|
|
|
|
|
Zuhang Wu, Yun Zhang, Lifeng Zhang, Xiaolong Hao, Hengchi Lei and Hepeng Zheng
In this study, we evaluated the performance of rain-retrieval algorithms for the Version 6 Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) products, against disdrometer observations and improved their retrieval algorithms by...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Georgia Papacharalampous, Hristos Tyralis, Anastasios Doulamis and Nikolaos Doulamis
Merging satellite products and ground-based measurements is often required for obtaining precipitation datasets that simultaneously cover large regions with high density and are more accurate than pure satellite precipitation products. Machine and statis...
ver más
|
|
|
|
|
|
|
|
|
|
|
Niloufar Beikahmadi, Antonio Francipane and Leonardo Valerio Noto
Accurate precipitation estimation remains a challenge, though it is fundamental for most hydrological analyses. In this regard, this study aims to achieve two objectives. Firstly, we evaluate the performance of two precipitation products from the Integra...
ver más
|
|
|
|
|
|
|
|
|
|
|
Na Zhao
Accurate estimation of precipitation is critically important for a variety of fields, such as climatology, meteorology, and water resources. However, the availability of precipitation measurements has proved to be spatially inadequate for many applicatio...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|