Evaluation of Satellite-Based and Reanalysis Precipitation Datasets with Gauge-Observed Data over Haraz-Gharehsoo Basin, Iran

Abstract

Evaluating satellite-based products is vital for precipitation estimation for sustainable water resources management. The current study evaluates the accuracy of predicting precipitation using four remotely sensed rainfall datasets—Tropical Rainfall Measuring Mission products (TRMM-3B42V7), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Records (PERSIANN-CDR), Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR), and National Centers for Environmental Prediction (NCEP)-Climate Forecast System Reanalysis (CFSR)—over the Haraz-Gharehsoo basin during 2008–2016. The benchmark values for the assessment are gauge-observed data gathered without missing precipitation data at nine ground-based measuring stations over the basin. The results indicate that the TRMM and CCS-CDR satellites provide more robust precipitation estimations in 75% of high-altitude stations at daily, monthly, and annual time scales. Furthermore, the comparative analysis reveals some precipitation underestimations for each satellite. The underestimation values obtained by TRMM CDR, CCS-CDR, and CFSR are 8.93 mm, 20.34 mm, 9.77 mm, and 17.23 mm annually, respectively. The results obtained are compared to previous studies conducted over other basins. It is concluded that considering the accuracy of each satellite product for estimating remotely sensed precipitation is valuable and essential for sustainable hydrological modelling.

Assessing the impact of COVID-19 lockdowns on water quality in Anzali Wetland, Iran, using remote sensing data

“…According to the literature review, most of research during the COVID-19 outbreak uses satellite imagery to assess water quality. One of the most significant advantages of using remote sensing imagery over ground-based data is its broader coverage across the globe (Goodarzi et al 2022a). For instance, Cherif et al (2020) studied water temperature and quality at the west coast of Tangier, Morocco, using Sentinel-3 images at multiple points in April 2019 and 2020.…”

Climate change impacts on snow cover area and snowmelt runoff in the Ajichai Basin‐Iran

“…On the other hand, with the expansion of urbanization and the increase of greenhouse gas emissions, according to the studies conducted and the reports published in this field, it is expected that the world will gradually face climate change, which is known as the climate change phenomenon (Piao et al, 2010; Zahabiyoun et al, 2013). A phenomenon that will affect temperature and precipitation in the future (Bal et al, 2016; Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022). Snow is closely related to temperature, and an increase in temperature causes a decrease in snowfall or a faster melting of snow (Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022).…”

“…A phenomenon that will affect temperature and precipitation in the future (Bal et al, 2016; Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022). Snow is closely related to temperature, and an increase in temperature causes a decrease in snowfall or a faster melting of snow (Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022). Even an increase in precipitation will affect the quicker melting of snow in the region, which can cause floods in the area (Sui & Koehler, 2001).…”