Investigating Alternative Strategies for Streamflow Simulation in Data Sparse Watersheds

Abstract

Satellite based precipitation (SBPP’s) have proved their significance as a main source of input data for various hydrological simulations in recent decades. These models are crucial, particularly in regions with complicated topography or ungauged basins where ground-based observatories are typically few or non-existent. SBPP’s have the potential to overcome the issues of data scarcity caused by sparse rain gauges. However, significant uncertainties appear in these precipitation data, and especially in complex topographic regions. Before being used in practice, these precipitation products' accuracy must be assessed. The objective of this research is to evaluate semi distributed modelling of a data scarce watershed by using Arc swat model utilizing four different SBPPs (SM2RAIN, PERSIANN, PERSIANN-CDR and MEERA-2). Arc-SWAT model was analyzed with precipitation data from 2010 to 2022 for hydrological modelling and SWAT-CUP was used for Calibration and Validation. The time period of 2010 to 2014 as warm-up period and from 2015 to 2018 calibration time period and from 2019 to 2022 was time period of validation in SWAT-CUP by using SUFI-2 method. This study assessed the applicability and accuracy evaluation of notable SBPP’s in sparsely gauged catchment. Harro river, which is a catchment of Khanpur Dam causes challenges for hydrological modelling and was selected as the study are for this research project. SBPP’s were analyzed on the basis of statically matrices R², NS, SSQR, PBIAS, KGE, and RSR. The results revealed that (add the numbers of performance metrics like R^{2 of all SBPPS} and than write that based upon all other metrics SM2RAIN pefromed better)

Conclude that on the bases this evaluation matrices the SM2RAIN well performance then other SBPP’s under consideration.