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Nuaman Ejaz, Aftab Haider Khan, Muhammad Shahid, Kifayat Zaman, Khaled S. Balkhair, Khalid Mohammed Alghamdi, Khalil Ur Rahman and Songhao Shang
Satellite precipitation products (SPPs) are undeniably subject to uncertainty due to retrieval algorithms and sampling issues. Many research efforts have concentrated on merging SPPs to create high-quality merged precipitation datasets (MPDs) in order to...
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Sellaperumal Pazhanivelan, Vellingiri Geethalakshmi, Venkadesh Samykannu, Ramalingam Kumaraperumal, Mrunalini Kancheti, Ragunath Kaliaperumal, Marimuthu Raju and Manoj Kumar Yadav
The prevalence of the frequent water stress conditions at present was found to be more frequent due to increased weather anomalies and climate change scenarios, among other reasons. Periodic drought assessment and subsequent management are essential in e...
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Nutchanart Sriwongsitanon, Chanphit Kaprom, Kamonpat Tantisuvanichkul, Nattakorn Prasertthonggorn, Watchara Suiadee, Wim G. M. Bastiaanssen and James Alexander Williams
Precise estimation of the spatial and temporal characteristics of rainfall is essential for producing the reliable catchment response needed for proper management of water resources. However, in most parts of the world, gauged rainfall stations are spars...
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Yacine Mohia, Rafik Absi, Mourad Lazri, Karim Labadi, Fethi Ouallouche and Soltane Ameur
To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were implemented using MSG (Meteosat Second Genera...
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Surabhi Upadhyay, Priya Silwal, Rajaram Prajapati, Rocky Talchabhadel, Sandesh Shrestha, Sudeep Duwal and Hanik Lakhe
High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent...
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Helani Perera, Nipuna Senaratne, Miyuru B. Gunathilake, Nitin Mutill and Upaka Rathnayake
Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications...
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Kindie Engdaw Tadesse, Assefa M. Melesse, Adane Abebe, Haileyesus Belay Lakew and Paolo Paron
This study presents three global precipitation products and their downscaled versions (CHIRPSv2, TAMSATv3, PERSIANN_CDR, CHIRPS_D, PERSIANNN_CDR_D, and TAMSAT_D) estimated with observed values from 1983 to 2014. Performance evaluation of global precipita...
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Mariame Rachdane, El Mahdi El Khalki, Mohamed Elmehdi Saidi, Mohamed Nehmadou, Abdellatif Ahbari and Yves Tramblay
Precipitation is a crucial source of data in hydrological applications for water resources management. However, several regions suffer from limited data from a ground measurement network. Remotely sensed data may provide a viable alternative for these re...
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Bagus Setiabudi Wiwoho, Ike Sari Astuti, Imam Abdul Gani Alfarizi and Hetty Rahmawati Sucahyo
A total of three different satellite products, CHIRPS, GPM, and PERSIANN, with different spatial resolutions, were examined for their ability to estimate rainfall data at a pixel level, using 30-year-long observations from six locations. Quantitative and...
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Rodrigo Valdés-Pineda, Juan B. Valdés, Sungwook Wi, Aleix Serrat-Capdevila and Tirthankar Roy
The combination of Hydrological Models and high-resolution Satellite Precipitation Products (SPPs) or regional Climatological Models (RCMs), has provided the means to establish baselines for the quantification, propagation, and reduction in hydrological ...
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