Sustainable Storm Water Management by Predicting Climate Change Using Fuzzy Neural Network and GIS
| Autor: | I. A. Kebria, W. Hogland |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Iranica Journal of Energy and Environment, Vol 10, Iss 1, Pp 65-71 (2019) |
| Druh dokumentu: | article |
| ISSN: | 2079-2115 2079-2123 |
| DOI: | 10.5829/ijee.2019.10.01.10 |
| Popis: | Analysis of urban climate changing is the basis for the implementation of storm water management measurements. Climate tensions such as changing precipitation patterns, fluctuations in temperature, and extreme events are already affecting water resources. For instance, precipitation pattern will be changed due to more water vapor in the atmosphere. Hence, it will not be evenly distributed. Some places will see more rain, others will get less snow. However, climate changes, such as the amount, timing, and intensity of rain events, in combination with land development, can significantly affect the amount of storm water runoff that needs to be managed. Firstly, this essay will be discussed about the prediction of climate change using a fuzzy neural network (FNN) and it shows the accuracy of this method for anticipating storm water. Secondly, based on the results of the first phase, it determines the critical area for preparing storm water systems with the application of GIS tools and technology. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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