Basin hydrologic response relations to distributed physiographic descriptors and climate

The long-term (climatic) hydrologic response of a basin may be quantified using the evaporation efficiency (E/Ep or actual evaporation ratio with potential evaporation) and runoff ratio (R/P or ratio of runoff loss to precipitation). A key question is the degree to which the basin's physiographic features and regional climate can explain or predict these hydrologic response measures. In this paper we present the results from 10 basins in diverse climates and terrains. The long-term hydrologic response is estimated using an equilibrium surface water-groundwater interaction model. We investigate variability between basins with an examination of the relationships between various physical characteristics and the hydrologic properties of basins. Neither climate nor physiography alone can explain observed interbasin variability. Six variables are selected to represent the basins' climate, geomorphology, and lithology, each of which has a conceptual relationship to basin-scale equilibrium hydrology. The parameters include median slope, relief ratio, drainage density, wetness ratio, infiltration capacity, and a saturated zone efficiency index. Two hydrologic variables (runoff ratio and evaporation efficiency) are selected from the output of a distributed hydrologic equilibrium model. We perform a stepwise regression to identify which combinations of variables are valuable in predicting the basin-average hydrologic fluxes. A combination of two variables estimate the runoff ratio with an R(2) or explained-variance fraction of 0.76; use of all six variables increases the prediction to an R(2) of 0.90. The stepwise regression technique fails to achieve a statistically significant model for evaporation efficiency, but a regression model using all six variables nonetheless achieves an R(2) of 0.79. This paper demonstrates that physiographic and climate descriptors can explain a large fraction of basin-to-basin differences in modeled hydrologic response. The case has been built on modeled surface water-groundwater interaction and should next be extended to hydrologic response descriptors derived from observations alone.