Locating areas with infiltration potential by using the mixture discriminant analysis model

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Agriculture is not only the largest user of groundwater resources throughout the world but also its economy is highly dependent on these sources. Thanks to having more effective parameters and subsequently more accurate results, the classification methods in many fields, such as sustainable agriculture has been taken into consideration. Discriminant analysis models are more complex, more accurate and more efficient in comparison to modern methods. In current study, the areas with infiltration potential located in some parts of Khomein, Shazand, Azna, Aligudarz and Durood areas (Marboreh watershed) were went under investigation using the mixture discriminant analysis (MDA) model. For this purpose, the infiltration samples gathered by double ring test, with the environment-effecting layers on infiltration, were prepared and then introduced to R_studio, employed to run MDA. In order to assess the results, validation indices (ROC curve, CCI, TSS, Recall and Precision indices) were used. According to the results, 6.2, 6.1, 12.7, 13.3 and 15.9% of areas of Shazand, Khomein, Durood, Azna and Aligodarz respectively lie in highly potential infiltration, whereas 1.1 16.5, 14.3, 19.6 and 10.8% of those areas were found to have extremely potential infiltration. Most of these areas have sandy soil texture and Quaternary formations with agricultural and range land uses. The accuracy indices that obtained as 0.89%, 76.66, 0.53, 0.91% and 0.73%, witnessing the acceptance and excellence of model performance. The results of this study can be useful in the decision-making for managers and planners regarding to the groundwater recharge in accordance with urban and agricultural needs, because groundwater resources and ensuring their stability are the main factors for sustainable agriculture.
Language:
Persian
Published:
Journal of Range and Watershed Management, Volume:76 Issue: 3, 2023
Pages:
287 to 304
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