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Inclusion of modified snow melting and flood processes in the SWAT model

(2018) WATER. 10(12).
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Abstract
Flooding, one of the most serious natural disasters, poses a significant threat to people's lives and property. At present, the forecasting method uses simple snowmelt accumulation and has certain regional restrictions that limit the accuracy and timeliness of flood simulation and prediction. In this paper, the influence of accumulated temperature (AT) and maximum temperature (MT) on snow melting was considered in order to (1) reclassify the precipitation categories of the watershed using a separation algorithm of rain and snow that incorporates AT and MT, and (2) develop a new snow-melting process utilizing the algorithm in the Soil and Water Assessment Tool Model (SWAT) by considering the effects of AT and MT. The SWAT model was used to simulate snowmelt and flooding in the Tizinafu River Basin (TRB). We found that the modified SWAT model increased the value of the average flood peak flow by 43%, the snowmelt amounts increased by 45%, and the contribution of snowmelt to runoff increased from 44.7% to 54.07%. In comparison, we concluded the snowmelt contribution to runoff, flood peak performance, flood process simulation, model accuracy, and time accuracy. The new method provides a more accurate simulation technique for snowmelt floods and flood simulation.
Keywords
snowmelt process, degree-day, accumulated temperature (AT), flood process, SWAT, TEMPERATURE-INDEX, CLIMATE-CHANGE, AIR-TEMPERATURE, GLACIER MELT, RIVER-BASIN, RUNOFF, VARIABILITY, IMPACTS, ROUTINE, REGION

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Chicago
Duan, Yongchao, Tie Liu, Fanhao Meng, Min Luo, Amaury Frankl, Philippe De Maeyer, Anming Bao, Alishir Kurban, and Xianwei Feng. 2018. “Inclusion of Modified Snow Melting and Flood Processes in the SWAT Model.” Water 10 (12).
APA
Duan, Y., Liu, T., Meng, F., Luo, M., Frankl, A., De Maeyer, P., Bao, A., et al. (2018). Inclusion of modified snow melting and flood processes in the SWAT model. WATER, 10(12).
Vancouver
1.
Duan Y, Liu T, Meng F, Luo M, Frankl A, De Maeyer P, et al. Inclusion of modified snow melting and flood processes in the SWAT model. WATER. 2018;10(12).
MLA
Duan, Yongchao et al. “Inclusion of Modified Snow Melting and Flood Processes in the SWAT Model.” WATER 10.12 (2018): n. pag. Print.
@article{8582255,
  abstract     = {Flooding, one of the most serious natural disasters, poses a significant threat to people's lives and property. At present, the forecasting method uses simple snowmelt accumulation and has certain regional restrictions that limit the accuracy and timeliness of flood simulation and prediction. In this paper, the influence of accumulated temperature (AT) and maximum temperature (MT) on snow melting was considered in order to (1) reclassify the precipitation categories of the watershed using a separation algorithm of rain and snow that incorporates AT and MT, and (2) develop a new snow-melting process utilizing the algorithm in the Soil and Water Assessment Tool Model (SWAT) by considering the effects of AT and MT. The SWAT model was used to simulate snowmelt and flooding in the Tizinafu River Basin (TRB). We found that the modified SWAT model increased the value of the average flood peak flow by 43\%, the snowmelt amounts increased by 45\%, and the contribution of snowmelt to runoff increased from 44.7\% to 54.07\%. In comparison, we concluded the snowmelt contribution to runoff, flood peak performance, flood process simulation, model accuracy, and time accuracy. The new method provides a more accurate simulation technique for snowmelt floods and flood simulation.},
  articleno    = {1715},
  author       = {Duan, Yongchao and Liu, Tie and Meng, Fanhao and Luo, Min and Frankl, Amaury and De Maeyer, Philippe and Bao, Anming and Kurban, Alishir and Feng, Xianwei},
  issn         = {2073-4441},
  journal      = {WATER},
  language     = {eng},
  number       = {12},
  pages        = {24},
  title        = {Inclusion of modified snow melting and flood processes in the SWAT model},
  url          = {http://dx.doi.org/10.3390/w10121715},
  volume       = {10},
  year         = {2018},
}

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