Zobrazeno 1 - 10
of 711
pro vyhledávání: '"Flood modeling"'
Autor:
Ebenezer K. Siabi, Akwasi Adu-Poku, Nathaniel Oppong Otchere, Edward A. Awafo, Amos T. Kabo-bah, Nana S. A. Derkyi, Komlavi Akpoti, Geophrey K. Anornu, Eunice Akyereko Adjei, Francis Kemausuor, Mashael Yazdanie
Publikováno v:
Discover Water, Vol 4, Iss 1, Pp 1-30 (2024)
Abstract This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and
Externí odkaz:
https://doaj.org/article/27e7d8d0c3444d61a3a44f17975182b1
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103029- (2024)
Extreme floods can cause significant damage to infrastructure, property, and human life and have long-lasting social, economic, and environmental impacts. Flood risk assessment is critical in areas where the frequency of flood events is altering due
Externí odkaz:
https://doaj.org/article/af38ee658a4643d7826a7991409bac2c
Publikováno v:
Environmental Challenges, Vol 17, Iss , Pp 101029- (2024)
Flash floods are highly destructive, and their frequency and intensity are expected to escalate due to climatic changes. This study thus investigated flash flood susceptibility (FFS) by applying machine learning algorithms and climate projection to p
Externí odkaz:
https://doaj.org/article/9a550c5c76bc45beb0f289a1962f38ae
Autor:
Sarmad Dashti Latif, Mohammad Abdullah Almubaidin, Chua Guang Shen, Michelle Sapitang, Ahmed H. Birima, Ali Najah Ahmed, Mohsen Sherif, Ahmed El-Shafie
Publikováno v:
Ain Shams Engineering Journal, Vol 15, Iss 9, Pp 102916- (2024)
The objective of the current study is to investigate the effectiveness of specifically the Support Vector Machine (SVM) and the k-Nearest Neighbors (kNN) models for sea level prediction. The SVM and kNN models are compared using the predicted data de
Externí odkaz:
https://doaj.org/article/5a8686320a214774b2e9aa0d798379b8
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 54, Iss , Pp 101864- (2024)
Study area: Six catchments of different hydrological characteristics in the Harz Mountains, Germany. Study focus: A new scenario free method for determining changes of flood peaks considering climate change is developed. Compared to existing methods,
Externí odkaz:
https://doaj.org/article/b82514d2b59845dcb2c44171656fceee
Spatiotemporal Variability of Channel Roughness and its Substantial Impacts on Flood Modeling Errors
Autor:
Md Abdullah Al Mehedi, Shah Saki, Krutikkumar Patel, Chaopeng Shen, Sagy Cohen, Virginia Smith, Adnan Rajib, Emmanouil Anagnostou, Tadd Bindas, Kathryn Lawson
Publikováno v:
Earth's Future, Vol 12, Iss 7, Pp n/a-n/a (2024)
Abstract Manning's roughness coefficient, n, is used to describe channel roughness, and is a widely sought‐after key parameter for estimating and predicting flood propagation. Due to its control of flow velocity and shear stress, n is critical for
Externí odkaz:
https://doaj.org/article/3ff04120942443dcb07a036b61646fa1
Publikováno v:
Aerul şi Apa: Componente ale Mediului, Vol 2024, Iss 1, Pp 51-64 (2024)
Floods have been a significant concern for Romania, with notable events post-2000. These floods have been influenced by several factors, such as climate change, massive deforestation, inadequate urban planning and inadequate hydraulic infrastructure.
Externí odkaz:
https://doaj.org/article/2837bdedde2444d995a32b4e9f056303
Publikováno v:
Journal of Hydroinformatics, Vol 26, Iss 2, Pp 459-479 (2024)
Developing countries face significant challenges in accessing sufficient and reliable hydro-meteorological data, hindering the implementation of effective disaster management strategies. This research proposes solutions for limitations on performing
Externí odkaz:
https://doaj.org/article/d03d90c8eaf341e0bd94061a7960ac89
Autor:
Tao Huang, Venkatesh Merwade
Publikováno v:
Journal of Flood Risk Management, Vol 17, Iss 2, Pp n/a-n/a (2024)
Abstract Evaluation of the performance of flood models is a crucial step in the modeling process. Considering the limitations of single statistical metrics, such as uncertainty bounds, Nash Sutcliffe efficiency, Kling Gupta efficiency, and the coeffi
Externí odkaz:
https://doaj.org/article/e16f6166b28d4ef08529609c751f85b3
Publikováno v:
Hydrology Research, Vol 54, Iss 11, Pp 1387-1406 (2023)
In urban flood modeling, the accuracy of surface and subsurface flow calculations greatly depends on the parameterization of the drainage system. Incorporating the influence of the sewer pipe system is, therefore, integral to accurately simulating ur
Externí odkaz:
https://doaj.org/article/abd9544d2bd74bd6ab6f2c2071732665