1. Estimation of Groundwater Recharge in a Stony Soil Based on Monitoring of Soil Hydraulic Data Emerstorfer N., A. Klik and G. Kammerer Institute of Hydraulics and Rural Water Management Department of Water, Atmosphere and Environment University of Natural Resources and Applied Life Sciences, Vienna, Austria Contact: nicole.emerstorfer@boku.ac.at Introduction As pilot project, the Hydrographic Monitoring-Network of Unsaturated Zone in Austria equipped eight locations with sensors to measure soil temperature, soil water content θ (TDR) and soil water potential h (tensiometers and granular matrix sensors) in six depths up to 150 cm hourly. The aim of this study was: development of a method to gain time series of soil water content and corresponding matric potential based on field monitoring calculation of groundwater recharge application of this method to other locations in Austria Materials and Methods For demonstration of applicability one location in Styria (Kalsdorf near Graz) in the investigated period 2004 was selected. The upper layer of the soil (from 0 to 30 cm) is a sandy loam with 75 % of fine particles ( 30 cm) has more than 65 % rock fragments. 1. Filtering raw data for gaps and outliers 1. Times series of matric potential data (tensiometer and granular matrix sensors) were merged to close gaps in tensiometer data. 2. Set-up guidelines (e.g. elimination of: frost, tensiometer fillings, tensiometer values -100 hPa, etc.) → lead to the end matric potential. 2. Calculation of groundwater recharge 1. Determination of evapotranspiration was avoided by the assumption of zero flux at the soil surface during night periods without precipitation. 2. Calculation of the gradient of the total soil physical potential I at the two deepest measurement levels → change in profile water content (from θ-readings) divided by I (determined from the two lowermost tensiometers) → k unsat (h); Dataset of k unsat (h) and θ (h) was imported into the program RETC → closed functions for retention and hydraulic conductivity behaviour. Results 1. Filtering raw data for gaps and outliers Merging of tensiometer and granular matrix sensor data according to the set-up guidelines lead to distribution shown in Fig.2. Fig.1. View of the north (left) and soil profile (right) of the measurement site Kalsdorf Fig.2. Temporal distribution of precipitation, soil temperature, matric potential and soil water content in 30cm depth References VAN GENUCHTEN, LEIJ F. J. and YATES S. R., 1991. RETC: Code for Quantifying the Hydraulic Functions of Unsaturated Soil. US Salinity Laboratory USDA, ARS Recorded θ for greater measurement depths were similar to the values for 30 cm (Fig.2) in the range between 10 % and 15 %. Soil from the field was sieved and pacted into the soil column with the original partical size distibution and bulk density in five 15 cm layers (Fig.3). In each of the four intermediats two trase sensors horizontally and two tensiometers vertically were installed. Constant irrigation rate was applied to the surface and increased steepwise. h and θ values were recorded automatically. 2. Calculation of groundwater recharge Conclusions better calibration of the TDR sensors in the field required more replications of TDR sensors in each depth in a stony soil procedure has to be improved for stony soil Between constant irrigation steps the column could drain freely. From this period θ-values at the experiment were 10 % higher than field data for similar h-values (Fig.4). For comparison retention function determined with ROSETTA based on texture read out from a digital soil map (ebod) was plotted. Fig.3. Lab experiment (soil column) Fig.4. Retention curve of field data (black points) and experimental data (coloured points) in 30 cm depth Corresponding van-Genuchten parameters and saturated hydraulic conductivity k o were calculated with RETC (Van Genuchten, Leij and Yates, 1991) (Tab.1). Calculation yielded to an implausible height groundwater recharge. Experiments are going on. Tab.1. Soil parameter values in 150 cm depth