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Actual evaporation (Ea) can be calculated as a fraction of potential evaporation (PE), which refers to the evaporation rate if supply water is unlimited. Potential evaporation depends on the available energy and the underlying material, and different approaches to estimate potential evaporation exist nowadays. This study provides a detailed analysis of the evaporation dynamics over fully saturated, sandy soil (PEs) and an open water surface (PEw). Moreover, the performance of commonly used methods to estimate PE is assessed. At the basis of these analyses is a lysimeter experiment in the Guanzhong Basin, China, which allowed a precise measurement of PE with a very high temporal resolution. Temperature profiles in lysimeters and meteorological data were also measured during the experiment. A comparison of PEs and PEw was carried out for seven consecutive days (August 11th to 17th, 2016). Results show that PEw is smaller than PEs on a daily scale, with PEw rates being bigger than PEs at night but smaller during daytime. Furthermore, the temporal dynamics of PEw lags 4–5 h behind PEs. In accordance with the energy balance equation, PE dynamics are mainly governed by “available energy”. The PE rates calculated by Penman-Monteith (PM) and Priestly-Taylor (PT) based on these measurements were also evaluated. The measured PE is relatively well reproduced by PM and PT equations. Finally, the effect of using different approaches to estimate PE on calculating Ea was tested by an integrated hydrological model that calculates water flow in the unsaturated zone by solving the Richards equation. The relative differences were up to 17.5%.

[EN] Irrigated agriculture is very important for securing food production for an increasing population over the next decades. Given scarcity of water resources, optimal irrigation management is needed to reduce water while realizing maximal crop productivity. The new method of integrating soil water content measurements and the Community Land Model (CLM) using sequential data assimilation (DA) is promising to improve the prediction of soil water status and efficiently design irrigation strategies. Soil water content measured by FDR (Frequency Domain Reflectometry) was assimilated into CLM by LETKF (Local Ensemble Transform Kalman Filter) to improve model predictions. Atmospheric input data from GFS (Global Forecast System) were used to force CLM in order to predict short-term soil water contents. The irrigation amount was then calculated on the basis of the difference between predicted and targeted soil water content over the root zone. During the real-time irrigation campaigns in Picassent (Spain) in 2015 and 2016, there were 6 fields irrigated according the data assimilation-optimization approach (CLM-DA), 2 further fields according the FAO (Food and Agriculture Organization) water balance method and also 2 fields traditionally according the farmers preference. The required amount of irrigation water for each citrus field was applied by SCADA (supervisory control and data acquisition system). Compared with the traditionally irrigated fields by farmers, 24% less irrigation water was needed for the CLM-DA scheduled fields averaged over both years from July to September, while the FAO fields were irrigated with 22% less water. Stem water potential data and soil moisture recordings of the CLM-DA scheduled fields did not indicate significant water stress during the irrigation period. The CLM-DA scheduled fields received less irrigation water than traditionally irrigated fields, but the orange production was not significantly suppressed. Overall, our results show that the CLM-DA method is attractive given its water saving potential and automated approach, ease of incorporation of on-line measurements and ensemble based predictions of soil moisture evolution., The first author of this paper was funded by a stipend from the Government of China (CSC scholarship). The support of the super computing facilities of Forschungszentrum Juelich (JURECA) is gratefully acknowledged. We are also thankful to our colleagues in IVIA and Universitat Politecnica de Valencia for the installation of soil moisture sensors and conducting stem water potential measurements.

[EN] Real-time data from on-line sensors offer the possibility to update environmental simulation models in real-time. Information from on-line sensors concerning contaminant concentrations in groundwater allow for the real-time characterization and control of a contaminant plume. In this paper it is proposed to use the CPU-efficient Ensemble Kalman Filter (EnKF) method, a data assimilation algorithm, for jointly updating the flow and transport parameters (hydraulic conductivity and porosity) and state variables (piezometric head and concentration) of a groundwater flow and contaminant transport problem. A synthetic experiment is used to demonstrate the capability of the EnKF to estimate hydraulic conductivity and porosity by assimilating dynamic head and multiple concentration data in a transient flow and transport model. In this work the worth of hydraulic conductivity, porosity, piezometric head, and concentration data is analyzed in the context of aquifer characterization and prediction uncertainty reduction. The results indicate that the characterization of the hydraulic conductivity and porosity fields is continuously improved as more data are assimilated. Also, groundwater flow and mass transport predictions are improved as more and different types of data are assimilated. The beneficial impact of accounting for multiple concentration data is patent. © 2012 Elsevier B.V., The authors gratefully acknowledge the financial support by ENRESA (Project 0079000029) and the Spanish Ministry of Science and Innovation (Project CGL2011-23295). Extra travel Grants awarded to the first and second author by the Ministry of Education (Spain) are also acknowledged. Dr. Jichun Wu and an anonymous reviewer are grateful acknowledged for their comments which helped improving the final version of the manuscript.

This paper focuses on the role of heat transport in river-aquifer interactions for the study area Hardhof located in the Limmat valley within the city of Zurich (Switzerland). On site there are drinking water production facilities of Zurich water supply, which pump groundwater and infiltrate bank filtration water from river Limmat. The artificial recharge by basins and by wells creates a hydraulic barrier against the potentially contaminated groundwater flow from the city.A three-dimensional finite element model of the coupled variably saturated groundwater flow and heat transport was developed. The hydraulic conductivity of the aquifer and the leakage coefficient of the riverbed were calibrated for isothermal conditions by inverse modelling, using the pilot point method. River-aquifer interaction was modelled using a leakage concept. Coupling was considered by temperature-dependent values for hydraulic conductivity and for leakage coefficients. The quality of the coupled model was tested with the help of head and temperature measurements. Good correspondence between simulated and measured temperatures was found for the three pumping wells and seven piezometers. However, deviations were observed for one pumping well and two piezometers, which are situated in an area, where zones with important hydrogeological heterogeneity are expected. A comparison of simulation results with isothermal leakage coefficients with those of temperature-dependent leakage coefficients shows that the temperature dependence is able to reduce the head residuals close to the river by up to 30%. The largest improvements are found in the zone, where the river stage is considerably higher than the groundwater level, which is in correspondence with the expectations.Additional analyses also showed that the linear leakage concept cannot reproduce the seepage flux in a downstream section during flood events. It was found that infiltration is enhanced during flood events, which is attributed to additional infiltration areas. (C) 2010 Elsevier B.V. All rights reserved.