Surface Water Isoscape Modeling in the Himalayan Region: An Alternative for Moisture Source Investigation, Hydrograph Separation, and Paleolatitude Estimation

Abstract

AbstractThe spatial distribution of water isotopes provides essential scientific data for understanding many hydrological, paleoclimate, and ecological processes. The limited isotopic data across the Himalayan River Basins (HRB) obstructs the study of basin‐scale hydrological processes. New data of stable isotopes of oxygen and hydrogen from Indus, in combination with a comprehensive compiled data set from HRB, was used for the first time to create isoscapes (δ18O and d‐excess) for specifically representing surface water. The δ18O and d‐excess isoscape define a clear isotopic distinction along a topographic gradient from south to north and west to east that could be reproduced (predicted) by using a Geographically weighted Regression Model (GWRM) based on surface heterogeneity by considering a combination of predictors (precipitation, temperature, evapotranspiration, runoff, elevation, slope, aspect, and land use landcover). The d‐excess isoscape demonstrates more complicated spatial variability, owing to differential moisture inputs from westerlies and the Indian Summer Monsoon, as well as secondary evaporation processes in the region. GWRM isoscapes have been able to compute the fractional contributions from different water sources across HRB. The model‐derived predicted δ18O and elevation values suggest a second‐order polynomial relationship that represents the Isotopic Lapse Rate more accurately than a linear one. The GWRM predictive isoscapes are sufficiently accurate to serve as a good proxy for the influence of moisture source and runoff estimation, palaeoecological studies, climate reconstruction, and changes in hydrological processes because of climate change. Therefore, GWRM can be applied to other regions where data is lacking.