A Comparison of Simulated Runoff Based on Ground Rain Gauges and Persiann-CDR Satellite Precipitation Records Using Swat Model

Abstract

Abstract. Easy access to valid climatic data has always played a fundamental role in progressing hydrological studies. That is why numerous satellite-based precipitation products (SPPs) have been generated in the contemporary era. Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) is considered one of the most popular climatic databases which started to produce daily rainfall data with 0.25° × 0.25° temporal and spatial resolutions in 1983. The aim of this research is to evaluate how well PERSIANN-CDR has performed in a rainfall-runoff modeling application over the period of 1994 to 2015. In this regard, using Soil & Water Assessment Tool (SWAT), two rainfall-runoff models based on Ground-based Rain Gauge stations (GRGs) and PERSIANN-CDR precipitation records were developed for the Chelgerd sub-basin, which is the main branch of the Zayandeh-Roud Basin in central Iran, in order to analyze how accurate the simulated runoff by PERSIANN-CDR database is. Comparing the developed SWAT model calibration results using the satellite database precipitation (NS = 0.78, P-Factor = 0.52, and R-Factor = 0.41) to calibration results of the developed model based on GRGs (NS = 0.81, P-Factor = 0.54, and R-Factor = 0.42) showed that although PERSIANN-CDR precipitation magnitudes were typically less than GRGs records, accuracy indicators of simulated runoffs to Ghale-Shahrokh were almost the same.

Using Optical Satellite Images and Satellite Altimetry Data to Estimate Volume Variations in Dams

“…In monitoring the water volume variations of Lake Victoria, elevation data from ERS-1, ERS-2, and Envisat obtained through the Ice-1 re-tracking algorithm, along with water surface area data from MODIS/Terra image processing, were used over 22 years (Tong et al, 2016). Also, in Iran, some studies have been related to the watersheds, as described in the sources (Ahmadi et al, 2022;Barezaei & Jalali, 2023;He et al, 2023;Jalali et al, 2021;Kordi & Yousefi, 2022;Mohammadpouri et al, 2023). Another study focused on the vital role of monitoring lake dynamics in understanding water balance, resource management, and ecological sustainability.…”