Abstract. Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS) data have been recognized as an alternative to in-situ hydrometeorological data in remote and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models.In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modeling approach based entirely on RS and reanalysis data: precipitation was obtained from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), temperature from the European Centre for Medium-Range Weather Forecast's (ECMWF) Operational Surface Analysis dataset and reference evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat) measurements of reservoir water levels. The modeling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several large reservoirs and scarce hydrometeorological data that is located in Central Asia and shared between 4 countries with conflicting water management interests.Correspondence to: P. Bauer-Gottwein (pbau@env.dtu.dk)The modeling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar altimetry data significantly improved the performance of the hydrological model. Without assimilation of radar altimetry data, model performance was limited, probably because of the size and complexity of the model domain, simplifications inherent in model design, and the uncertainty of RS and reanalysis data. Altimetry data assimilation reduced the mean absolute error of the simulated reservoir water levels from 4.7 to 1.9 m, and overall model RMSE from 10.3 m to 6.7 m. Model performance was variable for the different reservoirs in the system. The RMSE ranged from 10% to 76% of the mean seasonal reservoir level variation.Because of its easy accessibility and immediate availability, radar altimetry lends itself to being used in real-time hydrological applications. As an impartial source of information about the hydrological system that can be updated in real time, the modeling approach described here can provide useful medium-term hydrological forecasts to be used in water resources management.

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American Society of Civil Engineers Riegels, N.; Pulido-Velazquez, M.; Doulgeris, C.; Sturm, V.; Jensen, R.; Moller, F.; BauerGottwein, P. (2013) Under the first approach, all wholesale water users in a river basin face the same volumetric 26 price for water. This water price does not vary in space or in time, and surface water and 27 groundwater are priced at the same rate. Under the second approach, surface water is priced 28 using a volumetric price, while groundwater use is controlled through adjustments to the price of 29 energy, which is assumed to control the cost of groundwater pumping. For both approaches, 30 optimization is used to identify optimal prices, with the objective of maximizing welfare while 31 reducing human water use in order to meet constraints associated with EU WFD ecological and 32 groundwater sustainability objectives. The second pricing policy, in which the energy price is 33 used as a surrogate for a groundwater price, shifts a portion of costs imposed by higher water 34 prices from low value crops to high value crops and from small urban/domestic locations to 35 larger locations. Because growers of low value crops will suffer the most from water price 36 increases, the use of energy costs to control groundwater use offers the advantage of reducing 37 this burden. 38

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