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- Bui, Dieu Tien, et al.
(författare)
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Effects of Inter-Basin Water Transfer on Water Flow Condition of Destination Basin
- 2020
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Ingår i: Sustainability. - Switzerland : MDPI. - 2071-1050. ; 12:338
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the intensification of drought and unsustainable management and use of water resources have caused a significant decline in the water level of the Urmia Lake in the northwest of Iran. This condition has affected the lake, approaching an irreversible point such that many projects have been implemented and are being implemented to save the natural condition of the Urmia Lake, among which the inter-basin water transfer (IBWT) project from the Zab River to the lake could be considered an important project. The main aim of this research is the evaluation of the IBWT project effects on the Gadar destination basin. Simulations of the geometrical properties of the river, including the bed and flow, have been performed, and the land cover and flood map were overlapped in order to specify the areas prone to flood after implementing the IBWT project. The results showed that with the implementation of this project, the discharge of the Gadar River was approximately tripled and the water level of the river rose 1 m above the average. In April, May, and June, about 952.92, 1458.36, and 731.43 ha of land adjacent to the river (floodplain) will be inundated by flood, respectively. Results also indicated that UNESCO’s criteria No. 3 (“a comprehensive environmental impact assessment must indicate that the project will not substantially degrade the environmental quality within the area of origin or the area of delivery”) and No. 5 (“the net benefits from the transfer must be shared equitably between the area of origin and the area of water delivery”) have been violated by implementing this project in the study area. The findings could help the local government and other decision-makers to better understand the effects of the IBWT projects on the physical and hydrodynamic processes of the Gadar River as a destination basin.
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| 2. |
- Nhu, Viet-Ha, et al.
(författare)
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Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran
- 2020
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Ingår i: Applied Sciences. - Switzerland : MDPI. - 2076-3417. ; 10:15
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims to apply and compare the performance of the three machine learningalgorithms–support vector machine (SVM), bayesian logistic regression (BLR), and alternatingdecision tree (ADTree)–to map landslide susceptibility along the mountainous road of the SalavatAbad saddle, Kurdistan province, Iran. We identified 66 shallow landslide locations, based on fieldsurveys, by recording the locations of the landslides by a global position System (GPS), Google Earthimagery and black-and-white aerial photographs (scale 1: 20,000) and 19 landslide conditioningfactors, then tested these factors using the information gain ratio (IGR) technique. We checked thevalidity of the models using statistical metrics, including sensitivity, specificity, accuracy, kappa,root mean square error (RMSE), and area under the receiver operating characteristic curve (AUC).We found that, although all three machine learning algorithms yielded excellent performance, theSVM algorithm (AUC=0.984) slightly outperformed the BLR (AUC=0.980), and ADTree (AUC=0.977) algorithms. We observed that not only all three algorithms are useful and effective tools foridentifying shallow landslide-prone areas but also the BLR algorithm can be used such as the SVMalgorithm as a soft computing benchmark algorithm to check the performance of the models in future.
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