Chauhan Tejasvi, Devanand Anjana, Roxy Mathew Koll, Ashok Karumuri, Ghosh Subimal
Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India.
Interdisciplinary Program in Climate Studies, Indian Institute of Technology Bombay, Mumbai, India.
Nat Commun. 2023 Sep 22;14(1):5928. doi: 10.1038/s41467-023-41668-x.
Massive river interlinking projects are proposed to offset observed increasing droughts and floods in India, the most populated country in the world. These projects involve water transfer from surplus to deficit river basins through reservoirs and canals without an in-depth understanding of the hydro-meteorological consequences. Here, we use causal delineation techniques, a coupled regional climate model, and multiple reanalysis datasets, and show that land-atmosphere feedbacks generate causal pathways between river basins in India. We further find that increased irrigation from the transferred water reduces mean rainfall in September by up to 12% in already water-stressed regions of India. We observe more drying in La Niña years compared to El Niño years. Reduced September precipitation can dry rivers post-monsoon, augmenting water stress across the country and rendering interlinking dysfunctional. Our findings highlight the need for model-guided impact assessment studies of large-scale hydrological projects across the globe.
印度是世界上人口最多的国家,为应对日益频繁的干旱和洪水,该国提出了大规模的河流联网工程。这些工程涉及通过水库和运河将多余流域的水调至缺水流域,但对水文气象后果缺乏深入了解。在此,我们运用因果关系划定技术、区域气候耦合模型以及多个再分析数据集,结果表明陆地-大气反馈在印度各流域之间形成了因果路径。我们还发现,调水增加灌溉后,印度水资源本就紧张的地区9月平均降雨量最多可减少12%。与厄尔尼诺年相比,拉尼娜年的干旱情况更严重。9月降水量减少会使季风过后河流干涸,加剧全国的水资源紧张状况,导致河流联网工程无法正常运行。我们的研究结果凸显了对全球大型水文项目开展模型指导下的影响评估研究的必要性。