Ongoing Work As part of a project intended to evaluate the potential for improving water resources management in Mexico through use of climate forecasts, we are implementing an operational reservoir model in the Rio Yaqui river basin. The Simulator-Optimizer (SIMOP) was developed by the Instituto Mexicano de Tecnologia del Agua (IMTA) to create better predictions of water releases by the water storages. Key features of the model include: Use of a genetic algorithm to optimize the water used for irrigation in a 1-year cycle using the maximum and minimum levels of different dams and runoff. Variables of the genetic algorithm include levels and slopes of the change between maximum and minimum reservoir levels. The model accounts for the water uses in the basin (irrigation and potable) through the volumes of water available for certain activities at each dam. Every reservoir is linked in the file called "definition of policies" which are the parameters that define the operation of the dam. The hydrological forecast system will provide the variables needed for its operation, such as runoff and Evaporation. Intraseasonal-to-interannual hydrologic prediction and water resource applications in the NAME Tier 1 core area 1 Francisco Munoz-Arriola, 1 Shraddhanand Shukla, 1 Theodore Bohn, 2 Andrea Ray, 3 Rene Labato Sanchez, 3 Ana Wagner Gomes, and 1 Dennis P. Lettenmaier 1) Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, ) NOAA Earth System Research Laboratory, Boulder, CO 3) Instituto Mexicano de Tecnología del Agua, Jiutepec, Morelos, Mexico Over half of the annual precipitation over the southwestern United States and northwestern Mexico (essentially the NAME Tier 1 core area) occurs during the summer, and is critical to determining the availability and allocation of the region’s water resources. Although seasonal hydrologic predictions could improve the efficiency of water use substantially, advanced hydrologic prediction methods are not widely used in this area, primarily because predictability is thought to be low. In an attempt to evaluate the potential for the use of climate forecasts in connection with water supply in the region, the University of Washington West-wide Seasonal Hydrological Prediction System (WSHPS) has been extended southward into Mexico. UWWHS uses simulated hydrological variables produced by the Variable infiltration Capacity (VIC) macroscale hydrology model, which we currently run in near real-time. In its implementation within WSHPS, VIC is forced by current precipitation, maximum and minimum temperature, and wind speed. These hydrological outputs represent the initial conditions used for Ensemble Streamflow Predictions (ESP). ESP is based on resampling of ensemble members (VIC forcings) from a 40-year climatology, which produce 40 soil moisture, runoff and streamflow ensemble members. Over the Tier 1 core area of the North American Monsoon System WHSPS produces a near-real-time display of the surface hydrological condition, while twice a month produces a complete one-year led streamflow forecast, including spatial distribution of hydrological conditions. Here, we assess hydrologic predictability during the 2007 and 2008 winter and monsoon months. Forecasted runoff and soil moisture percentile spatial distributions as well as streamflow forecasts are compared with modeled values obtained from the simulations forced by observed meteorological conditions. Results show agreement in the area of influence of the North American Monsoon System in a wet year such as 2008 and a drier year such as Future developments will allow us to evaluate ESP-based forecasts in comparison with Climate Forecast System-based forecasts, with the aim of improving hydrologic forecast reliability in the NAME Tier 1 core area. Extended Domain References Wood, A.W. and D.P. Lettenmaier, 2006: A testbed for new seasonal hydrologic forecasting approaches in the western U.S., Bulletin of the American Meteorological Society, 87(12), , doi: /BAMS Zhu C.M. and D.P. Lettenmaier, 2007:Long-term climate and derived surface hydrology and energy flux data for Mexico, , Journal of Climate, 20, Methods The WSHPS produces hydrological nowcasts for the US and Mexico. Over Mexico the forecast system currently uses the Ensemble Streamflow Prediction (ESP). We are working with Princeton University to implement ensemble forecasts based on the Climate Forecast System (CFS) over Mexico. Hydrological forecasts are produced twice a month (every 1 st and 15 th of the month) for one year lead times for soil moisture, runoff, and evapotranspiration on a monthly basis. We also generate naturalized streamflow forecasts at 23 stations in Mexico, half of which are located in the Tier 1 core area. The present experiment shows the forecast reliability for a winter and a monsoon months during 2007 and While monsoon months represent more than 50% of the annual precipitation in the Tier1 core area of the NAMS, winter precipitation has a significant impact on agriculture due to its contribution to the water storage and the agricultural activities in the region. The water stored during these months dictates the agricultural practices during the summer. The WSHPS produces seasonal forecasts twice monthly using the Ensemble Streamflow Prediction (ESP) method applied to the Variable Infiltration Capacity (VIC) macroscale hydrology model. Forty streamflow ensemble members represent forecast scenarios for different stations located over 15 basins in Mexico. ESP ensembles are produced by VIC forced climatological data from 1960 to Key aspects of the implementation include: The initial hydrologic state (at forecast time) is provided by the VIC nowcast. The nowcast operates by retrieving precipitation and temperature data from more than 800 meteorological stations over Mexico (provided by the Servicio Meteorologico Nacional). When the station data are not available, we substitute NCEP NDAS and/or NARR data. Hydrological outputs are post-processed (as percentiles and means) and are provided as numeric data and plot formats that are available on the web ( Predicted soil moisture percentiles are calculated at 1-, 2-, and 3-month leading times. For this experiment we used February initial conditions and 1-month leading percentiles to assess March. For the forecast assessment during August we initialize the system in May and July and use the 3-month and 1- month leading percentiles, respectively. Interannual and Intraseasonal Hydrological Forecasts Conclusions Initial conditions play an important role in the reliability of hydrological forecasts in the Tier 1 core area of NAMS. The impact of initial conditions varies according to the season. During winter the effect of initial conditions is relatively small. However, during monsoon months, the availability of moisture is more important and its absence produced soil moisture percentiles patterns of variability influenced by the climatology. During winter and summer the hydrological forecasts are also influenced by the availability of soil moisture in the system and influences the performance of the UW-west wide forecast system. Abstract Hydrological Forecast Operation Initial conditions for February, May, and July 2007 were consistently wetter than those in 2008 in the Tier 1 core area of NAMS. In general, the forecasted soil moisture percentiles between both years show a relatively small effect of initial conditions over the monsoon domain. Areas in northeastern Sonora and southeastern Chihuahua showed the largest differences, while the magnitudes and spatial patterns were more similar for the rest of the domain. For the assessment of forecast soil moisture percentiles in August we initialized the forecast in May (pre monsoonal drought and 3-month lead percentile) and July (monsoon precipitation peak and 1-month lead percentile). Here, we observed that initial conditions in 2007 contributed to obtain better hydrological forecasts. In this case, soil moisture played a major role in the dynamics of the hydrological cycle due to the availability of water provided by the wet conditions. However, the observed patterns in 2007 show in general an over-estimation of the soil moisture percentiles for August. For 2008, the reduced availability of water due to dry conditions (as observed in May and July initial conditions) makes the soil moisture percentiles more sensitive to the soil moisture climatological values. This produces similar soil moisture percentile patterns in the northern part of the Tier 1 core area of NAMS no matter the leading time applied. winter monsoon Initial Conditions Monsoon Predicted Percentiles Winter Predicted Percentiles Observed Percentiles Acknowledgments Funding for this study was provided by CPPA NA060AR , "*Intraseasonal-to-Interannual hydrologic prediction and water resource applications in the NAME Tier 1 core area".