Simulating evapotranspiration in a semi-arid environment

Summary In this work, simulations with the mesoscale meteorological model FOOT3DK for a semi-arid research site in southern morocco are presented. The main aim of this study is to introduce two different ways to improve the soil moisture distribution towards a more realistic pattern. One of them resembles the availability of groundwater resources below the lower boundary of the soil part of the model, the other one resembles irrigation practices in the region. Additionally, we introduce a newly derived land use/land cover data set obtained from analysis of LANDSAT data and compare the simulation results to those obtained with the USGS GLCC data. To evaluate the results with the refinements in soil moisture and land use/land cover, we focus on evapotranspiration, as the quantity which is most tentative to the changes in soil moisture and is an important part of the local hydrological cycle. To evaluate the importance of sub-grid scale surface heterogeneity in soil moisture and land use/land cover, we present simulations with enhanced surface resolution. Simulation results are compared to point measurements at different sites in the research area for validation.The results show, that a deep groundwater table and irrigation of parts of the research area can be represented by the methods we used. Simulated transpiration is overestimated compared to measured values, but this is due to the maximum approach used in this work. Finer tuning of the artificial enhancement of soil moisture with the two methods presented here are expected to lead to realistic distributions of evapotranspiration and related quantities, therewith drastically enhancing simulation accuracy for this site. As uncertainties of soil moisture distribution and restricted representation of soil moisture dynamics in meteorological models is a common problem especially for arid and semi-arid sites, we expect our results to be useful for meteorological simulations in other arid or semi-arid areas as well.