Study region: Madeira River basin, southwestern Amazonia Study focus: This study investigates spatial and temporal changes in precipitation, evaporation, and streamflow, and their relationship with deforestation in the Madeira River basin, the largest Amazonian sub-basin. We applied Mann-Kendall trend analysis, change-point detection, and correlation analysis across multiple spatial scales, using satellite, reanalysis, and observed data from 1981 to 2015. These methods enabled us to detect long-term trends, identify shifts, and quantify the relationships between forest loss and hydrological changes New hydrological insights for the region: The basin experienced an average deforestation rate of 2810 km² per year from 2001 to 2020, predominantly in the Brazilian portion. Between 1981 and 2016, we observed statistically significant negative trends in precipitation, evaporation, and streamflow, especially in the most deforested areas during the wet season. Correlation analysis (2001–2015) showed a statistically significant and positive relationship between forest area and evaporation in wet months (r = 0.73, p < 0.1) and a negative correlation between forest area and streamflow during the same season (r = –0.6, p < 0.1). These findings highlight the critical role of forests in modulating hydrological processes, supporting the hypothesis that deforestation may reduce evaporation, alter moisture recycling, and slow the water cycle. While our results are robust, we acknowledge that factors such as climate variability and land management practices may also influence hydrological changes and should be considered in future research.

While drought impacts are widespread across the globe, climate change projections indicate more frequent and severe droughts. This underscores the pressing need to increase resistance and resilience to drought. The strategic application of Preventive Drought Management Measures (PDMMs) is a suitable avenue to reduce the likelihood of drought and ameliorate associated damages. In this study, we use an optimisation approach with a multicriteria decision-making method to allocate PDMMs for reducing the severity of agricultural and hydrological droughts. The results indicate that implementing PDMMs can reduce the severity of agricultural and hydrological droughts, and the obtained management scenarios (solutions) highlight the utility of multi-objective optimisation for PDMMs planning. However, examined management scenarios also illustrate the trade-off between managing agricultural and hydrological droughts. PDMMs can alleviate the severity of agricultural droughts while producing opposite effects for hydrological droughts (or vice versa). Furthermore, the impact of PDMMs displays temporal and spatial variabilities. For instance, PDMMs implementation within a specific subbasin may mitigate the severity of one type of drought in a given month yet exacerbate drought conditions in preceding or subsequent months. In the case of hydrological droughts, the PDMMs may intensify streamflow deficits in the intervened subbasins while alleviating the hydrological drought severity downstream (or vice versa). These complexities emphasise a customised implementation of PDMMs, considering the basin characteristics (e.g., rainfall distribution over the year, soil properties, land use, and topography) and the quantification of PDMMs' effect on the severity of each type of drought.

Cap-Haïtien, the second largest city in Haiti, is highly vulnerable to earthquakes, landslides, and flooding. The rapid pace of urbanization and deforestation has exacerbated the risk of flooding, resulting in disasters in November 2012, 2016, and 2022. This study aims to assess the impact of urbanization and deforestation on river flooding in Cap-Haïtien by applying the hydrological model Soil Water Assessment Tool (SWAT) and the hydrodynamic model Sobek-Rural. We examined the current situation and a scenario of future urbanization and deforestation. Urbanization and deforestation are found to play a pivotal role in the production and deposition of sediment along the lower Haut-du-Cap River reaches. The existing hydraulic capacity of the river and its drainage system cannot handle the estimated peak flows. The mountain ravines west of the city are found to be the primary source of sediment-laden flash floods. We recommend retention basins, drainage extensions, and pragmatic public policies to mitigate flood risk. Comprehensive strategies are needed to address the detrimental effects of urbanization and deforestation on flooding in Cap-Haïtien and similar regions where a lack of water governance has worsened the flooding alongside urbanization and deforestation. We generalize our experiences from Cap-Haïtien into a broader framework for data-scarce areas.

The Upper Indus Basin (UIB) heavily depends on its frozen water resources, and an accelerated melt due to the projected climate change may significantly alter future water availability. The future hydro-climatic regime and water availability of the Hunza basin (a sub-basin of UIB) were analysed using the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections. A data and parameter parsimonious precipitation-runoff model, the Distance Distribution Dynamics (DDD) model, was used with energy balance-based subroutines for snowmelt, glacier melt and evapotranspiration. The DDD model was set up for baseline (1991–2010), mid-century (2041–2060) and end-century (2081–2100) climates projections from two global circulation models (GCM), namely EC-Earth3 and MPI-ESM. The projections indicate a substantial increase in temperature (1.1–8.6 °C) and precipitation (12–32%) throughout the twenty-first century. The simulations show the future flow increase between 23–126% and the future glacier melt increase between 30–265%, depending on the scenarios and GCMs used. Moreover, the simulations suggest an increasing glacier melt contribution from all elevations with a significant increase from the higher elevations. The findings provide a basis for planning and modifying reservoir operation strategies with respect to hydropower generation, irrigation withdrawals, flood control, and drought management.

In many high altitude river basins, the hydro-climatic regimes and the spatial and temporal distribution of precipitation are little known, complicating efforts to quantify current and future water availability. Scarce, or non-existent, gauged observations at high altitudes coupled with complex weather systems and orographic effects further prevent a realistic and comprehensive assessment of precipitation. Quantifying the contribution from seasonal snow and glacier melt to the river runoff for a high altitude, melt dependent region is especially difficult. Global scale precipitation products, in combination with precipitation-runoff modelling may provide insights to the hydro-climatic regimes for such data scarce regions. In this study two global precipitation products; the high resolution (0.1° × 0.1°), newly developed ERA5-Land, and a coarser resolution (0.55° × 0.55°) JRA-55, are used to simulate snow/glacier melts and runoff for the Gilgit Basin, a sub-basin of the Indus. A hydrological precipitation-runoff model, the Distance Distribution Dynamics (DDD), requires minimum input data and was developed for snow dominated catchments. The mean of total annual precipitation from 1995 to 2010 data was estimated at 888 mm and 951 mm by ERA5-Land and JRA-55, respectively. The daily runoff simulation obtained a Kling Gupta efficiency (KGE) of 0.78 and 0.72 with ERA5-Land and JRA-55 based simulations, respectively. The simulated snow cover area (SCA) was validated using MODIS SCA and the results are quite promising on daily, monthly and annual scales. Our result showed an overall contribution to the river flow as about 26% from rainfall, 37–38% from snow melt, 31% from glacier melt and 5% from soil moisture. These melt simulations are in good agreement with the overall hydro-climatic regimes and seasonality of the area. The proxy energy balance approach in the DDD model, used to estimate snow melt and evapotranspiration, showed robust behaviour and potential for being employed in data poor basins.

The Upper Blue Nile (UBN) basin is less-explored in terms of drought studies as compared to other parts of Ethiopia and lacks a basin-specific drought monitoring system. This study compares six drought indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Evapotranspiration Deficit Index (ETDI), Soil Moisture Deficit Index (SMDI), Aggregate Drought Index (ADI), and Standardized Runoff-discharge Index (SRI), and evaluates their performance with respect to identifying historic drought events in the UBN basin. The indices were calculated using monthly time series of observed precipitation, average temperature, river discharge, and modeled evapotranspiration and soil moisture from 1970 to 2010. The Pearson’s correlation coefficients between the six drought indices were analyzed. SPI and SPEI at 3-month aggregate period showed high correlation with ETDI and SMDI (r > 0.62), while SPI and SPEI at 12-month aggregate period correlate better with SRI. The performance of the six drought indices in identifying historic droughts: 1973–1974, 1983–1984, 1994–1995, and 2003–2004 was analyzed using data obtained from Emergency Events Database (EM-DAT) and previous studies. When drought onset dates indicated by the six drought indices are compared with that in the EM-DAT. SPI, and SPEI showed early onsets of drought events, except 2003–2004 drought for which the onset date was unavailable in EM-DAT. Similarly, ETDI, SMDI and SRI-3 showed early onset for two drought events and late onsets in one-drought event. In contrast, ADI showed late onsets for two drought events and early onset for one drought event. None of the six drought indices could individually identify the onsets of all the selected historic drought events; however, they may identify the onsets when combined by considering several input variables at different aggregate periods.