Analysis of the spatial variations in river networks and the related influencing factors is crucial for the management and protection of basins. To gain insight into the spatial variations and influencing factors of river networks between large basins, in this study, three river basins from north to south in China (Songhua River Basin, Yellow River Basin and Pearl River Basin) were selected for investigation. First, based on a digital elevation model, different river networks with six drainage accumulation thresholds of three basins were extracted using ArcGIS. The optimal networks were determined through fitting the relationship between the accumulation threshold and related drainage density. Then, we used two indicators, drainage density and water surface ratio, to characterize the spatial variations of three basins. Finally, Pearson’s correlation coefficients were calculated between those two indicators and natural/human influencing factors. The results showed that drainage density and water surface ratio decreased from north to south in China and were negatively correlated with natural/human influencing factors. Drainage density was more influenced by natural factors than by human factors, while the opposite was true for water surface ratio. These findings may provide some basis for the management and protection of the river network.

Hydrologic (water temperature) and hydrodynamic (water depth, flow velocity, and Froude number) factors affect fish spawning activities, and spawning grounds provide suitable hydrologic and hydrodynamic conditions for fish spawning to occur. However, locating fish spawning grounds is encumbered by uncertainty, particularly for pelagic spawners. This may be because such fish species have unique hydrologic and hydrodynamic requirements during their spawning periods, resulting in the wide-ranging approaches used to locate their spawning grounds. Accordingly, this study was designed to accurately locate fish spawning grounds through means of spatial suitability evaluation. For this experiment, the four major “Asian carp” target species were selected in the Dongta spawning reach, a tributary of the Pearl River. First, we investigated the historical information on the location of the spawning reaches. An acoustic doppler current profiler (ADCP) was used to measure topographic and hydrodynamic data of the spawning reaches during the spawning period. Then, based on the spatial clustering method, cluster analysis on spatial attributes (water depth, flow velocity, water temperature, and Froude number) was conducted on potential spawning grounds. The cluster analysis method uses k-means clustering; a method often employed to classify large amounts of data. Finally, we analyzed and evaluated the spatial suitability of spawning reaches by combining fish spawning suitability curves to obtain spatial preferences associated with fish spawning activities. Proportionally, results revealed a high suitability (>0.4) area (60.86%). Moreover, spawning suitability in curved river sections and deep pools in straight river sections were significantly higher than bifurcated sections. Furthermore, areas near the riverbanks were more suitable than mid-course sections of the river. Finally, the locations of six potential Asian carp spawning grounds were determined according to their spatial suitability. This study provides technical support to accurately locate spawning grounds for the fish that produce drifting eggs.