Abstract
Appropriate representation of the vegetation dynamics is crucial in hydrological modelling. To improve an existing limited vegetation parameterization in a semi-distributed hydrologic model, called the Soil Moisture and Runoff simulation Toolkit (SMART), this study proposed a simple method to incorporate daily leaf area index (LAI) dynamics into the model using mean monthly LAI climatology and mean rainfall. The LAI-rainfall sensitivity is governed by a parameter that is optimized by maximizing the Pearson correlation coefficient (R) between the estimated and satellite-derived LAI time series. As a result, the LAI-rainfall sensitivity is smallest for forest, shrub, and woodland regions across Australia, and increases for grasslands and croplands. The impact of the proposed method on catchment-scale simulations of soil moisture (SM), evapotranspiration (ET) and discharge (Q) in SMART was examined across six eco-hydrologically contrasted upland catchments in Australia. Results showed that the proposed method produces almost identical results compared to simulations by the satellite-derived LAI time series. In addition, the simulation results were considerably improved in nutrient/light limited catchments compared to the cases with the default vegetation parameterization. The results showed promise, with possibilities of extension to other hydrologic models that need similar specifications for inbuilt vegetation dynamics.
Highlights
Terrestrial vegetation plays an important role in the water and energy cycles
leaf area index (LAI) time series at each grid cell were estimated by Equation (4) using the calibrated k
A method was proposed for effectively incorporating LAI dynamics in a hydrologic model, SMART, by only using monthly mean LAI climatology and rainfall data over a region
Summary
Terrestrial vegetation plays an important role in the water and energy cycles. Changes in the vegetation cover affect land surface properties, carbon generation and consumption, and significantly impact regional and global climate systems dynamics [1,2,3]. Vegetation density (e.g., leaf area index (LAI)) and physiological properties (e.g., stomatal conductance) control partitioning of rainfall into runoff and evapotranspiration [4]. Changes in LAI impact evapotranspiration rates, and can affect subsequent hydrologic processes including soil moisture, baseflow and runoff [5,6]. Such long term changes in vegetation cover in response to environmental factors can manifest themselves through nonstationary hydrologic responses where long-term trends in annual runoff to precipitation ratios in 20 anthropogenically unaffected catchments in Australia are observed [7]
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