Partitioning and sourcing of evapotranspiration using coupled MARMITES-MODFLOW model, La Mata catchment (Spain)

Abstract

The new, two-way coupled, distributed and transient MARMITES-MODFLOW (MM-MF) model, coupling land surface and soil zone domains with groundwater, is presented. It implements model-based partitioning and sourcing of subsurface evapotranspiration (ETss) as part of spatio-temporal water balance (WB). The partitioning of ETss involves its separation into evaporation (E) and transpiration (T), while the sourcing of E and T involves separation of each of the two into soil zone (Esoil and Tsoil) and groundwater (Eg and Tg) components. The objective of that development was to understand the system dynamics of a catchment with shallow water table, through spatio-temporal quantification of water fluxes and evaluation of their importance in water balances, focusing on the Eg and Tg components of ETss. While the Eg is computed using formulation from published study, the Tg is obtained through a novel phenomenological function, based on soil moisture availability and transpiration demand driven by climatic conditions. The MM-MF model was applied in the small La Mata catchment (~4.8 km2, Salamanca Province, Spain), characterized by semi-arid climate, granitic bedrock, shallow water table and sparse oak woodland. The main catchment characteristics were obtained using remote sensing, non-invasive hydrogeophysics and classical field data acquisition. The MM-MF model was calibrated in transient, using daily data of five hydrological years, between 1st October 2008 and 30th September 2013. The WB confirmed dependence of groundwater exfiltration on gross recharge. These two water fluxes, together with infiltration and Esoil, constituted the largest subsurface water fluxes. The Eg was higher than the Tg, which is explained by low tree coverage (~7%). Considering seasonal variability, Eg and Tg were larger in dry seasons than in wet season, when solar radiation was the largest and soil moisture the most depleted. A relevant observation with respect to tree transpiration was that during dry seasons, the decline of Tsoil, associated with the decline of soil moisture, was compensated by increase of Tg, despite continuously declining water table. However, in dry seasons, T was far below the atmospheric evaporative demand, indicating that the groundwater uptake by the tree species of this study constituted a survival strategy and not a mechanism for continued plant growth. The presented MM-MF model allowed to analyze catchment water dynamics and water balance in detail, accounting separately for impacts of evaporation and transpiration processes on groundwater resources. With its unique capability of partitioning and sourcing of ETss, the MM-MF model is particularly suitable for mapping groundwater dependent ecosystems, but also for analyzing impacts of climate and land cover changes on groundwater resources.

Multi-scale assessment of interactions between surface water and groundwater fluxes in hard rock, water limited environment

“…Different approach than in the EVT Package, providing non-linear dependence of 𝐸𝐸𝐸𝐸 𝑔𝑔 upon WT depth, but addressing specific, riparian wetland environment was proposed byBaird and Maddock (2005); other, more general solution has been proposed recently byFrancés and Lubczynski (2023), where the 𝐸𝐸 𝑔𝑔 and 𝐸𝐸 𝑔𝑔 are simulated separately, being primarily dependent on climate forcing.The current TSA model has undergone number of relevant changes/improvements as compared to the former Sardon model (Chapter 2); these are as follow: (i) externally defined and improved 𝐸𝐸 𝐼𝐼 ; to illustrate the difference between the two solutions (Table4.3), the 16-year mean 𝐸𝐸 𝐼𝐼 in the TSA was 63.7 mm (11.3% 𝑃𝑃), whereas in the Sardon model in the same period, was only 35.2 mm (6.4% 𝑃𝑃); (ii) improved 𝑃𝑃𝐸𝐸𝐸𝐸 estimated as product of temporally variable 𝐸𝐸𝐸𝐸 0 and spatiotemporally variable LULC factor (𝐾𝐾 𝑐𝑐 ) derived from satellite products, replaced former 𝑃𝑃𝐸𝐸𝐸𝐸 by Jensen et al 𝐾𝐾 𝑠𝑠 , 𝜃𝜃 𝑠𝑠 , 𝜃𝜃 𝑟𝑟 and WRC) of the soil samples obtained from various depths at profile B to parametrize the unsaturated zone; and (vii) improvement of state variables constraining model calibration by the additional use of four monitoring soil moisture profiles and MODIS 𝐸𝐸𝐸𝐸 not used in the former Sardon model. The PRMS driving forces and their parameterization changed substantially (Table…”