Causal effects of dams and land cover changes on flood changes in mainland China

Abstract. Quantifying the effects of human activities on floods is challenging because the knowledge and observations toward the effects are limited. Many previous methods fail to isolate different effects and reduce the uncertainty caused by small samples. We use panel regressions to derive the sensitivity of annual maximum discharges (Q) to the changing values of three human factors: urban areas, cropland areas, and reservoir indexes for large and middle dams. We also test whether the effects increase or decrease with increasing initial values of human factors. This method is applied in 2739 hydrological stations in China. Results show that a 1 % increase of urban areas causes around a 2.9 % increase of Q. Cropland areas have no significant effect on Q. Reservoir index has a decreasing effect: a 1 unit increase of reservoir index causes a decrease in Q from 23.1 % to 5.4 % for catchments with initial reservoir indexes from 0 to 5. From 1992 to 2017, increasing urban areas cause more than 10 % increases in Q in 10.4 % of the 2739 catchments, most of which are located in the North Plain of China. From 1960 to 2017, increasing reservoir indexes cause a more than 10 % decrease of Q in 53.4 % of 777 catchments with at least one dam. Among 1074 catchments with limited impacts from urban areas and reservoir indexes, 210 (19.6 %) catchments have more than 10 % unexplained decreasing rates in Q per decade during 1960–2017, and 62.4 % of the 210 catchments are located in the middle and down streams of the Yellow River Basin and the upper streams of the Haihe River Basin. This study extends the panel regression method in hydrology and sheds light on the attribution of flood changes on a national scale.