Abstract
AbstractWe used the new process‐based, tracer‐aided ecohydrological model EcH2O‐iso to assess the effects of vegetation cover on water balance partitioning and associated flux ages under temperate deciduous beech forest (F) and grassland (G) at an intensively monitored site in Northern Germany. Unique, multicriteria calibration, based on measured components of energy balance, hydrological function and biomass accumulation, resulted in good simulations reproducing measured soil surface temperatures, soil water content, transpiration, and biomass production. Model results showed the forest “used” more water than the grassland; of 620 mm average annual precipitation, losses were higher through interception (29% under F, 16% for G) and combined soil evaporation and transpiration (59% F, 47% G). Consequently, groundwater (GW) recharge was enhanced under grassland at 37% (~225 mm) of precipitation compared with 12% (~73 mm) for forest. The model tracked the ages of water in different storage compartments and associated fluxes. In shallow soil horizons, the average ages of soil water fluxes and evaporation were similar in both plots (~1.5 months), though transpiration and GW recharge were older under forest (~6 months compared with ~3 months for transpiration, and ~12 months compared with ~10 months for GW). Flux tracking using measured chloride data as a conservative tracer provided independent support for the modelling results, though highlighted effects of uncertainties in forest partitioning of evaporation and transpiration. By tracking storage—flux—age interactions under different land covers, EcH2O‐iso could quantify the effects of vegetation on water partitioning and age distributions. Given the likelihood of drier, warmer summers, such models can help assess the implications of land use for water resource availability to inform debates over building landscape resilience to climate change. Better conceptualization of soil water mixing processes and improved calibration data on leaf area index and root distribution appear obvious respective modelling and data needs for improved simulations.
Highlights
Vegetation exerts a strong control on land‐surface water and energy partitioning, and the resulting ecohydrological fluxes of “green water” as evaporation and transpiration (Baldocchi, Xu, & Kiang, 2004; Llorens & Domingo, 2007; Villegas et al, 2015; Wang, Good, & Caylor, 2014), and the residual “blue water” fluxes to groundwater recharge and run‐off (Jencso & McGlynn, 2011; Williams et al, 2012)
The application of EcH2O‐iso to the monitoring site at Lake Stechlin, followed on from a successful catchment‐scale application of the model in a wet, boreal catchment in Scottish Highlands (Kuppel et al, 2018a), and the present study provided an opportunity to test the model in a comparative forest/grassland plot‐scale study in a more water‐limited site and, more importantly, use direct measures of biomass accumulation and turnover for model calibration
Groundwater recharge was greatly enhanced under grassland at 37% of precipitation compared with 12% for forest
Summary
Vegetation exerts a strong control on land‐surface water and energy partitioning, and the resulting ecohydrological fluxes of “green water” as evaporation and transpiration (Baldocchi, Xu, & Kiang, 2004; Llorens & Domingo, 2007; Villegas et al, 2015; Wang, Good, & Caylor, 2014), and the residual “blue water” fluxes to groundwater recharge and run‐off (Jencso & McGlynn, 2011; Williams et al, 2012). As an independent check on how well EcH2O‐iso captures interactions between water storage, flux dynamics, and associated mixing relationships, we used the chloride data collected from precipitation, throughfall and soil water as an assumed conservative tracer in the model for the forest site (cf Peters & Ratcliffe, 1998) This was not possible at the grassland site as concentrations were too low and uncertainties too high in the absence of monitoring of throughfall and the effects of dry and occult deposition on the grass sward. For the forest plot, measurements of tree biomass production enabled us to explicitly include in the model calibration process metrics of daily, seasonal, and/or long‐term plant physiological dynamics (stem and leaf growth, transpiration, canopy cover, etc.), along with more commonly used observations pertinent to the energy (e.g., soil temperatures) and water balance (e.g., soil moisture) components.
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