Yanping Qu

Soil moisture (SM) remote sensing is widely used for agricultural drought monitoring, yet most applications still emphasize static moisture states rather than event-scale wetting responses. We developed an interpretable Earth observation (EO) framework to evaluate precipitation–SM product consistency and diagnose wetting processes across China’s croplands. Multi-source precipitation and SM products, including ERA5-Land, Soil Moisture Active Passive (SMAP), Soil Moisture of China by in situ data (SMCI), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Grid-based Precipitation dataset for Mainland China (CHM_PRE), were assessed using lagged consistency between rainfall forcing and relative soil moisture increments. The selected pairing was then used to model daily wetting increments at three depths with eXtreme Gradient Boosting (XGBoost), Shapley additive explanations (SHAPs), generalized additive models (GAMs), and quantile regression (QR). ERA5-Land precipitation paired with ERA5-Land SM showed the strongest reanalysis-constrained event-scale consistency (peak mean r = 0.43 at a 1-day lag), providing an internal-consistency baseline for comparison with independent satellite-derived combinations rather than an absolute accuracy ranking. EO-derived wetting signals showed depth-dependent lags, with a 1-day surface response and an approximately 2-day delayed profile signal at 28–100 cm; this pattern should not be interpreted as direct evidence of rapid physical infiltration to 100 cm. Precipitation transition thresholds followed a U-shaped dependence on antecedent wetness, with higher rainfall requirements under extremely dry and near-saturated states. These findings indicate that event-scale EO diagnostics can characterize product consistency, lagged wetting responses, and state-dependent precipitation thresholds, while same-system and deep-layer interpretations remain constrained by reanalysis coupling and model-assisted root-zone products.

Reservoir operations play a pivotal role in modifying drought propagation processes, particularly by influencing the transition from meteorological to hydrological drought. This study investigates the drought propagation characteristics in the middle reaches of the Hanjiang River Basin, China, under both natural and observed (reservoir‐influenced) conditions. The Standardized Precipitation Evapotranspiration Index and Standardized Streamflow Index were utilized to characterize meteorological and hydrological drought, respectively. The Soil and Water Assessment Tool was employed to reconstruct natural streamflow, providing a baseline for comparison. A nonlinear copula function was applied to model the dependence between meteorological and hydrological drought characteristics, and a Copula‐Bayesian network was developed to quantify propagation probabilities. Under the regulation of the Danjiangkou Reservoir, drought propagation characteristics for 1–12‐month timescales have shifted markedly: the average propagation time downstream was prolonged from 0.25–0.70 months to 0.94–2.36 months, while the propagation rate declined from 0.83–0.89 to 0.48–0.65, and the sensitivity decreased from 0.83–0.96 to 0.68–0.79. In the natural scenario, the optimal propagation model was based on the Gumbel copula, whereas the observed scenario was best fitted by the Frank copula. The likelihood of hydrological drought increased with the intensity and duration of meteorological drought. However, compared to natural conditions, reservoir regulation significantly delayed the onset and reduced the probability of hydrological drought occurrence. These findings elucidate the nonlinear dynamics of drought propagation and underscore the regulating effect of large‐scale reservoirs on downstream hydrological responses.

Quantifying historical extreme drought is crucial to better understand and contextualize historical extreme droughts and prepare for extreme drought events that may occur in the future. However, the potential impacts of extreme droughts such as those in historical records considering modern day drought resistance and mitigation capacities remain unclear. In order to present the methods of reconstructing historical drought recurrence and conduct a historical drought recurrence scenario analysis under the current defense conditions, a modern day recurrence of the Guangxu drought during the Qing Dynasty from 1875 to 1879 was proposed using the Qing Palace Archives. In which, the historical annual precipitation in core drought areas was quantitatively reconstructed based on snow-rain records derived from the Qing Dynasty archives. And the extreme Guangxu drought was analyzed by establishing the corresponding relationship between precipitation anomaly percentage and the historical drought catalog.. This allowed for the characterization of possible impacts of severe drought on water resources, water supply, food production, and economy under current defense conditions. The results showed that if the Guangxu drought occurred today under the current natural geographical conditions, core drought areas like Beijing, Tianjin, Hebei, Shanxi, Shaanxi, Henan, and Shandong would experience water shortages greater than 50% of their multi-year average water resources. In addition, we found that water transfer projects and large-medium-sized reservoirs will play central roles in drought mitigation in the event of an historical extreme drought.

Investigating changes in compound dry and hot events (CDHEs) and evaluating the associated socioeconomic exposure under climate change are critical for developing effective climate change mitigation and adaptation strategies. However, the socioeconomic exposure and the contributions of various driving factors to socioeconomic exposure under different warming levels remain poorly understood. Using the latest climate experiments from Coupled Model Intercomparison Project Phase 6 (CMIP6), this study assessed future changes in the frequency and socioeconomic exposure of CDHEs and explored the contributing drivers in the Yangtze River Basin (YRB) under 1.5 °C, 2.0 °C, and 3.0 °C global warming scenarios. Results indicate that the occurrences of CDHEs are projected to increase by 2.9, 3.9, and 4.8 times in a 1.5 °C, 2.0 °C, and 3.0 °C warmer world, respectively, compared to the present period (1985–2014). Population exposure to CDHEs increases significantly, with the greatest magnitude occurring at the 2 °C warming scenario. GDP exposure is expected to intensify continuously as the global average temperature rises, with the area experiencing significant increases continuously expanding. Climate change is the dominant driver of total projected changes in population exposure to CDHEs, accounting for approximately 105.6% at 1.5 °C, 110.3% at 2.0 °C, and 141.0% at 3.0 °C. At 1.5 °C, 2.0 °C, and 3.0 °C warming levels, changes in GDP exposure are primarily driven by the synergistic interaction between climate and GDP, accounting for 50.7%, 62.0%, and 64.8%, respectively. These findings provide valuable insights for climate change mitigation and adaptation strategies.

Existing studies on the vulnerability assessment of ecological drought often focus on analyzing vegetation phenotypic characteristics, overlooking the impact of drought on ecosystem services. This study proposes an ecosystem vulnerability assessment method under ecological drought stress from the perspective of ecosystem service value (ESV), considering the characteristics and interactions of hazard-causing factors and hazard-bearing bodies. The spatiotemporal evolution of ecological drought, the spatial characteristics of ecosystem vulnerability, and the vulnerability characteristics of different ecosystem types in the North China region from 1991 to 2021 were evaluated. The results showed that: (1) ecological drought exhibited a trend of intensification followed by alleviation, with the most severe droughts occurring between 2002 and 2011, affecting up to 64.3% of the region; (2) ESV was mainly influenced by vegetation cover and precipitation gradients, displaying a spatial pattern of high values in the southeast and low values in the northwest, with total ESV averaging CNY 18.23 trillion; (3) grasslands exhibited higher sensitivity to drought compared to forests, and the sensitivity was higher in summer and autumn than in winter and spring. This method assessed the vulnerability of ecological drought from the perspective of ecosystem services, providing a new approach for a more comprehensive understanding of the impact of drought on ecosystem service functions.

Ecological drought has emerged as a critical research topic within eco‐hydrology, driven by the increased drought risk associated with global warming. This study aims to unravel the hydrological processes driving ecological drought in Northwest China by (1) constructing standardized indices for precipitation, groundwater storage anomaly, and ecological water deficit to detect variation across different hydrological components; (2) developing a framework to assess the joint and relative impacts of precipitation and groundwater variations on ecological drought; and (3) identifying the primary hydrological drivers of ecological drought across different regions. The results indicate that the joint impact of precipitation and groundwater on ecological drought variation dominates approximately 60% of the area, primarily in arid and semi‐arid regions. The average contribution of this joint impact to the alleviation of ecological drought ranges between 0.26 and 0.43 across all seasons. Notably, groundwater scarcity, rather than precipitation variation, is the primary driver of ecological drought in regions such as southern Shaanxi, southeastern Gansu, and southern Qinghai, accounting for 12.7% to 21.8% of the total area. These insights into the complex hydrological processes underlying ecological drought have significant implications for water resource management and ecosystem conservation in drought‐prone regions. This research provides valuable information for mitigating drought impacts and protecting vulnerable ecosystems in Northwest China and similar regions worldwide.

With the continuous growth in the global population, rapid socioeconomic development, and the impacts of factors like climate change, we are facing increasingly severe challenges regarding water scarcity. The scientific and rational allocation of water resources has become a key factor in ensuring sustainable development. The Henan Yellow River water supply zone occupies a crucial position in the socioeconomic development of Henan Province. Currently, there is a shortage of water resources with relatively low utilization rates. To alleviate the contradiction between water supply and demand, a study on the optimization of water resources (with p = 90%) for the years 2025 and 2030 was conducted. In this study, we constructed a multi-objective optimization model with the objectives of maximizing economic benefits, minimizing total water shortage, and maximizing water use efficiency. The second-generation non-dominated sorting genetic algorithm (NSGA-II) was utilized to solve this model. The results indicate that by 2025, the optimized allocation of water resources will correspond to 17.663 billion m³, reducing the average water shortage rate in the research area to 9.69%. By 2030, the optimized allocation of water resources will further increase to 18.363 billion m³, bringing down the average water shortage rate to 8.34%. Concurrently, the supply structure of the research area will significantly improve after optimization. This is manifested through an increase in the proportion of surface water supply and a substantial rise in the proportion of supply from other water sources, while the proportion of groundwater supply noticeably decreases. These research findings can serve as a reference for the rational utilization and distribution of water resources in the future and can also offer insights for optimizing water resource allocation in other regions.

Soil moisture is a crucial factor that directly influences agricultural drought. As such, investigating drought-monitoring methods utilizing soil moisture data is of significant importance for accurately evaluating and predicting agricultural drought. However, the current soil moisture data for the Daling River Basin is insufficient. Therefore, the variable infiltration capacity (VIC) hydrological model was utilized to simulate soil moisture in the Daling River Basin. The simulated data were then analyzed in conjunction with the standardized moisture anomaly index (SMAPI) to analyze and evaluate the spatio-temporal characteristics of agricultural drought in the Darling River Basin. The results indicate that the frequency of drought occurrence in the basin follows a seasonal pattern of winter > spring > autumn > summer. Between 1981 and 2019, 24 out of 39 years experienced slight or greater drought, 15 years experienced moderate or more severe drought, and 4 years experienced severe drought. Drought conditions have become exceptionally severe in the 21st century. Specifically, the frequency of drought occurrence from 2001 to 2019 was nearly 10 times higher compared to the period from 1981 to 2000. The droughts were most severe in the southeast and southwest of the Daling River Basin, while the northeast and northwest experienced relatively mild drought. Agricultural drought is influenced by numerous complex factors. The contribution of climate change (CC) and other factors (OF) to agricultural drought was quantified by using a partial derivative under six different scenarios. Results showed that SMAPI was positively correlated with precipitation and solar radiation, while negatively correlated with temperature. From 1981 to 2000, SMAPI exhibited an increasing trend that accounted for 61.66% of variability, while a decreasing trend accounted for 38.34%. From 2001 to 2019, SMAPI exhibited a significant decreasing trend that accounted for 93.53% of the variability, while the increasing trend only accounted for 6.47%. CC was the dominant factor in most of the areas with increased SMAPI. OF was the main controlling factor for areas with decreased SMAPI.

Due to the complex coupling between drought and climatic factors, the future drought conditions that might occur under climate change is still unclear. In this research, we used the daily SPEI algorithm to project global drought conditions during 2016–2100 based on the data from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We also employed partial correlation analysis to explore the influence of climate factors on drought. Our analyses show the following: (1) Drought conditions projected by CMIP6 under different models are similar; however, they can vary widely across regions. (2) According to the MK trend test, drought conditions in most regions around the world are expected to become increasingly severe in the future, and this trend is significant. (3) Based on the results of the partial correlation analysis results, it is understood that drought events in most regions worldwide are primarily driven by precipitation. This study contributes to the discussion of projecting future drought conditions and expands the application by utilizing the state−of−the−art CMIP6 climate models and scenarios.Highlight

Droughts are serious natural disasters that adversely affect water resources, agriculture, the economy, and the environment. Reconstructing historical drought records is necessary to assess the impact of droughts and their evolution and has become a top priority to support and improve sustainable water management decisions. In this study, we used Shanxi Province as the research area, and meteorological data from the early years of Guangxu in the Qing Dynasty were reconstructed using historical rain and snow records. The Variable Infiltration Capacity (VIC) model is driven by the reconstruction of historical meteorological data. The study area’s monthly runoff and soil water sequence from 1875 to 1879 were simulated, and the hydrology and soil of the ancient historical period were reproduced in the absence of data. The results show the following: (1) The idea of reconstructing hydrological parameters using historical data is feasible and the VIC model can be used to study drought characteristics under specific scenarios. (2) The proportions of areas with runoff depths less than 10 mm throughout Shanxi from 1875 to 1879 were 55%, 48%, 58%, 19%, and 30%. The annual runoff depth in each region from 1875 to 1877 was less than 60 mm. The hydrological drought from 1875 to 1877 was very serious, and the area covered by the drought was relatively large. (3) The annual average soil water content of various regions was stable between 150 and 510 mm from 1875 to 1879. The soil water content had no apparent interannual variation. The area with soil water content less than 180 mm accounted for ratios as high as 31%. This research provides new ideas for ancient drought research and a scientific basis for regional drought prevention, mitigation, and water resources management, and ensures the orderly progress of agricultural production activities.