Abstract: Groundwater fluxes in tidal marshes largely control key ecosystem functions and services, such as vegetation growth, soil carbon sequestration, and nutrient cycling. In tidal marshes restored on formerly embanked agricultural land, groundwater fluxes are often limited as compared to nearby natural marshes, as a result of historical agricultural soil compaction. To improve the functioning of restored tidal marshes, knowledge is needed on how much certain design options can optimize soil-groundwater interactions in future restoration projects. Based on measured data on soil properties and tidally induced groundwater dynamics, we calibrated and evaluated a 2D vertical model of a creek-marsh cross-section, accounting for both saturated and unsaturated groundwater flow and solute transport in a variably saturated groundwater flow model. We found that model simulations of common restoration practices such as soil amendments (increasing the depth of porous soil on top of the compact layer) and creek excavation (increasing the creek density) increase the soil aeration depth and time, the drainage depth and the solute flux, and decrease the residence time of solutes in the porewater. Our simulations indicate that increasing the depth to the compact layer from 20 cm to 40 cm, or increasing the creek density from 1 creek to 2 creeks along a 50 m marsh transect (while maintaining the total creek cross-sectional area), in both cases more than doubles the volume of water processed by the marsh soil. We discuss that this may stimulate nutrient cycling. As such, our study demonstrates that groundwater modelling can support the design of marsh restoration measures aiming to optimize groundwater fluxes and related ecosystem services.

Abstract: A quasi 3D modelling approach was developed by integrating a crop growth (LINGRA-N) and a hydrological model (Hydrus-1D) to simulate and visualize water flow, soil-water storage, water stress and crop yield over a heterogeneous sandy field. We assessed computational efficiency and uncertainty with low to high-spatial resolution input factors (soil-hydraulic properties, soil-layer thickness and groundwater level) and evaluated four irrigation scenarios (no, current, optimized and triggered) to find the optimal and cost-effective irrigation scheduling. Numerical results showed that the simulation uncertainty was reduced when using the high-resolution information while a fast performance was maintained. The approach accurately determined the field scale irrigation requirements, taking into account spatial variations of input information. Optimal irrigation scheduling is obtained by triggered-irrigation resulting in saving up to similar to 300% water as compared to the current-irrigation, while yield increased similar to 1%. Overall, the approach can be useful to help decision makers and applicants in precision farming. (C) 2017 Published by Elsevier Ltd.

Abstract: Monitoring and modelling tools may improve irrigation strategies in precision agriculture. We used non-invasive soil moisture monitoring, a crop growth and a soil hydrological model to predict soil water content fluctuations and crop yield in a heterogeneous sandy grassland soil under supplementary irrigation. The sensitivity of the soil hydrological model to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed after integrating models. Free drainage and incremental constant head conditions were implemented in a lower boundary sensitivity analysis. A time-dependent sensitivity analysis of the hydraulic parameters showed that changes in soil water content are mainly affected by the soil saturated hydraulic conductivity K-s and the Mualem-van Genuchten retention curve shape parameters n and alpha. Results further showed that different parameter optimization strategies (two-, three-, four- or six-parameter optimizations) did not affect the calculated water stress and water content as significantly as does the bottom boundary. In this case, a two-parameter scenario, where K-s was optimized for each layer under the condition of a constant groundwater depth at 135-140 cm, performed best. A larger yield reduction, and a larger number and longer duration of stress conditions occurred in the free drainage condition as compared to constant boundary conditions. Numerical results showed that optimal irrigation scheduling using the aforementioned water stress calculations can save up to 12-22 % irrigation water as compared to the current irrigation regime. This resulted in a yield increase of 4.5-6.5 %, simulated by the crop growth model.

Abstract: Field water flow processes can be precisely delineated with proper sets of soil hydraulic properties derived from in situ and/or laboratory experiments. In this study we analyzed and compared soil hydraulic properties obtained by traditional laboratory experiments and inverse optimization tension infiltrometer data along the vertical direction within two typical Podzol profiles with sand texture in a potato field. The main goal was to identify proper sets of hydraulic parameters and to evaluate their relevance on hydrological model performance for irrigation management purposes. Tension disc infiltration experiments were carried out at four and five different depths for both profiles at consecutive negative pressure heads of 12, 6, 3 and 0.1 cm. At the same locations and depths undisturbed samples were taken to determine Mualem-van Genuchten (MVG) hydraulic parameters (theta(r), residual water content, theta(s), saturated water content, alpha and n, shape parameters and K-ls, saturated hydraulic conductivity) in the laboratory. Results demonstrated horizontal differences and vertical variability of hydraulic properties. The tension disc infiltration data fitted well in inverse modeling using Hydrus 2D/3D in combination with final water content at the end of the experiment, theta(f). Four MVG parameters (theta(s), alpha, n and field saturated hydraulic conductivity K-fs) were estimated (theta(r) set to zero), with estimated K-ls and alpha values being relatively similar to values from Wooding's solution which used as initial value and estimated theta(s) corresponded to (effective) field saturated water content, theta(f). The laboratory measurement of K-ls yielded 2-30 times higher values than the field method K-fs from top to subsoil layers, while there was a significant correlation between both K-s values (r = 0.75). We found significant differences of MVG parameters theta(s), n and alpha values between laboratory and field measurements, but again a significant correlation was observed between laboratory and field MVG parameters namely K-s, n, theta(s) (r >= 0.59). Assessment of the parameter relevance in 1-D model simulations, illustrated that the model over predicted and under predicted top soil-water content using laboratory and field experiments data sets respectively. The field MVG parameter data set resulted in better agreement to observed soil-water content as compared to the laboratory data set at nodes 10 and 20 cm. However, better simulation results were achieved using the laboratory data set at 30-60 cm depths. Results of our study do not confirm whether laboratory or field experiments data sets are most appropriate to predict soil water fluctuations in a complete soil profile, while field experiments are preferred in many studies. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: A spatially distributed model for leaching of Cd from the unsaturated zone was developed for the Belgian-Dutch transnational Kempen region. The model uses as input land-use maps, atmospheric deposition data, and soil data and is part of a larger regional model that simulates transport of Cd in soil, groundwater, and surface water. A new method for deriving deposition from multiple sites was validated using soil data in different wind directions. Leaching was calculated for the period 1890 to 2010 using a reconstruction of metal loads in the region. The model was able to reproduce spatial patterns of concentrations in soil and groundwater and predicted the concentration in shallow groundwater adequately well for the purpose of evaluating management options. For 42% of the data points, measurements and calculations were within the same concentration class. The model was used for forecasting under a reference scenario, an autonomous development scenario including climate change, and a scenario with implementation of remediation measures. The impact of autonomous development (under the most extreme scenario of climatic change) amounted to an increase of 10% in cumulative Cd flux after 100 yr as compared with the reference scenario. The impact of remediation measures was mainly local and is less pronounced (i.e., only 3% change in cumulative flux at the regional scale). The integrated model served as a tool to assist in developing management strategies and prioritization of remediation of the wide-spread heavy metal contamination in the region.