No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Drought risk assessment on arid region under different socioeconomic scenarios: A case of Loess Plateau, China
ResearchGate has not been able to resolve any citations for this publication.
Urbanization exerts considerable impact on ecological, environmental and meteorological processes and systems. However, the effects of urbanization on local drought remain under-explored. Here we characterize the effects of urbanization on drought across the world’s cities using global weather station observations. We find that drought severity has increased at ~36% of global sites, while the extreme (less than a fifth) Standardized Precipitation Evapotranspiration Index has increased at ~43% of the city sites globally. We investigate the primary driving mechanisms behind drought exacerbation using physics-based weather research and forecasting model simulations. We find that urbanization induced warmer and drier urban environments, which has suppressed light rainfall and aggravated extreme local drought conditions. Furthermore, mid-twenty-first century CMIP6 projections indicate that nearly 57 and 70% of urban regions would consistently suffer exacerbated drought severity and extreme Standardized Precipitation Evapotranspiration Index due to urban expansion. Our findings highlight cities causing rainfall extremes and call for heightened attention to urban drought preparedness in the face of continued urbanization, population growth and climate change.
Drought events, in combination with social, economic, and environmental issues such as food prices, limited access to water, and soil degradation, have made farmers more vulnerable in society. Therefore, focusing on traditional, conventional, and organic agricultural systems, this study evaluates social, economic, and environmental aspects of drought events along with the impacts of adaptation strategies on them simultaneously and globally. According to the findings, hydrological droughts have an average economic impact of approximately 1.2% on traditional agricultural systems. Furthermore, drought has significant socioeconomic effects, causing a 1.9% decrease in average livelihood in organic agricultural systems. However, drought does not have a statistically significant impact on conventional agriculture. The findings also revealed that conventional agriculture depends on expensive off-farm inputs that use large quantities of non-renewable fossil fuels. In addition, the selection of adaptation strategies in traditional agricultural systems led to an improvement in the economy (0.14%), livelihood (0.86%), and environment (0.62%). Overall, this study highlights the importance of examining different agricultural systems and their geographical distributions into account, through a global lens when assessing the impact of adaptation strategies to drought.
Vegetation dynamics result from the interaction between human activities and climate change. Numerous studies have investigated the contributions of human activities and climate change to vegetation cover dynamics using statistical methods. However, these studies have not focused much on the spatially non-stationary effects of human activities on vegetation cover changes and future trends. Taking the Three Gorges Reservoir (TGR) area as the case study area, it was divided into 32 combinations by considering the spatially varying effects of five factors related to human activity and climate change, including gross domestic product (GDP), population, land use change, precipitation, and temperature. Regression in terms of pixels was then performed for each combination at the pixel scale. The result showed that from 2001 to 2020, the annual average normalized digital vegetation index (NDVI) in the TGR area exhibited an upward trend (slope = 0.0051, p < 0.01), with the mean NDVI increasing from 0.53 to 0.64. Compared with the regression with climate variables, the proposed model improved the value from 0.2567 to 0.6484, with the p-value in the t-test reduced from 0.2579 to 0.0056. It indicated that changes in vegetation were dominated by human activities and climate change in 48.77% and 3.19% of the TGR area, respectively, and 43.70% of the vegetation coverage was dominated by both human activities and climate change. This study also predicted the future NDVI according to the shared socioeconomic pathways (SSPs) and representative concentration pathway (RCP) scenarios provided by the Intergovernmental Panel on Climate Change. It suggests that, assuming future regional policies are the same as the historical policies in the TGR, the SSP5–8.5 scenario would have the highest and fastest growth in average NDVI, with the average NDVI increasing from 0.68 to 0.89, because of the large increase in the GDP, lower population in this scenario, and adequate hydrothermal conditions.
Increased human activities in China’s coastal zone have resulted in the depletion of ecological land resources. Thus, conducting current and future multi-scenario simulation research on land use and land cover change (LUCC) is crucial for guiding the healthy and sustainable development of coastal zones. System dynamic (SD)-future land use simulation (FLUS) model, a coupled simulation model, was developed to analyze land use dynamics in China’s coastal zone. This model encompasses five scenarios, namely, SSP1-RCP2.6 (A), SSP2-RCP4.5 (B), SSP3-RCP4.5 (C), SSP4-RCP4.5 (D), and SSP5-RCP8.5 (E). The SD model simulates land use demand on an annual basis up to the year 2100. Subsequently, the FLUS model determines the spatial distribution of land use for the near term (2035), medium term (2050), and long term (2100). Results reveal a slowing trend in land use changes in China’s coastal zone from 2000–2020. Among these changes, the expansion rate of construction land was the highest and exhibited an annual decrease. By 2100, land use predictions exhibit high accuracy, and notable differences are observed in trends across scenarios. In summary, the expansion of production, living, and ecological spaces toward the sea remains prominent. Scenario A emphasizes reduced land resource dependence, benefiting ecological land protection. Scenario B witnesses an intensified expansion of artificial wetlands. Scenario C sees substantial land needs for living and production, while Scenario D shows coastal forest and grassland shrinkage. Lastly, in Scenario E, the conflict between humans and land intensifies. This study presents pertinent recommendations for the future development, utilization, and management of coastal areas in China. The research contributes valuable scientific support for informed, long-term strategic decision making within coastal regions.
Sustaining or enhancing nature’s contributions to people (NCPs) requires a comprehensive understanding of both nature’s contributions and people’s needs. However, the 2 aspects for water-related NCPs are spatially mismatched. We introduced an assessment framework for water-related NCPs from a spatial flow perspective, considering the local nature’s contributions assessed using the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model, as well as people’s needs in the downstream assessed via a distance decay method. We assessed 3 water-related NCPs’ spatial distribution and correlation on the Loess Plateau from 2000 to 2020, where a large-scale ecological restoration was implemented that may affect downstream people. The results showed that NCP6 (downstream needs from water yield) showed no increasing trend in the majority watersheds over the past 20 years, in contrast to NCP7 (downstream needs from water purification) and NCP8 (downstream needs from soil conservation). There are spatial synergies among NCP6, NCP7, and NCP8. From 2000 to 2020, the spatial synergy between NCP7 and NCP8 increased while decreased between other NCPs. The temporal dynamics of NCP6 and NCP8 showed a trade-off, while NCP6 and NCP7 showed a synergy. NCP7 and NCP8, in turn, showed a transition from synergy to trade-off. Guided by nature’s contributions and people’s needs, we proposed 3 ecological measures: thinning and intermediate cutting measures, control nonpoint source pollution, and soil and water conservation projects to promote ecological restoration. This assessment can offer multifunctional guidance for planning ecological conservation and restoration in the upstream based on people’s needs in the downstream.
Early warning systems (EWS) are broadly regarded as crucial components of disaster risk reduction strategies and action plans. Desertification, a significant land degradation process, is accompanied by detrimental environmental and socioeconomic consequences. However, no operational web-based system has yet been designed to effectively mitigate the impacts of desertification. Consequently, the design and development of web-based early warning systems for desertification could serve as an effective step toward achieving the United Nations Sustainable Development Goals (SDGs) and enhancing environmental risk management in desertification-prone countries. The aim of this research is to introduce an online, integrated, people-centred, model-based early warning system for desertification. This system represents a comprehensive knowledge-based platform predicated on four vital components: risk assessment, monitoring, stakeholder awareness-raising, and the provision of management strategies. The key components of early warning desertification systems include: 1-risk assessment based on global models, 2-monitoring of spatiotemporal indicators based on regional conditions, 3-awareness-building among stakeholders through ICT infrastructure, and 4-provision of management strategies grounded in conceptual models such as SWOT and DPSIR. The significance of this research lies in the fact that web-based systems enhance access to data and accelerate communication with and among stakeholders. Online systems also facilitate the creation of comprehensive databases, which has consistently posed a challenge for warning systems. While these systems are still in their initial stages of design and implementation, they offer unique opportunities to researchers and managers. As tools and applications continue to evolve, web-based early warning systems for desertification have the potential to substantially mitigate the human and financial impacts of hazards.
Droughts continuously threaten human life, livestock, and agriculture across the Horn of Africa (HOA). As climate change exacerbates drought frequency and severity, accurately quantifying spatiotemporal drought patterns is critical to developing evidence-based policies that mitigate impacts and build resilience among vulnerable communities. This study conducted a spatiotemporal analysis of soil moisture drought over the HOA, utilizing high-resolution ERA5 reanalysis data between 1951 and 2020. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated at 3-, 6-, 9-, and 12-month timescales to identify historical drought events and assess drought duration and intensity changes over 70 years. Spatial analysis revealed decreasing soil moisture levels across HOA, with the most substantial reductions of 45% occurring in Djibouti and Northern Somalia. Comparisons between the baseline period (1951–1985) and the recent period (1986–2020) showed increasingly negative SPEI intensities, indicating a shift towards drier conditions, especially in Somalia, Kenya, and Ethiopia. The results also pointed to rising frequencies of moderate droughts by around 15% and severe droughts by 5–10% from 1986 to 2020 in the baseline period. The findings can inform policy to improve regional drought monitoring systems and the development of climate-resilient agriculture strategies, water resource management, and disaster risk reduction planning to protect lives and food security.
Water management in mountainous regions faces significant challenges due to deep uncertainties arising from data scarcity, knowledge gaps, and the complex interplay of climate and socio-economic changes. While existing approaches focused on uncertainty reduction and water system optimization contribute to managing uncertainties, they often require probability distributions that can be difficult to obtain in data-scarce mountain regions. To address these challenges, we demonstrate the effectiveness of Exploratory Modeling and Analysis (EMA) in assessing water management strategies and identifying operational ranges that avoid future water scarcity. Through a case study in the complex and data-scarce Peruvian Andes, we employed EMA to run 12,000 simulations by 2050, incorporating deep uncertainties from climate and socio-economic scenarios, and hydrological modeling parameters. This analysis identified specific policy combinations demonstrating greater robustness across diverse scenarios and uncertainties. EMA explicitly identifies operational ranges of policies to avoid water scarcity but also highlights the conditions that might trigger policy failure. We also delve into the roles of the different factors used in EMA and their significance in water management applications. Our research illustrates that an exploratory hydrological modeling approach based on robust decision-making can foster a more informed decision-making process for long-term water adaptation in rapidly changing mountain regions under data scarcity and deep uncertainties.
The incidence and magnitude of hazards in Africa are escalating. Extant knowledge base of disaster risk (DR) trends, factors, and hotspots is lacking for the continent. Here we applied random forest machine learning regressions, spatial stratified het-erogeneity, and hotspot analyses on INFORM data to identify DR patterns, factors and interactions, and notable risk hotspots. We show that although DR is generally decreasing in Africa, the Eastern, Southern, and Western regions record increasing DR. Physical exposure to floods, epidemics, and violent conflicts are hazard drivers of DR in Africa. Other significant DR drivers are mostly clustered under vulnerable groups and poor infrastructural coping capacities. Human hazards interact with other factors, exhibiting the highest influences on DR. Precisely, 19 out of 53 African countries in this study are DR hotspots. Eritrea is identified as a new hotspot. Targeted policies, resilience building, vulnerability reduction measures and comprehensive sustainability-infused solutions are required for DR reduction and sustainable development in Africa.
KEYWORDS: Africa, disaster risk assessment, disaster risk reduction, resilience, sustainable development, vulnerability
Under climate change, drought assessment, which can address nonstationarity in drought indicators and anthropogenic implications, is required to mitigate drought impacts. However, the development of drought indices for a reliable drought assessment is a challenging task in the warming climate. Thus, this study discusses factors that should be considered in developing drought indices in changing climate. Inconsistent drought assessment can be obtained, depending on the baseline period defined in developing drought indices. Therefore, the baseline period should represent the contemporary climate but should also correspond to long enough observations for stable parameter estimation. The importance of accurate potential evapotranspiration (PET) for drought indices becomes higher under a warming climate. Although the Penman–Monteith method yields accurate PET values, depending on the climate and vegetation cover, other suitable PET formulas, such as the Hargreaves method, with fewer hydrometeorological data can be used. Since a single drought index is not enough to properly monitor drought evolution, a method that can objectively combine multiple drought indices is required. Besides, quantifying anthropogenic impacts, which can add more uncertainty, on drought assessment is also important to adapt to the changing drought conditions and minimize human-induced drought. Drought is expected to occur more frequently with more severe, longer, and larger areal extent under global warming, since a more arid background, which climate change will provide, intensifies land–atmosphere feedback, leading to the desiccation of land and drying atmosphere. Thus, an accurate drought assessment, based on robust drought indices, is required.
In recent years, extreme precipitation events have shown a significant increasing trend in both intensity and amount. Therefore, it is urgent to delineate the areas vulnerable to extreme precipitation and formulate more reasonable measures to reduce the risk of extreme precipitation. In this study, we selected gross domestic product, population, nighttime light, normalized difference vegetation index, runoff depth, and relief degree of land surface data to comprehensively characterize surface vulnerability. We selected the 90, 95, and 99% precipitation quantiles and their occurrence frequencies in the historical and future periods as hazard factors, and calculated the extreme precipitation risks faced by different regions of China based on a risk calculation formula. The results indicate that the Qinghai-Tibet Plateau and urbanized regions such as the Yangtze River Delta are high-risk areas affected by extreme precipitation. The precipitation simulated by the Beijing Climate Center climate system model version 2 (BCC-CSM2-MR) global climate model selected in this study is relatively smaller than the historical precipitation, but it can basically reflect the actual spatial distribution characteristics of precipitation. Under four future climate scenarios, the joint occurrence probability of extreme precipitation will decrease, while high-risk areas of extreme precipitation will still be located in the Qinghai-Tibet Plateau and densely urbanized areas. This study systematically analyzed the spatial distribution characteristics of extreme precipitation risk under historical and future scenarios, providing theoretical support for the formulation of more reasonable measures to prevent extreme precipitation risk.
The main objective of this study was to analyze drought-induced agricultural livelihood vulnerability through a comprehensive assessment of agro-meteorological, biophysical, and socioeconomic variables in North Wollo. The study area has four main livelihood zones, namely, Abay Tekeze watershed (ATW), North Wollo east plain (NWEP), North Wollo highland belg (NWHB), and Northeast woina-dega mixed cereal (NEWMC). A total of 274 sample households were selected from all the livelihood zones by considering wealth rankings. A Survey questionnaire, supplemented with focus group discussions and key informant interviews, was used to collect the data. Principal component analysis was applied to determine the indicators and assign weights. Consequently, from 66 indicators 32 were prioritized to measure the exposure, sensitivity, and adaptive capacity of the system. Both the livelihood vulnerability framework (LVI) and vulnerability sourcebook approach (LVIVSBA) were applied to assess livelihood vulnerability. The results revealed that the entire study area was characterized by higher exposure (0.653) and higher sensitivity (0.632) scores to drought impacts, while it exhibited a lower adaptive capacity (0.37). In both approaches, NWHB obtained the highest vulnerability score (0.681/0.715) followed by NWEP (0.634/0.619), whilst ATW revealed the lowest (0.583/0.555) in LVI and LVIVSBA, respectively. Similarly, the poor (0.671/0.670), medium (0.589/0.593), and better-off (0.554/0.537) were relatively ordered from the highest to the lowest. In conclusion, differential livelihood vulnerability does exist across the livelihood zones and wealth groups. The major sub-components which worsen household’s vulnerability were access to irrigation, food self-sufficiency problem, scarcity of livestock fodder, poor access to basic infrastructure, lower livelihood diversification, inadequate economic resources, low educational status, lack of training and support. Hence, the study calls for decision-makers and development partners to develop context-specific planning and interventions that strengthen the farmers’ adaptive capacity and minimize their exposure and sensitivity to the issue.
1. The social–ecological trap is an emerging concept that describes situations in which self- reinforcing social and ecological feedbacks maintain or push a social–ecological system towards an undesirable state and threaten the sustainability of human societies. Understanding a system's feedback loops and identifying the leading factors of such traps is essential to develop effective management strategies to warn, avoid and escape traps.
2. To better understand the dynamics of social–ecological traps, we developed a quantitative diagnostic framework that combines the social–ecological network approach and composite system state index. We demonstrated the effectiveness of the framework by examining the rural social–ecological evolution in China's Loess Plateau (LP) from 1949 to 2020, an area once faced with severe social–ecological challenges such as soil erosion, land degradation and poverty.
3. Our analysis identified three stages of trap dynamics in LP: locked in the trap (1949– 1981), reacting to the trap (1981–2003) and escaping the trap (2003–2020). In the first stage, LP was locked into an undesirable trajectory where reinforcing feedback occurs between rapid population growth, limited livelihood opportunities, excessive reliance on agriculture and severe soil erosion. Our results also found that the LP has made significant progress in escaping this social–ecological trap during the 21st century through ecological restoration practices and socio- economic development.
4. Similar social–ecological traps are also observed in many other regions of the world, particularly in developing countries. Our analysis recommends three pathways for addressing social– ecological traps in the LP: (1) promoting urbanization and livelihood diversity, (2) implementing site-specific engineering measures (e.g. terraces and check dams in the LP) and (3) investing in ecological restoration programs. Escaping the trap is not the end of the story, but could be an early stage of another trap. Policymakers and managers should keep assessing and monitoring the policy practices and outcomes to avoid entering new trap situations.
A risk-based approach is more meaningful to quantify the effects of drought on crop yield given the randomness nature of past drought events, compared to the deterministic approach. However, the majority of these probabilistic studies are conducted at national or global scale to assess the yield loss probability under given drought conditions. There is still a lack of research combining droughts and crop yields in a probabilistic way at a local scale. Moreover, it is unclear how drought threshold triggering yield loss at a given conditional probability will vary in dryland cropping regions. Here, we used wheat yield data from 66 shires in New South Wales (NSW) wheat belt and meteorological data from 986 weather stations. A copula-based probabilistic method was developed to explore the yield loss probability to various drought conditions. We investigated the drought threshold under a given yield loss probability using the constructed copula function. We found that SPEI-6 in October was the optimal drought index to represent detrended wheat yield variation as this period covered the main growth stages of winter wheat in the study region. Our results show that as the severity of drought increased, the wheat yield loss probability also increased. Yield loss probability varied among the study shires, mainly due to the various climate conditions of each region. The drought threshold in subregion 1 (the northwest) was highest, followed by subregion 2 (the southwest) and subregion 3 (the eastern), indicating that wheat yield in subregion 1 was more sensitive to drought. The findings could provide important direction and benchmarks for stakeholders in evaluating the agricultural impact of drought, especially in those drought prone areas. We expect that the methodological framework developed here can be extended to other dryland areas to provide helpful information to growers, risk management policy makers and agricultural insurance evaluators.
Freshwater blue spaces (FBS), such as ponds, are key elements of the urban landscape and are under strong anthropogenic pressure. Land-use types and diversity may exert a negative or positive impact on FBS’ water quality depending on their nature and arrangement. The information available in this respect is remarkably scarcer for water bodies in the Global South than for the north. Thus, we aim to identify and quantify the land-use types in a 500-m buffer zone of urban ponds in the Pampean region (Argentina) to assess their impact on water quality. We based our study on 15 FBS located in neighborhoods of Buenos Aires province during cold and warm seasons. We analyzed physical, chemical, and biological variables, and estimated water conditions by means of water quality indexes (WQIs) and quality guidelines. We quantified the dominant land-use type and the diversity of uses in the ponds’ buffer zones, and evaluated their relationships with WQIs. Our results showed that WQIs were negatively related to a high proportion of residential areas in the adjacent zone, while positively to recreational ones. The diversity of land uses did not influence the water quality. We propose a new WQIpond with fewer key response variables, and as sensitive as the currently used WQIobjetive. We conclude that water quality from urban ponds in the Pampean region can be affected by dominant land-use type in the adjacent area but also the quality of their water supply sources (superficial and/or underground), clandestine wastewater discharges, and non-point pollution.
Droughts cause enormous ecological, economical and societal damage, and they are already undergoing changes due to anthropogenic climate change. The issue of defining and quantifying droughts has long been a substantial source of uncertainty in understanding observed and projected trends. Atmosphere-based drought indicators, such as the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI), are often used to quantify drought characteristics and their changes, sometimes as the sole metric representing drought. This study presents a detailed systematic analysis of SPI- and SPEI-based drought projections and their differences for Great Britain (GB), derived from the most recent set of regional climate projections for the United Kingdom (UK). We show that the choice of drought indicator has a decisive influence on the resulting projected changes in drought frequency, extent, duration and seasonality using scenarios that are 2 and 4 ∘C above pre-industrial levels. The projected increases in drought frequency and extent are far greater based on the SPEI than based on the SPI. Importantly, compared with droughts of all intensities, isolated extreme droughts are projected to increase far more with respect to frequency and extent and are also expected to show more pronounced changes in the distribution of their event durations. Further, projected intensification of the seasonal cycle is reflected in an increasing occurrence of years with (extremely) dry summers combined with wetter-than-average winters. Increasing summer droughts also form the main contribution to increases in annual droughts, especially using the SPEI. These results show that the choice of atmospheric drought index strongly influences the drought characteristics inferred from climate change projections, with a comparable impact to the uncertainty from the climate model parameters or the warming level; therefore, potential users of these indices should carefully consider the importance of potential evapotranspiration in their intended context. The stark differences between SPI- and SPEI-based projections highlight the need to better understand the interplay between increasing atmospheric evaporative demand, moisture availability and drought impacts under a changing climate. The region-dependent projected changes in drought characteristics by two warming levels have important implications for adaptation efforts in GB, and they further stress the need for rapid mitigation.
A useful spatial pattern of cultivated land utilization in mountainous areas is a basic prerequisite for promoting efficient utilization of cultivated land and has a practical use for ensuring regional food security and rural revitalization. In this paper, we use Enshi and Lichuan cities as case studies and the PLUS model to analyze the spatial differentiation characteristics of cultivated land from 2000 to 2020. In addition, we simulated the spatial pattern of cultivated land in 2030 concerning the ecological priority scenario (scenario I) and the ecological and economic coordination scenario (scenario II). The results show that (1) the degree of cultivated land fragmentation from 2000 to 2020 is characterized as “high in the east and low in the west,” and the spatial aggregation of cultivated land decreases slightly over time and that there is a risk of increasing fragmentation of cultivated land in the future. (2) The complexity of cultivated land shape shows a fluctuating decrease between 2000 and 2030, and an overall trend of landscape homogenization. (3) The spatial distribution of cultivated land is concentrated in the peak cluster depressions and river valleys. The imbalance in the distribution of cultivated land has increased in the past two decades which should be curbed in the future. (4) In 2030, concerning the ecological priority development scenario, cultivated land use tends to evolve in the direction of balanced distribution and a relatively complex shape. (5) Concerning the coordinated ecological and economic development scenario, the spatial aggregation of cultivated land is higher and the patches of cultivated land are more regular, but the distribution imbalance is more serious. The results can provide scientific references for sustainable and effective use of cultivated land in mountainous areas.
Drought is a detrimental global warming effect that severely impacts the environment, society, and economy. Drought indices are used worldwide for drought monitoring and assessments. This study aims to develop a new meteorological drought index based on fuzzy logic (FL) and neuro-fuzzy models to describe and predict droughts. The developed models were compared to nine conventional drought indices and correlated with multiple drought indicators. Different combinations of inputs (such as maximum temperature, mean temperature, precipitation, and potential evapotranspiration) were tested to develop the models. Observed weather data from Alice Springs, Australia, were used to examine the developed models and train the adaptive neuro-fuzzy inference system (ANFIS) model. Additionally, historical records of various drought indicators were used to evaluate the predictions of all models, including deep soil moisture, lower soil moisture, root zone soil moisture, upper soil moisture, and runoff. This study showed that the rainfall anomaly drought index (RAI) was the best conventional drought index, with the highest correlation (0.718) between the drought index and upper soil moisture (drought indicator). The average of the best-performing FL models outperformed all conventional indices, with a correlation of 0.784 with the upper soil moisture. Moreover, when the average output of the best-performing FL models was used for training, the best ANFIS model had a correlation of 0.809 with upper soil moisture. The best ANFIS model in terms of correlation with conventional drought indices had a correlation of 0.941 with the RAI when the normalised average output of the best-performing conventional drought indices was used for training. To validate the developed models, drought assessment was conducted for five stations in different climate zones and seasons. The validation results showed that the developed models had similar performance to the best-correlated conventional drought index (RAI) in most cases. The developed models yielded better predictions compared to the conventional index in the subtropical and tropical regions. Overall, the developed soft computing drought indices based on fuzzy logic and ANFIS outperformed conventional methods, thus effectively contributing to more precise drought prediction and mitigation.
The effects of climate change (CC) have intensified in Ghana, especially in the Greater Accra region over the last two decades. CC assessment under the new IPCC scenarios and consistent local station data is limited. Consequently, CC assessment is becoming difficult in data-scarce regions in Ghana. This study utilizes six different Regional Climate Models under the 6th IPCC Report's Shared Socioeconomic Pathway scenarios (SSPs) of the CMIP6, which were bias-corrected with CMhyd over Greater Accra using ground station and PUGMF reanalysis data. The study reveals a reduction and potential shift in the intensity of precipitation in the region under the SSPs. Maximum temperature is expected to increase by 0.81-1.45 • C, 0.84-1.54 • C, 0.96-1.70 • C and 0.98-1.73 • C, while minimum temperature would likely increase by 1.33-2.02 • C, 1.49-2.22 • C, 1.71-4.75 • C and 1.75-4.83 • C under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Thus, temperature will likely increase, especially at night in the near future. Rising temperatures and changes in precipitation have impacts on all strata of society , from agricultural production to power generation and beyond. These findings can help
In order to control the desertification, large-scale afforestation programs have been attempted worldwide. Among them, China initiated the world’s largest afforestation program, Three-North Afforestation Program (TNAP, 1978–2050), in which the afforestation in sandy land has been questioned during the first 40 years. In fact, the contribution of the TNAP to vegetation establishment and its effectiveness in desertification control still remain unclear, which limited the further construction of the program. To answer the questions, we detected the dynamics of vegetation distribution (forest, shrubland, and grassland) and desertification status (slight, moderate, severe, and extremely severe) during 1978–2017 in the sandy land (45.5 million ha), by visual interpretation of 5-period remote sensing images with validation based on 3,100 sample plots from field surveys and 15,175 sample plots from the National Forest Resource Inventory. Vegetation degradation was identified by analysis combining the trends of net primary productivity and precipitation use efficiency. By Geographical Detector model, the driving forces of vegetation degradation (climate change, human activities, vegetation type, and sandy land type) were ranked and the contributions of the influential factors (climate change, human activities, and vegetation dynamics) to desertification changes were estimated. The results showed that for the 40 years, vegetation coverage increased by 0.5%, with increasing 113.8% and 338.8% of forest and shrubland, but decreasing 9.0% of grassland. Desertification area had little change while the overall intensity decreased. The TNAP contributed to desertification dynamics by 10.3%, which is lower than expected. Vegetation type was the dominant factor of vegetation degradation in general. Forest is less suitable for afforestation in sandy land than shrubland and grassland because of its lower stand establishment rate, higher degradation rate, and less contribution to desertification control. Thus, adjusting vegetation type to match local conditions (e.g., use shrub-land, grassland, and native species) and improving the vegetation resistance (e.g., transform monoculture forests into mixed forests, and make proper proportion for forest, shrubland, and grassland) was suggested. Our study provided specific and feasible strategies for further planning and implementation of TNAP, and references for vegetation restoration of sandy lands worldwide.
The National Ecological Barrier Zones are an important part of China’s ecological security strategy. The construction of a scientific and reasonable ecological security pattern (ESP) is important for the healthy development of national ecological barrier zones. The existing literature does not consider the impact of the potential changes in ecosystem health and land use on ESP construction. In this study, we considered a typical composite national ecological barrier area, the Sichuan-Yunnan ecological barrier, to analyze the ecosystem health of such areas; we considered the probability of future land growth change, circuit theory, and ecosystem service trade-off and synergy, to construct a sustainable ESP. Spatial heterogeneity was observed in the ecosystem health level of the Sichuan-Yunnan ecological barrier; the high-value areas of ecosystem health were mostly distributed in the central and southern parts of the study area, but the low-value areas were mostly distributed in the northeastern and western regions. The ESP contained 246 ecological sources (distributed in the forest and grassland contiguous areas in the south, central, and northeast regions), 563 ecological corridors that portrayed obvious differences in spatial distribution, 123 ecological pinchpoints, 231 ecological barriers, and topographic gradient characteristics. Based on this data, we proposed the relevant policy opinions on zoning control. The results show that incorporating trade-offs for ecosystem services into ecosystem health assessments can lead to a more effective selection of ecological sources. Meanwhile, the ESP constructed by using the probability of land growth changes to correct the resistance surface can more truly reflect the need for ESP construction under the future development trend. The research framework of “ecosystem health assessment that incorporates ecosystem service trade-offs - the probability of future land growth changes - circuit theory” could address the technical issues in constructing the ESP of compound large regional/national ecological barrier regions and key ecological function areas.
Abstract
Ecological well-being performance (EWP), a novel concept in sustainable development research, diverges from traditional ecological efficiency in terms of perspectives, core content, and driving factors. However, research on EWP remains insufficiently comprehensive, particularly the corresponding theoretical and methodological investigations into driving pathways. To address this gap, this study develops an “economy-environment-health” framework, incorporating air pollution and associated health losses into the evaluation system, and employs a two-stage Super-NSBM and Window DEA model for reevaluating EWP. The study further investigates the primary pathways of EWP, focusing on environmental regulations, technological innovation, and structural adjustments through both quantitative and qualitative methods. Quantitative spatial econometric analysis reveals that factors such as market-driven environmental regulations, green invention patents, and industrial and energy consumption structures significantly enhance EWP. While examining the “net effects” contributions of individual variables using spatial econometric models, the fsQCA method is employed to identify four effective driving paths for EWP from a configurational perspective. These paths are 1) technological innovation and structural adjustment under environmental regulations with public participation; 2) a combination of environmental regulation, technological innovation, and structural adjustment; 3) structural adjustment with minimal influence from environmental regulations and technological innovation; and 4) structural adjustment directed by market-incentive environmental regulations.
Highlights
•
A novel EWP evaluation is proposed within the "economy-environment-health" tri-dimensional framework.
•
A mixed methods that combines qualitative and quantitative analysis is applied.
•
EWP's driving sources are identified using a multidimensional classification method and SDM model.
•
Four effective driving paths for enhancing China's EWP are proposed by fsQCA.
Desertification in karst is an effect of climate change and not sustainable anthropogenic activities, the combination
of which, however, causes the gradual loss of karst natural resources, such as soil, vegetation, and
groundwater. A considerable percentage of global karst areas is found in drylands, characterized by negative
water balance and scarce presence of soils. High fragility of the karst environment, and its vulnerability to land
degradation and pollution because of the peculiar anisotropic setting, environmental dynamics, and of the direct
connection between the surface and the subsurface, are at the origin of the severe problems deriving from
desertification processes in karst. In addition to natural drivers, such as geology and topography, karst desertification
is generally due to four main factors, mostly or partly related to human activity: deforestation, improper
land use, groundwater overexploitation, and climate changes. Through the analysis of a collection of studies
conducted in several karst territories around the world, the present paper aims to provide an overview of the
processes leading to desertification risks in karst areas. Emphasizing the need to preserve these fragile environments,
characterized by peculiar features and precious freshwater resources, this review summarizes the main
situations at the global scale of rocky desertification in karst, at the same time providing indications for
developing innovative and multi-disciplinary approaches addressed toward mitigation of the risk related to
desertification in karst.
In the last 50 years, various parts of North Africa (NAF) have suffered devastating droughts, associated with high socio-economic impacts. This arid to semi-arid region is one of the most water-scarce areas in the world. In the context of water scarcity, many studies have focused on droughts approaching their impact from different disciplines and perspectives. However, more integrative studies covering both physical and social aspects are lacking for the region. The present study reviews drought's physical and human drivers, the associated socio-economic impacts in NAF countries, actual adaptation and management options. We summarize and intercompare management policies implemented by NAF governments to face the severity of such events. Our review highlights a contrasting vulnerability to droughts across the NAF countries, with relatively higher impacts in the western part. Studies show a lack of consistency about the observed increase in meteorological droughts severity and frequency in various regions of NAF. However, more consistent and slightly higher increases in agricultural drought intensity have been revealed, suggesting that the atmospheric evaporative demand due to the increased evapotranspiration has contributed to augmenting the severity of agricultural and ecological droughts compared to meteorological droughts. The North Atlantic Oscillation (NAO) is linked to dry and wet episodes in Northwest Africa from daily to centennial time scales. Changes in the planetary to the regional-scale circulation have been suggested to be responsible for the past and future projected drought increase. Other anthropogenic drivers, such as land use changes, increasing water demand and irrigation, strongly affect the severity of NAF droughts. The analysis of the historical events reveals extensive impacts on agriculture, employment, food security, health and internal migration. The adaptation strategies to drought include irrigation efficiency, groundwater overexploitation and the use of non-conventional water resources such as desalinated water. Various forms of drought monitoring and early warning operate on several institutional levels under the coordination of different institutions/ministries. An improved understanding of the characteristics of droughts and their impacts in NAF countries is important to guide the transition from emergency response to more proactive policies and long-term planning, but also to assess and identify gaps in drought management capacities.
As a complex natural disaster, drought encompasses significant and wide-ranging impacts on various environmental aspects. While meteorological, hydrological, agricultural, and socioeconomic droughts have been extensively studied, the scientific understanding of environmental droughts (the proposed fifth classification) remains relatively limited, hampering practical assessment efforts. To address this gap, the present study, for the first time, conducted a rigorous assessment of the applicability of a novel method, namely the heuristic method, in conjunction with a newly developed Environmental Drought Index (EDI). The present study thoroughly analyzed environmental drought events in India's Brahmani River basin, specifically focusing on the Jaraikela catchment. Firstly, the Minimum in-stream Flow Requirement (MFR) was determined using Tennant’s method to synthetically estimate discharge rates to maintain the optimum flow range during the historical period (1980–2014). Secondly, Drought Duration Length (DDL) was calculated by counting consecutive water deficit months with negative monthly Streamflow Rate (SFR) and MFR differences. Three General Circulation Models (GCMs) output ensembles, namely EC-Earth3, MPI-ESM1-2-HR, and MRI-ESM2-0, participating in CMIP-6, were used for past (1980–2014) and future periods (FP-1: 2015–2022, FP-2: 2023–2045) under emission scenarios SSP245 and SSP585. The HydroClimatic Conceptual Streamflow (HCCS) model was employed to simulate the historical and future SFR. Thirdly, the largest water deficit magnitude during DDL was used to estimate the Water Shortage Level (WSL). Finally, integrating DDL and WSL provided the EDI for each environmental drought event. Results demonstrated a strong correspondence between the simulated EDI obtained using MPI-ESM1-2-HR under SSP585 and the observed EDI values, thereby indicating the credibility of the EDI in assessing environmental droughts. Furthermore, the study found severe droughts (i.e., EDI-3) dominating (71–73% of all droughts; occurring during non-monsoonal months) during FP-2 under SSP585 across all three GCMs, differing from moderate droughts in SSP245 of FP-2, both scenarios of FP-1, and the historical period. Based on the findings, the study finally proposed several adaptive measures to mitigate the impacts of increasing environmental drought events in the catchment.
The question of whether environmental regulation fosters technological innovation and green development, as a
nuanced extension of the Porter hypothesis, constitutes a focal point in contemporary research. Despite this
attention, the literature often omits a multifaceted evaluation framework for green development and fails to
consider multiaspectual environmental regulation and technological innovation. This study develops a
comprehensive model of green total factor productivity (GTFP), situating the Chinese economy within an
economy–environment–health nexus. The extended Cr´ epon–Dugeut–Mairesse model is employed to revisit the
“strong”, “weak”, and “narrow” Porter hypotheses. The analysis reveals that formal environmental regulation
exerts a crowding-out effect on research and development (R&D), whereas informal environmental regulation
exhibits a facilitating effect, corroborating the narrow version of the Porter hypothesis. Both categories of
regulation contribute to substantial innovation. Following the incorporation of R&D factors, heterogeneity in the
“weak” Porter hypothesis emerges in the Chinese context, contingent upon specific types of environmental
regulation and technological innovation. Environmental regulation positively influences GTFP, affirming the
“strong” Porter hypothesis, primarily through the vector of technical progress change. A developmental trajec-
tory to enhance GTFP is thus articulated: judicious environmental regulation leads to R&D, which in turn fosters
innovation quality, subsequently affecting the technical progress change index and ultimately GTFP. Corre-
spondingly, policy recommendations are delineated across three dimensions: judicious environmental regulation,
targeted innovation support, and regional coordination.
Droughts have impacted human society throughout its history. However, the occurrence of severe drought events in the last century and the concerns on the potential effects of climate change have prompted remarkable advances in drought conceptualization and modeling in recent years. This review intends to present the state-of-the-art on drought characterization and propagation, as well as providing insights on how climate dynamics and anthropogenic activities might affect this phenomenon. For this purpose, we first address the distinct concepts of droughts and their relationships. Next, we present two frequently utilized methods based on the run theory for drought characterization and explain the development and recovery stages of droughts. Then, we discuss potential drivers for drought occurrence and propagation, with focus on meteorological factors, catchments' physical characteristics and human activities. Later, we describe how droughts can affect several parameters of water quality. This review also addressed flash droughts, encompassing their definitions, commonly used indices, and potential drivers. Finally, we briefly address the roles of climate change and long-term persistence on future drought scenarios. This review may be useful for researchers and stakeholders for attaining a broader understanding on drought dynamics and impacts.
In the summer of 2022, climate change significantly affected several parts of the world, causing drought in many countries. Drought is a natural hazard considered a significant future challenge for society and agriculture. Due to climate change, drought is predicted to become more frequent, last longer, and be more intense. This study aims to assess the drought risk priorities and evaluate the efficient solutions/strategies worldwide to achieve drought resilience. To achieve this, a comprehensive literature screening was performed to identify the drought impacts on the agriculture sector and the most commonly used adaptation techniques. A well-designed survey that targeted drought experts across the world was designed where they ranked both the identified drought impacts and the associated potential solutions. Finally, a participatory integrated innovative approach utilizing the failure Modes and Effects Analysis and 'Analytic Hierarchy Process (FMEA-AHP) was performed to assess the impact of drought risk factors and identify the best strategy accordingly. Results were presented to depict the drought effect on each agriculture sector in each county and even more in each geographical region worldwide. The research output provided a comprehensive vision of the drought risk priorities in each country with a direct link to reduction or adaptation strategies, which provide an efficient tool for the decision-maker and planner toward drought-resilient societies.
In recent years, rural-farmer families have encountered a higher level of vulnerability to drought than all other communities in the world including Iran. As well, their vulnerability has been intensified due to the gap in the previous research on resilience and the lack of a comprehensive program for their sustainability in drought conditions. To fill this gap, this research pursued two goals: (i) studying the resilience level of rural-farmer families in drought conditions and (ii) studying the factors underpinning resilience improvement. Given the drought severity in the region, the statistical population consisted of all rural farmers in Kerman province, southeastern Iran. Data were analyzed in the SPSS software package. The main research instrument was a questionnaire whose validity was confirmed by a panel of experts and its reliability was estimated by Cronbach's alpha. Rural households in the study had weak resilience and livelihood assets, and their situation worsened with increasing drought. The results also revealed a negative significant relationship between drought severity and the resilience of rural-farmer families. Furthermore, hierarchical regression analysis revealed that 24 indicators of livelihood assets (financial, social, human, natural, physical) accounted for 84% of the variance in improving rural households' resilience under drought conditions.
Scientific understanding of the driving relationship between water-related ecosystem services (WESs) and influencing factors, as well as the trade-off and synergy relationship between WESs and WESs, is the premise of reasonably bringing them into management decisions. However, the existing research often separates the above-mentioned two relationships and conducts independent research, which leads to the conflict of research conclusions and cannot be well adopted by managers. Therefore, based on the panel data of Loess Plateau in 2000-2019, this paper uses the simultaneous equation model to combine the two kinds of relationships existing between WESs and influencing factors, establish a feedback loop, and reveal the interactions mechanism of WESs nexus. The results show that: (1) The fragmentation of land use leads to the uneven spatial-temporal distribution of WESs. (2) Vegetation factors and land factors are the main driving factors that affect WESs, and the impact of climate factors on WESs is decreasing year by year. (3) The increase of water yield ecosystem services will lead to the obvious increase in soil export ecosystem services, and there is a synergistic relationship between soil export ecosystem services and nitrogen export ecosystem services. The conclusion can provide an important reference for implementing the strategy of ecological protection and high-quality development.
Canada's boreal forests, which occupy approximately 30% of boreal forests worldwide, play an important role in the global carbon budget. However, there is little quantitative information available regarding the spatiotemporal changes in the drought‐induced tree mortality of Canada's boreal forests overall and their associated impacts on biomass carbon dynamics. Here, we develop spatiotemporally explicit estimates of drought‐induced tree mortality and corresponding biomass carbon sink capacity changes in Canada's boreal forests from 1970 to 2020. We show that the average annual tree mortality rate is approximately 2.7%. Approximately 43% of Canada's boreal forests have experienced significantly increasing tree mortality trends (71% of which are located in the western region of the country), and these trends have accelerated since 2002. This increase in tree mortality has resulted in significant biomass carbon losses at an approximate rate of 1.51±0.29 MgC ha‐1 year‐1 (95% confidence interval) with an approximate total loss of 0.46±0.09 PgC year‐1 (95% confidence interval). Under the drought condition increases predicted for this century, the capacity of Canada's boreal forests to act as a carbon sink will be further reduced, potentially leading to a significant positive climate feedback effect.
Global warming can result in changes in droughts and hot events (or compound droughts and hot events, CDHEs), which can take a heavy toll on the society and environment. Recent studies have made substantial progress in the projection of these events. However, previous projection studies mostly focus on the concurrences of meteorological droughts and hot events but ignore the difference among various CDHEs. Specifically, the concurrence of hot events and different types of droughts (e.g., agricultural droughts and hydrological droughts) has been seldom explored from a hydrological perspective. Based on phase six of the Coupled Model Intercomparison Project (CMIP6), we evaluate changes in different types of CDHEs, including compound meteorological drought-hot events (CMDHEs), compound agricultural drought-hot events (CADHEs) and compound hydrological drought-hot events (CHDHEs), for different future periods at the global scale. Based on comparisons with data from Global Land Data Assimilation System Version 2 (GLDAS-2.0), CMIP6 can reproduce the overall spatial distribution and temporal variation of different CDHEs at the global scale. In addition, the frequency and spatial extent of the three compound events show a marked increase during different future periods relative to the base period 1995–2014. The projected increase in global average frequency of CMDHEs in the long term period is lower than that of CADHEs (increase by 73.74% and 113.95% for CMDHEs and CADHEs, respectively). The uncertainty in the simulation of CADHEs and CHDHEs is relatively larger than CMDHEs in the future periods over most regions. The results of this study highlight the urgent demand for adaptation measures of CDHEs to cope with compound extremes in the future.
As a sensitive region, identifying land cover change in drylands is critical to understanding global environmental change. However, the current findings related to land cover change in drylands are not uniform due to differences in data and methods among studies. We compared and judged the spatial and temporal characteristics, driving forces, and ecological effects by identifying the main findings of land cover change in drylands at global and regional scales (especially in China) to strengthen the overall understanding of land cover change in drylands. Four main points were obtained. First, while most studies found that drylands were experiencing vegetation greening, some evidence showed decreases in vegetation and large increases in bare land due to inconsistencies in the datasets and the study phases. Second, the dominant factors affecting land cover change in drylands are precipitation, agricultural activities, and urban expansion. Third, the impact of land cover change on the water cycle, especially the impact of afforestation on water resources in drylands, is of great concern. Finally, drylands experience severe land degradation and require dataset matching (classification standards, resolution, etc.) to quantify the impact of human activities on land cover.
The severity of potential drought impacts is influenced not only by physical characteristics, such as precipitation, soil moisture, and temperature but also by local socioeconomic conditions that influence a region's exposure and vulnerability. This study aims to demonstrate projected future global drought risk, which is quantified based on indicators representing three risk components, namely, hazard, exposure, and vulnerability. Drought hazard is evaluated using the standardized precipitation-evapotranspiration index. Drought exposure considers population and agricultural land use, and drought vulnerability accounts for gross domestic product, total water storage, and water consumption. This global-scale study was conducted for the historical and future periods of 1975–2005 and 2070–2099, respectively, and employed three combined scenarios consisting of representative concentration pathways (RCPs) and shared socioeconomic pathways (SSPs) with datasets from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). To evaluate the proposed approach, the results obtained for the historical period were compared with drought records. The projections suggest that in addition to increasing drought hazards caused by climate change, populous regions, or areas heavily dependent on agriculture are at a higher risk than other regions because of high water consumption levels. The contributions analysis indicates that agricultural land use is the largest contributor to drought risk, except for Africa, where the population makes the largest contribution. Model uncertainty of the General Circulation Models (GCMs) and Hydrological Models (HMs) is dominant compared to the RCP and SSP scenarios, with uncertainty from the GCMs the most dominant. This study provides possible depictions and their uncertainties of future drought risks and can assist decision-makers in developing better adaptation and mitigation strategies for climatic, environmental, and socioeconomic changes.