Spatial–temporal evolution of the distribution pattern of river systems in the plain river network region of the Taihu Basin, China

Abstract

Understanding the spatial–temporal distribution characteristic and evolution tendency of river systems is important in integrated river basin management. In this paper, six indicators were adopted to describe the physical characteristic of river systems. The spatial–temporal evolution of the distribution pattern of river systems in the plain river network region of the Taihu Basin (PRNRTB) during the 1960s–2000s was analyzed using exploratory spatial data analysis (ESDA) and the gravity centre model. The impacts of urbanization were then investigated. Results indicated that the global distribution patterns of box dimension and river density were all statistically significant spatially clustered, and river sinuosity was partially spatially clustered, while water surface ratio, main river area length ratio and river development coefficient were not spatially clustered. Moreover, the water surface ratio was the most stable parameter, box dimension was also relatively stable parameter, but the others were unstable. Meanwhile, the mutual transformations of hot and cold spots of river systems especially water surface ratio, river development coefficient, and river sinuosity were frequent. The hot spot regions were mainly located in the northeast region. In addition, most gravity centres migrated gradually from southeast to northwest with low distance, except those of river development coefficient and river density. These aforementioned differences were caused by the rapid urbanization. Based on the integrated river basin management suggestions for PRNRTB, the river density, box dimension and river sinuosity should be maintained and restored across the whole watershed, and the river conservation and restoration should focus on countermeasures against the reduction of river development coefficient, and main attention should be paid on the river systems conserving and restoring in Haiyan and Haining in southeast PRNRTB.