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Determining the Maximum Flood Discharge Using the Response Surface Methodology in Darrehrood Sub-Basins, Ardebil Province | ||
| پژوهش های آبخیزداری | ||
| Article 8, Volume 35, Issue 1 - Serial Number 134, March 2022, Pages 88-104 PDF (4.14 M) | ||
| Document Type: Research | ||
| DOI: 10.22092/wmrj.2021.354467.1409 | ||
| Author | ||
| Yaser Hoseini* | ||
| Moghan College of Agriculture and Natural resources, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| Abstract | ||
| It is impossible to manage water resources in basins without the accurate determination of the peak flood discharge. Therefore, this study was carried out to determine the peak flood discharge for the return period of 10, 25, 50, and 100 years using RSM model in Darrehrood sub-basins with 12900 km2 area in Ardebil Province. Flow data of 16 hydrometric stations were collected in a statistical period of 15 years (2001-2005) and statistical deficiencies in the joint period were eliminated by using regression methods between hydrometric stations. Floods were calculated with different return periods. Also, physiographic characteristics of sub-basins that affect flood rate including area, slope, shape factor, height average, concentration time, and curve number were achieved using ArcGIS10.2 and WMS7.1 (watershed modeling system). The Goodness of Fit (R2) in the return periods of 10, 25, 50, and 100 years was estimated to be 96, 97, 95, and 94%, respectively. This indicates the model's high accuracy to predict the peak discharge in the sub-basins using the basin physiographic parameters. Model performance indexes of the model evaluation for return period of 10, 25, 50 and 100 years were calculated respectively including root mean square error (RMSE) of 20.99, 7.16, 29.05, 39.55, relative percentage error (ε) of 52.7, 37.7, 45.1, 49.13, mean absolute error (MAE) of 0.52, 0.45, 0.48, 0.55, coefficient of residual mass (CRM) of 0.28, 0.16, 0.56, 0.82, and model efficiency (EF) of 0.74, 0.85, 0.71, 0.75. Cross-validation diagrams showed that RSM model was very suitable for the whole return periods. Paired t-test showed that the difference between predicted and actual values in different return periods was not significant (P< 0.01). The results of this study showed that the RSM has good accuracy for estimating floods in sub-basins of Ardebil Province. | ||
| Keywords | ||
| Ardabil province; return period; RSM; sub basin; statistical distribution | ||
| References | ||
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