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Shu Wu, Momcilo Markus, David Lorenz, James R. Angel and Kevin Grady
Many studies have projected that as the climate changes, the magnitudes of extreme precipitation events in the Northeastern United States are likely to continue increasing, regardless of the emission scenario. To examine this issue, we analyzed observed ...
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David Dunkerley
The inter-tip times (ITTs) of tipping-bucket rain gauges (TBRGs) potentially provide the highest-resolution intensity data that can be acquired from this type of gauge. At an intensity of 100 mm h-1, a typical gauge with a sensitivity of 0.2 mm of rainfa...
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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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Radoslaw Drozdziol and Damian Absalon
The paper compares precipitation measurements from the Stratus manual rain gauge from the CoCoRaHS network and two Davis Vantage Vue and Davis Vantage Pro 2A rain gauges with the Hellmann rain gauge. Comparative measurements were made on a specially prep...
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Chi Xu, Chuanqi Liu, Wanchang Zhang, Zhenghao Li and Bangsheng An
Complex terrain, the sparse distribution of rain gauges, and the poor resolution and quality of satellite data in remote areas severely restrict the development of watershed hydrological modeling, meteorology, and ecological research. In this study, base...
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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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Seng Choon Toh, Sai Hin Lai, Majid Mirzaei, Eugene Zhen Xiang Soo and Fang Yenn Teo
This study introduces a systematic methodology whereby different technologies were utilized to download, pre-process, and interactively compare the rainfall datasets from the Integrated Multi-Satellite Retrievals for Global Precipitation Mission (IMERG) ...
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Monzur Alam Imteaz, Abdullah Gokhan Yilmaz, Cristina Santos and Amimul Ahsan
Most of the studies on rainwater harvesting analysis present the outcomes for particular cities, representing a single set of results for a specific city. However, in reality, significant spatial and weather variabilities may exist, due to which presenti...
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Syed Imran Ahmed, Ramesh Rudra, Pradeep Goel, Alamgir Khan, Bahram Gharabaghi and Rohit Sharma
Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in So...
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