Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Optimizing Physics Parameters for Heavy Rainfall Forecasting in the Kelani River Basin Using the WRF Model
It is imperative to increase the precision of flood forecasts for the long-term sustainability of developing economies, particularly for reducing losses and damages in metropolitan regions, which are typically the driving forces behind the economy. Moreover, with climate change, floods are becoming more frequent, underscoring the need for an accurate flood forecasting system to reduce property and life losses. A precise prediction of floods requires accurate estimations of extreme rainfall occurrences with a longer lead time. To produce fine-scale rainfall predictions, regional weather forecasting models with high resolution, such as the Weather Research and Forecasting (WRF) model, are frequently utilized to provide rainfall estimations at fine grid spacing. These events depend on multi-scale interactions and model parameters such as grid spacing, physical parameterization, and initialization. This study sought to discover the most effective set of physics parameters for forecasting heavy rainfall events in the Kelani River basin by evaluating the predictability of the WRF model with several model physics alternatives. The WRF model consisted of three domains with a resolution of 27, 9, and 3 km used in this work by taking into account two representative extreme rainfall events that occurred during the South West monsoon season in 2020 and 2021, over the Kelani River basin. Each event was simulated with ensembles involving four different microphysics and two cumulus parameterizations. The simulated rainfalls were evaluated against the observations from 15 rainfall gauging stations in the river basin. The results suggest that the WSM3 and WSM6 microphysics schemes with the Betts–Miller–Janjic cumulus scheme can be chosen as the optimum parameterization schemes to be used in this region.
Optimizing Physics Parameters for Heavy Rainfall Forecasting in the Kelani River Basin Using the WRF Model
It is imperative to increase the precision of flood forecasts for the long-term sustainability of developing economies, particularly for reducing losses and damages in metropolitan regions, which are typically the driving forces behind the economy. Moreover, with climate change, floods are becoming more frequent, underscoring the need for an accurate flood forecasting system to reduce property and life losses. A precise prediction of floods requires accurate estimations of extreme rainfall occurrences with a longer lead time. To produce fine-scale rainfall predictions, regional weather forecasting models with high resolution, such as the Weather Research and Forecasting (WRF) model, are frequently utilized to provide rainfall estimations at fine grid spacing. These events depend on multi-scale interactions and model parameters such as grid spacing, physical parameterization, and initialization. This study sought to discover the most effective set of physics parameters for forecasting heavy rainfall events in the Kelani River basin by evaluating the predictability of the WRF model with several model physics alternatives. The WRF model consisted of three domains with a resolution of 27, 9, and 3 km used in this work by taking into account two representative extreme rainfall events that occurred during the South West monsoon season in 2020 and 2021, over the Kelani River basin. Each event was simulated with ensembles involving four different microphysics and two cumulus parameterizations. The simulated rainfalls were evaluated against the observations from 15 rainfall gauging stations in the river basin. The results suggest that the WSM3 and WSM6 microphysics schemes with the Betts–Miller–Janjic cumulus scheme can be chosen as the optimum parameterization schemes to be used in this region.
Optimizing Physics Parameters for Heavy Rainfall Forecasting in the Kelani River Basin Using the WRF Model
Lecture Notes in Civil Engineering
Dissanayake, Ranjith (Herausgeber:in) / Mendis, Priyan (Herausgeber:in) / De Silva, Sudhira (Herausgeber:in) / Fernando, Shiromal (Herausgeber:in) / Konthesingha, Chaminda (Herausgeber:in) / Attanayake, Upul (Herausgeber:in) / Gajanayake, Pradeep (Herausgeber:in) / Perera, P. L. L. N. (Autor:in) / Neluwala, N. G. P. B. (Autor:in) / Wijetunge, J. J. (Autor:in)
International Conference on Sustainable Built Environment ; 2023 ; Kandy, Sri Lanka
Proceedings of the 14th International Conference on Sustainable Built Environment ; Kapitel: 24 ; 325-339
28.08.2024
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Impact of Lockdown on the Surface Water Quality in Kelani River, Sri Lanka
| DOAJ | 2023
Numerical Prediction of Heavy Rainfall Using Weather and Research Forecasting Model
| British Library Conference Proceedings | 2013