Fred Hattermann

Implications of complexity and uncertainty for integrated modelling and impact assessment in river basins

The paper focuses on implications of complexity and uncertainty in climate change impact assessment at the river basin and regional scales. The study was performed using the process-based ecohydrological spatially semi distributed model SWIM (Soil and Water Integrated Model). The model integrates hydrological processes, vegetation/crop growth, erosion and nutrient dynamics in river basins. It was developed from the SWAT and MATSALU models for climate and land use change impact assessment. The study area is the German part of the Elbe River basin (about 100,000km^2). It is representative for semi-humid landscapes in Europe, where water availability during the summer season is the limiting factor for plant growth and crop yield. The validation method followed the multi-scale, multi-site and multi-criteria approach and enabled to reproduce (a) water discharge and nutrient load at the river outlet along with (b) local ecohydrological processes like water table dynamics in subbasins, nutrient fluxes and vegetation growth dynamics at multiple scales and sites. The uncertainty of climate impacts was evaluated using comprehensive Monte Carlo simulation experiments.

Parameter and input data uncertainty estimation for the assessment of long-term soil organic carbon dynamics

The use of integrated soil organic matter (SOM) models to assess SOM dynamics under climate change, land use change and different land management practices require a quantification of uncertainties and key sensitive factors related to the respective modelling framework. Most uncertainty studies hereby focus on model parameter uncertainty, neglecting other sources like input data derived uncertainties, and spatial and temporal properties of uncertainty. Sources of uncertainties assessed in this study stem from uncertainties in model parameterisation and from uncertainties in model input data (climate, soil data, and land management assumptions). Thereby, Monte Carlo based global sensitivity and uncertainty analysis using a latin hypercube stratified sampling technique was applied to derive plot scale (focusing on temporal propagation) and river basin scale propagation of uncertainty for long-term soil organic carbon (SOC) dynamics. The model used is the eco-hydrological river basin model SWIM (Soil and Water Integrated Model), which has been extended by a process-based multi-compartment model for SOM turnover. Results obtained by this study can be transferred and used in other simulation models of this kind. Uncertainties resulting from all input factors used (model parameters+model input data) show a coefficient of variation between 5.1 and 6.7% and accounted for+/-0.065 to+/-0.3% soil carbon content (0.06-0.15t Cha^-^1yr^-^1). Parameter derived uncertainty contributed most to overall uncertainty. Concerning input data contributions, uncertainties stemming from soil and climate input data variations are striking. At the river basin scale, cropland and forest ecosystems, loess and gleyic soils possess the highest degree of uncertainty. Quantified magnitudes of uncertainty stemming from the examined sources vary temporally and spatially due to specific natural settings (e.g. climate, land use and soil properties) and deliver useful information for interpreting simulation results on long-term soil organic carbon dynamics under environmental change. Derived from this analysis, key sensitive model parameters and interactions between them were identified: the mineralization rate coefficient, the carbon use efficiency parameter (synthesis coefficient) along with parameters determining the soil temperature influence on SOM turnover (mainly Q10 value) and the soil input related data (soil bulk density and initial soil C content) introduced the highest degree of model uncertainty. The here gained information can be transferred to other process-based SOM turnover models to consider stronger most crucial parameters introducing highest uncertainty contribution to soil C storage assessment under changing environmental conditions.

Integrating groundwater dynamics in regional hydrological modelling

Abstract The paper presents an integrated catchment model and a method with which it is possible to analyse local water table dynamics inside subbasins along with river flow on the regional scale. A simple but comprehensive mechanistic groundwater module coupled with the eco-hydrological model SWIM (Soil and Water Integrated Model), which integrates hydrological processes, vegetation, erosion and nutrient dynamics at the watershed scale, was used in the study. The reliability of the model results was tested under well defined boundary conditions by comparing the results with those from a two dimensional numeric groundwater model under steady-state and transient conditions as well as with observed data for two meso-scale basins, using contour maps of the long term mean water table, observed groundwater level data in wells and observed river discharge. Especially in lowland catchments, where the water table is relatively shallow, the dynamics of river discharge are mainly influenced by changes in groundwater contribution to river flow. However, a correct reproduction of river discharge by hydrological models does not guarantee the adequacy of simulated spatio-temporal dynamics of soil moisture, water fluxes and groundwater in the basin. But even though the primary purpose of distributed hydrological models is to reproduce river discharge and water fluxes in the entire catchment, they are often validated using only the observed river discharge at the basin outlet for comparisons. The additional use of groundwater observations for model validation can serve as a measure to overcome the problem. The study area is located in the lowland part of the Elbe river basin, which is representative for semi-humid landscapes in Europe, where water availability during the summer season is the main limiting factor for plant growth and crop yields. The importance of adequate reproduction of the groundwater dynamics is illustrated in an investigation of a decreasing trend in regional groundwater level.

Practices and Lessons Learned in Coping with Climatic Hazards at the River-Basin Scale: Floods and Droughts

Climatic hazards such as floods and droughts have always been a primary matter of concern for human populations. Severe floods damage settlements, transport networks, and arable land. Although devastating droughts are harmful primarily for agriculture and terrestrial ecosystems, they can also lead to local water supply shortages. Despite significant achievements in science and technology and success stories in environmental management in the 20th century, people still continue to suffer the consequences of climate hazards worldwide. This paper provides an overview of existing practices for coping with floods and droughts, compares strategies in different river basins, and outlines the areas that need improvement. First, the existing protection measures and response strategies against floods and droughts are briefly described. An overview is given of expected climate change and existing coping strategies for floods and droughts in seven case study basins. Four of the basins, namely the Elbe, Guadiana, Rhine, and Tisza, are located in Europe; the Nile and the Orange are in Africa; and the Amudarya is in Central Asia. Analysis of the coping strategies shows that structural measures exist in all seven river basins, but that nonstructural measures are generally not very extensive and/or advanced. Finally, the success stories in dealing with climatic hazards and lessons learned, taken partly from the seven case study basins and partly from literature, are summarized.

Climate change adaptation and sustainable regional development: a case study for the Federal State of Brandenburg, Germany

Located in a relatively dry region and characterized by mainly sandy soils, the German Federal State of Brandenburg (surrounding the capital city of Berlin) is especially vulnerable to climate change impacts (e.g., summer droughts) and cascading effects on ecological systems (e.g., decreasing ground water tables, water stress, fire risk, productivity losses) with socioeconomic implications. Furthermore, a complex interplay of unemployment, rural exodus, and an aging population challenges this structurally weak region. We discuss adaptation measures that are either implemented or planned, as well as research into adaptation strategies to climate change for the sectors forestry, agriculture, and water management as well as in nature conservation in light of socioeconomic and ecological challenges and benefits. In doing so, we adopt a systemic view of Brandenburg where the sectors discussed are seen as subsystems embedded in a larger regional system. This at least partially holarchical approach enables the identification of conflicts between adaptation measures, but also of synergies among the sectors that pertain to successful adaptation to climate change. The insights gained ultimately highlight the need for cross-sectoral, adaptive management practices that jointly target a sustainable regional development.

Projection of low flow conditions in Germany under climate change by combining three RCMs and a regional hydrological model

The present study is aimed to: (a) project future low flow conditions in the five largest river basins in Germany, and (b) to account for the projections uncertainties. The eco-hydrological model SWIM was driven by different regional climate models (REMO, CCLM, and Wettreg) to simulate daily river discharges in each study basin. The 50-year low flow was estimated for the period 1961 to 2000, and its return period was assessed for two scenario periods, 2021–2060 and 2061–2100, using the generalized extreme value distribution. The 50-year low flow is likely to occur more frequently in western, southern, and parts of central Germany after 2061, as suggested by more than or equal to 80% of the model runs. The current low flow period (from August to September) may be extended until late autumn at the end of this century. The return period of 50-year deficit volume shows a similar temporal and spatial pattern of change as for the low flow, indicating slightly less severe conditions with lower confidence. When compared with flood projections for the same area using the same models, the severer low flows projected in this study appear more pronounced, consistent, and have lower uncertainty.

Differences in flood hazard projections in Europe – their causes and consequences for decision making

ABSTRACT This paper interprets differences in flood hazard projections over Europe and identifies likely sources of discrepancy. Further, it discusses potential implications of these differences for flood risk reduction and adaptation to climate change. The discrepancy in flood hazard projections raises caution, especially among decision makers in charge of water resources management, flood risk reduction, and climate change adaptation at regional to local scales. Because it is naïve to expect availability of trustworthy quantitative projections of future flood hazard, in order to reduce flood risk one should focus attention on mapping of current and future risks and vulnerability hotspots and improve the situation there. Although an intercomparison of flood hazard projections is done in this paper and differences are identified and interpreted, it does not seems possible to recommend which large-scale studies may be considered most credible in particular areas of Europe. EDITOR D. Koutsoyiannis ASSOCIATE EDITOR not assigned

Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins

This paper aims to evaluate sources of uncertainty in projected hydrological changes under climate change in twelve large-scale river basins worldwide, considering the mean flow and the two runoff quantiles Q10 (high flow), and Q90 (low flow). First, changes in annual low flow, annual high flow and mean annual runoff were evaluated using simulation results from a multi-hydrological-model (nine hydrological models, HMs) and a multi-scenario approach (four Representative Concentration Pathways, RCPs, five CMIP5 General Circulation Models, GCMs). Then, three major sources of uncertainty (from GCMs, RCPs and HMs) were analyzed using the ANOVA method, which allows for decomposing variances and indicating the main sources of uncertainty along the GCM-RCP-HM model chain. Robust changes in at least one runoff quantile or the mean flow, meaning a high or moderate agreement of GCMs and HMs, were found for five river basins: the Lena, Tagus, Rhine, Ganges, and Mackenzie. The analysis of uncertainties showed that in general the largest share of uncertainty is related to GCMs, followed by RCPs, and the smallest to HMs. The hydrological models are the lowest contributors of uncertainty for Q10 and mean flow, but their share is more significant for Q90.

Modelling climate and land-use change impacts with SWIM: lessons learnt from multiple applications

Abstract The Soil and Water Integrated Model (SWIM) is a continuous-time semi-distributed ecohydrological model, integrating hydrological processes, vegetation, nutrients and erosion. It was developed for impact assessment at the river basin scale. SWIM is coupled to GIS and has modest data requirements. During the last decade SWIM was extensively tested in mesoscale and large catchments for hydrological processes (discharge, groundwater), nutrients, extreme events (floods and low flows), crop yield and erosion. Several modules were developed further (wetlands and snow dynamics) or introduced (glaciers, reservoirs). After validation, SWIM can be applied for impact assessment. Four exemplary studies are presented here, and several questions important to the impact modelling community are discussed. For which processes and areas can the model be used? Where are the limits in model application? How to apply the model in data-poor situations or in ungauged basins? How to use the model in basins subject to strong anthropogenic pressure? Editor D. Koutsoyiannis; Associate editor C. Perrin