Most land surface models (LSMs) used in Earth System Models produce a lower ratio of transpiration (T) to evapotranspiration (ET) than field observations, degrading the credibility of Earth System Model‐projected ecosystem responses and feedbacks to climate change. To interpret this model deficiency, we conducted a pair of model experiments using a three‐dimensional, process‐based ecohydrological model in a subhumid, mountainous catchment. One experiment (CTRL) describes lateral water flow, topographic shading, leaf dynamics, and water vapor diffusion in the soil, while the other (LSM like) does not explicitly describe these processes to mimic a conventional LSM using artificially flattened terrain. Averaged over the catchment, CTRL produced a higher T/ET ratio (72%) than LSM like (55%) and agreed better with an independent estimate (79.79 ± 27%) based on rainfall and stream water isotopes. To discern the exact causes, we conducted additional model experiments, each reverting only one process described in CTRL to that of LSM like. These experiments revealed that the enhanced T/ET ratio was mostly caused by lateral water flow and water vapor diffusion within the soil. In particular, terrain‐driven lateral water flows spread out soil moisture to a wider range along hillslopes with an optimum subrange from the middle to upper slopes, where evaporation (E) was more suppressed by the drier surface than T due to plant uptake of deep soil water, thereby enhancing T/ET. A more elaborate representation of water vapor diffusion from a dynamically changing evaporating surface to the height of the surface roughness length reduced E and increased the T/ET ratio.
Winters in snow-covered regions have warmed, likely shifting the timing and magnitude of nutrient export, leading to unquantified changes in water quality. Intermittent, seasonal, and permanent snow covers more than half of the global land surface. Warming has reduced the cold conditions that limit winter runoff and nutrient transport, while cold season snowmelt, the amount of winter precipitation falling as rain, and rain-on-snow have increased. We used existing geospatial datasets (rain-on-snow frequency overlain on nitrogen and phosphorous inventories) to identify areas of the contiguous United States (US) where water quality could be threatened by this change. Next, to illustrate the potential export impacts of these events, we examined flow and turbidity data from a large regional rain-on-snow event in the United States’ largest river basin, the Mississippi River Basin. We show that rain-on-snow, a major flood-generating mechanism for large areas of the globe (Berghuijs et al 2019 Water Resour. Res.55 4582–93; Berghuijs et al 2016 Geophys. Res. Lett.43 4382–90), affects 53% of the contiguous US and puts 50% of US nitrogen and phosphorus pools (43% of the contiguous US) at risk of export to groundwater and surface water. Further, the 2019 rain-on-snow event in the Mississippi River Basin demonstrates that these events could have large, cascading impacts on winter nutrient transport. We suggest that the assumption of low wintertime discharge and nutrient transport in historically snow-covered regions no longer holds. Critically, however, we lack sufficient data to accurately measure and predict these episodic and potentially large wintertime nutrient export events at regional to continental scales.
We used the weighted wavelet method to perform spectral analysis of observed long-term precipitation, streamflow, actual evapotranspiration, and soil water storage at a sub-humid mountain catchment near Tucson, Arizona, USA. Fractal scaling in precipitation and the daily change in soil water storage occurred up to a period of 14 days and corresponded to the typical duration of relatively wet and dry intervals. In contrast, fractal scaling could be observed up to a period of 0.5 years in streamflow and actual evapotranspiration. By considering long-term observations of hydrologic fluxes and storages, we show that, in contrast to previous findings, the phase relationships between water balance components changed with component period and were not perfectly in or out of phase at all periods. Self-averaging behavior was apparent, but the temporal scales over which this behavior was applicable differed among the various water balance components. Conservative tracer analysis showed that this catchment acted as a fractal filter by transforming white noise in the precipitation input signal to a 1/f flicker in the streamflow output signal by means of both spatial and temporal subsurface advection and dispersion processes and soil wetting properties. This study provides an improved understanding of hydrological filtering behavior in mountain critical zones that are critical sources of water and ecosystem services throughout the world.