Hans-Georg Frede

Comparison of two different approaches of sensitivity analysis

Abstract Due to spatial variability, budget constraints or access difficulties model input parameters always are uncertain to some extent. Therefore the knowledge of sensitive input parameters is beneficial for model development and application. It can lead to a better understanding and to better estimated values and thus reduced uncertainty. In the present paper two simple approaches of sensitivity analysis are compared by the use of the physically based, continuous time hydrological model SWAT. In both approaches, one parameter is varied at a time while holding the others fixed, but the way of defining the range of variation is different. Similar results are obtained suggesting that parameter sensitivity may be determined without the results being influenced by the chosen method. Most sensitive parameters for hydrology and water quality are the physical soil properties such as bulk density, available water capacity or hydraulic conductivity. Plant specific parameters like maximum stomatal conductance or maximum leaf area index as well as slope length, slope steepness, and curve number also show a high sensitivity. Both approaches can be considered as equivalent, as they provide the same overall ranking into more and less sensitive parameters. An identification of the sensitive parameters is possible independently from the chosen variation range.

Hydrologic Response to land use changes on the catchment scale

Abstract Regional land use changes due to European market policy have far reaching consequences for various landscape functions. Among others land use change influences the local water balance. Simulation models are mostly used to analyse the effect of management practices on water quality but they can also be a useful tool to quantify the hydrologic response of a catchment to different land use options. In this study the physically based, continuous time step model SWAT mod has been applied within the joint research project SFB 299 at the Giessen University to support the development of sustainable land use concepts. In a first step the model has been calibrated and validated for four mesoscale watersheds with differing land use distributions. Then the model performance for changing land use has been tested in an artificial watershed with a single crop at one time and one underlying soil type to eliminate the complex interactions of natural watersheds. In relation to forest barley produced the strongest response of the water balance components. Finally a case study for the Dietzholze watershed with two land use scenarios derived with the ProLand model has been carried out. The impact of land use change on the annual water balance was relatively small due to compensating effects in a complex catchment. The decrease of forest due to a grassland bonus amplifies the peak flow rate and thus increases the risk of flooding.

Plant parameter values for models in temperate climates

Abstract Ecological, and especially hydrological models used to assess the effects of land cover changes require various input parameters for plants. Regional model applications rely on detailed information about the properties of the vegetation, especially if process-based approaches are chosen. As raising acceptable data is a time consuming issue, scientists often use globally approximated plant parameter ranges, rather than considering published data sets. The plant parameters summarised in this overview, i.e. albedo, interception capacity, maximum leaf area index, rooting depth, plant height and stomatal conductance, can be used as data for a wide range of published ecological and hydrological models. We concentrate on a presentation of values for temperate regions in order to list a manageable amount of data. Information on plant species is grouped into four main land cover types, crops, pasture (herbs, forbs, grasses), coniferous and deciduous trees. Overall, more than 1300 values for the described parameters have been gathered and present a solid data base for future applications. Further properties of species and sites, such as stand age, basal area, stock density, plant height, mean annual precipitation, mean annual temperature, coordinates and country are given, if available. In many cases of model applications scientists used parameter spans, with no further information or testing of the distribution of data. Twenty-two of the total of 26 data sets subsumed in this data base contained sufficient values to perform a Kolmogorov–Smirnov-test. Twenty of these 22 data sets are normally distributed. In order to investigate spatial differences, the data for stomatal conductance, leaf area index and interception capacity were grouped into North American and European land cover species. Significant differences could only be determined for the leaf area index of deciduous trees and pasture species between the continents.

Parameter uncertainty and the significance of simulated land use change effects

Abstract Uncertainty in parameters characterising different land covers leads to uncertainty in model predictions of land use change effects. In this study, a new approach is presented which allows a model to be assessed to see whether it is suitable for investigating land use change scenarios in the sense that different land covers can be significantly distinguished in their effects on model output. It consists of the following steps: (a) The uncertainty in land cover-dependent parameters is quantified. (b) The model of an artificial catchment with representative characteristics and uniform land cover is established. (c) Using this artificial catchment, Monte Carlo simulations are carried out to determine the uncertainty in the model response to different land covers. (d) By comparing the results for two covers, respectively, a dimensionless test statistic, the distinction level, is calculated. The distinction level is a normalised probability that two independent realisations of land covers which are parameterised within their range of natural uncertainty will yield distinct model responses. If the distinction level is greater than or equal to 90%, the land covers are assumed to have a significantly different effect on the model output. An example of the application of the new method is provided using the eco-hydrologic model SWAT-G. The land covers forest, pasture and arable land can be significantly distinguished by their long-term means of surface runoff, groundwater recharge and streamflow. The minimum proportion of the catchment area on which land cover must change in order to obtain significantly distinct model responses depends on the land covers involved and the considered hydrologic variable. In the case of a change between pasture and forest and with regard to average streamflow, this minimum proportion amounts to about 25%, a value that compares well with the results of paired catchment studies.

SWAT-G, a version of SWAT99.2 modified for application to low mountain range catchments

Abstract The Soil and Water Assessment Tool (SWAT) is a well established distributed eco-hydrologic model. However, using the example of a mesoscale catchment in Germany it is shown that the version SWAT99.2 is not able to correctly reproduce the runoff generation in a low mountain region. The calculated contribution of the baseflow to the streamflow is far too high whereas the interflow is strongly underestimated. Alternatively, the modified version SWAT-G can be used which, as is demonstrated in this paper, yields far better results for catchments with predominantly steep slopes and shallow soils over hard rock aquifers. In the example, calibrating the model over three hydrologic years of daily streamflow, the model efficiency increases from −0.17 to +0.76. The modifications in SWAT-G allow hydrological processes to be modelled in low mountain ranges while not restraining the applicability of the model to catchments with other characteristics.

Software, Data and Modelling News: CMF: A Hydrological Programming Language Extension For Integrated Catchment Models

Hydrological models are created for a wide range of scales and intents. The Catchment Modelling Framework (CMF) extends the Python programming language with hydrology specific language elements, to setup specific hydrological models adapted to the scientific problems and the dominant flow processes of a particular study area. CMF provides a straightforward method to test hydrological theories and serve as a transport module in integrated, interdisciplinary catchment model approaches.

Current concepts in nitrogen dynamics for mesoscale catchments

Abstract The study of global change impacts on nitrogen dynamics in mesoscale catchments remains an important topic. The primary mechanisms of change can be grouped broadly into those focused on land management, land use, climatic change, as well as on N deposition patterns. The current state of mesoscale studies of N dynamics is outlined in an effort to present the potential tools and methods available to researchers, as well as to outline future directions for additional research. This review focuses on a comparison of the common model approaches that are used to simulate the N cycle in catchments. The review is not meant as an exhaustive list of all models that might include N cycling, but instead outlines a classification framework as a means of better understanding key differences between common modelling strategies. We conclude with a blueprint of what hydro-biogeochemical models should be capable of, and which additional efforts should be considered in the course of model development and verification.

DRIPS—a DSS for estimating the input quantity of pesticides for German river basins

The GIS-based decision support system (DSS)—drainage runoff input of pesticides in surface water, DRIPS—has been developed on behalf of the German EPA (UBA) for exposure assessment of agriculturally used pesticides in surface waters. The tool estimates the quantity of pesticide input from non-point sources via surface runoff, tile drainage and spraydrift. Furthermore, the resulting predicted environmental concentration of pesticides in surface waters (PECsw) can be calculated considering the mean daily inputs of substances into river basins, characterized by their daily discharge. A graphical user interface (GUI) was created to provide users of the DSS with easy access to the model algorithms. Model parameters such as sorption (Koc), half-life (DT50), dose rate and application date of pesticides can be modified by the user in order to generate customized scenarios predicting PECsw for a choice of field crops, orchards or vineyards. Results are available as grid cell maps for the territory of Germany, featuring monthly catchment specific PECsw values.

Interdisciplinary modeling and the significance of soil functions

The coupling and integration of models from different disciplines to an interdisciplinary modeling network facilitates the simultaneous description of effects due to ecological, economical or legal changes of land management in selected areas of the natural environment. In all these models soils play a crucial role With their physical and chemical characteristics. In the Interdisciplinary Research Project Land use concepts for peripheral regions (Sonderforschungsbereich SFB 299) three mesoscale GIS-based models are developed and adapted to specific conditions of a low German mountain range: the comparative static economic model ProLand, the habitat models ANIMO, ELLA, and YELL, and the hydrological continuum model SWAT. As an example of the interdisciplinary model network, it is demonstrated how changes in land management due to increasing field size affect the landscape services natural production, economic output, water balance, and biodiversity. Numerous soil parameters are employed simultaneously in a variety of modules and processes in they models. The economic model ProLand requites soil data to assess tillage costs, the potential yield from agriculture and fotestry production. In order to regionalize the occurrence of typical species by ANIMO and ELLA, universal soil descriptions in combination with exposure classes are formulated and delineated by GIS on the basis of a soil map at 1:50,000 and a digital elevation model. Especially soil physical properties are input parameter of high sensitivity for the hydrological model SWAT. Whenever soil parameters are to be used in interdisciplinary modeling approaches great care must be devoted whether the preconditions for such an application are fulfilled. This problem is pointed out by some examples.

Set up of an automatic water quality sampling system in irrigation agriculture.

We have developed a high-resolution automatic sampling system for continuous in situ measurements of stable water isotopic composition and nitrogen solutes along with hydrological information. The system facilitates concurrent monitoring of a large number of water and nutrient fluxes (ground, surface, irrigation and rain water) in irrigated agriculture. For this purpose we couple an automatic sampling system with a Wavelength-Scanned Cavity Ring Down Spectrometry System (WS-CRDS) for stable water isotope analysis (δ2H and δ18O), a reagentless hyperspectral UV photometer (ProPS) for monitoring nitrate content and various water level sensors for hydrometric information. The automatic sampling system consists of different sampling stations equipped with pumps, a switch cabinet for valve and pump control and a computer operating the system. The complete system is operated via internet-based control software, allowing supervision from nearly anywhere. The system is currently set up at the International Rice Research Institute (Los Baños, The Philippines) in a diversified rice growing system to continuously monitor water and nutrient fluxes. Here we present the systems technical set-up and provide initial proof-of-concept with results for the isotopic composition of different water sources and nitrate values from the 2012 dry season.