[1] Micrometeorological measurements of evapotranspiration (ET) can be difficult to interpret and use for validating model calculations in the presence of land cover heterogeneity. Land surface fluxes, soil moisture (q), and surface temperatures (T s ) data were collected by an eddy correlation-based tower located at the Orroli (Sardinia) experimental field (covered by woody vegetation, grass, and bare soil) from April 2003 to July 2004. Two Quickbird high-resolution images (summer 2003 and spring 2004) were acquired for depicting the contrasting land cover components. A procedure is presented for estimating ET in heterogeneous ecosystems as the residual term of the energy balance using T s observations, a two-dimensional footprint model, and the Quickbird images. Two variations on the procedure are successfully implemented: a proposed two-source random model (2SR), which treats the heat sources of each land cover component separately but computes the bulk heat transfer coefficient as spatially homogeneous, and a common two-source tile model. For 2SR, new relationships between the interfacial transfer coefficient and the roughness Reynolds number are estimated for the two bare soil-woody vegetation and grass-woody vegetation composite surfaces. The ET versus q relationships for each land cover component were also estimated, showing that that the woody vegetation has a strong tolerance to long droughts, transpiring at rates close to potential for even the driest conditions. Instead, the grass is much less tolerant to q deficits, and the switch from grass to bare soil following the rainy season had a significant impact on ET.

[1] The structure and function of vegetation regulate fluxes across the biosphereatmosphere interface with large effects in water-limited ecosystems. Vegetation dynamics are often neglected in hydrological modeling except for simple prescriptions of seasonal phenology. However, changes in vegetation densities, influencing the partitioning of incoming solar energy into sensible and latent heat fluxes, can result in long-term changes in both local and global climates with resulting feedbacks on vegetation growth. This paper seeks a simple vegetation dynamics model (VDM) for simulation of the leaf area index (LAI) dynamics in hydrologic models. Five variants of a VDM are employed, with a range of model complexities. The VDMs are coupled to a land surface model (LSM), with the VDM providing the LAI evolution through time and the LSM using this to compute the land surface fluxes and update the soil water contents. We explore the models through case studies of water-limited grass fields in California (United States) and North Carolina (United States). Results show that a simple VDM, simulating only the living aboveground green biomass (i.e., with low parameterization), is able to accurately simulate the LAI. Results also highlight the importance of including the VDM in the LSM when studying the climate-soil-vegetation interactions over moderate to long timescales. The inclusion of the VDM in the LSM is demonstrated to be essential for assessing the impact of interannual rainfall variability on the water budget of a water limited region.

[1] Coarse soil moisture fields and nonlinear relationships between fluxes and soil moisture combine to yield errors in both diagnostic and predictive estimates of largescale mass and energy fluxes. Efforts to empirically define the dynamics of subgrid spatial variance of soil moisture have led to contradictory results. Moreover, most reports of soil moisture variability range from qualitative to descriptively quantitative, owing to the lack of a robust theoretical framework for moisture variance dynamics. In this paper we derive a conservation equation for the spatial variance of subgrid root zone soil moisture, based on first principles of statistical fluid mechanics. We arrive at a variance budget in which explicit covariances between moisture fields and land surface flux fields act to produce or destroy variance through time (according to the sign of the correlation between the flux and state fields). A series of examples are used to explore how simple forms of soil, vegetation, precipitation, topography, and initial moisture variability lead to evolving covariances between spatial fields of soil moisture and particular land surface fluxes and how these covariances relate to the temporal trajectory of the spatial variance of soil moisture. We isolate a set of processes and conditions that demonstrate variance production through time and a set that demonstrate variance destruction. Of particular interest is the tendency for transpiration and infiltration-runoff processes to either produce or destroy variance, depending on the background wetness regime. Field data are also employed and shown to demonstrate a temporal behavior of the spatial variance that is readily described by the proposed approach. Ultimately, this work should aid field data interpretation and, when supplemented with a closure model for the variance budget, lead to improved land surface flux predictability over coarse grids.

Abstract. Mediterranean ecosystems are commonly heterogeneous savanna-like ecosystems, with contrasting plant functional types (PFTs, e.g. grass and woody vegetation) competing for water. Mediterranean ecosystems are also commonly characterized by strong inter-annual rainfall variability, which influences the distributions of PFTs that vary spatially and temporally. An extensive field campaign in a Mediterranean setting was performed with the objective to investigate interactions between vegetation dynamics, soil water budget and land-surface fluxes in a water-limited ecosystem. Also a vegetation dynamic model (VDM) is coupled to a 3-component (bare soil, grass and woody vegetation) Land surface model (LSM). The case study is in Orroli, situated in the mid-west of Sardegna within the Flumendosa river basin. The landscape is a mixture of Mediterranean patchy vegetation types: trees, including wild olives and cork oaks, different shrubs and herbaceous species. Land surface fluxes, soil moisture and vegetation growth were monitored during the May 2003-June 2006 period. Interestingly, hydrometeorological conditions of the monitored years strongly differ, with dry and wet years in turn, such that a wide range of hydrometeorological conditions can be analyzed. The coupled VDM-LSM model is successfully tested for the case study, demonstrating high model performance for the wide range of eco-hydrologic conditions. Results demonstrate also that vegetation dynamics are strongly influenced by the inter-annual variability of atmospheric forcing, with grass leaf area index changing significantly each spring season according to seasonal rainfall amount.

Mediterranean ecosystems are commonly heterogeneous savanna-like ecosystems, with contrasting plant functional types (PFTs, e.g. grass and woody vegetation) competing for water. Mediterranean ecosystems are also commonly characterized by strong inter-annual rainfall variability , which influences the distributions of PFTs that vary spatially and temporally. An extensive field campaign in a Mediterranean setting was performed with the objective to investigate interactions between vegetation dynamics, soil water budget and land-surface fluxes in a water-limited ecosystem. Also a vegetation dynamic model (VDM) is coupled to a 3-component (bare soil, grass and woody vegetation) Land surface model (LSM). The case study is in Orroli, situated in the mid-west of Sardegna within the Flumendosa river basin. The landscape is a mixture of Mediterranean patchy vegetation types: trees, including wild olives and cork oaks, different shrubs and herbaceous species. Land surface fluxes, soil moisture and vegetation growth were monitored during the May 2003-June 2006 period. Interestingly , hydrometeorological conditions of the monitored years strongly differ, with dry and wet years in turn, such that a wide range of hydrometeorological conditions can be analyzed. The coupled VDM-LSM model is successfully tested for the case study, demonstrating high model performance for the wide range of eco-hydrologic conditions. Results demonstrate also that vegetation dynamics are strongly influenced by the inter-annual variability of atmospheric forcing, with grass leaf area index changing significantly each spring season according to seasonal rainfall amount.