Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution

Abstract

Abstract. Budyko (1974) postulated that long-term catchment water balance is controlled to first order by the available water and energy. This leads to the interesting question of how do landscape characteristics (soils, geology, vegetation) and climate properties (precipitation, potential evaporation, number of wet and dry days) interact at the catchment scale to produce such a simple and predictable outcome of hydrological partitioning? Here we use a physically-based hydrologic model separately parameterized in 12 US catchments across a climate gradient to decouple the impact of climate and landscape properties to gain insight into the role of climate-vegetation-soil interactions in long-term hydrologic partitioning. The 12 catchment models (with different paramterizations) are subjected to the 12 different climate forcings, resulting in 144 10 yr model simulations. The results are analyzed per catchment (one catchment model subjected to 12 climates) and per climate (one climate filtered by 12 different model parameterization), and compared to water balance predictions based on Budyko's hypothesis (E/P = ϕ(E p /P ); E: evaporation, P : precipitation, E p : potential evaporation). We find significant anti-correlation between average deviations of the evaporation index (E/P ) computed per catchment vs. per climate, compared to that predicted by Budyko. Catchments that on average produce more E/P have developed in climates that on average produce less E/P , when compared to Budyko's prediction. Water and energy seasonality could not explain these observations, confirming previous results reported by Potter et al. (2005). Next, we analyze which model (i.e., landscape filter) characteristics explain the catchment's tendency to produce more or less E/P . We find that the time scale that controls subsurface storage release explains the observed trend. This time scale combines several geomorphologic and hydraulic soil properties. Catchments with relatively longer subsurface storage release time scales produce significantly more E/P . Vegetation in these catchments have longer access to this additional groundwater source and thus are less prone to water stress. Further analysis reveals that climates that give rise to more (less) E/P are associated with catchments that have vegetation with less (more) efficient water use parameters. In particular, the climates with tendency to produce more E/P have catchments that have lower % root fraction and less light use efficiency. Our results suggest that their exists strong interactions between climate, vegetation and soil properties that lead to specific hydrologic partitioning at the catchment scale. This co-evolution of catchment vegetation and soils with climate needs to be further explored to improve our capabilities to predict hydrologic partitioning in ungauged basins.

Global pattern for the effect of climate and land cover on water yield

“…4c). Thus, R/P is not only affected by P/PET, but also by changes in land cover and difference in the watershed parameter, which highlights the fact that the effects of land cover changes on water yield are influenced by watershed characteristics and thus are watershed specific 22 .…”

Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

“…play a secondary role [55,56]. Recently, Troch et al [55] demonstrated the existence of strong interactions between climate, vegetation and soil that lead to specific hydrologic partitioning at the watershed scale.…”

“…play a secondary role [55,56]. Recently, Troch et al [55] demonstrated the existence of strong interactions between climate, vegetation and soil that lead to specific hydrologic partitioning at the watershed scale. As elaborated in Zhang et al [56], the rational function approach developed by Fu [57] is useful in understanding the dynamic nature of catchment water balance and its intra-annual variability while considering only the primary controlling factors.…”

What makes Darwinian hydrology "Darwinian"? Asking a different kind of question about landscapes

“…Methods have been (and continue to be) developed to extract the net effect of these properties at the watershed scale from the observed hydrologic signatures (e.g., Wittenberg, 1999;Jothityangkoon and Sivapalan, 2009;Kirchner, 2009), many derived from the notion of a "top-down" approach to conceptualizing hydrologic systems (Klemeš, 1983;Sivapalan et al, 2003). By separating the direct effects of climatic variability from the "filter" that transforms that variability into the hydrologic regime, these methods can reveal watershed hydrologic properties explicable in terms of their history, including the indirect effects of climate (e.g., Troch et al, 2013). The analysis of the passive tracer and biogeochemical "filtering" extends this type of integrated-scale analysis (e.g., Guan et al, 2011).…”

“…This curve has been examined by a number of modeling and observational studies (Milly, 1994;Zhang et al, 2001;Atkinson, 2002;Farmer et al, 2003;Porporato et al, 2004;Donohue et al, 2007;Yokoo et al, 2008;Gentine et al, 2012;Troch et al, 2013) that have elucidated the first-order controls on this partitioning. These suggest that for a given ratio of Ep/P the variation between watersheds (that is, the scatter around the curve) is largely controlled by a number of factors that can be summarized as follows:…”