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Linda Petutschnig, Thomas Clemen, E. Sophia Klaußner, Ulfia Clemen and Stefan Lang
International policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifyin...
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Kenneth Ekpetere, Mohamed Abdelkader, Sunday Ishaya, Edith Makwe and Peter Ekpetere
The long-term variability of lacustrine dynamics is influenced by hydro-climatological factors that affect the depth and spatial extent of water bodies. The primary objective of this study is to delineate lake area extent, utilizing a machine learning ap...
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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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Yakob Umer, Victor Jetten, Janneke Ettema and Gert-Jan Steeneveld
This study configures the Weather Research and Forecasting (WRF) model with the updated urban fraction for optimal rainfall simulation over Kampala, Uganda. The urban parameter values associated with urban fractions are adjusted based on literature revie...
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Alvin Pratama, Hayim Muhammad Agiel, Ade Ayu Oktaviana
Pág. 32 - 40
The availability of rainfall data is an important requirement in various activities. The limitations of observational data make the satellit precipitation product (SPPs) as an alternative. However, the data must be verified before being used. Verificatio...
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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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Kingsley Nnaemeka Ogbu, Oldrich Rakovec, Pallav Kumar Shrestha, Luis Samaniego, Bernhard Tischbein and Hadush Meresa
Hydrologic modeling in Nigeria is plagued by non-existent or paucity of hydro-metrological/morphological records, which has detrimental impacts on sustainable water resource management and agricultural production. Nowadays, freely accessible remotely sen...
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Alamin Molla, Liping Di, Liying Guo, Chen Zhang and Fei Chen
Lagos, Nigeria, is considered a rapidly growing urban hub. This study focuses on an urban development characterization with remote sensing-based variables for Lagos as well as understanding spatio-temporal precipitation responses to the changing intensit...
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