Attribution of climate change and human activities to urban water level alterations and factors importance analysis in Central Taihu Basin

Abstract

Attribution of climate change and human activities have been extensively discussed over the past few decades, particularly in urbanization area. However, the relationships among different factors may not be well explained by traditional statistical methods. In this study, we took one of the highly urbanized regions, Central Taihu Basin, as an example. Linear regression (LR), random forest (RF) and support vector machine (SVM) were used for regression and the attributions of climate change and human activities on water level alterations at different scales from 1961 to 2018 were quantified by residual analysis. The regression results indicated that SVM performed best. Water level at each scale showed an increasing trend and human activities were the dominant influence. The altered period was further divided into three sub-periods and human activities contributed the most in the sub-period II (2000–2009). Finally, the importance of thirty-eight factors were quantified by RF based on daily data series from 2008 to 2018. The results showed that cumulative antecedent precipitation (CAP) of five days was one of the important climate factors and daily maximum discharge of sluices were the important human activities factors. The methods and results of this study can help to provide support in flood control.