Spatiotemporal variations in the elasticity of runoff to climate change and catchment characteristics with multi-timescales across the contiguous United States

Abstract

There is a lack of understanding of the impact of timescales on runoff elasticity. In this study, gauged river flow and meteorological data time-series from 1916 to 2015 and 1941 to 2015 across the contiguous United States (CONUS) for 188 catchments were collected. We studied spatiotemporal variations of climate and catchment elasticity at multi-timescales (11, 20, 40, and 60 a) across the CONUS, and the relationships between the elasticity of runoff and climatic factors were also analyzed. Median descriptive statistics and Budyko-coupled climate elasticity methods were used to calculate runoff elasticity in each timescale. The original Mann–Kendall trend test was used to test the temporal trend significance in four timescales, respectively. The results show that (1) the trend and values of runoff elasticity may not be affected by timescales. (2) Catchment characteristics in some western regions may be the second-most sensitive factor for runoff following the maximum temperature. The roles of potential evaporation, maximum temperature, and catchment characteristics on runoff gradually become important from east to west. (3) Runoff elasticity is independent of precipitation, and wet regions tend to have lower elasticity of runoff. There are strong relationships between elasticity and most factors, except for precipitation, which can illustrate well its spatial pattern. HIGHLIGHTS Runoff elasticity including trend and value is stable at space and timescale.; Apart from precipitation, extreme temperature and catchment characteristics are also important factors for runoff alteration.; Runoff elasticity can be explained by the aridity index, runoff coefficient, runoff, and watershed properties.; The distinct spatial pattern occurs in the contiguous United States.;

Keywords

• catchment characteristics
• climate change
• runoff elasticity
• spatiotemporal variation
• trend analysis