Attribution and Risk Projections of Hydrological Drought Over Water‐Scarce Central Asia

Earth s Future, Год журнала: 2025, Номер 13(1)

Опубликована: Янв. 1, 2025

Abstract Central Asia (CA), a typical arid and semiarid region, has experienced worsening droughts, adversely impacting agricultural production socioeconomic development. However, the evolution of hydrological droughts in CA remains unclear. Here, we used instrumental streamflow reanalysis to demonstrate decline surface runoff since 1990s, with 44.6% 33.2% area dominated by reductions snowmelt precipitation, respectively. We found that global warming contributes long‐term decrease runoff, while short‐term fluctuations are caused El Niño‐Southern Oscillation, such as southern drying induced decreasing precipitation during La Niña. project future drought characteristics based on state‐of‐the‐art simulations increasing duration severity CA, especially Amu Darya basin, Caspian Sea East Coast basin. These exacerbated higher anthropogenic emissions, posing high‐level risks 39.01% land 35.9% human population under an extremely high emissions scenario. findings highlight need for improved water conservation technologies concerted development strategies should be considered national policy makers this water‐scarce climatically sensitive region.

Язык: Английский

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Prediction of global water use efficiency and its response to vapor pressure deficit and soil moisture coupling in the 21st century

Journal of Hydrology, Год журнала: 2024, Номер 635, С. 131203 - 131203

Опубликована: Апрель 16, 2024

Язык: Английский

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Human-induced intensification of terrestrial water cycle in dry regions of the globe

npj Climate and Atmospheric Science, Год журнала: 2024, Номер 7(1)

Опубликована: Фев. 23, 2024

Abstract Anthropogenic climate change (ACC) strengthens the global terrestrial water cycle (TWC) through increases in annual total precipitation (PRCPTOT) over land. While increase average PRCPTOT has been attributed to ACC, it is unclear whether this equally true dry and wet regions, given difference changes between two climatic regions. Here, we show regions twice as fast of globe during 1961–2018 both observations simulations. This faster projected grow with future warming, an intensified human-induced TWC driest globe. We phenomenon can be explained by warming response rates well stronger moisture transport under ACC. Quantitative detection attribution results that no longer ACC if are excluded. From 1961–2018, observed increased 5.63%~7.39% (2.44%~2.80%) (wet) much 89% (as little 5%) The ACC-induced likely have beneficial detrimental effects on globe, simultaneously alleviating scarcity while increasing risk major flooding.

Язык: Английский

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Cluster-based local modeling (CBLM) paradigm meets deep learning: A novel approach to soil moisture estimation

Journal of Hydrology, Год журнала: 2024, Номер 635, С. 131161 - 131161

Опубликована: Апрель 5, 2024

Язык: Английский

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Joint utilization of closure phase and closure amplitude for soil moisture change using interferometric synthetic aperture radar

Remote Sensing of Environment, Год журнала: 2025, Номер 319, С. 114620 - 114620

Опубликована: Фев. 7, 2025

Язык: Английский

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Spatiotemporal Trend and Influencing Factors of Surface Soil Moisture in Eurasian Drylands over the Past Four Decades

Forests, Год журнала: 2025, Номер 16(4), С. 589 - 589

Опубликована: Март 28, 2025

Eurasian drylands are vital for the global climate and ecological balance. Quantifying spatiotemporal variations in surface soil moisture (SSM) is essential monitoring water, energy, carbon cycles. The suitability of recent global-scale datasets arid semi-arid regions has not been comprehensively evaluated. This study investigates trends five SSM products—MERRA-2, ESACCI, GLEAM, GLDAS, ERA5—from 1980 to 2023. performance these products was evaluated using situ station data three-cornered hat (TCH) method, followed by partial correlation analysis assess influence environmental factors, including mean annual temperature (MAT), precipitation (MAP), potential evapotranspiration (PET), vapor pressure deficit (VPD), leaf area index (LAI), on from 1981 2018. results showed consistent patterns: higher values India, North China Plain, Russia, lower Arabian Peninsula, Iranian Plateau, Central Asia. Regionally, MAT, PET, VPD, LAI increased significantly (0.04 °C yr−1, 1.66 mm 0.004 kPa 0.003 m2 m−2 respectively; p < 0.05), while MAP rose non-significantly (0.29 yr−1). ERA5 exhibited strongest with (R2 = 0.42), GLEAM (0.37), ESACCI (0.28), MERRA2 (0.19), GLDAS (0.17). Additionally, highest (correlation 0.72), had lowest bias (0.03 m3 m−3) ubRMSE m−3). method identified as having uncertainties (<0.03 m−3), exceeding 0.05 m−3 northern regions. Across land cover types, cropland uncertainty among products, forest highest. Partial dominant factor primary driver SSM. highlighting their strengths limitations. It underscored MAP’s crucial role dynamics provided insights improving water resource management drylands, broader implications understanding hydrological impacts change.

Язык: Английский

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Drivers of aboveground biomass in Quercus wutaishanica Mayr forests based on random forest and structural equation modeling: A cross-scale analysis

Ecological Modelling, Год журнала: 2025, Номер 505, С. 111113 - 111113

Опубликована: Апрель 9, 2025

Язык: Английский

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Mapping the primary factors driving spatiotemporal variations of surface soil moisture in the Yellow River Basin of China

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 10, 2025

Spatiotemporal variations of soil moisture are affected by a combination factors many including climate, vegetation, human activities, which the primary vary greatly in different geographical zonal dimension Yellow River Basin. To identify and map dominant driving spatiotemporal variation surface Basin across zonality from 2003 to 2018, relationships between (precipitation, evaporation, NDVI (Normalized Difference Vegetation Index) land use) were analyzed two dimensions: longitude altitude. The results revealed that: (1) spatial distribution exhibited pattern "higher values east west, lower middle". Temporally, showed noteworthy upward trend with an average change rate 0.00066 m3/m3 year-1 over past 16 years. As altitude ascended, initially increase 0.00061 year⁻1 0.00078 year⁻1, followed decline 0.00035 year⁻1. However, above altitudes 4500 m, once again rose, reaching 0.00084 (2) Among three factors, use accounted for 45%, 18% 8% regional variations, respectively. Climate controlling mainly concentrated southwest, south, northeast, central Loess Plateau northern Hetao plain, distributed around some big cities. Additionally, 29% area was controlled combined effects these no factor evident scattered distribution. (3) From perspective multi-dimensional zonality, degree climate influence is high low middle, increases vegetation increased first then decreased west east. greater area, slightly peak value appeared middle at 1000 m. And activity intensity part.

Язык: Английский

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Soil moisture deficits triggered by increasing compound drought and heat events during the growing season in Arid Central Asia

Journal of Hydrology, Год журнала: 2025, Номер 660, С. 133397 - 133397

Опубликована: Апрель 29, 2025

Язык: Английский

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Spatiotemporal Evolution Patterns of Global Actual Evapotranspiration and Its Influencing Factors

Journal of Geophysical Research Atmospheres, Год журнала: 2025, Номер 130(10)

Опубликована: Май 15, 2025

Abstract Understanding the spatiotemporal dynamics of actual evapotranspiration (AET) and its drivers is critical for addressing climate change ensuring ecosystem sustainability. Here, we analyzed global AET trends from 2001 to 2019 assessed relative contributions six key influencing factors. Our findings reveal that exhibits a significant positive trend across 31.6% land surface, predominantly in Amazon Plain Loess Plateau China, whereas negative observed over 5.2% area, concentrated eastern Brazil southern Africa. The normalized difference vegetation index (NDVI) showed strongest partial correlation with AET, 26.6% area. Multiple linear regression (MLR) analysis indicates precipitation exerts greatest influence on 39.9% world, followed by wind speed (WS) at 37.9%, while soil moisture (SM) dominant factor only 0.2% Notably, WS drives 23.5% trends, contributes most just 8.6% Among factors evaluated, NDVI emerges as primary driver changes, precipitation, surface net solar radiation (SNSR) has weakest influence. These insights advance understanding AET's evolution driving mechanisms, offering foundation devising adaptive strategies mitigate impacts enhance resilience.

Язык: Английский

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