Abstract
Abstract. The statistical-dynamical annual water balance model of Eagleson (1978) is a pioneering work in the analysis of climate, soil and vegetation interactions. This paper describes several enhancements and modifications to the model that improve its physical realism at the expense of its mathematical elegance and analytical tractability. In particular, the analytical solutions for the root zone fluxes are re-derived using separate potential rates of transpiration and bare-soil evaporation. Those potential rates, along with the rate of evaporation from canopy interception, are calculated using the two-component Shuttleworth-Wallace (1985) canopy model. In addition, the soil column is divided into two layers, with the upper layer representing the dynamic root zone. The resulting ability to account for changes in root-zone water storage allows for implementation at the monthly timescale. This new version of the Eagleson model is coined the Statistical-Dynamical Ecohydrology Model (SDEM). The ability of the SDEM to capture the seasonal dynamics of the local-scale soil-water balance is demonstrated for two grassland sites in the US Great Plains. Sensitivity of the results to variations in peak green leaf area index (LAI) suggests that the mean peak green LAI is determined by some minimum in root zone soil moisture during the growing season. That minimum appears to be close to the soil matric potential at which the dominant grass species begins to experience water stress and well above the wilting point, thereby suggesting an ecological optimality hypothesis in which the need to avoid water-stress-induced leaf abscission is balanced by the maximization of carbon assimilation (and associated transpiration). Finally, analysis of the sensitivity of model-determined peak green LAI to soil texture shows that the coupled model is able to reproduce the so-called "inverse texture effect", which consists of the observation that natural vegetation in dry climates tends to be most productive in sandier soils despite their lower water holding capacity. Although the determination of LAI based on complete or near-complete utilization of soil moisture is not a new approach in ecohydrology, this paper demonstrates its use for the first time with a new monthly statistical-dynamical model of the water balance. Accordingly, the SDEM provides a new framework for studying the controls of soil texture and climate on vegetation density and evapotranspiration.
Highlights
In the subtropics and midlatitudes, water is the most important abiotic control on terrestrial plant productivity (Nemani et al, 2003)
The determination of leaf area index (LAI) based on complete or near-complete utilization of soil moisture is not a new approach in ecohydrology, this paper demonstrates its use for the first time with a new monthly statistical-dynamical model of the water balance
We provide an overview of the formulation of the Statistical-Dynamical Ecohydrology Model (SDEM) and its coupling to the two-component canopy model of Shuttleworth and Wallace (1985) The SDEM is based on the groundbreaking soil-vegetationclimate annual water balance model of Eagleson (Eagleson, 1978a–g, 2002)
Summary
In the subtropics and midlatitudes, water is the most important abiotic control on terrestrial plant productivity (Nemani et al, 2003). The seasonality in the model allows for application and testing of the following alternative hypothesis regarding the control that soil moisture exerts on vegetation productivity in water-limited systems: vegetation density, in the form of peak green leaf area index (LAI), is maximized for the mean water balance such that soil moisture in the latter half of the growing season just reaches the point at which water stress is experienced. We examine our alternative optimality hypothesis for two grassland sites in the US Great Plains This is done principally through an analysis of the sensitivity of modeled monthly mean root-zone soil moisture to variations in peak green LAI. In a companion paper (Kochendorfer and Ramırez, 2010), the alternative optimality hypothesis is used with the model to estimate long-term average peak green LAI and associated evapotranspiration partitioning over a domain encompassing the central United States
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