MT-DREAM(ZS) SWAT outputs

The multiple-try Differential Evolution Adaptive Metropolis (ZS) (MT-DREAM(ZS)) algorithm was used to quantify the uncertainty in the prediction of the Indicators of Hydrologic Alteration (IHA) and The Magnificent Seven indices from simulated streamflows. For modeling purposes, we used the Soil and Water Assessment Tool (SWAT) in an agriculture-dominated watershed in Michigan, US. We linked multi-objective calibration results using the U-NSGA-III algorithm with Bayesian parameter estimation via the prior distribution for model parameters. Here we provide the (posterior) sampled parameter values, the streamflow predictions, and the relative errors for the predicted hydrologic indices under different calibration settings. In addition, we provide the MATLAB codes for reproducing figures representing model parameter variability ranges, performance of streamflow predictions, and variability in predicted hydrologic indices.

本研究采用多尝试差分进化自适应马尔可夫链（ZS）(Multiple-try Differential Evolution Adaptive Metropolis (ZS)) 算法（MT-DREAM(ZS)），对基于模拟径流的水文改变指标（Indicators of Hydrologic Alteration, IHA）与七大指数（Magnificent Seven indices）的预测不确定性进行量化。建模过程中，我们在美国密歇根州一处以农业为主的流域内应用了土壤与水评估工具（Soil and Water Assessment Tool, SWAT）。我们将采用U-NSGA-III算法得到的多目标校准结果，与基于模型参数先验分布的贝叶斯参数估计进行关联。本数据集提供了不同校准设置下的后验采样参数值、径流预测值以及预测水文指数的相对误差。此外，本数据集还附带了用于复现反映模型参数变异范围、径流预测性能以及预测水文指数变异特征的相关图表的MATLAB代码。