Open AccessEstimation of River Discharge from Satellite Observations
Author(s) -
Dhanendra Bahekar
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i4.603
Subject(s) - streamflow , flood forecasting , quantile , environmental science , glue , hydrology (agriculture) , drainage basin , surface runoff , flood myth , routing (electronic design automation) , computer science , geology , statistics , mathematics , geography , cartography , ecology , computer network , materials science , geotechnical engineering , archaeology , composite material , biology
The role of streamflow is very important in any type of hydrologic. For very effective flood routing and hydraulic structure design, it is important to have a large dataset of past years. We now have a conceptual rainfall-runoff model that can predict streamflow based on pre-existing datasets. Because there is no or very little observed data in un-gauged basins, calibrating these models to predict daily streamflow becomes difficult. Nowadays, parameters for example river width can be observed using satellite images, and some studies show a promising associated relation between discharge and river width. The suggested study demonstrates a method for calculating streamflow from river width extracted with the help of satellite imagery. To predict streamflow, hydrological models are calibrated using river width instead of in site observed streamflow, and for estimating uncertainty Generalized Likelihood Uncertainty Estimation (GLUE) is used. For validation, the suggested method is implemented in the Kharun river basin situated in the Chhattisgarh state of India. The obtained Nash-Sutcliffe efficiency is 92.6 % for simulated river discharge in 2019-2020 at the 50% quantile, which is promising.