WANG Y X, LIU X, SHEN Y J. Applicability of the random forest model in quantifying the attribution of runoff changes[J]. Chinese Journal of Eco-Agriculture, 2022, 30(5): 864−874. DOI: 10.12357/cjea.20210652
Citation: WANG Y X, LIU X, SHEN Y J. Applicability of the random forest model in quantifying the attribution of runoff changes[J]. Chinese Journal of Eco-Agriculture, 2022, 30(5): 864−874. DOI: 10.12357/cjea.20210652

Applicability of the random forest model in quantifying the attribution of runoff changes

  • Climate change and human activity have a significant impact on runoff in basins. As an important ecological barrier,the upper Yongding River Basin of has undergone significant changes in the ecological environment over the past 50 years, and the problem of water shortage has become increasingly prominent. It is necessary to restore the water ecology and analyze the influence of climate and human activities on runoff dynamics. Therefore, this study established a comparative approach between the random forest and Soil and Water Assessment Tool (SWAT) models in the Yanghe River Basin, which is greatly affected by human activities in the upper Yongding River Basin. The main conclusions were as follows: 1) in terms of the runoff simulation effect, the SWAT model was reliable for revealing the runoff dynamics in the Dongyanghe River Basin, Nanyanghe River Basin, and Yanghe River Basin. The R2 values of the simulated and observed runoff in the three basins were above 0.65 in both the calibration and verification periods, and the Nash coefficients (NSE) were also above 0.65 in the three basins. However, the random forest model outperformed the SWAT model in terms of NSE and R2 in the three basins, and its NSE and R2 values were mostly above 0.80. 2) In quantifying the attribution of runoff changes, the results based on the SWAT model showed that the contribution rates of climate change to runoff decline in the three basins were generally between 5.0% and 15.7%, and those of human activities were 84.3%–95.0% in the three basins. The results based on the random forest model were similar to the attribution results of runoff decline based on the SWAT model; the contribution rates of climate change and human activities to runoff decline in the three basins were generally 2.4%–11.5% and 88.5%–97.6% in the three basins. This is consistent with the research results of other experts and scholars that human activities are the main cause of runoff decline in the Yanghe River Basin. Random forest can be applied in runoff simulation in the Yanghe River Basin, and the simulated model results can be used in water resource management. In this study, the SWAT model and random forest were combined to reveal the impacts of climate change and human activities on the changes in runoff in the Yanghe River Basin. Additionally, the applicability of the random forest model in the Yanghe River Basin was evaluated, which demonstrated the possibility of integrating the random forest model in hydrological modeling in further research. However, random forest is a black-box model in theory and lacks consideration of hydrological processes. Although this study preliminarily explored the method and it has been proven to be applicable in runoff simulation, the uncertainty of this method in runoff simulation or runoff evolution needs to be further explored.
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