP and GPP products and to potentially calibrate the MODIS NPP/GPP algorithm parameters.
The objective of this research is to develop a global remote sensing evapotranspiration (ET) algorithm based on Cleugh et al.'s [Cleugh, H.A., R. Leuning, Q. Mu, S.W. Running (2007) Regional evaporation estimates from flux tower and MODIS satellite data. Remote Sensing of Environment 106, page 285–304- 2007 (doi: 10.1016/j.rse.2006.07.007).] Penman–Monteith based ET (RS-PM). Our algorithm considers both the surface energy partitioning process and environmental constraints on ET. We use ground-based meteorological observations and remote sensing data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to estimate global ET by (1) adding vapor pressure deficit and minimum air temperature constraints on stomatal conductance; (2) using leaf area index as a scalar for estimating canopy conductance; (3) replacing the Normalized Difference Vegetation Index with the Enhanced Vegetation Index thereby also changing the equation for calculation of the vegetation cover fraction (FC); and (4) adding a calculation of soil evaporation to the previously proposed RS-PM method.
Climate change affects forests both directly and indirectly through disturbances. Disturbances are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. When disturbances exceed their natural range of variation, the change in forest structure and function may be extreme. Each disturbance affects forests differently. Some disturbances have tight interactions with the species and forest communities which can be disrupted by climate change. Impacts of disturbances and thus of climate change are seen over a board spectrum of spatial and temporal scales. Future observations, research, and tool development are needed to further understand the interactions between climate change and forest disturbances.