Snow is the main hydrological component, and its contribution plays a key role in runoff formation in Uzbekistan, Central Asia. However, climate change has altered snow accumulation dynamics over the past two decades. This study investigated the impacts of seasonal changes in snow on river runoff in the Pskem and Uradarya Basins over the past 22 hydrological years (2001–2023), considering air temperature and precipitation variations. In-situ data from meteorological and hydrological stations in the study areas were used to examine the trend dynamics during the study period. Pearson’s correlation analysis was applied to examine the statistical relationship between the winter snow accumulation and summer discharge. The statistical significance of the trend dynamics was tested using the Mann-Kendall test. The results revealed a significant reduction in snow accumulation over the study period and the number of overall snowfall days, with a marked decline observed in recent years. Consequently, the contribution of seasonal snow to river runoff has markedly decreased, leading to a reduction in the discharge volume during the vegetation period. A reduction in discharge volume in both basins over the past 22-year period (2001–2023) was statistically confirmed based on in-situ data.

Drought events in arid regions can be categorized as traditional, characterized by slow development and long duration, and flash, marked by rapid intensification over short timescales. This study assesses the spatial and temporal characteristics of both drought types in Uzbekistan’s Kashkadarya region from 1990 to 2019 using root-zone soil moisture (SM) data from the SiBUC land surface model, compared to ERA5-Land and CCISM datasets. SM anomalies were identified using percentile thresholds, alongside temperature and precipitation anomalies. Flash droughts typically developed in spring under combined short-term precipitation deficits and elevated temperatures, rapidly depleting SM during critical vegetation growth. Traditional droughts evolve more gradually, due to sustained precipitation deficits, with longer duration and greater spatial extent. Traditional droughts showed more severe SM anomalies often below –0.6, while flash droughts were more localized, with anomalies between –0.5 and –0.1. Model comparisons against CCISM indicate that ERA5-Land strongly overestimates wet-season SM, whereas SiBUC shows a weaker positive bias. Nevertheless, all datasets confirm intensifying drought frequency and severity in recent decades, particularly in dryland and pasture zones. These findings support importance of high-resolution SM data for improving drought monitoring, early warning systems, and targeted adaptation strategies in complex land use and water-stressed arid agricultural regions.

A hydrogeochemical investigation was conducted at Takezaki Spring, located in the Nango Valley within the Aso Caldera – one of the largest caldera volcanoes in the world – where the spring is thought to be formed by the mixing of multiple groundwater flow systems. The study was conducted from October 2024 (wet season) to June 2025 (dry season). Seasonal variations in dissolved ion concentrations and stable isotope ratios of oxygen and hydrogen revealed that, toward the dry season, the contribution of groundwater from the central cone flow system – characterized by a larger and more stable flow – became increasingly dominant in the spring discharge. In addition, a marked rise in the oxygen isotope ratio and an increase in discharge was observed after mid-April, when paddy field irrigation commenced upstream. These observations suggest that irrigation water may have significantly contributed to spring discharge even during the dry season. Analysis using multiple hydrological tracers clarified the seasonal and temporal variability of end-members from the wet to the dry season.

This study examined the usability of agricultural reservoirs as water resources and the sustainability of their maintenance and management across Japan, with a focus on the characteristics of municipalities. Using a nationwide database of agricultural reservoirs, we developed metrics to quantitatively assess the water availability and maintenance difficulty of agricultural reservoirs in each municipality, based on precipitation and population data. These metrics were applied in regional analyses, revealing spatial patterns that reflect both demographic and climatic conditions. Future values of the metrics were also estimated using climate model-based precipitation projections and population forecasts derived from the cohort component method. The results emphasized that the potential and challenges for utilizing and managing agricultural reservoirs vary among municipalities. The analysis further identified scattered municipalities across Japan – including not only western Japan, which has traditionally been recognized as having a large number of agricultural reservoirs, but also other regions – where increased attention to reservoir management and utilization will be required in the future.