Weekly VPD and Monthly Precipitation as Contrasting Dominant Drivers of Soil Moisture in the Yangtze River Basin

Multiscale and seasonal meteorological drought variability in China’s Lancang River Basin: Relative roles of precipitation and potential evapotranspiration

SWAT-based multi-index assessment of meteorological, agricultural, and hydrological drought characteristics in the Mekong River Basin

Drought has intensified across the Mekong River Basin (MRB) due to climate variability and increasing human interventions, creating substantial risks for water resources and agriculture. This study applied the SWAT model to simulate hydrological processes and evaluate meteorological, agricultural, and hydrological droughts using the SPI, SSWI, and SRI indices. Model calibration (1982–2001) and validation (2002–2019) at seven hydrological stations produced satisfactory to very good performance, with R2 values ranging from 0.80 to 0.89 and 0.52 to 0.69, respectively. The model effectively captured seasonal flow dynamics, although uncertainties increased toward downstream regions influenced by reservoir operations and land-use change. Analysis of precipitation and soil moisture revealed strong spatial contrasts among sub-basins: upstream areas exhibited limited infiltration and rapid drainage. At the same time, midstream and downstream regions retained soil moisture longer due to favorable topography and soil characteristics. Multi-decadal drought evaluation reveals several prominent drought periods from 1970 to 2000, consistent with major large-scale climate anomalies. Correlation analysis shows stronger linkages among drought indices at longer accumulation periods, indicating tighter coupling of drought processes under prolonged dry conditions. Overall, integrating SWAT simulations with multi-index drought diagnostics provides a robust framework for characterizing meteorological, agricultural, and hydrological drought dynamics, supporting improved drought monitoring and water resource management in the MRB.

Hydroclimatic Variability and Water Balance Instability in Semi-Arid Steppe Ecosystems Under Climate Warming

This study investigates hydroclimatic variability and water balance dynamics in the Akmola region during 2003–2023 using observations from 16 meteorological stations. The study evaluates changes in air temperature, precipitation, reference evapotranspiration (ET0), climatic water balance, and drought conditions. Reference evapotranspiration was calculated using the FAO-56 Penman–Monteith method, while drought variability was assessed using the 12-month Standardized Precipitation–Evapotranspiration Index (SPEI-12). Temporal trends were analyzed using the Mann–Kendall test and Sen’s slope estimator. The results revealed significant spatial heterogeneity in hydroclimatic conditions across the region. Air temperature showed a consistent increasing trend at most stations, accompanied by increasing atmospheric evaporative demand. All stations were characterized by a persistently negative climatic water balance, with mean annual values of approximately −750 mm, indicating a regional moisture deficit. Reference evapotranspiration exhibited significant spatial variability, with the highest values observed in the southern and central parts of the region. Precipitation remained the dominant control of water balance variability (r = 0.79–0.96), while increasing temperature intensified moisture deficits through increased evapotranspiration. SPEI-12 indicated recurrent drought episodes and increasing drought vulnerability associated with warming-induced atmospheric water demand. The study demonstrates that increasing evapotranspiration is becoming a major driver of water stress in the Akmola region and highlights the importance of integrating climatic water balance and SPEI indicators for drought monitoring and climate adaptation in semi-arid steppe regions.

Climate change impacts on water resources in the Low Zab River Basin: a spatiotemporal analysis

Climate change affects water resources in semi-arid basins by altering precipitation, land surface temperature (LST), evapotranspiration, and surface-water persistence. This study assessed hydroclimatic variability in the Lower Zab River Basin (LZRB), Iraq, during 2000–2021 using satellite and reanalysis datasets processed in Google Earth Engine. Linear regression, Mann-Kendall tests, Sen's slope, Spearman correlation, and partial correlation were applied to evaluate trends and climate-water relationships. Surface-water extent showed a slight decreasing tendency (Sen slope = −0.0125% yr−1; p = 0.091), while annual mean precipitation also decreased non-significantly (−0.00114 mm h−1 yr−1; p = 0.191) and LST increased non-significantly (+0.0406 °C yr−1; p = 0.341). Northern and eastern areas were wetter, with higher evapotranspiration and lower LST, whereas the southwest was warmer and drier. Water-body area was more strongly associated with precipitation (R² = 0.6398; r ≈ 0.80) than with LST (R² = 0.483; r ≈ −0.70), while rank-based and partial correlations confirmed LST as an important inverse stress factor. Overall, water-body variability reflects the combined effects of precipitation supply and thermal-evaporative stress, supporting cloud-based geospatial monitoring of climate-water interactions in semi-arid basins.

Multi-Layer Soil Moisture Variability and Its Hydroclimatic Controls in Tajikistan, Central Asia

Tajikistan is highly vulnerable to climate change and depends heavily on agriculture, making soil moisture dynamics critical for water and food security. This study provides a comprehensive assessment of soil moisture variability across four depth layers (0–10 cm, 10–40 cm, 40–100 cm, and 100–200 cm) from 2000 to 2021 using NASA’s GLDAS-2 model and remote sensing data for land-air temperature, precipitation, and vegetation to identify key nexus of soil moisture change. Moisture data were converted to volumetric water content (m3/m3) to enable valid cross-layer comparisons. Our findings show that volumetric soil moisture increases with depth, from 0.219 m3/m3 at the surface to 0.293 m3/m3 in the deepest layer. Eastern Tajikistan exhibits higher moisture levels than the west, likely due to differing precipitation patterns. Seasonally, spring replenishes the soil with the highest moisture (0.270 m3/m3 at 0–10 cm), while summer strips it away (0.194 m3/m3 at 0–10 cm), potentially reflecting evapotranspiration losses. A significant warming trend is evident, with mean annual temperature peaking at 4.32 °C in 2016. Precipitation strongly influences upper-layer moisture (correlation: 0.49 at 0–10 cm; 0.44 at 10–40 cm). While annual averages remain stable, seasonal trends reveal significant winter wetting (+0.00043 m3/m3 per year, p < 0.001) and summer drying in the deepest layer, indicating intensifying seasonal contrasts. Vegetation follows a parallel pattern, declining from 2000 to 2010 and recovering thereafter. Greening is observed in 16.74% of the area, concentrated in the western mountains and northern highlands, while only 2.98% shows decline, mostly in small, fragmented patches. These findings highlight the substantial connection between climate, soil moisture, and vegetation in Tajikistan. They also suggest the need for depth-specific and seasonally aware water management strategies in this climate-sensitive region. Managing water here means looking beyond surface averages and thinking in layers, seasons, and geography.

Spatiotemporal variability and trends of precipitation, temperature, and evapotranspiration in the Muger sub-basin of the Abbay basin Ethiopia

This study used time series data from 1980 to 2022 to investigate spatiotemporal changes and trends of precipitation, temperature, and evapotranspiration in Muger sub-basin. The coefficient of variation (CV), precipitation concentration index (PCI), and seasonality index (SAI) were used to assess variability, while the Mann–Kendall test, Sen’s slope estimator, and innovative trend analysis (ITA) were applied to detect and quantify trends in climatic variables. Seasonally, the CV was highest in the winter season, indicating strong rainfall variability. Irregular rainfall distribution was observed at Debre Berhan station, as indicated by high PCI values. The SAI results show that the Muger sub-basin alternates between dry and wet conditions for both temperature and rainfall. The maximum significant increasing trend ( P  < 0.05) in annual rainfall was recorded at Gerba Guracha station (Z = 2.74, S = 8), while a significant decreasing trend was observed at Jeldu station (Z = − 3.28, S = − 23.26). The annual maximum temperature showed, the maximum significant increasing trend 0.038 °C/year recorded at Addis Ababa station. The minimum temperature reveals the maximum significant increasing trends across all seasons, with rate of 0.013 °C/year in winter, 0.046 °C/year in the spring, 0.033 °C/year in the summer, and 0.025 °C/year in the autumn. Sen’s slope revealed a maximum increasing rate 5.89 mm/year, whereas ITA of annual rainfall reveals upward and downward tendency at low, medium, and high cluster categories. All stations displayed an upward trend in annual ET 0 , with exception of Jeldu station, which had a magnitude of (− 6.195 mm/year). The rising trend in ET 0 could be the result of increasing temperature during the 1980–2022 period, further increasing stress on water resources. These changes indicate ongoing climate variability in the sub-basin, which may have important information for water resource availability and agricultural planning strategies in the Muger sub-basin.