It is difficult to predict and track the propagation of a hydrological drought because it is hard to determine its propagation speed. We propose a useful framework for calculating the hydrological drought instantaneous propagation speed which includes the instantaneous development speed (IDS) and instantaneous recovery speed (IRS). First, the run theory was applied to subdivide the propagation of individual hydrological drought events into the development and recovery stages and to determine the individual propagation times (drought development duration and drought recovery duration). Then the hydrological drought instantaneous propagation speed of each hydrological drought event, including the IDS and IRS, were determined based on the variable motion relationship of speed‐time process commonly applied in physics. Finally, the optimal theoretical values of the IDS and IRS were evaluated using a cross‐validation method. Three hydrometric stations, located at the upstream catchment with less human activities influence, were chosen from different countries (China, the United States, and Germany) to demonstrate the satisfactory performance of this proposed framework. The results indicate that the variable motion relationship of speed‐time process can provide an assessment of the overall hydrological drought propagation and perform well for identifying the propagation time in these study areas. The optimal theoretical values of IDS (or IRS) obtained by the variable motion relationship can simulate the actual drought development duration (or drought recovery duration) of hydrological drought well. The sensitivity of IDS (or IRS) of hydrological drought is correlated with climate, catchment characteristics, and human activities that should be explored to improve hydrological drought propagation prediction.

Simulation of low flow process is critical to water quality, water supply, and aquatic habitat. However, the poor performance of Soil and Water Assessment Tool (SWAT) in dry seasons has impeded its application to watersheds characterized largely by low-flows. Aiming at overcoming this shortage, a seasonal calibration scheme was proposed, in which SWAT was calibrated separately for the dry and wet periods and the “optimal” simulation results of these two periods were combined into a complete runoff series. An extended SWAT model incorporating with the proposed seasonal calibration scheme, named SWAT-SC was constructed and compared with the original SWAT to simulate daily runoff in the Jinjiang watershed dominated by a typical subtropical monsoon climate in southeastern China. The study reveals that when Nash-Sutcliffe efficiency (ENS) of the original SWAT model indicated a satisfied model performance in a wet season or a whole year, it may not guaranty acceptable performance for the dry period. A significant improvement was achieved by using SWAT-SC for simulating runoffs in the dry period, and although not as notably as the dry period, improvements for runoff simulation of the wet and overall periods were observed as well

Determining the amount of rainfall that will eventually become runoff and its pathway is a crucial process in hydrological modelling. We proposed a method to better estimate curve number by adding an additional component (AC) to better account for the effects of daily rainfall intensity on rainfall-runoff generation. This AC is determined by a regression equation developed from the relationship between the AC series derived from fine-tuned calibration processes and observed rainfall series. When incorporated into the Soil and Water Assessment Tool and tested in the Anxi Watershed, it is found, overall, the modified SWAT (SWAT-ICN) outperformed the original SWAT (SWAT-CN) in terms of stream flow, base flow, and annual extreme flow simulation. These models were further evaluated with the data sets of two adjacent watersheds. Similar results were achieved, indicating the ability of the proposed method to better estimate curve number.