DOI: 10.5281/zenodo.10054665
title: Outputs of the WiMMed hydrological model for Sierra Nevada (Spain). Sept2015-Aug2022

description: Ecosystem  Services related to flood prevention, aquifer recharge and erosion prevention in SIERRA NEVADA (Spain) were quantified through the WiMMed hydrological model (Watershed Integrated Model in Mediterranean Environments; Herrero et al., 2014). WiMMed is a distributed and physically based model that combines hourly and daily meteorological data with soil hydro-physical properties and land use and land cover information to simulate water balance and flow circulation at basin scale (see Herrero et al. (2014) for details). 
In this study we applied the WiMMed model considering the land use and land cover data for 2020 (according to SIPNA) and the meteorological data from Sept2015 to Aug2022 to evaluate the value of ecosystem services, following the work made by Moreno-Llorca et al. (2020). Specific parameters, expressing the influence of vegetation changes in the hydrological processes of the study area, were considered, namely on evapotranspiration, interception, infiltration, overland flow and soil erodibility. Aquifer recharge (mm/m2/year) was calculated as the total volume of water moving from the soil into the aquifer and becoming groundwater. For that, the model firstly interpolates the precipitation at the cell scale (Herrero et al., 2009), and then calculates rainfall/snowfall partition, reproduces the interception from the vegetation, calculates the snow accumulation and melting (Herrero et al., 2009), and separates surface runoff from infiltration on the ground surface. Vertical and horizontal soil water movement was reproduced by a two-layer soil approach, using Darcy-Buckingham law with Mualem-vanGenuchten parameterization (Muñoz Carpena and Ritter Rodriguez, 2005). Evapotranspiration extract water from soil using a parameterization based on potential evapotranspiration and soil water content (Herrero et al., 2014). Water percolating through the second layer of soil becomes aquifer recharge. Soil erosion prevention (T/ha/year) was calculated by considering the inverse of soil loss by water flow concentration (rill processes) and raindrop impacts (interrill processes). WiMMed uses the variation of different parameters that link soil loss, with changes in vegetation cover and land uses, as described in (Millares et al., 2019). Changes on soil erodibility were estimated from vertical distribution of root biomass, by adapting empirical models (e.g. Gale and Grigal, 1987; Jackson et al., 1996) to Mediterranean environments reported previously (Martinez- Fernandez et al., 1995). From these estimations, distributed soil erodibility was calculated from the empirical model proposed by Flanagan and Livingstone (1995). The calibration and validation of the WiMMed model in Sierra Nevada has been conducted through a series of studies that analysed each hydrological process in the area and designed and corrected each WiMMed module, pertaining to snow (Herrero et al., 2009), soil (Aguilar and Polo, 2011), baseflow (Millares, 2008; Millares et al., 2009), river flow (Pérez-Palazón et al., 2014), or soil loss and sediment transportation (Bergillos et al., 2016; Millares et al., 2020).
INPUT DATA
The input data used in the hydrological simulations were:

Digital elevation model from national remote sensing program PNOA-LIDAR MDT02 and the topographic features calculated by WiMMed from the DEM: surface drainage system, river delineation, slope, aspect, sky view factor and horizon (sky obstruction in 8 directions).
Meteorological data from more than 50 weather stations in the area: hourly/daily rainfall (mm), hourly and daily temperature (oC), daily solar radiation (MJ/m2), average daily wind speed (m·s−1), average daily relative humidity (%), average daily barometric pressure (hPa).
Physico-chemical and hydraulic properties of the soil selected from the available spatial database performed by Rodríguez (2008), in which thematic maps were obtained for Andalusia at a 250-m resolution: hydraulic conductivity (mm·h−1), saturation and residual moisture values (mm·mm−1), air-entry matric potential (mm), retention parameter of the van Genuchten (dimensionless) and soil thickness (mm).
Land cover and land use information from SIPNA 2020.
Aquifer regions and information from hydrogeological atlas of Andalusia (ITGE-Junta de Andalucía, 1998; Castillo, 2008).
OUTPUT DATA
The results contained in this database are raster files in UTM ETRS89 30S, with a spatial resolution of 30x30 meters, for the whole SIerra Nevada. The raster files are Esri-ASCII ArcGIS (.asc) grids with 3846 columns (X) and 2099 rows (Y). There are different time scales for each variable. The prefix of the file indicates this time scale, namely "Ano" for annual maps, "mes" for monthly maps and "Tot" for the whole simulation. The suffix indicates the variable of interest:

Pre: Accumulated precipitation (solid + liquid) in mm
T_m: Mean temperature in ºC
P_n: Accumulated snowfall in mm
ErT: Accumulated total erosion (rill + interrill) in kg/m2
ET0: Accumulated potential evapotranspiration in mm
EvC: Accumulated real evaporation from canopy (intercepted precipitation) in mm
EvN:Accumulated real sublimation from snow in mm
EvS: Accumulated real evapotranspiration ration from soil in mm
Exp: Accumulated direct runoff in mm
Fus: Accumulated snowmelt in mm
HSol1: Instantaneous soil moisture in surface layer 1 (upper 25 cm) in mm
HSol2: Instantaneous soil moisture in deep layer 2 in mm
Inf: Accumulated infiltration from surface into soil in mm
Per: Accumulated aquifer recharge (from soil to groundwater) in mm
Qlat: Accumulated lateral flow (horizontal movement of water between cells) in mm
Tmn: Minimum temperature in ºC
Tmx: Maximum temperature in ºC
There are also some other grid files (Tot_XXX.asc) related to the initial and final conditions of the state variables or internal conditions of the model.
References
Aguilar, C., Polo, M.J., 2011. Generating reference evapotranspiration surfaces from the Hargreaves equation at watershed scale. Hydrol. Earth Syst. Sci. 15, 2495–2508. doi: 10.5194/hess-15-2495-2011.
Bergillos, R.J., Rodríguez-Delgado, C., Millares, A., Ortega-Sánchez, M., Losada, M.A., 2016. Impact of river regulation on a Mediterranean delta: assessment of managed versus unmanaged scenarios. Water Resour. Res. 52 (7), 5132–5148.
Castillo, A. 2008. Manantiales de Andalucía. Agencia Andaluza del agua, Consejería de Medio Ambiente, Junta de Andalucía, Sevilla, 410 pp.
Herrero, J., Polo, M.J., Moñino, A., Losada, M.A., 2009. An energy balance snowmelt model in a Mediterranean site. J. Hydrol. 371 (1-4), 98–107.
Herrero, J., Millares, A., Aguilar, C., Egüen, M., Losada, M.A., 2014. Coupling spatial and time scales in the hydrological modelling of mediterranean regions: WiMMed, in: CUNY Academic Works. In: Presented at the International Conference on Hydroinformatics, p. 8. ITGE-Junta de Andalucía: Atlas Hidrogeológico de Andalucía. Madrid, 216 pp., ISBN: 84-7840-351-5, available at: http: //aguas.igme.es/igme/publica/libros1 HR/libro110/lib110.htm, last access: 18 March 2012, 1998
Millares, A., 2008. Integración del caudal base en un modelo distribuido de cuenca. Estudio de las aportaciones subterráneas en ríos de montaña. University of Granada.
Millares, A., Polo, M.J., Losada, M.A., 2009. The hydrological response of baseflow in fractured mountain areas. Hydrol. Earth Syst. Sci. 13 (1261–1271), 2009.
Millares, A., Díez-Minguito, M., Moñino, A., 2019. Evaluating gullying effects on modeling erosive responses at basin scale. Environ. Modell. Software 111, 61–71. Millares, A., Herrero, J., Bermúdez, M., Leiva, J.F., Cantalejo, M., 2020. Long-term modelling of soil loss and fluvial transport processes in a mountainous semi-arid basin, southern Spain, in: River Flow 2020 - Twentieth International Conference on Fluvial Hydraulic. Delf, Netherlands.
Moreno-Llorca, R., Vaz, A. S., Herrero, J., Millares, A., Bonet-García, F. J., & Alcaraz-Segura, D. 2020. Multi-scale evolution of ecosystem services' supply in Sierra Nevada (Spain): An assessment over the last half-century. Ecosystem Services, 46, 101204.
Muñoz Carpena, R., Ritter Rodriguez, A., 2005. Hidrología Agroforestal. Mundiprensa.
Pérez-Palazón, M. J., Pimentel, R., Herrero, J., & Polo-Gómez, M. J. 2014. Analysis of snow spatial and temporary variability through the study of terrestrial photography in the Trevelez river valley. In Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI (Vol. 9239, pp. 358-368). SPIE.
Rodríguez, J. A. 2008. Sistema de Inferencia Espacial de Propiedades Físico-Químicas e Hidráulicas de los Suelos de Andalucía. Herramienta de Apoyo a la Simulación de Procesos Agro-Hidrológicos a Escala Regional. Informe Final. Empresa Pública Desarrollo Agrario y Pesquero, Consejería de Agricultura y Pesca, Sevilla.
 
 
description: This work is part of the project "Thematic Center on Mountain Ecosystem & Remote sensing, Deep learning-AI e-Services University of Granada-Sierra Nevada" (LifeWatch-2019-10-UGR-01), which has been co-funded by the Ministry of Science and Innovation through the FEDER funds from the Spanish Pluriregional Operational Program 2014-2020 (POPE), LifeWatch-ERIC action line, within the Workpackages LifeWatch-2019-10-UGR-01_WP-8, LifeWatch-2019-10-UGR-01_WP-7 and LifeWatch-2019-10-UGR-01_WP-4.