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Definition of drought characteristics namely drought duration (D) and drought severity (S) using the run theory
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The agricultural drought significantly affects the socio-economic sectors in the agrarian country like India. Though there is a larger variability in the drought characteristics, the time to propagation from meteorological to agricultural drought is not investigated at regional scale in India. The Standardised Precipitation Evapotranspiration Index...
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Citations
... For the entire island, we pass from a value of ~ 15.5 °C during the 'Control' period, to a value of ~ 19.5 °C at the end of the 21st century, namely a + 4 °C variation in the mean annual temperature. Regardless of the main topic of this work, reaching this value might exacerbate droughts, water scarcity and desertification in this area (Carvalho et al. 2022;Noto et al. 2023a, b), resulting in a concrete risk for agriculture and biodiversity (Iglesias et al. 2011;Das et al. 2023). ...
Depth-Duration-Frequency (DDF) curves are an essential tool in hydrological planning and risk management. However, the assumption of stationarity that is traditionally embedded in their derivation, is increasingly questioned by the impacts of climate change. This study focuses on adapting and projecting DDF curves for Sicily (Italy), which is experiencing an intensification of rainfall extremes, particularly for shorter durations. The proposed framework adapts the most up-to-date regional frequency analysis for the island by using an adaptation factor that incorporates the thermodynamic relationship between extreme precipitation and temperature, as well as future climate projections for temperature from an ensemble of regional climate models under the worst-case scenario. By the end of the century, the design rainfall estimates may require to be increased up to 50%, especially for hourly durations, to account for climate change effects. The results also highlight a strong spatial variability in the precipitation quantiles, with higher values observed in specific areas such as the north-eastern part of the island, which is characterized by small catchments and particularly prone to flash floods. Finally, this study provides a simple but still physical-based approach to updating DDF curves, that can be useful for engineers and practitioners, enhancing international efforts to mitigate climate change impacts through improved hydrological planning.
... Under the recent scenario of sudden changes in the climatic system, the number and severity of the drought has been increased. The demand for water resources also increased tremendously according to the increasing population and development [8,9]. Hence it is necessary to study drought occurrence and propagation for wise management of its adverse impacts. ...
... In the long run, this deficiency reduces surface and subsurface runoff and leads to hydrological drought. The prolonged deficiency in precipitation with an increasing rate of evaporation triggers soil moisture drought [8]. Bisht et al. [3] reveal that drought risk in India will be high in the future under different climate change scenarios. ...
... In recent times, drought propagation studies were concentrated more on propagation from meteorological drought to agricultural drought. Such studies mainly employed correlation analysis to identify the propagation time between the two droughts [9] and run theory to explain the drought characteristics like frequency, duration, and severity [6,8]. Xu et al. [22] investigated the spatiotemporal variations in meteorological to agricultural drought propagation in China. ...
... Accelerating climate change and human activities question the reliability of assessing drought characteristics under stationary assumptions (Milly et al., 2008), emphasizing the need for a paradigm shift towards nonstationary approaches (Zhang et al., 2022). While many studies use non-stationary statistical models for drought analysis (Das et al., 2020;Das et al., 2023aDas et al., , 2023bDu et al., 2015;Mondal & Mujumdar, 2015;Sun et al., 2020), adopting such models increases complexity and uncertainty in estimating design events for planning and management (Serinaldi & Kilsby, 2015). Non-stationary models should be used judiciously under significant time-varying conditions (Apurv & Cai, 2019), as the inherent non-stationarity in drought characteristics is often overlooked . ...
Climate change and anthropogenic influences amplify drought complexity, entangle non‐stationarity (NS) and further challenge drought comprehension. This study aims to understand the dynamic evolution of drought propagation patterns due to climatic and anthropogenic pressures by assessing the non‐stationary linkages between hydrological variables and drought characteristics. It employs four standardized drought indicators to comprehensively examine the spatio‐temporal evolution of meteorological (MD) and hydrological (HD) drought characteristics. Data from 29 semi‐arid catchments from six river basins in Peninsular India, are analyzed to uncover distinct drought propagation patterns. This study utilizes a novel Non‐overlapping Block‐stratified Random Sampling (NBRS) approach to detect NS in drought characteristics and hydrological variables, shedding light on the underlying drivers of this dynamic behavior. The results indicate similarities in drought behavior for the Sabarmati, Mahi and Tapi (SMT) basins compared with the Godavari, Krishna and Pennar (GKP) basins, with shorter (longer) propagation times noted for SMT (GKP) basins. While HD severity decreases over time in SMT basins, it intensifies in GKP basins, which are linked to intensive anthropogenic interventions such as river regulation and reservoir operations, thus resulting in prolonged and intensified droughts. Rainfall primarily exhibits time‐invariance, while significant NS is observed in potential evapotranspiration (particularly in the Krishna and Pennar basins), streamflow and baseflow across all basins. The study also identified three distinct drought propagation patterns in these basins, highlighting cases where MD did not transition to HD, instances of HD occurring without preceding MD and synchronous propagation of MD to HD. The study outcomes provide profound insights into the evolution of drought dynamics under climatic and anthropogenic pressures, which will aid policymakers and stakeholders in formulating strategies for drought preparedness and response.
... This reduced soil moisture in the crop root zone depth will further affect crop growth and yield causing agricultural drought in the region 8 . Previous studies have considered the soil moisture as a proxy for agricultural drought by limiting the depth of the soil moisture data to the crop root zone [9][10][11] . The soil moisture stress may not always reflect in the vegetation stress due to the short drought duration and hence researchers are using soil moisture drought and vegetation drought terms separately to avoid confusion, nevertheless both are the proxies for the agricultural drought assessment 12 . ...
... There are very few regional studies in India that concentrate on the examination of the propagation mechanism that triggers agricultural drought. The recent study 11 , has examined the propagation of drought conditions from meteorological to agricultural realms over India. Large-scale climatic oscillations and local hydro-meteorological variables were used in the computation of the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardised Soil Moisture Index (SSMI). ...
... The spatial distribution of agricultural drought properties i.e., average drought duration and severity based on SSMI-1 time series computed using ERA-5 soil moisture product over the various meteorological sub-divisions of India during the period of 1981-2020 (40 years) is given in Fig. 3a Overall, agricultural drought characteristics shows the significant spatial variation over India, with the observation that arid and semi-arid regions from central India having the homogeneous pattern. Identical findings were reported in past 11 showing a similar pattern for the spatial variation of the agricultural drought properties over India. It is noteworthy that there is synchrony between drought duration and severity over Indian regions, as locations with greater levels of drought duration also exhibit higher values of drought severity. ...
Agricultural drought affects the regional food security and thus understanding how meteorological drought propagates to agricultural drought is crucial. This study examines the temporal scaling trends of meteorological and agricultural drought data over 34 Indian meteorological sub-divisions from 1981 to 2020. A maximum Pearson's correlation coefficient (MPCC) derived between multiscale Standardised Precipitation Index (SPI) and monthly Standardised Soil Moisture Index (SSMI) time series was used to assess the seasonal as well as annual drought propagation time (DPT). The multifractal characteristics of the SPI time series at a time scale chosen from propagation analysis as well as the SSMI-1 time series were further examined using Multifractal Detrended Fluctuation Analysis (MF-DFA). Results reveal longer average annual DPT in arid and semi-arid regions like Saurashtra and Kutch (~ 6 months), Madhya Maharashtra (~ 5 months), and Western Rajasthan (~ 6 months), whereas, humid regions like Arunachal Pradesh, Assam and Meghalaya, and Kerala exhibit shorter DPT (~ 2 months). The Hurst Index values greater/less than 0.5 indicates the existence of long/short-term persistence (LTP/STP) in the SPI and SSMI time series. The results of our study highlights the inherent connection among drought propagation time, multifractality, and regional climate variations, and offers insights to enhance drought prediction systems in India.
... In this study, the term "drought" is related to meteorological drought, i.e. negative and short-term precipitation anomaly. The SPEI is a standardized and multi-timescale index that can fulfill the requirements for drought analysis in different regions under different climatic conditions (Chiang et al., 2021;Das et al., 2023;Vicente-Serrano et al., 2010Yu et al., 2014). For the calculation of SPEI, we closely follow the studies of Vicente-Serrano et al. (2010) and Yu et al. (2014). ...
... Many researchers carried out a probability-based stochastic approach in estimating the drought hazard propagation threshold from meteorological to the hydrological domain (Sattar et al. 2019;Gu et al. 2020). However, there can be non-stationarity in the drought index time series intending non-stationarity in the drought propagation (Das et al. 2023;Jehanzaib et al. 2023). Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) are applied to understand drought propagation mostly by identifying high spectral densities corresponding to historical times (Huang et al. 2017;Wang et al. 2020;Li et al. 2020). ...
The advent of climate change has induced frequent occurrence of droughts in the past few decades. Identification of hydrological droughts require computation of drought indices by probabilistic standardization procedures. The existing hydrological drought indices could not answer the zero monthly streamflow condition for the ephemeral streams. This issue was resolved by developing a modified Standardized Streamflow Index to characterize the hydrological drought of Upper Kangsabati River Basin, West Bengal, India. 45 hydrological droughts were extracted for the basin and the most severe drought occurred in the year 2015–2016. The basin experienced the most severe drought of 10.67 severity and longest drought duration of 13 months. A bivariate analysis of drought characteristics was carried out using copula technique to determine different design drought events. The bivariate distribution which showed the basin experienced most severe drought of 16 years and longest duration drought of 15 years ‘OR’ return period. Propagation time of the drought hazard from the meteorological to the hydrological drought is extensively studied in this research using both correlation and Cross Wavelet Transform (XWT) methods. XWT was mostly used for qualitative comparison of hydrological and meteorological signal in drought propagation studies in the past. In this research, a novel quantitative approach of using XWT and the phase angles obtained between the hydrological and meteorological signals is proposed to determine the drought propagation times. It was concluded that the basin had in general a drought propagation time of 2 months. However, there were seasonal variability in the drought propagation times showing prompt response in the summer season which increased to 2 months for monsoons and stretching far to 5 months for the late winter.
... In India, about 68% of the country is at risk of some level of drought, 35% of the areas that get between 750 and 1125 mm of rain are considered droughtprone, and 33 percent of the areas that get less than 750 mm of rain are considered chronically drought-prone (Rawat et al. 2022). India has faced significant droughts from 1870 to 2016, causing the famine resulting in the death of millions of people with heavy socio-economic agricultural loss (Amrit et al. 2018;Mishra et al. 2019;Das et al. 2023). The paucity of water over a long period is termed drought, possibly due to below-average precipitation in that region (Mishra and Desai 2005). ...
The complex topography of the Himalayan region makes it difcult to analyze its climatic variables over the region. The
study has been carried out to identify the trends in climate variables and drought analysis over the Beas River basin in the
western Himalayas. To understand the impact of changing climate on the Beas River basin, fve downscaled global circulation
models (GCMs) were used, namely BNU-ESM, Can-ESM2, CNRM CM5, MPI-ESM MR, and MPI-ESM LR. These GCMs
were obtained for two representative concentration pathway (RCP) scenarios: 4.5, which represents the normal scenario,
and 8.5, which represents the most extreme scenario for anticipated concentrations of carbon and greenhouse gases. The
multi-model ensemble (MME) of these 5 GCMs were used to project rainfall and temperature. Further Innovative Trends
Analysis (ITA) and modifed Mann–Kendell (mMK) trend tests have been used for trend analysis at a 5% signifcance level.
The drought pattern in the future timescale of the ensembled model is calculated using the Standardised Precipitation Index
(SPI) for both RCPs. The ITA, Mann–Kendell, and Sen’s slope trends showed decreased precipitation under RCP 4.5 in the
Manali region and showed an increasing trend for the remaining locations under both scenarios. Furthermore, SPI values
showed frequent droughts under both RCPs. The study outcomes will serve as a scientifc foundation for the sustainability
of water resources and agricultural output in arid inland regions vulnerable to changing climate.
... The frequency and spatial extent of droughts and heatwaves in India have increased significantly in past decades, primarily driven by a mean summer monsoon rainfall decline and rise in temperatures Nepal et al. 2021;Pal and Ojha 2021;Saha and Sateesh 2022;Goyal et al. 2023). Recent years have seen an emphasis on flash droughts, transition between different types of droughts, and drought indices (Bhardwaj et al. 2020;Shah and Mishra 2020;Prajapati et al. 2021;Rehana and Naidu 2021;Das et al. 2022Das et al. , 2023Kanthavel et al. 2023;Mahto and Mishra 2023). Bhardwaj et al. (2020) found that the Indus, Sabarmati, and Godavari River basins have higher propagation times for meteorological to hydrological droughts. ...
India has a growing water crisis fueled by global warming and a rising population. There is an urgent need for accurate water availability assessments and sustainable water management strategies for urban and rural areas. This can be achieved by developing novel decision-making tools for effective water resource management by improving the hydrological models and our understanding of hydrological processes. The changing climate adds complexity to hydrological processes, necessitating accurate modelling and impact assessments to build climate change-resilient water resource systems. This review examines the advancements in hydrological process understanding and surface hydrological modelling in India from 2019 to 2023. Recent years have witnessed substantial contributions from the Indian hydrology community, which include quantifying climate change impacts on water and carbon cycle at a basin scale, improvements in hydrological modelling and forecasting extremes, the introduction of novel physics-based data-driven approaches, urban flood modelling and the development of first-ever state-of-the-art flood early warning system among other notable climate services. In addition, the idea of studying natural systems as coupled human-natural systems has gained prominence in India. This review aims to provide insights into recent developments in surface water hydrology in India and highlight the potential future avenues of research that can uplift water resources management in India.
... Although the PCC effectively measures linear relationships, it falls short in capturing the complex, nonlinear interactions often found in drought dynamics, a limitation significant in meteorological to agricultural drought propagation where relationships are not strictly linear . Recent studies by Xu et al. (2023) and Das et al. (2023) have investigated the propagation times of agricultural droughts from meteorological droughts, considering their nonlinear linkage. Fang et al. (2020) utilized a comprehensive approach to identify drought propagation, considering both linear and nonlinear dependencies, and Li et al. (2022) employed copula techniques to explore this aspect further. ...
Meteorological drought precedes the agricultural drought and studying the propagation time from meteorological to agricultural drought can substantially reduce agricultural losses. To find this propagation time between the meteorological and agricultural drought, this study analyzed the copula-based conditional probability between the Standardized Precipitation Index at 12 timescales (SPI-1 to12, meteorological drought) and Standardized Soil Moisture Index at 1 month timescale (SSI-1, agricultural drought), over the fifteen Agro-Climatic Zones (ACZs) of India. SSI is computed using a total column Soil Moisture (SM) derived from ESACCI SM using the Statistical Soil Moisture Profile (SSMP) model. The SSMP-based ESACCI SM is positively correlated (Correlation Coefficient of 0.871) with ERA5 Land SM. To compute the conditional probability, three copulas namely Frank, Clayton, and Gumbel copulas are fitted between SPI-1 to 12 and SSI-1. The Goodness of Fit analysis showed the dominance of the Gumbel copula among the Clayton, Frank, and Gumbel copulas. Gumbel copula completely dominated the SPI timescales of 1-3 and 11-12 whereas Clayton copula was relatively favored for SPI timescales of 4-10. The propagation time results revealed that the monsoon season (JAS) consistently exhibits the highest propagation time, averaging around 10 months followed by summer (AMJ, 7 months), spring (JFM, 4 months), and winter (OND, 2-3 months) seasons. The Mann-Kendall trend test revealed that the same season can have different trends in different ACZs and vice versa, underlining the localized and season-specific strategies for drought management, considering each ACZ's unique environmental, agricultural, and socioeconomic conditions in each zone. Overall, this study showcases the capability of remote sensing and copula-based statistical models, in understanding meteorological to agricultural drought propagation. It also highlights the efficiency of statistical models in deriving total column SM from surface SM.
... As irrigation requirements are highly dependant on the prevailing meteorological conditions, a comprehensive assessment of the interannual variability of requirements should be based on a relatively long time series (Döll and Siebert, 2002). To characterise the relationship between meteorological drought and agricultural drought, various studies have compared the standardised precipitation-evapotranspiration index (SPEI; Vicente-Serrano et al., 2010;Beguería et al., 2014) with information related to agricultural droughts (e.g., Bachmair et al., 2018;Parsons et al., 2019;Vicente-Serrano et al., 2019;Das et al., 2022;Qin et al., 2023). As meteorological data are readily available, the linking of irrigation requirements to meteorological drought conditions can serve an important need for water resource planning for both researchers and practitioners. ...
As climate change brings about hotter and often drier summers, an improved understanding of how irrigation requirements vary according to climatic conditions is of increasing importance. Within Germany, temperate conditions have historically enabled most agriculture to be supplied solely by green water, but recent crop yield reductions and crop failures have demonstrated its increased vulnerability to climatic conditions. The raster-based mGROWA hydrological water balance model was implemented over all agricultural areas in Germany for the period 1961–2020 at a high spatial (200 m) and temporal (daily) resolution. Grid-cells were each assigned one of 10 major crop classes, which account for 86.7 % of all agricultural areas in Germany, and effectively all irrigated areas. Using crop-specific irrigation rules that reflect actual practices, irrigation requirements were simulated for all crop areas. To investigate the relationship between climatic water balance over the crop growing season and irrigation requirements, the simulated annual irrigation requirements were compared with the standardised precipitation-evapotranspiration index (SPEI-6), calculated at the end of September. Through this comparison, irrigation requirements could be characterised for near-normal and dry conditions, and results were aggregated to the district level. Additionally, using district-level data on the areas with irrigation infrastructure, the actual water used for irrigation was estimated. The results highlight marked increases in irrigation requirements in dry conditions compared to near-normal conditions (median increase of 72 %), which are more pronounced over crops in silty soils than in sandy soils. The results also demonstrate how the increased irrigation requirements in dry years are in many cases higher than what is suggested by guidelines for irrigation management in Germany. This study provides important information for actors related to the agricultural sector and water management and is based on a robust and transferable framework to quantify how irrigation requirements vary according to climatic variability and local soil conditions.
