Abstract
Abstract. The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m3 s–1) from the Global River Discharge Center (GRDC) and a linear reservoir model were used to obtain baseflow recession coefficients (kbf) for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR) and aridity index (AI) were found to explain 49% of the spatial variation of kbf. The rest of climatic indices and the terrain indices average catchment slope (SLO) and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE), a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for kbf parameterisation in ungauged catchments.
Highlights
The gradual depletion of water stored in a catchment during dry weather constitutes the drainage or baseflow recession (Tallaksen, 1995)
Values obtained from drainage theory have been used in PCR-GLOBWB (Van Beek and Bierkens, 2008) whereas calibrated values were used in the global application of WASMOD-M (Widen-Nilsson et al, 2007) and in an application of the Catchment Land Surface Model (CLSM) to the Somme River Basin (Gascoin et al, 2009)
The results showed that baseflow recession from a linear reservoir was best explained by climatic attributes, with catchment aridity index (AI, the ratio of rainfall to potential evapotranspiration) explaining 27% of the variation in derived recession coefficients
Summary
The gradual depletion of water stored in a catchment during dry weather constitutes the drainage or baseflow recession (Tallaksen, 1995). Several assessments of global water resources have been conducted using hydrological models and land surface models (LSMs); mainly in response to increase in water demand and potential impacts of climatic and land use change (Vorosmarty et al, 2000; Oki and Kanae, 2006). The linear reservoir application in global hydrological models used fixed parameter values, e.g. the routing HD model (Hagemann and Dumenil, 1998), macro-PDM (Arnell, 1999, 2003) and WGHM (Doll et al, 2003). The use of drainage theory is questionable at large scales and hindered by the uncertain quality of data needed to estimate various parameters. The theoretical approach of Brutsaert and Nieber (1977), one of the few analytical ways to obtain aquifer parameters from hillslope to catchment scales, was used by Zecharias and Brutsaert (1988) to advance a proportionality relationship between the recession coefficient and aquifer characteristics: Published by Copernicus Publications on behalf of the European Geosciences Union
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