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Drought is a natural hazard which occurs in all climatic zones and affects different sectors, such as irrigation, energy, water supply, and ecology. Monitoring and predicting drought are pressing challenges, as drought is becoming more common and severe owing to the impacts of climate change and increased climatic variability. However, in many areas of the globe, the temporal and spatial characterization of droughts and drought severities are hindered by a lack of reliable, locally-measured long-term data and unevenly distributed, erratic meteorological stations. In this situation, remote sensing datasets such as Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) can offer valuable insights into long-term developments and the spatial characteristics of droughts. Nonetheless, it is often uncertain to which extent data such as CHIRPS succeeds in representing local dynamics and how this varies between geographical regions and climate zones. In this analysis, we aim to evaluate spatial drought conditions over the Seyhan River basin in Turkey in the Eastern Mediterranean. Using the Standardized Precipitation Index (SPI) as a drought index, the applicability of CHIRPS as a long-term satellite precipitation product for drought monitoring is investigated. We compare two spatial representations of the SPI: one derived on a per-pixel basis from CHIRPS data since 1981, the other based on data from 19 meteorological stations scattered across the basin, which was spatialized using inverse distance weighted interpolation (IDW). Our results offer insights into the relative accuracy of CHIRPS data and avenues towards optimizing the quality of spatial drought characterization. [ABSTRACT FROM AUTHOR]

This study aims to analyze future snowmelt runoff and snow extent for the Upper Euphrates Basin (41 109 km 2) which is the most upstream basin of the water tower Mesopotamia and located in the Eastern mountainous part of Türkiye. The future characterization of snowmelt runoff and snow water equivalent is investigated taking the regional climate model projections into account through hydrological model applications. The basin is divided into two major sub-basins Karasu Basin and Murat Basin. The conceptual hydrological models, HBV and HEC-HMS have been utilized to establish a rainfall-runoff relationship. The models are calibrated and validated with observed daily total precipitation and average temperature data for the 1980–2011 period. Future projections are selected for the 2025–2100 periods using EU-CORDEX data with various global circulation models. MPI-ESM-LR and CNRM-CM5 data sets and RCP4.5 and RCP8.5 emission scenarios are used for future projections. The results indicate a decrease in snow cover extent and an increase in snowmelt runoff. The overall assessment will help us to understand how these changes will affect the operations of water resources systems (downstream reservoirs) in terms of flood control, energy production, irrigation, water supply, etc. [ABSTRACT FROM AUTHOR]