Philipp Kraft

LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale

We present a new model system, which facilitates scaling of ecosystem processes from the site to regional simulation domains. The new framework LandscapeDNDC—partly based on the biogeochemical site scale model DNDC—inherits a series of new features with regard to process descriptions, model structure and data I/O functionality. LandscapeDNDC incorporates different vegetation types and management systems for simulating carbon, nitrogen and water related biosphere–atmosphere–hydrosphere fluxes in forest, arable and grassland ecosystems and allows the dynamic simulation of land use changes. The modeling concept divides ecosystems into six substates (canopy air chemistry, microclimate, physiology, water cycle, vegetation structure, and soil biogeochemistry) and provides alternative modules dealing with these substates. The model can be applied on the site scale, as well as for three-dimensional regional simulations. For regional applications LandscapeDNDC integrates all grid cells synchronously forward in time. This allows easy coupling to other spatially distributed models (e.g. for hydrology or atmospheric chemistry) and efficient two-way exchange of states. This paper describes the fundamental design concept of the model and its object-oriented software implementation. Two example applications are presented. First, calculation of a nitrous oxide emission inventory from agricultural soils for the State of Saxaony (Germany), including data preprocessing of the regional model input data. The computational effort for the LandscapeDNDC preprocessing and simulation could be speed up by a factor of almost 100 compared to the approach using the original DNDC version 9.3. Calculated N2O emissions for Saxony with LandscapeDNDC (2693 t N2O–N/a) were compared with the original DNDC model (2725 t N2O–N/a), the IPCC Tier I methodology (1107 t N2O–N/a), and the German National Inventory Report (equal to IPCC Tier II, 2100 t N2O–N/a). The second example illustrates the capabilities of LandscapeDNDC for building a fully coupled three-dimensional model system on the landscape scale. Therefore we coupled the biogeochemical and plant growth calculations to a hydrological transport model and demonstrate the transport of nitrogen along a virtual hillslope and associated formation of indirect nitrous oxide emissions.

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.

Critical loads and their exceedances at intensive forest monitoring sites in Europe

Intensive forest monitoring by means of harmonised methods has been conducted in Europe for more than a decade. Risks of atmospheric nitrogen and sulphur deposition are assessed by means of calculations of critical loads and their exceedances. In the present study throughfall and bulk deposition of nitrate (N-NO(3)), ammonium (N-NH(4)) and sulphate (S-SO(4)) show marked spatial patterns and temporal trends. In the period of observation (1999-2004), sulphate deposition on intensive monitoring plots decreased by about one quarter. This is in line with the reduction of S deposition by 70% since 1981 in Europe as a result of successful air pollution control politics under the Convention on Long-range Transboundary Air Pollution (CLRTAP). However, sulphate and especially nitrate and ammonium deposition were found to still exceed critical loads at many forest sites, indicating a continued need for further implementation of air pollution abatement strategies.

Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide

In regional climate impact studies, good performance of regional models under present/historical climate conditions is a prerequisite for reliable future projections. This study aims to investigate the overall performance of 9 hydrological models for 12 large-scale river basins worldwide driven by the reanalysis climate data from the Water and Global Change (WATCH) project. The results serve as the basis of the application of regional hydrological models for climate impact assessment within the second phase of the Inter-Sectoral Impact Model Intercomparison project (ISI-MIP2). The simulated discharges by each individual hydrological model, as well as the ensemble mean and median series were compared against the observed discharges for the period 1971–2001. In addition to a visual comparison, 12 statistical criteria were selected to assess the fidelity of model simulations for monthly hydrograph, seasonal dynamics, flow duration curves, extreme floods and low flows. The results show that most regional hydrological models reproduce monthly discharge and seasonal dynamics successfully in all basins except the Darling in Australia. The moderate flow and high flows (0.02–0.1 flow exceedance probabilities) are also captured satisfactory in many cases according to the performance ratings defined in this study. In contrast, the simulation of low flow is problematic for most basins. Overall, the ensemble discharge statistics exhibited good agreement with the observed ones except for extremes in particular basins that need further scrutiny to improve representation of hydrological processes. The performances of both the conceptual and process-based models are comparable in all basins.

SPOTting Model Parameters Using a Ready-Made Python Package.

The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

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.

HydroCrowd: a citizen science snapshot to assess the spatial control of nitrogen solutes in surface waters.

We organized a crowdsourcing experiment in the form of a snapshot sampling campaign to assess the spatial distribution of nitrogen solutes, namely, nitrate, ammonium and dissolved organic nitrogen (DON), in German surface waters. In particular, we investigated (i) whether crowdsourcing is a reasonable sampling method in hydrology and (ii) what the effects of population density, soil humus content and arable land were on actual nitrogen solute concentrations and surface water quality. The statistical analyses revealed a significant correlation between nitrate and arable land (0.46), as well as soil humus content (0.37) but a weak correlation with population density (0.12). DON correlations were weak but significant with humus content (0.14) and arable land (0.13). The mean contribution of DON to total dissolved nitrogen was 22%. Samples were classified as water quality class II or above, following the European Water Framework Directive for nitrate and ammonium (53% and 82%, respectively). Crowdsourcing turned out to be a useful method to assess the spatial distribution of stream solutes, as considerable amounts of samples were collected with comparatively little effort.

Prediction and uncertainty analysis of a parsimonious floodplain surface water – groundwater interaction model

Floodplains provide a variety of hydrological and ecological functions and are therefore of great importance. The flooding frequency, as well as the height and duration of inundations are particularly relevant for ecosystem states and are dependent on the exchange between surface water and groundwater. In this study, we developed a fully distributed model approach to simulate distributed groundwater levels in a floodplain in Hesse, Germany (14.8 km2). To overcome the problem of large computation times we simplified the surface water equation. Thus, the water surface of flooding is at the same level everywhere and the dynamic effect of the flooding is ignored. In this way, it was possible to run the model 5,000 times and investigate its parameter uncertainty using Latin hypercube sampling. Behavioral model runs were selected based on a threshold criterion of a mean root mean square error that was smaller than 0.26 m. All the simulated groundwater wells show an individual RMSE between 0.17 and 0.41 m for the calibration period. Regarding the parameterization, the model shows rather large variance in parameters that are capable of generating good simulations: a range of saturated conductivity of 2,793 m/day, porosity of 0.4 m3/m3, residual wetness of soil of 0.2 m3/m3/soil and range of soil thickness of 2.9 m.

Parallel Multiphysics Simulations Using OpenPALM with Application to Hydro-Biogeochemistry Coupling

Multiphysics systems consist of more than one component governed by its own principle for evolution or equilibrium. As an example, we consider an agricultural land use scenario comprising a hydrology model and a biogeochemistry model. We employ the OpenPALM tool to realize a coupling scheme where the models run concurrently using an individual parallelization. Although the two models demand for very different computational effort to compute one time step, we achieve a balance by allocating appropriate computational resources for each of them. We assess the parallel performance of the coupled application in a 3D scenario. Our concurrent operator splitting scheme shows superior efficiency compared to common coupling approaches.

Erratum to: Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide

Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide (vol 141, pg 381, 2017)