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  • 1
    Language: English
    In: Journal of Hydrology, 2011, Vol.397(1), pp.1-9
    Description: ► Lysimeter data were analysed using Genetic Programming (GP). ► A simple model was recurrently evolved in multiple GP runs. ► GP model supported structure of a hydrological model that was published earlier. Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.
    Keywords: Data Mining ; Machine Learning ; Diagnostic Model Evaluation ; Model Structure Uncertainty ; Parsimonious Inductive Model ; Data-Based Modelling ; Dominant Process Concept ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 2
    Language: English
    In: Journal of Hydrology, 12 April 2013, Vol.486, pp.31-38
    Description: ► We studied patterns of scores for a principal component analysis of water quality. ► Association of principal component scores with supplementary data was analyzed. ► Catchment processes governing water quality were identified and localized. The analysis of spatial–temporal patterns of scores, including their association with supplementary data, can refine a principal component analysis of water quality data. We hypothesized that this type of analysis could considerably improve the understanding of processes governing water quality at catchment scales. To test this, water quality data from the 180 km Ammer catchment in south-western Germany was investigated using principal component analysis. We analyzed data for (a) surface water from the Ammer River and its tributaries, (b) spring water from the main aquifers and (c) deep groundwater from wells. Using the analysis of scores, we found that the quality of both surface and groundwater primarily reflected the input of solutes determined by land use and geology. For water quality in the Ammer catchment, the conservative mixing of water of different origins and ages was more important than reactive transport processes along the flow paths. These results demonstrate the potential of our analysis of principal component scores to identify dominant processes at catchment scales.
    Keywords: Hydrogeochemistry ; Multivariate Statistics ; Watershed ; Groundwater Surface Water Interaction ; Dominant Process Concept ; End Member Mixing Analysis ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 3
    Language: English
    In: Geoderma, 2011, Vol.160(3), pp.569-578
    Description: Deep percolation under irrigation is often indirectly estimated from Richards' equation models. A Richards' equation model requires soil hydraulic and crop specific parameters that may be estimated from soil moisture data at different soil depths. This paper examined whether parameters of a Richards' equation model estimated from soil moisture data can be used to adequately predict deep percolation under surface irrigation. For this purpose, we used data from a lysimeter experiment on a loam soil under surface irrigation. Monte Carlo simulations of a 1-D Richards' equation model were generated using a set of model parameters sampled from a feasible range of parameter values. For each Monte Carlo simulation (a set of model parameters), adequacy of model predictions was evaluated against lysimeter data on soil moisture and independently measured deep percolation. Adequacy was assessed by fitting a linear regression of observed data on simulated values and testing for the null hypotheses of unit slope and zero intercept. Using this approach, we did not succeed in predicting simultaneously soil moisture and deep percolation. This lack of simultaneous fit likely indicates an inadequate model structure as data uncertainty was of secondary importance in our lysimeter study. For surface irrigation, preferential infiltration can probably not be avoided even when soil cracking is not apparent. Under such conditions, the use of a simple Richards' equation model appears inadequate. A conceptual model that was published earlier is considered to be more appropriate as it adequately predicted deep percolation, effectively accounts for preferential infiltration during surface irrigation and required less data than the Richards' equation model. ► We simulated water flow in surface irrigated lysimeter using Richards' equation model. ► Model parameters were simultaneously fitted to soil moisture and deep percolation. ► A lack of simultaneous fit indicated an inadequate model structure.
    Keywords: Deep Drainage ; Groundwater Recharge ; Model Adequacy ; Soil Hydrology ; Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 4
    In: Global Change Biology, May 2017, Vol.23(5), pp.1891-1901
    Description: Reductions in emissions have successfully led to a regional decline in atmospheric nitrogen depositions over the past 20 years. By analyzing long‐term data from 110 mountainous streams draining into German drinking water reservoirs, nitrate concentrations indeed declined in the majority of catchments. Furthermore, our meta‐analysis indicates that the declining nitrate levels are linked to the release of dissolved iron to streams likely due to a reductive dissolution of iron() minerals in riparian wetland soils. This dissolution process mobilized adsorbed compounds, such as phosphate, dissolved organic carbon and arsenic, resulting in concentration increases in the streams and higher inputs to receiving drinking water reservoirs. Reductive mobilization was most significant in catchments with stream nitrate concentrations 〈6 mg L. Here, nitrate, as a competing electron acceptor, was too low in concentration to inhibit microbial iron() reduction. Consequently, observed trends were strongest in forested catchments, where nitrate concentrations were unaffected by agricultural and urban sources and which were therefore sensitive to reductions of atmospheric nitrogen depositions. We conclude that there is strong evidence that the decline in nitrogen deposition toward pre‐industrial conditions lowers the redox buffer in riparian soils, destabilizing formerly fixed problematic compounds, and results in serious implications for water quality.
    Keywords: Atmospheric Deposition ; Carbon Cycle ; Nitrogen Biogeochemistry ; Organic Matter ; Riparian Zone ; Streamwater Chemistry
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 5
    In: Groundwater, April 2015, Vol.53(S1), pp.156-165
    Description: For karstified aquifer systems, numerical models of groundwater flow are difficult to setup and parameterize. However, a system understanding useful for groundwater management may be obtained without applying overly complicated models. In this study, we demonstrate for a karstified carbonate aquifer in south‐western Germany that a combination of methods with moderate data requirements can be used to infer flowpaths and transit times of groundwater to production wells.
    Keywords: Aquifers – Analysis ; Aquifers – Environmental Aspects ; Tracers (Biology) – Analysis ; Tracers (Biology) – Environmental Aspects ; Groundwater Flow – Analysis ; Groundwater Flow – Environmental Aspects ; Groundwater – Analysis ; Groundwater – Environmental Aspects;
    ISSN: 0017-467X
    E-ISSN: 1745-6584
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  • 6
    Language: English
    In: Environmental Monitoring and Assessment, 2016, Vol.188(2), pp.1-12
    Description: As field data on in-stream nitrate retention is scarce at catchment scales, this study aimed at quantifying net retention of nitrate within the entire river network of a fourth-order stream. For this purpose, a practical mass balance approach combined with a Lagrangian sampling scheme was applied and seasonally repeated to estimate daily in-stream net retention of nitrate for a 17.4 km long, agriculturally influenced, segment of the Steinlach River in southwestern Germany. This river segment represents approximately 70 % of the length of the main stem and about 32 % of the streambed area of the entire river network. Sampling days in spring and summer were biogeochemically more active than in autumn and winter. Results obtained for the main stem of Steinlach River were subsequently extrapolated to the stream network in the catchment. It was demonstrated that, for baseflow conditions in spring and summer, in-stream nitrate retention could sum up to a relevant term of the catchment’s nitrogen balance if the entire stream network was considered.
    Keywords: Nitrate retention ; In-stream processes ; Mass balance approach ; Stream network ; Catchment scale
    ISSN: 0167-6369
    E-ISSN: 1573-2959
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  • 7
    In: Global Change Biology, September 2017, Vol.23(9), pp.e5-e6
    Description: Increasing concentrations of dissolved iron and DOC are likely linked to decreasing nitrogen depositon.
    Keywords: Atmospheric Deposition ; Carbon Cycle ; Nitrogen Biogeochemistry ; Organic Matter ; Riparian Zone ; Water Quality
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 8
    Language: English
    In: Environmental Modelling and Software, 2010, Vol.25(8), pp.919-926
    Description: Catchment models simulate water and solute dynamics at catchment scales and are invaluable tools for natural resource management. Parameters for catchment models can provide useful information about the importance of the hydrological processes involved. We propose and demonstrate a bootstrap approach to assess parameter uncertainty in dynamic catchment models. This approach, which is non-Bayesian and essentially non-parametric, requires no distributional assumptions about parameters and only weak assumptions about the distributional form of the model residuals. It is able to handle autocorrelated model errors which are very common in the application of dynamic hydrological models at catchment scales. The ability of our bootstrap approach to assess parameter uncertainty is demonstrated using numerical experiments with the hydrological model and an application of a conceptual model of salt load from an irrigated catchment in southeastern Australia.
    Keywords: Conceptual Rainfall-Runoff Modelling ; Conceptual Catchment Models ; Parameter Calibration ; Model Calibration ; Bayesian Inference ; Engineering ; Environmental Sciences ; Computer Science ; Ecology
    ISSN: 1364-8152
    E-ISSN: 1873-6726
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  • 9
    In: Hydrological Processes, 15 June 2016, Vol.30(12), pp.1824-1835
    Description: Adequate irrigation inputs are essential for the application of hydrological models in irrigated catchments, but reliable data on both the amount and the frequency of irrigation applications are often missing at an appropriate spatial scale. In this paper, we demonstrate and test approaches to estimate irrigation inputs for distributed hydrological modelling. In this context, the Soil and Water Assessment Tool was applied to simulate water balances for an irrigated catchment in southeast Australia during the period 2008–2010. Two methods for estimating irrigation inputs were tested. One method was based on a fixed irrigation application rate, whereas the other one had variable irrigation rates depending on season and the irrigated crop. These two approaches were also compared with the ‘auto‐irrigation’ method within the Soil and Water Assessment Tool model. The method with variable irrigation rates resulted in the most reasonable interpretation of the readily available irrigation data, consistent estimates of irrigation runoff coefficients throughout the year and the best fit to observed data on both drain flows at the catchment outlet and spatial evapotranspiration patterns. We also found that the different irrigation inputs significantly affected simulated water balances, in particular deep percolation under relatively dry climatic conditions. All these results suggest that it is possible to infer irrigation inputs from readily available data and local knowledge, adequate for hydrological modelling in irrigated catchments. Our study also demonstrates that, in order to predict reliable water balances in irrigated catchments, an accurate knowledge of irrigation scheduling and irrigation runoff is required. Copyright © 2015 John Wiley & Sons, Ltd.
    Keywords: Swat ; Irrigation Runoff ; Remotely Sensed Evapotranspiration
    ISSN: 0885-6087
    E-ISSN: 1099-1085
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  • 10
    Language: English
    In: Environmental Earth Sciences, 2013, Vol.69(2), pp.469-477
    Description: Over the course of hydrological research projects often a large number of heterogeneous data sets are acquired from sources as diverse as boreholes, gauging stations or satellite imagery. This data then need to be integrated into models for the simulation of hydrological processes. We propose a framework for exploration of geoscientific data and visually guided preparation of such models. Data sets from a large number of sources can be imported, combined and validated to avoid potential problems due to artefacts or inconsistencies between data sets in a subsequent simulation. Boundary conditions and domain discretisations for surface and subsurface models can be created and tested regarding criteria indicating possible numerical instabilities. All data sets including simulation results can be integrated into a user-controlled 3D scene and aspects of the data can be enhanced using a number of established visualisation techniques including thresholding and user-defined transfer functions. We present the application of this framework for the preparation of a model for simulation of groundwater flow in a river catchment in southwest Germany investigated in the scope of the WESS project.
    Keywords: Data exploration ; Hydrology ; Simulation ; Visualisation ; OpenGeoSys
    ISSN: 1866-6280
    E-ISSN: 1866-6299
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