Hydrological Modeling: A Better Alternative to Empirical Methods for Monthly Flow Estimation in Ungauged Basins

Abstract

Water resource is required for agricultural, industrial, and domestic activities and for environmental preservation. However, with the increase in population and growth of urbanization, industrialization, and commercial activities, planning and management of water resources have become a challenging task to meet various water demands globally. Information and data on streamflow hydrology are, thus, crucial for this purpose. However, availability of measured flow data in many cases is either inadequate or not available at all. When there is no gauging station available at the site of interest, various empirical methods are generally used to estimate the flow there and the best estimation is chosen. This study is focused on the estimation of monthly average flows by such methods popular in Nepal and assessment of how they compare with the results of hydrological simulation. Performance evaluation of those methods was made with a newly introduced index, Global Performance Index (GPI) utilizing six commonly used goodness-of-fit parameters viz. coefficient of determination, mean absolute error, root mean square error, percentage of volume bias, Nash Sutcliff Efficiency and Kling-Gupta Efficiency. This study showed that hydrological modeling is the best among the considered methods of flow estimation for ungauged catchments.