A FIRST APPROACH MODELING IBERÁ WETLANDS USING VIC HYDROLOGIC MODEL Ricardo Vidal 1 - Inés Camilloni 2 1 Departamento de Ciencias de la Atmósfera y los.

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Presentation transcript:

A FIRST APPROACH MODELING IBERÁ WETLANDS USING VIC HYDROLOGIC MODEL Ricardo Vidal 1 - Inés Camilloni 2 1 Departamento de Ciencias de la Atmósfera y los Océanos - Facultad de Ciencias Exactas y Naturales- UBA 2 Centro de Investigaciones del Mar y la Atmósfera (CIMA) - CONICET METODOLOGY & DATASETS Corrientes basin including wetlands and closure point. Rain gauge stations. Temperature stations. RESULTS The calibration period for the model was The model parametrs were selected according to the best fit to observations: B (variable infiltration curve parameter) = DSmax (maximun velocity of baseflow) = 2.5 m/s DS (fraction of DSmax where non-linear baseflow begins) = WS (fraction of soil mosture where non-linear baseflow occurs) = 0.5 The validation period was was not included in this period to avoid forcing the model to an extreme El Niño event when severe floods occured all over the region. Simulated (MOD) and observed (OBS) monthly mean streamflows time series are shown for both periods. 3-months backward running average of the monthly simulated streamflows are also presented. REFERENCES Hansen et al, 2000: Global land cover classification at 1 km resolution using a decision tree classifier. Int. J. Remote Sensing, 21, Hastings et al, 1999: The Global Land One-Kilometer Base Elevation (GLOBE) Digital Elevation Model, Versión 1.0. National Geophysical Data Center – NOAA. Liang et al, 1994: A simple hidrologically based model of land surface water energy fluxes for GSMs. J. Geophys. Res. 99, Saurral R. 2007: Impactos de las variaciones climáticas en la cuenca del río Uruguay. Tesis de Licenciatura en Ciencias de la Atmósfera.- UBA Su et al, 2005: Modeling of land surface processes in La Plata basin. Proceedings of the AGU fall meeting, San Francisco, CA, USA.. DISCUSSION  In general terms, theVIC model simulates the average streamflow in the validation period similarly than during the calibration period.  Simulated monthly streamflow series explain 55% of the variance of the observed monthly streamflow series in the calibration period, but it decreases to 35% in the validation period.  Due to the inherent limitation of the Routing Model to simulate the acumulation of water that is produced in wetlands systems such as Iberá, it tends to run off the precipitated water into the basin in a cuasi-instantaneous way simulating spurious streamflow peaks at the closure point. For that reason, the E estimator results lower than the 0.5 threshold.  By considering three months backward running average of the monthly modeled series, model performance is enhanced which is reflected in incresing values of E estimator. FUTURE WORK  To analyze the relationship between Iberá wetlands water level and the measured streamflow at the closure point of the basin.  To study the variability of Iberá wetlands water level in response to different future climate scenarios by simulating the mean streamflow of the Corrientes River.  VIC model successfully simulates the mean streamflow at the closure point of Corrientes basin, but it does not represent properly the monthly variability due to the impossibility of the Routing Model to acumulate the precipitated water in a lacunal area. Consequently, the routing scheme needs to be modified by adding the possibility of acumulate water up to a terrain dependent threshold and to rout the surplus. This way, the monthly variability of the streamflow at the closure point will be better simulated and it will be also possible to infer the water level of the lagoons of the Iberá wetlands system. INTRODUCTION & OBJECTIVE Most of La Plata basin and central-eastern Argentina has become increasingly vulnerable to floods and droughts with important social, economic and environmental consequences. A detailed knowledge of the hydrological variability in the region as a consequence of climate variability and change will be an important tool for the development of adaptation strategies for the conservation of the region. The Iberá wetlands are considered one of the most important wetlands of the world due to its high level of conservation and biodiversity. They are located in the central-northern province of Corrientes in northeastern Argentina, covering approximately Km². Location of Iberá wetlands. The objective of this work is to evaluate the ability of the VIC hydrologic model to represent the Corrientes River streamflows downstream of Iberá wetlands in order to be used as a tool for estimating future environmental conditions in the region under different climate scenarios. It is important to note that VIC model was not designed specifically to simulate streamflows in flooded areas, such as Iberá wetlands. For this reason the main objective at this time is simply to evaluate the ability of the model to reproduce the mean streamflows of the river. Iberá wetlands Corrientes basin closure point “Los Laureles” The VIC Model The Variable Infiltration Capacity (VIC) macroscale hydrologic model was developed at University of Washington, USA (Liang et al 1994) and it has already been succesfully applied to La Plata basin (Su et al 2005) and to the Uruguay basin (Saurral 2007). In this work the VIC model was applied to Corrientes basin, which includes Iberá wetlands, with closure point at the gauge station “Los Laureles” (29.76ºS, 59.22ºW). Basically the model divides the basin into an equally-spaced grid and it calculates the hydrologic balance equations for every point at each time step. To do that it takes into account three sub-superficial layers and the vegetal canopy. Furthermore, every grid point is subdivided into subregions depending on the different types of vegetal covers that exists in that point. To evaluate the evapotranspiration it considers the Penman-Monteith formula.. Model parameters: * Temporal resolution: Daily * Spatial resolution: 0.125º latitud x 0.125º longitude * Integration mode: “Water Balance” When VIC ends the integration, results are given in the form of daily and monthly water fluxes at each grid point, which need to be routed to obtain the streamflow at the closure point of the basin. Routing Model requires a Digital Elevation Model (DEM) that accounts for the elevation of each grid point of the domain. In this case GLOBE (Global Land One- Kilometer Base Elevation) data was used at original spatial resolution of 1 Km. (Hastings et al 1990) and then interpolated to the VIC model resolution. Datasets: * Soil type dataset: Soil Map of the World (UNESCO). Spatial resolution: 0.5º lat x 0.5º lon. * Vegetal cover type dataset: University of Meryland (Hansen et al 2000) from setellite estimations between , spatial resolution of 1 Km. * Meteorological dataset: - Precipitation: 221 daily gauge stations (National Climatic Data Center – NOAA, Instituto Nacional de Tecnología Agropecuaria (INTA), Subsecretaría de Recursos Hídricos de la Nación, EVARSA, Servicio Meteorológico Nacional (SMN)) - Max/Min Temperatures: 37 daily data stations (National Climatic Data Center – NOAA, Instituto Nacional de Tecnología Agropecuaria (INTA), Servicio Meteorológico Nacional (SMN)) - Wind data: Daily mean 10m wind velocity from NCEP/NCAR reanalysis All datasets were gridded at the model resolution by Krigging interpolation method. In spite of the main objective of the simulation which is to reproduce the average streamflow in the validation period, the E estimator (Nash and Sutcliffe (1970) was calculated as a measure of the quality of the adjustment. This parameter has the form: where: Q o t = measured streamflow at time t Q m t = simulated streamflow at time t = observed average streamflow Calibration is considered to be “fine” if E > 0.5. The percentage of variance of the observed series that is explained by the model (R 2 ) was also calculated. The following table summarizes the results: OBSSIMDiffR² SIM RUN AVE Diff (*) R² average streamflow calibration period (m 3 /s) % %0.58 average streamflow validation period (m 3 /s) % %0.30 E calibration period E validation period ACKNOWLEDGMENTS The authors thank Ramiro Saurral for his advices and important tips on working with the VIC model.