Hydrological Drought Severity Research Articles

Comprehensive evaluation of the response relationship between meteorological drought and hydrological drought in the Yalong River Basin, China

Extreme climate events are becoming increasingly severe owing to global warming. In recent years, the Yalong River has experienced frequent droughts, which has seriously hindered the development of hydropower. Based on standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI) values, this study employed transfer entropy, multivariate Copula functions, and a cloud model to study the response relationship and risk situation between meteorological and hydrological droughts. The results showed that: (1) The smaller the scale of SPEI and SRI, the more sensitive the identification of drought and the faster the detection of drought trend changes. (2) Combined with small-scale drought index analyses, the trend and severity of meteorological and hydrological droughts propagating from the upper and middle reaches to the lower reaches is increasing from year to year. (3) The Gumbel-Hougaard Copula function reveals the relationship between meteorological and hydrological drought, with the longest joint return period of 13–15 months. (4) In cloud model risk evaluation, the degree, uncertainty and stochasticity of drought risk in the basin are increasing, and the risk degree of interannual meteorological and seasonal hydrological droughts in the basin was high. This study provides theoretical support for optimizing water resource allocation and drought risk situation analysis in the basin.

Changes in Drought Characteristics in the Yellow River Basin during the Carbon-Neutral Period under Low-Emission Scenarios

Droughts have a severe impact on the environment and social economy, and predicting their future changes is challenging due to significant uncertainties in climate change and human activities. Many countries have pledged to achieve carbon neutrality to limit global warming; however, few studies have focused on drought changes during the carbon-neutral period. Here, we analyzed the variations in drought characteristics across the Yellow River Basin (YRB) during the carbon-neutral period under two low-emission scenarios from 7 CMIP6 model outputs. The results show that the temperature and precipitation will increase significantly during the 2015–2100 period under both SSP1-1.9 and SSP1-2.6 scenarios. Compared to the historical period (1979–2014), the hydrological drought frequency is projected to decrease by 15.5% (13.0–18.1%), while drought severity is expected to increase by 14.4% (13.2–15.7%) during the carbon-neutral period. Meteorological droughts exhibit a similar changing trend, although the results vary between different regions. In general, more severe hydrological droughts may occur in the southern YRB in the carbon-neutral period under low-emission scenarios. This study has implications for future drought mitigation within the Yellow River Basin.

The Impact of Climate Change on Hydro-Meteorological Droughts in the Chao Phraya River Basin, Thailand

This study evaluated the impacts of climate change on hydro-meteorological droughts in the Chao Phraya River Basin (CPRB), Thailand under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). We used three Reginal Climate Models (RCMs) of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment—Southeast Asia (SEACLID/CORDEX-SEA), which are bias corrected. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow for future periods. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were estimated and used for drought characterization at three time scales (3, 6, and 12 months). The lag time between meteorological and hydrological droughts is approximately 1–3 months. The results suggest that the CPRB is likely to experience less frequent hydro-meteorological drought events in the future. The meteorological drought is projected to be longer, more severe, and intense. The severity of hydrological drought tends to decrease, but the intensity could increase. Climate change has been discovered to alter drought behaviors in the CPRB, posing a threat to drought monitoring and warning because droughts will be less predictable in future climate scenarios. The characterization of historical and future droughts over the CPRB is therefore valuable in developing an improved understanding of the risks of drought.

Propagation characteristics of meteorological drought to hydrological drought considering nonlinear correlations - A case study of the Hanjiang River Basin, China

Meteorological drought serves as the precursor to hydrological drought. Clarifying the propagation characteristics from meteorological drought to hydrological drought is crucial for predicting and mitigating this severe natural disaster. In this study, we proposed an assessment framework that integrates both linear and nonlinear methods to characterize the transition from meteorological to hydrological drought in terms of drought response time, effective drought transformation rate, and drought propagation threshold. Utilizing ERA5 land reanalysis data (1951–2022) and focusing on the Hanjiang River Basin in China, we analyzed drought propagation features with and without inter-basin water diversion. Extracted drought event pairs indicate that a more significant meteorological drought does not necessarily result in a more severe hydrological drought, and vice versa, which confirms the nonlinear propagation from meteorological to hydrological drought. The drought response times derived using the linear method are, on average, two months shorter than those derived using the nonlinear method. Inter-basin water diversion will weaken the drought linear correlation while strengthening the nonlinear correlation. When the annual water diversion exceeds 12.0 billion m3, the drought response time will experience a sudden reduction. This research provides a scientific method and reference for basin-scale water resource management and drought mitigation practice.

Impact of hydrological drought occurrence, duration, and severity on Murray-Darling basin water quality

The severity and frequency of droughts are projected to increase globally due to climate change, but the effects of this on water quality are uncertain. The Murray-Darling Basin (MDB) is the largest river system in Australia and has been impacted by droughts of varying severity within recent decades. In this study, we assessed the influence of hydrological droughts and their characteristics (severity and duration) on water quality, utilising a long-term (1980–2017) dataset from two monitoring sites. The main drought periods, and their duration and severity, were identified using the calculated Standardised Drought Index values (SDI) from averaged monthly streamflow data. While several hydrological drought periods were identified, the longest duration and greatest severity were during the Millennium Drought (1998–2010). Nutrient loads and concentrations of Total Nitrogen and Total Phosphorus of drought and post-drought periods were significantly different. The drought period showed the lowest median and interquartile range of nutrient (total nitrogen, TN; oxidised nitrogen, NOX; total phosphorus, TP; and soluble reactive phosphorus, SRP) concentrations and loads for both sites, whereas the highest nutrient loads and concentrations were reported during the post-drought period (approx. 1 × 103 to 1 × 105 kg day−1 increase in nutrient loads). Our analysis found significant relationships between nutrient loads and SDI during droughts. The load of N and P in the initial flush post-drought increased with drought at both sites. This suggests that nutrients were retained in the landscape during the drought and released in higher loads post-drought when the catchment became wetter, the hydrology was activated, and nutrients were mobilised. Hydrology is a key driver controlling the water quality within the inter-drought period and the peak nutrient loads post-drought. The duration and the severity of droughts had a significant (p = 0.01) influence on peak TN and TP monthly loads but not cumulative loads over a 12-month period. Hydrological droughts are important factors in controlling the water quality of the MDB. Therefore, management efforts should be focused on reducing the occurrence and duration of these events, along with the implementation of catchment nutrient control measures.

Temporal rainfall variability and drought characterization in Cheleka Watershed, Awash River Basin, Ethiopia

Study regionCheleka Watershed, lower Awash River Basin, Ethiopia. Study focusThe lower part of Awash River (Cheleka Watershed) with an area of 1744.48 km2 has limited rainfall temporal variability and drought incidence data. So, the study analyzed the temporal rainfall variability and drought incidence from five meteorological station starting from1988 up to 2017. Coefficient of variation, precipitation concentration index, mean and standard deviation were computed to analysis the temporal variations of rainfall; frequency and severity of droughts were characterized through rainfall anomalies indexes (RAI) and standardized precipitation indexes (SPI). New hydrological insights for the regionThe study found that, mean annual rainfall with a range value of 908.90 mm - 1181.48 mm in Batie and Majetie station respectively. Kiremt rainfall total with the highest coefficient of variation (22.93–29.12%) next to Belg rainfall total (39.31–52.43%) and the lowest variations of annual rainfall total (15–22.59%). Frequency of drought in 12 month’s interval indicates severely dry droughts, most frequently next to moderately dry drought. The maximum frequency for severely dry (8.61%) and moderately dry (11.39%) drought were occurred in Kemisse station. The longest duration and the highest magnitude drought were occurred in Kombolcha station next to Kemisse. As recommendation, since, this study was focused only temporal rainfall variability and drought characteristic, it is better that, future research will be conducted to evaluate the spatial rainfall variability and hydrological drought severity nature and its impact on socio-economic and human well-beings in the area.

Influence of large-scale climate indices and regional meteorological elements on drought characteristics in the Luanhe River Basin

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly.

Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin

Abstract. The typical drivers of drought events are lower than normal precipitation and/or higher than normal evaporation. The region's characteristics may enhance or alleviate the severity of these events. Evaluating the combined effect of the multiple factors influencing droughts requires innovative approaches. This study applies hydrological modelling and a machine learning tool to assess the relationship between hydroclimatic characteristics and the severity of agricultural and hydrological droughts. The Soil Water Assessment Tool (SWAT) is used for hydrological modelling. Model outputs, soil moisture and streamflow, are used to calculate two drought indices, namely the Soil Moisture Deficit Index and the Standardized Streamflow Index. Then, drought indices are utilised to identify the agricultural and hydrological drought events during the analysis period, and the index categories are employed to describe their severity. Finally, the multivariate regression tree technique is applied to assess the relationship between hydroclimatic characteristics and the severity of agricultural and hydrological droughts. Our research indicates that multiple parameters influence the severity of agricultural and hydrological droughts in the Cesar River basin. The upper part of the river valley is very susceptible to agricultural and hydrological drought. Precipitation shortfalls and high potential evapotranspiration drive severe agricultural drought, whereas limited precipitation influences severe hydrological drought. In the middle part of the river, inadequate rainfall partitioning and an unbalanced water cycle that favours water loss through evapotranspiration and limits percolation cause severe agricultural and hydrological drought conditions. Finally, droughts are moderate in the basin's southern part (Zapatosa marsh and the Serranía del Perijá foothills). Moderate sensitivity to agricultural and hydrological droughts is related to the capacity of the subbasins to retain water, which lowers evapotranspiration losses and promotes percolation. Results show that the presented methodology, combining hydrological modelling and a machine learning tool, provides valuable information about the interplay between the hydroclimatic factors that influence drought severity in the Cesar River basin.

Challenges of typical inter-basin water transfer projects in China: Anticipated impacts of climate change on streamflow and hydrological drought under CMIP6

Inter-basin water transfer projects are critical for economic development in water scarcity regions. However, the streamflow reduction and the frequent dry extremes in a warming environment raise significant concerns regarding the sustainability of such projects. Based on the latest CMIP6 data, hydrological model, Standardized Streamflow Index (SSI), and run theory, this study systemically examined the future streamflow and hydrological drought changes in the Hanjiang to Weihe River Water Diversion Project (HWWDP) area, China. Significantly, as the most challenging project management scenario, the response of spatially compound hydrological drought (i.e., concurrent hydrological drought in both the water intake and receiving area) was further revealed. This analysis offers the potential to yield novel insights into the prospective management strategies for the HWWDP. The investigation covers the baseline period (1971–2014) and future periods (2021–2100) under SSP245 and SSP585 scenarios. The outcomes demonstrate a decline in annual average streamflow of 5.0–6.4 (SSP245) hundred million cubic meters in the water receiving area and 4.6–7.5 (SSP245) and 3.4–8.1 (SSP585) hundred million cubic meters in the water intake area, respectively, compared to the baseline period. Furthermore, hydrological drought frequency may increase in both the water receiving and source areas, particularly in the summer under SSP585. The duration, severity, and peak intensity of hydrological drought events in the receiving area are expected to exacerbate due to climate change, while those impacts on water intake area should be relatively minor. The spatially compound hydrological drought is expected to occur more frequently in different months except April. The conditional probabilities of spatially compound hydrological drought occurrence may rise by 5.2%-18.7% (SSP245) and 5.9%-20.4% (SSP585) in different months when drought occurs in the water intake area. Moreover, higher probabilities are expected to be observed from April to October when the water receiving area experiences drought. These findings underscore the necessity for adaptive climate change management of the HWWDP to address the future reduction in streamflow and more severe hydrological drought.

The socioeconomic impact of severe droughts on agricultural lands over different provinces of Iran

The lack of rainfall is the primary cause of drought, reduced crop harvest (CH), and socioeconomic drought. Agriculture is the primary source of income for most Iranians, and drought can harm people's lives irreparably. This study examines the changes in the CHs and crop prices (CPs) across provinces of Iran during the most severe drought of all time in Iran and its impact on producers (farmers), consumers, and public prosperity using the Surplus Economic Method (SEM). Our study focused on crops that have a big impact on Iranian life, such as wheat, barley, potato, onion, tomato, lentils, chickpeas, and alfalfa. Our results indicated that Iran's most severe hydrological drought occurred from 2000 to 2002. The rainfed farms experienced the most pronounced changes in terms of CH, while financial damages were the highest in irrigated areas. Among the crops investigated, rainfed wheat has experienced the greatest reduction of 80%. Moreover, grains have the greatest price change (40% increase) during the hydrological drought. Wheat underwent the steepest CH reduction. Legumes experienced the steepest price rise. During the drought, most crops had lower yields, causing losses for consumers, but some producers still made a profit. The drought affected northwest and west Iran farmers adversely, but southern and central Iran farmers gained from the drought through increased product prices. Drought has had adverse effects on the public prosperity for most of the examined crops and reduced it. The greatest reduction corresponds to barley in the western regions and the Zagros Mountains. The diversity of crops in northwestern and western Iran has made these regions the most important areas for farming and crop supply in Iran. Agricultural droughts in these regions can affect the lives of all Iranian people and lead to socioeconomic drought in Iran. Our study demonstrated that hydrological droughts in northwestern and western areas of Iran are chiefly caused by the shortage of winter and spring rains. Moreover, Identifying the primary factors of hydrological drought showed that the hydrological drought is most affected by the depth of snow during winter. Additionally, the data analysis revealed that the combined effect of winter precipitation with snow depth and snow depth with snow coverage has the highest impact on hydrological drought (61%). The results can make farming policies based on the region and climate, marketing plans for droughts, and solutions to address the harmful effects of drought.

Attribution of runoff and hydrological drought changes in an ecologically vulnerable basin in semi‐arid regions of China

AbstractClimate change and human activities have been widely recognized as two major factors that deeply influence hydrological processes. Evaluating and identifying the contribution between different drivers contributes to better regional water management regulation. In this study, we used the variable infiltration capacity (VIC) model to quantify the contributions of different climatic variables and human activities to runoff in the Hunhe basin, which has a semiarid climate, in northern China. Through trend analysis, the study period is divided into the ‘baseline period’ (1982–1999) and the ‘change period’ (2000–2020). The results indicated that compared with climate change, human activities were the major factors decreasing runoff, contributing more than 86.3% to the runoff reduction in the change period. Climate change increased winter runoff but decreased summer and autumn runoff, resulting in an overall decrease in runoff. There is a trend of increasing severity of hydrological drought in the Hunhe basin, where climate change accounted for 28.2% of the total impact and human activities accounted for 72.8%. The change in runoff and hydrological drought was mainly due to human activities, including changing farmland to grassland and forest. These results would be helpful for policy‐makers and researchers to better understand the responses of runoff and hydrological drought to these changing environmental conditions and offering references for future water resource planning and management at the basin scale.

Can water release from local reservoirs cope with the droughts of downstream lake in a large river-lake system?

Lake is an important component of the Earth’s surface water bodies. Frequent and serious drought events in lakes have affected the security of regional water resources and caused the degradation of the lake ecosystem. Poyang Lake, the largest freshwater lake in China, has been suffering from increasingly severe hydrological droughts. This study simulated and investigated the effects of water release from local reservoirs in dry season on hydrological droughts in Poyang Lake based on a hydrodynamic model MIKE 21, and quantified the effectiveness of the joint operation of local reservoirs and the Three Gorges Reservoir (TGR). Major results showed that the water level of Poyang Lake during the dry period was significantly raised by the water release from local reservoirs, especially in the northern lake area. The average and the lowest lake level increased from 10.99 m to 11.18–11.59 m and from 9.97 m to 10.14–10.50 m at Xingzi station, respectively. Meanwhile, both the duration of low water and the drought severity/intensity (DS/DI) decreased significantly, with the duration decreasing from 128 days to 105–115 days for typical threshold lake level of 12.0 m, and the DS and DI decreasing from 176.6 m and 1.38 m/day to 117.6–155.3 m and 1.12–1.35 m/day, respectively. Moreover, the release oflocal reservoirs shortened the exposure duration of beach wetland, from nearly 3 months to about 1.5–2.5 months at the northern channel of Poyang Lake. The area with long exposure duration (>120 days) was also significantly reduced. In addition, the hydrodynamic simulations revealed that the joint operation of local reservoirs and the TGR further raised the average and the lowest lake level and decreased the duration of low water and drought severity and intensity. Outcomes of the study provided valuable references for mitigating lake droughts in complex river-lake-catchment system.

Future changes in hydrological drought across the Yangtze River Basin: identification, spatial–temporal characteristics, and concurrent probability

Hydrological droughts have caused greater damage due to climate change and rapid socio-economic development. Exploring future hydrological drought variations is imperative for drought defense and infrastructure construction. This study aims to investigate future changes in hydrological droughts across the Yangtze River Basin during 2025 ∼ 2100. The Distributed Time-Variant Gain Model coupled with the Standard Operation Policy module (DTVGM-SOP) was employed to project future runoff driven by the bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) data. Subsequently, future spatial–temporal changes in the characteristics of hydrological droughts were analyzed based on the Standardized Runoff Index (SRI). Lastly, future changes in the probability of concurrent hydrological droughts were evaluated using the bivariate copula functions. Results show that: (1) The DTVGM-SOP model can satisfactorily simulate monthly streamflow with a high Nash-Sutcliff Efficiency (NSE) of 0.75 ∼ 0.92. Future annual maximum discharge and annual average discharge in the mainstream and the northern tributaries are expected to increase by 3.34%∼58.19% and 3.11%∼32.66% respectively, while annual maximum discharge in the southern tributaries decreases by 0.54%∼20.09%. (2) The future annual and seasonal hydrological drought frequency is expected to decrease in most regions, while the frequency in spring increases in the Qinghai Tibet Plateau. The duration and severity of future hydrological droughts are expected to decrease by 9.52%∼78.69% and 5.13%∼81.36% in the whole basin except the source area and the Yalong River Basin. (3) Future concurrent hydrological droughts will be mitigated with decreasing frequency. The probability of concurrent hydrological droughts is expected to decrease by 46.15%∼96.47%, while future changes in the conditional probability of the mainstream are diverse in different concurrent scenarios with a range of −93.41%∼40.09%. The findings are helpful to improve the understanding of future hydrological drought variations in the Yangtze River Basin and provide essential information for damage reduction.

The role of human activities in the weakening of the propagation relationship between meteorological and hydrological droughts in the Heihe River Basin

AbstractMeteorological droughts could propagate into hydrological droughts and cause agricultural and societal damage. However, the quantitative impact of human activities on the drought propagation has not been well understood. Based on the precipitation and streamflow observational data and hydrological model simulations during 1961–2013, this study analysed the drought propagation characteristics and quantified the impact of human activities on the propagation in the upper and middle reaches of Heihe River Basin. The matched meteorological and hydrological drought events indicated that the drought propagation was characterized by a lagged onset, weakened drought severity and reduced development and recovery speeds. In the upstream area, the correlations between meteorological and hydrological droughts were significant, and human activities had a negligible impact on the drought propagation. In contrast, the impact from human activities was significant in the midstream area, and the effect was two‐fold. Specifically, human activities (e.g., reservoir regulation) reduced the propagation probability of one or several meteorological droughts propagating into a hydrological drought by 16%. Meanwhile, human activities had remarkable effects on long‐lasting and extreme hydrological droughts through reducing their duration and severity by 18% and 37% respectively. On the other hand, the occurrence probability of mismatched drought events, that is, meteorological droughts without causing hydrological droughts and hydrological droughts without preceding meteorological droughts, increased by 34% due to human interventions. Human activities also accelerated the development speed of slowly developing hydrological droughts. In addition, human activities increased the mean duration and severity of moderate hydrological droughts by 32% and 18%. The results are expected to provide scientific bases for understanding the formation and development process of hydrological drought and improving drought forecasting under global change.

Hydrological drought forecasting under a changing environment in the Luanhe River basin

Abstract. Forecasting the occurrence of hydrological drought according to a forecasting system is an important disaster reduction strategy. In this paper, a new drought prediction model adapted to changing environments was constructed. Taking the Luanhe River basin in China as an example, first, nonstationarity analysis of hydrological sequences in the basin was carried out. Then, conditional distribution models with the human activity factor as an exogenous variable were constructed to forecast hydrological drought based on meteorological drought, and the results were compared with the traditional normal distribution model and conditional distribution model. Finally, a scoring mechanism was applied to evaluate the performance of the three drought forecasting models. The results showed that the runoff series of the Luanhe River basin from 1961 to 2010 were nonstationary; moreover, when human activities were not considered, the hydrological drought class tended to be the same as the meteorological drought class. The calculation results of the models involving HI as an exogenous variable were significantly different from the models that did not consider human activities. When the current drought class tended towards less severe or normal, the meteorological drought tended to turn into more severe hydrological drought with the increase in human index values. According to the scores of the three drought forecasting models, the conditional distribution models involving the human index can further improve the forecasting accuracy of drought in the Luanhe River basin.

Model-Based Assessment of Preventive Drought Management Measures’ Effect on Droughts Severity

Preventive Drought Management Measures (PDMMs) aim to reduce the chance of droughts and minimize drought-associated damages. Selecting PDMMs is not a trivial task, and it can be asserted that actual contributions to drought alleviation still need to be adequately researched. This study evaluates the effects of three potential PDMMs, namely, rainwater harvesting ponds, forest conservation, and check dams, on agricultural and hydrological drought severity. The Soil Water Assessment Tool is used for hydrological modeling and representing PDMMs. The threshold level method is applied to analyze droughts and evaluate the impact of PDMMs on drought severity. Findings show that rainwater harvesting ponds applied on agricultural land reduce the severity of agricultural droughts and hydrological droughts, particularly during the first months of the drought events observed in the rainy season. Results also reveal that forest conservation contributes to reducing the severity of hydrological droughts by up to 90%. Finally, check dams and ponds in upstream subbasins considerably reduce agricultural and hydrological drought severity in the areas where the structures are applied; however, they exacerbate drought severity downstream. The analysis was developed in the Torola River Basin (El Salvador) for the period spanning 2004 to 2018.

Evaluating the duration, severity, and peak of hydrological drought using copula

Evaluating the duration, severity, and peak of hydrological drought using copula

Possible Future Climate Change Impacts on the Meteorological and Hydrological Drought Characteristics in the Jinghe River Basin, China

Revealing the impact of future climate change on the characteristics and evolutionary patterns of meteorological and hydrological droughts and exploring the joint distribution characteristics of their drought characteristics are essential for drought early warning in the basin. In this study, we considered the Jinghe River Basin in the Loess Plateau as the research object. The standardized precipitation index (SPI) and standardized runoff index (SRI) series were used to represent meteorological drought and hydrological drought with monthly runoff generated by the SWAT model. In addition, the evolution laws of the JRB in the future based on Copula functions are discussed. The results showed that: (1) the meteorological drought and hydrological drought of the JRB displayed complex periodic change trends of drought and flood succession, and the evolution laws of meteorological drought and hydrological drought under different spatiotemporal scales and different scenario differ significantly. (2) In terms of the spatial range, the JRB meteorological and hydrological drought duration and severity gradually increased along with the increase in the time scale. (3) Based on the joint distribution model of the Copula function, the future meteorological drought situation in the JRB will be alleviated when compared with the historical period on the seasonal scale, but the hydrological drought situation is more serious. The findings can help policy-makers explore the correlation between meteorological drought and hydrological drought in the background of future climate change, as well as the early warning of hydrological drought.

Spatial Downscaling of GRACE Data Based on XGBoost Model for Improved Understanding of Hydrological Droughts in the Indus Basin Irrigation System (IBIS)

Climate change may cause severe hydrological droughts, leading to water shortages which will require to be assessed using high-resolution data. Gravity Recovery and Climate Experiment (GRACE) satellite Terrestrial Water Storage (TWSA) estimates offer a promising solution to monitor hydrological drought, but its coarse resolution (1°) limits its applications to small regions of the Indus Basin Irrigation System (IBIS). Here we employed machine learning models such as Extreme Gradient Boosting (XGBoost) and Artificial Neural Network (ANN) to downscale GRACE TWSA from 1° to 0.25°. The findings revealed that the XGBoost model outperformed the ANN model with Nash Sutcliff Efficiency (NSE) (0.99), Pearson correlation (R) (0.99), Root Mean Square Error (RMSE) (5.22 mm), and Mean Absolute Error (MAE) (2.75 mm) between the predicted and GRACE-derived TWSA. Further, Water Storage Deficit Index (WSDI) and WSD (Water Storage Deficit) were used to determine the severity and episodes of droughts, respectively. The results of WSDI exhibited a strong agreement when compared with the Standardized Precipitation Evapotranspiration Index (SPEI) at different time scales (1-, 3-, and 6-months) and self-calibrated Palmer Drought Severity Index (sc-PDSI). Moreover, the IBIS had experienced increasing drought episodes, e.g., eight drought episodes were detected within the years 2010 and 2016 with WSDI of −1.20 and −1.28 and total WSD of −496.99 mm and −734.01 mm, respectively. The Partial Least Square Regression (PLSR) model between WSDI and climatic variables indicated that potential evaporation had the largest influence on drought after precipitation. The findings of this study will be helpful for drought-related decision-making in IBIS.

Hydrological Drought Severity in Different Return Periods in Rivers of Ardabil Province, Iran

Hydrological drought (HD) characterization with different return periods is essential to appropriately design the best water management practices. In particular, characterizing the interactive relations of discharge, drought, and return periods using a novel triple diagram can deepen the interpretation of regional droughts, which have not been adequately considered, especially in semi-arid areas. Considering the critical role of HD in water exploitation and management in Iran, this study was therefore conducted to analyze the HD in different return periods in rivers of the Ardabil Province (area = 17,953 km2). To this end, the streamflow drought index (SDI) was computed using DrinC software at 1-, 3-, and 6-month time scales for 25 hydrometric stations during 1981–2014. Then, the drought severity was evaluated by CumFreq software in different return periods (2, 5, 10, 25, 50, and 100 years). Finally, the relationship between discharge, SDI, and return periods was analyzed using triple diagram models. The results revealed that the drought events had mild (−1 ≤ SDI < 0) and moderate (−1.5 ≤ SDI < −1) severity for most study stations in the study area. The mean values of SDI in the 1-, 3-, and 6-month time scales were 1.08, 0.80, and 0.55, respectively. At all study time scales, the drought severity in both rivers with low and high flows increased with increasing return periods. In such a way, the maximum drought severity has been found for rivers with high flow at a 100-year return period. The current results can be considered a screening tool for the distinctive conservation and directive management of watershed resources.