Statistical Modeling to Predict the Hydrological Characteristics of the Sub- Basins of the Northern Jordan Rift Valley | ||||
| مجلة كلية الآداب - جامعة القاهرة | ||||
| Volume 2023, Issue 7, July 2023 | ||||
| DOI: 10.21608/jarts.2023.214891.1366 | ||||
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| Abstract | ||||
| Morphometric parameters are an applicable method to understand the hydrological system of water drainage basins. To determine the capabilities of sub-basins, morphometric analysis was adopted, using the linear, areal, drainage network, formality, and relief variables of the drainage basin. Moreover, remote sensing and GIS have been proven to be efficient tools for identifying morphological parameters. The morphological parameters were calculated from the digital elevation model (DEM) file with a 30 m resolution obtained from U.S. Geological Survey (USGS). Also, using algorithms formulas, represented by the SCS method for runoff estimation, equations for morphometric variables, and equations for hydrological variables estimation. A correlation matrix (Pearson's correlation coefficient) was set up between the hydrological and morphometric variables to determine that the morphometric variables had a statistically significant relationship with the hydrological variables. This would enable us to predict the hydrological variables of the sub-basins of the study area, based on linear regression analysis using SPSS. The results of the study indicate that the creation of statistical models has the ability to predict the hydrologic variables, which are runoff, lag time, concentration time, drainage time, the velocity of runoff, and flood factor. Based on morphometric variables, they were thirty-one. This is illustrated by the related equations and graphs and their applicability to drainage basins in other regions. The study might help to take water conservation measures and undertake repairs of drainage basin management structures for better decision-making in the future. | ||||
| Keywords | ||||
| Jordan Rift Valley. hydrological variable; morphometric variable. Regression coefficient; Pearson's correlation; Statistical models | ||||
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Statistics Article View: 15 |
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