It is widely recognized that multi-year drought can induce changes in catchment hydrological behaviors. However, at present, our understanding about multi-year, drought-induced changes in catchment hydrological behaviors and its driving factors at the process level is still very limited. This study proposed a new approach using a data assimilation technique with a process-based hydrological model to detect multi-year drought-induced changes in catchment hydrological behaviors and to identify driving factors for the changes in an unimpaired Australian catchment (Wee Jasper) which experienced prolonged drought from 1997 to 2009. Modelling experiments demonstrated that the multi-year drought caused a significant change in the catchment rainfall-runoff relationship, indicated by significant step changes in the estimated time-variant hydrological parameters SC (indicating catchment active water storage capacity) and C (reflecting catchment evapotranspiration dynamics), whose average values increased 23.4% and 10.2%, respectively, due to drought. The change in the rainfall-runoff relationship identified by the data assimilation method is consistent with that arrived at by a statistical examination. The proposed method provides insights about the drivers of the changes in the rainfall-runoff relationship at the processes level. Declining groundwater and deep soil moisture depleted by persistent evapotranspiration of deep-rooted woody vegetation during drought are the main driving factors for the catchment behaviors change in the Wee Jasper catchment. The new method proposed in this study was found to be an effective technique for detecting both the change of hydrological behaviors induced by prolonged drought and its driving factors at the process level.

The Budyko framework, which can describe a simple but useful partitioning of precipitation under supply and energy limits, is used widely to estimate evapotranspiration (ET). Previous studies have investigated time-variant Budyko functions on annual or interannual scales but seldom on the intra-annual scale. This study used a monthly two-parameter ( κ and y0) Budyko function and three schemes that considered single observations (ET or streamflow (Q)) and dual observations (ET and Q) to assimilate the time-varying parameters using the ensemble Kalman filter method. The study considered the contiguous USA (CONUS) using the Model Parameter Estimation Experiment dataset. The time-varying parameters were explained on the basis of time series analysis and correlation with meteorological data. Three conclusions were as follows. (1) The identified time-varying parameters ( κ and y0) of the Budyko function could effectively simulate ET. (2) The assimilation using only ET observations could identify a plausible set for parameter κ but was inadequate for y0 . (3) Most time-varying parameters exhibited a 12-month period, and the trend and change points detected for Midwest CONUS were related to anthropogenic influences such as extraction and use of groundwater. The findings show that changing environment can be detected by using the proposed time-varying parameters of the Budyko function.

The runoff generating processes and water fluxes exchange are essential simulating the physical nonlinear rainfall-runoff relations in hydrological models. However, current runoff generation representation in hydrological models is constraint due to both vertical and horizontal heterogeneity of meteorological factors and underlying surface condition, hampering the streamflow simulation performances. To address this concern, by integrating a hybrid runoff generation mechanism in the upper layer and baseflow curve in the lower layer, this work develops a modified Variable Infiltration Capacity (VIC) hydrological model. With consideration of both vertical and horizontal heterogeneity runoff, the modified VIC model can simulate Horton and Dunne runoff through the hybrid mechanism and lateral runoff based on three soil-layer structure. The upper reach of Hanjiang River basin with substantial climate variations is selected as a case study to validate the performance of the modified model. Results show that the modified VIC model can produce a better performance of streamflow simulation in terms of Nash-Sutcliffe Efficiency, at around 0.8 on average, especially for semi-humid and mountainous catchments. In addition, parameters related to the hybrid mechanism are sensitive to the hydrological performance, indicating that the improved performance should be attributed to the hybrid mechanism.