Emerging trends and spatial shifts of drought potential across global river basins.

Droughts have devastating effects on various sectors and are difficult to quantify and track because of the invisible and slow but prevalent propagation. This dilemma is more significant in the case of the complex interactions between land and atmosphere mechanisms, which are inadequately considered in previous drought metrics. Here, we investigate the spatiotemporal variability of the recently devised metric called 'Drought Potential Index (DPI)', which incorporates the antecedent land water storage and current precipitation. Using the spatial weighted centroid method, we elucidate the emerging spatial movement of the DPI within 168 major global river basins and analyze its influential factors. Improved drought detection and performance disparity of DPI as compared with multi-scale (i.e., 1, 3, 6, 9, 12-month) Standardized Precipitation Index, ensemble soil moisture anomaly, and Total Storage Deficit Index corroborate the robustness and improved insights of DPI. Higher increasing trends in DPI are detected over dryland basins (0.39 ± 0.43 %/a) than in the humid zones (0.15 ± 0.34 %/a). Six hotspot basins, namely, Don, Yellow, Haihe, Rio Grande, Sao Francisco, and Ganges river basins, are identified with increasing (2.1-3.5%/a) DPI during 2003-2021. The interannual occurrence of the highest DPI, spatial shifts, and relative contribution of DPI's constituent variables correspond well to the climatic and anthropogenic changes in humid and dry land basins. The absolute latitudinal/longitudinal shifts of ∼2° (as high as ∼3.2/4.9°) in DPI in 30% (47 out of 168 basins) of the global basins highlight the need for analyzing the water scarcity problems from both the perspectives of long-term trends and spatial shifts. Our findings provide a global assessment of the spatiotemporal shifts of drought potential and will be beneficial to understanding the anthropogenic and climatic influences on water resource management under a changing environment.

Future projections of worst floods and dam break analysis in Mahanadi River Basin under CMIP6 climate change scenarios.

This study provides a comprehensive analysis of the hydrological effects and flood risks of the Hirakud Reservoir, considering different CMIP6 climate change scenarios. Using the HEC-HMS and HEC-RAS models, the study evaluates future flow patterns and the potential repercussions of dam breaches. The following summary of the work: firstly, the HEC-HMS model is calibrated and validated using daily stage-discharge observations from the Basantpur station. With coefficient of determination (R2) values of 0.764 and 0.858 for calibration and validation, respectively, the model demonstrates satisfactory performance. Secondly, The HEC-HMS model predicts future flow for the Hirakud Reservoir under three climate change scenarios (SSP2-4.5, SSP3-7.0 and SSP5-8.5) and for three future periods (near future, mid future and far future). Thirdly, by analyzing time-series hydrographs, the study identifies peak flooding events. In addition, the HEC-RAS model is used to assess the effects of dam breaches. Downstream of the Hirakud Dam, the analysis highlights potential inundation areas and depth variations. The study determines the following inundation areas for the worst flood scenarios: 3651.52 km2, 2931.46 km2 and 4207.6 km2 for the near-future, mid-future and far-future periods, respectively. In addition, the utmost flood depths for these scenarios are determined to be 31 m, 29 m and 39 m for the respective future periods. The study area identifies 105 vulnerable villages and several towns. This study emphasizes the importance of contemplating climate change scenarios and implementing proactive measures to mitigate the peak flooding events in the Hirakud reservoir region.