Volume 14, Issue 27 (8-2023)
jwmr 2023, 14(27): 135-145 |
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Kiyani Majd M, Nohtani M, Dehmardeh Ghaleh No M R, Shikh Z. (2023). Simulating the Runoff of Watersheds in Dry Areas on A Monthly Scale using the SWAT Model (Case Study: Lar Watershed). jwmr. 14(27), 135-145. doi:10.61186/jwmr.14.27.135
URL: http://jwmr.sanru.ac.ir/article-1-1214-en.html
URL: http://jwmr.sanru.ac.ir/article-1-1214-en.html
University of Zabol
Abstract: (1060 Views)
Extended Abstract
Introduction and Objective: mankind has witnessed various hydrological events such as water shortage, drought, flood, avalanche, etc., and the scope of these events depends on the behavior of hydrological variables and characteristics of watersheds. The lack of statistics and information or the lack of correct and appropriate statistics has caused the investigation and recognition of the behavior of hydrological variables and the characteristics of watersheds with acceptable accuracy. Based on this, hydrological models are a suitable tool for evaluating the current state of water resources and predicting future conditions with knowledge and understanding of the prevailing interactions at the level of watersheds.
Material and Methods: In this research, using the SWAT model, the precipitation-runoff simulation of the Lar watershed was carried out, and for this purpose, the daily data of precipitation, temperature and discharge during the common statistical period (1988-2017) were used. The initial simulation of the hydrological model was done in the SWAT plugin, and the SWAT-CUP software and the SUFI-2 method were used as an optimal algorithm for sensitivity analysis, calibration and validation of the model.
Results: Based on the SWAT model, the study area was divided into 37 sub-basins and 308 hydrological response units. In addition, by analyzing the sensitivity of 24 parameters affecting the simulation of the monthly runoff of the Lar watershed, it was determined that 7 parameters based on the values of the t-state and p-value indicators were selected as the parameters with the greatest effect, and out of these 7 parameters, Three parameters curve number for medium humidity conditions, base flow return factor to the main waterway and average usable water were identified as the most sensitive parameters in runoff simulation. Then 18 years of the statistical period (1988-2005) were selected for recalibration and 12 years (2006-2017) for validation. Also, the effectiveness and efficiency of the model was evaluated using NS, R2, p-factor and r-factor coefficients. Model efficiency was evaluated using NS, R2, p-factor and r-factor coefficients. The values of these coefficients were estimated as 0.80, 0.82, 0.80 and 0.33 during the calibration period and 0.90, 0.90, 0.39 and 0.43 during the validation period. In addition, the temporal compatibility of the high and low points of the simulated and measured discharge hydrographs also confirmed the high accuracy of the model in the simulation.
Conclusion: The obtained results show that despite the seasonal flow and no base flow, as well as the frequency of days with zero flow, the SWAT model has a high ability to simulate the monthly discharge of watersheds in dry areas.
Introduction and Objective: mankind has witnessed various hydrological events such as water shortage, drought, flood, avalanche, etc., and the scope of these events depends on the behavior of hydrological variables and characteristics of watersheds. The lack of statistics and information or the lack of correct and appropriate statistics has caused the investigation and recognition of the behavior of hydrological variables and the characteristics of watersheds with acceptable accuracy. Based on this, hydrological models are a suitable tool for evaluating the current state of water resources and predicting future conditions with knowledge and understanding of the prevailing interactions at the level of watersheds.
Material and Methods: In this research, using the SWAT model, the precipitation-runoff simulation of the Lar watershed was carried out, and for this purpose, the daily data of precipitation, temperature and discharge during the common statistical period (1988-2017) were used. The initial simulation of the hydrological model was done in the SWAT plugin, and the SWAT-CUP software and the SUFI-2 method were used as an optimal algorithm for sensitivity analysis, calibration and validation of the model.
Results: Based on the SWAT model, the study area was divided into 37 sub-basins and 308 hydrological response units. In addition, by analyzing the sensitivity of 24 parameters affecting the simulation of the monthly runoff of the Lar watershed, it was determined that 7 parameters based on the values of the t-state and p-value indicators were selected as the parameters with the greatest effect, and out of these 7 parameters, Three parameters curve number for medium humidity conditions, base flow return factor to the main waterway and average usable water were identified as the most sensitive parameters in runoff simulation. Then 18 years of the statistical period (1988-2005) were selected for recalibration and 12 years (2006-2017) for validation. Also, the effectiveness and efficiency of the model was evaluated using NS, R2, p-factor and r-factor coefficients. Model efficiency was evaluated using NS, R2, p-factor and r-factor coefficients. The values of these coefficients were estimated as 0.80, 0.82, 0.80 and 0.33 during the calibration period and 0.90, 0.90, 0.39 and 0.43 during the validation period. In addition, the temporal compatibility of the high and low points of the simulated and measured discharge hydrographs also confirmed the high accuracy of the model in the simulation.
Conclusion: The obtained results show that despite the seasonal flow and no base flow, as well as the frequency of days with zero flow, the SWAT model has a high ability to simulate the monthly discharge of watersheds in dry areas.
Type of Study: Research |
Subject:
هيدرولوژی
Received: 2022/11/2 | Revised: 2023/08/7 | Accepted: 2023/01/11 | Published: 2023/08/7
Received: 2022/11/2 | Revised: 2023/08/7 | Accepted: 2023/01/11 | Published: 2023/08/7
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