Comparison of two model approaches in the Zambezi river basin with regard to model reliability and identifiability

Abstract

Abstract. Variations of water stocks in the upper Zambezi river basin have been determined by 2 different hydrological modelling approaches. The purpose was to provide preliminary terrestrial storage estimates in the upper Zambezi for comparison with estimates derived from the Gravity Recovery And Climate Experiment (GRACE). The first modelling approach is GIS-based, distributed and conceptual (STREAM). The second approach uses lumped elementary watersheds identified and modelled conceptually (LEW). The STREAM model structure has been assessed using GLUE (Generalized Likelihood Uncertainty Estimation) a posteriori to determine parameter identifiability. The LEW approach could, in addition, be tested for model structure, because computational efforts of LEW are low. Both models are threshold models, where the non-linear behaviour of the Zambezi river basin is explained by a combination of thresholds and linear reservoirs. The models were forced by time series of gauged and interpolated rainfall. Where available, runoff station data was used to calibrate the models. Ungauged watersheds were generally given the same parameter sets as their neighbouring calibrated watersheds. It appeared that the LEW model structure could be improved by applying GLUE iteratively. Eventually, it led to better identifiability of parameters and consequently a better model structure than the STREAM model. Hence, the final model structure obtained, better represents the true hydrology. After calibration, both models show a comparable efficiency in representing discharge. However the LEW model shows a far greater storage amplitude than the STREAM model. This emphasizes the storage uncertainty related to hydrological modelling in data-scarce environments such as the Zambezi river basin. It underlines the need and potential for independent observations of terrestrial storage to enhance our understanding and modelling capacity of the hydrological processes. GRACE could provide orthogonal information that can help to constrain and further enhance our models. In the near future, other remotely sensed data sources will be used to force modelling efforts of the Zambezi (e.g. satellite rainfall estimates) and to identify individual storage components in the GRACE observations (e.g. altimeter lake levels and microwave soil moisture). Ultimately, this will create possibilities for state updating of regional hydrological models using GRACE.

Use of Satellite Information on Wetness and Temperature for Crop Yield Prediction and River Resource Planning

“…In contrast, low BWI values (less than 1) contain a high confidence that the flow will be near the base flow. These results compared favorably to model prediction for the Zambezi presented by Winsemius et al (2006), whose predictions were based on a more complex model. As a result, the BWI can be a quantitative indicator for periods and frequencies of flow associated with limited water -of particular relevance to obligations and commitments agreed upon in international water treaties.…”

Detecting the long-term impacts from climate variability and increasing water consumption on runoff in the Krishna river basin (India)

“…The water balance is calculated for each grid-cell using a direct runoff, soil water and groundwater component (see Appendix A). The STREAM model has been successfully applied in various forms for climate and hydrology studies in a number of river basins with similar size and characteristics as the Krishna river basin (Van Deursen and Kwadijk, 1994;Aerts et al, 1999;Aerts et al, 2000;Middelkoop et al, 2001;Winsemius et al, 2006). These studies have confirmed that a monthly time step is sufficient for detecting decadal, inter-annual and seasonal changes in the hydrological cycle, such as those caused by water consumption and climatic change.…”

Hydraulic–hydrologic model for water resources management of the Zambezi basin

“…Compared with past attempts to model discharges in key locations of the Zambezi basin (Vorosmarty et al 1991;Harrison & Whittington 2002;Winsemius et al 2006a;Meier et al 2011), the results can be considered as acceptable for applying the model to simulate development scenarios, taking into account the fact that the scenarios comparison will be based on relative values. The present work constitutes a significant contribution in terms of reliability and error assessment as it implemented a thorough validation procedure and used a hydrological model tailored to meet some of the specificities of the Zambezi River basin.…”

“…In another modeling attempt, the Spatial Tools for River basin Environmental Analysis and Management 2 T. Cohen Liechti et al (Aerts et al 1999) and a Lumped Elementary Watershed model were calibrated on the same sub-basin over the period 1960-1972 at a monthly time step (Winsemius et al 2006a). The NS coefficient was about 0.8.…”