Results 11 to 20 of about 12,906 (298)
Development of an Inductive Rain Gauge [PDF]
Sensors, 2022 Measuring weather data in an urban environment is an important task on the journey towards smart cities. Heavy rain can cause flooding in cities and prevent emergency services from reaching their destination because roads or underpasses are blocked.
Christoph Clemens +5 more
doaj +4 more sources
Quantification of node importance in rain gauge network: influence of temporal resolution and rain gauge density. [PDF]
Sci Rep, 2020 AbstractRain gauge network is important for collecting rainfall information effectively and efficiently. Rain gauge networks have been studied for several decades from a range of hydrological perspectives, where rain gauges with unique or non-repeating information are considered as important.
Tiwari S, Jha SK, Singh A.
europepmc +7 more sources
Considering Rain Gauge Uncertainty Using Kriging for Uncertain Data [PDF]
Atmosphere, 2018 In urban hydrological models, rainfall is the main input and one of the main sources of uncertainty. To reach sufficient spatial coverage and resolution, the integration of several rainfall data sources, including rain gauges and weather radars, is often
Francesca Cecinati +2 more
exaly +4 more sources
A Methodology for Rain Gauge Network Evaluation Considering the Altitude of Rain Gauge [PDF]
Journal of Wetlands Research, 2014 The observed rainfall may be different along with the altitude of rain gauge, resulting in the fact that the characteristics of rainfall events occurred in urban or mountainous areas are different. Due to the mountainous effects, in higher altitude, the uncertainty involved in the rainfall observation gets higher so that the density of rain gauges ...
Ji Ho Lee
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Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China
Remote Sensing, 2020 Radar-rain gauge merging methods have been widely used to produce high-quality precipitation with fine spatial resolution by combing the advantages of the rain gauge observation and the radar quantitative precipitation estimation (QPE). Different merging
Jia Liu, Jiyang Tian, Chuanzhe Li
exaly +3 more sources
Optimization of rain gauge sampling density for river discharge prediction using Bayesian calibration [PDF]
PeerJ, 2020 River discharges are often predicted based on a calibrated rainfall-runoff model. The major sources of uncertainty, namely input, parameter and model structural uncertainty must all be taken into account to obtain realistic estimates of the accuracy of ...
Alexandre M.J.-C. Wadoux +3 more
doaj +3 more sources
Remote Sensing, 2020 A well-designed rain gauge network can provide precise and detailed rainfall data for earth science research; meanwhile, satellite precipitation data has been developed to generate more real spatial features, which provides new data support for the ...
Yanyan Huang
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Data Mining of Remotely-Sensed Rainfall for a Large-Scale Rain Gauge Network Design
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Rain gauges are able to measure point rainfall with high accuracy compared with remote sensing observations. However, a single rain gauge cannot provide continuous spatial coverage, and thus, rain gauge networks need to be designed in a way that will ...
Zhenzhen Liu, Huimin Wang, Jing Huang
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Global Intensity-Duration-Frequency curves based on observed sub-daily rainfall (GSDR-IDF) [PDF]
Scientific DataShort-duration extreme rainfall events can cause flash flooding and infrastructure failures, yet resources to assess these remain limited, particularly at the global scale. Heterogeneous data availability, inconsistent quality control, and methodological
Amy C. Green +2 more
doaj +2 more sources
Citizen rain gauges improve hourly radar rainfall bias correction using a two-step Kalman filter [PDF]
Hydrology and Earth System Sciences, 2022 The low density of conventional rain gauge networks is often a limiting factor for radar rainfall bias correction. Citizen rain gauges offer a promising opportunity to collect rainfall data at a higher spatial density.
P. P. Mapiam +4 more
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