This paper presents management of groundwater resource using a Bayesian Decision Network (BDN). The Kordkooy region in North East of Iran has been selected as study area. The region has been sub-divided into three zones based on transmissivity (T) and electrical conductivity (EC) values. The BDN parameters: prior probabilities and Conditional Probability Tables -CPTs) have been identified for each of the three zones. Three groups of management scenarios have been developed based on the two decision variables including "Crop pattern" and "Domestic water demand" across the three zones of the study area: 1) status quo management for all three zones represent current conditions; 2) the effect of change in cropping pattern on management endpoints and 3) the effect of future increased domestic water demand on management endpoints. The outcomes arising from implementing each scenario have been predicted by use of the constructed BDN for each of the zones. Results reveal that probability of drawdown in groundwater levels of southern areas is relatively high compared with other zones.Groundwater withdrawal from northern and northwestern areas of the study area should be limited due to the groundwater quality problems associated with shallow groundwater of these two zones. The ability of the Bayesian Decision Network to take into account key uncertainties in natural resources and perform meaningful analysis in cases where there is not a vast amount of information and observed data available -and opportunities for enabling inputs for the analysis based partly on expert elicitation, emphasizes key advantages of this approach for groundwater management and addressing the groundwater related problems in a data-scarce area.

Soil and water resources are affected by land use changes such as land abandonment in vineyards. Changes in water resources and soil water dynamics can result in sudden alterations in erosion rates and trigger land degradation. In this study, we examined the impact of land abandonment on soil properties and hydrological processes in two paired plots: an active and an abandoned vineyard. Laboratory analyses were performed to assess texture, antecedent soil moisture, stoniness, soil water content, and organic matter (OM). A Guelph permeameter was used to quantify the permeability (Per) and saturated hydraulic conductivity (Kfs) at different slope positions and seasons (before and after harvest). Results showed that soil texture and OM were highly modified, and as consequence soil hydrology, after abandonment. We observed a significantly higher Per (26.8 mm h −1 ) and Kfs (8.4 mm h −1 ) in the active vineyard soil than in the abandoned one (Per of 14.2 mm h −1 and a Kfs of 5.4 mm h −1 ). The soils of the active vineyard showed a greater variability among seasons and slope positions. In the abandoned vineyard, the results showed a high correlation of Per and Kfs with gravel content and OM and a negative correlation with the clay fraction. Natural revegetation improved the soil water retention capacity. In the active vineyard, we could not find any relevant factor to explain the soil hydrological properties, and this may be attributed to the disturbance induced by human activities, such as machinery, trampling, and the use of herbicides.

Soil hydraulic properties, which are basically saturated and unsaturated hydraulic conductivity and water retention characteristics, remarkably control the main hydrological processes in catchments. Thus, adequate parameterization of soils is one of the most important tasks in physically based catchment modeling. To estimate these properties, the choice of the PTFs in a hydrological model is often made without taking the runoff characteristics of the catchment into consideration. Therefore, this study introduces a methodology to analyze the sensitivity of a catchment water balance model to the choice of the PTF. To do so, we define 11 scenarios including different combinations of PTFs to estimate the van Genuchten parameters and saturated hydraulic conductivity. We use a calibrated/validated hydrological model (WaSiM-ETH) as a baseline scenario. By altering the underlying PTFs, the effects on the hydraulic properties are quantified. Moreover, we analyze the resulting changes in the spatial/temporal variation of the total runoff and in particular, the runoff components at the catchment outlet. Results reveal that the water distribution in the hydrologic system varies considerably amongst different PTFs, and the water balance components are highly sensitive to the spatial structure of soil hydraulic properties. It is recommended that models be tested by careful consideration of PTFs and orienting the soil parameterization more towards representing a plausible hydrological behavior rather than focusing on matching the calibration data.

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Evapotranspiration is often estimated by numerical simulation. However, to produce accurate simulations, these models usually require on-site measurements for parameterization or calibration. We have to make sure that the model realistically reproduces both, the temporal patterns of soil moisture and evapotranspiration. In this study, we combine three sources of information: (i) measurements of sap velocities; (ii) soil moisture; and (iii) expert knowledge on local runoff generation and water balance to define constraints for a "behavioral" forest stand water balance model. Aiming for a behavioral model, we adjusted soil moisture at saturation, bulk resistance parameters and the parameters of the water retention curve (WRC). We found that the shape of the WRC influences substantially the behavior of the simulation model. Here, only one model realization could be referred to as "behavioral". All other realizations failed for a least one of our evaluation criteria: Not only transpiration and soil moisture are simulated consistently with our observations, but also total water balance and runoff generation processes. The introduction of a multi-criteria evaluation scheme for the detection of unrealistic outputs made it possible to identify a well performing parameter set. Our findings indicate that measurement of different fluxes and state variables instead of just one and expert knowledge concerning runoff generation facilitate the parameterization of a hydrological model.