This study focused on the infiltration process and the influence of subsurface structure on soil moisture dynamics during rainfall. The combination of time-lapse electrical resistivity tomography and self-potential was presented in the forest. Results demonstrated the potential of combined geophysical techniques to identify more detailed spatial-temporal hydrological processes and provided a basis for the hydrological connectivity and climate-sensitive response of soil water.

It is an important disaster reduction strategy to forecast hydrological drought. In order to analyse the impact of human activities on hydrological drought, we constructed the human activity factor based on the method of restoration. With the increase of human index (HI) value, hydrological droughts tend to transition to more severe droughts. The conditional distribution model involving of human activity factor can further improve the forecasting accuracy of drought in the Luanhe River basin.

In this study, a multivariate nonstationary risk analysis of annual extreme rainfall events, extracted from daily precipitation data observed at six meteorological stations in Haihe River basin, China, was done in three phases: (1) Several statistical tests, were applied to both the marginal distributions and the dependence structures to decipher different forms of nonstationarity; (2) Time-dependent copulas were adopted to model the distribution structure.