Hydroclimatic Research Group, Lab for Spatial Informatics, International Institute of Information Technology Hyderabad, Hyderabad, India.
Sci Rep. 2022 Jun 2;12(1):9222. doi: 10.1038/s41598-022-12996-7.
The impact of climate change on the oxygen saturation content of the world's surface waters is a significant topic for future water quality in a warming environment. While increasing river water temperatures (RWTs) with climate change signals have been the subject of several recent research, how climate change affects Dissolved Oxygen (DO) saturation levels have not been intensively studied. This study examined the direct effect of rising RWTs on saturated DO concentrations. For this, a hybrid deep learning model using Long Short-Term Memory integrated with k-nearest neighbor bootstrap resampling algorithm is developed for RWT prediction addressing sparse spatiotemporal RWT data for seven major polluted river catchments of India at a monthly scale. The summer RWT increase for Tunga-Bhadra, Sabarmati, Musi, Ganga, and Narmada basins are predicted as 3.1, 3.8, 5.8, 7.3, 7.8 °C, respectively, for 2071-2100 with ensemble of NASA Earth Exchange Global Daily Downscaled Projections of air temperature with Representative Concentration Pathway 8.5 scenario. The RWT increases up to7 °C for summer, reaching close to 35 °C, and decreases DO saturation capacity by 2-12% for 2071-2100. Overall, for every 1 °C RWT increase, there will be about 2.3% decrease in DO saturation level concentrations over Indian catchments under climate signals.
气候变化对世界地表水氧饱和度含量的影响是未来温暖环境下水质的一个重要议题。尽管气候变化信号导致的河水水温(RWT)升高已经成为近期多项研究的主题,但气候变化如何影响溶解氧(DO)饱和度水平尚未得到深入研究。本研究考察了 RWT 升高对饱和 DO 浓度的直接影响。为此,针对印度七个主要污染河流流域的稀疏时空 RWT 数据,开发了一种使用长短期记忆与 k-最近邻 bootstrap 重采样算法集成的混合深度学习模型,用于 RWT 预测。对于 2071-2100 年,NASA 地球交换全球每日下采样气温与代表性浓度路径 8.5 情景的集合预测,Tunga-Bhadra、Sabarmati、Musi、恒河和纳尔马达流域的夏季 RWT 预计将分别增加 3.1、3.8、5.8、7.3 和 7.8°C。夏季 RWT 增加高达 7°C,接近 35°C,并且在 2071-2100 年期间,DO 饱和度容量降低 2-12%。总体而言,在气候信号下,印度流域每升高 1°C 的 RWT,DO 饱和度浓度将降低约 2.3%。