Regional climate change projections show a changing climate in the metropolitan region of Hamburg for the end of the century: The temperature could increase and the precipitation in summer could decrease. To cope with the probably longer lasting and hotter summer conditions in Europe there are different possible adaptation measures in land management practice, e.g. forest conversion. That means the conversion of mostly coniferous forest monocultures to deciduous and mixed forests. Mixed forests are generally more adaptable in comparison to conifer forests. They ensure an increased groundwater recharge because of less canopy interception and reduced transpiration outside the growing season. An interesting question is how forest conversion would feedback to the regional climate under different climate conditions. To explore climate feedbacks, REMO (regional climate model at the Max Planck Institute for Meteorology, Hamburg) is applied. To get a more realistic representation of the land surface, a current dataset from a digital basis landscape model of the Federal Agency for Cartography and Geodesy is used instead of the standard representation of the land surface in REMO. In some areas of the metropolitan region of Hamburg the updated land surface increases the forest fraction. Additionally, all coniferous forest types are converted into broadleaf forest types to study the maximum impact on the simulated near surface climate. This set-up is used for a climate simulation with REMO, forced by ERA-INTERIM reanalysis data for the period of 1990-2008. Selected climate variables are analyzed and the associated processes are investigated: The different forest distributions affect particularly the evapotranspiration and thus the water- and energy cycle of the soil and the lower atmosphere. Especially, the effects in the very hot and dry year 2003 and in the wet year 2002 are analyzed. To study the impacts of the forest distributions under different climate conditions, a second climate simulation is set up with REMO, forced by ECHAM5-MPIOM for the historical period 1970-2000 and for the future time periods 2035-2065 and 2070-2100 under A1B emissions. This allows analyzing the impact of a changed forest cover under different climate conditions. It gives a first estimation of climate sensitivity.
A statistical downscaling method has been developed to produce highly resolved precipitation data from regional climate model (RCM) output, using the model CLM (2 runs, scenario A1B). The procedure is based on the analogue method with the predictors precipitation (daily sums on CLM grid points) and objective weather types (DWD). Analogue days of the time period 2001-2009 are searched using corrected and adjusted data of radar Essen and DWD measurements of objective weather types. The radar data is used to produce high-resolution precipitation data sets (1km², 5min) with realistic spatial and temporal correlations for three catchments in North Rhine-Westphalia. Results in
the reference period (1961 - 1990) are examined using extreme value statistics and compared to corrected station data. Data sets of the near and the far future (2021-2050, 2071-2100) are analysed with respect to future trends, and uncertainties of the downscaling procedure are discussed.
Rainfall statistics are composed based on data gained by precipitation measurements and from climate models. These statistics are carried out for both periods in the past and the future. When analysing the time series, different trends can be seen in the measured data of the past and the model data for future periods. Influences on the statistically determined precipitation amounts caused by changes can be neglected for past periods. However, significant increases of the statistical precipitation amounts can be observed for the future. Here a pragmatic approach is presented, showing how to consider possible increases in the statistical precipitation amounts – due to the climate change signal – in the dimensioning of water management systems.
The precipitation data of the Regional Climate Model CLM are used for the water management impact models within the dynaklim networking and research project. For this purpose, it is necessary to apply a bias correction to the CLM
precipitation data. First, the bias assessed for varying temporal resolutions and precipitation characteristics is described. Subsequently, a method for the bias correction is introduced. The developed methodology is a modified form of the socalled
quantile mapping. The focus lies on the corrections of the dry days and the heavy rainfall events. They are considered separately, deviating from other quantile mapping procedures.
The work presented here is part of the socioeconomic analysis that is carried out within the RADOST project. It has been the starting point of developing a dynamic regionalized Input-Output (IO) model that is used to assess the effects of climate change and adaptation strategies on the regional economy. In a first step the model has been set up for the tourist sector in Mecklenburg-Western Pomerania. The possible developments of the tourism demand – influenced by climate change and other factors – were represented in three scenarios, which in turn were used as input data for the IO model.
This work deal with a comparison between the common
"bathtub method" and a state-of-the-art hydrodynamic model, called MIKE21 HD Flow Model, for modelling storm surges. The aim of this study is to work out the differences between both approaches and to find out how probable differences look like. There is the question if the "bathtub method" represents flooding adequate or, if the consideration of physics by hydrodynamic models makes a major difference and displays maybe the "real" risk of
inundations. This work tries to underline the differences between those two approaches, where the strengths and weaknesses are and what influence those differences have for an inundation analysis. The investigation was made on a digital elevation model for the study area of Kiel, the capital city of the state Schleswig-Holstein in Germany. The two approaches were made on data for a small storm surge on the basis of water-level-change and wind-regime data from 2010.
Proceeding of the 12th International Conference on Urban Drainage, Porto Alegre/Brazil, 11-16 September 2011.
For the development of adaptation strategies in the research project dynaklim (Dynamic Adaptation of Regional Planning and Development Processes to the Effects of Climate Change in the Emscher-Lippe-Region) numerous models (e. g. sewer models) which need rainfall data as input are used. These models need data with a temporal and spatial resolution beyond the resolution provided by regional climate models. Therefore downscaling of the
precipitation data is performed with the help of weather radar data. Comparisons of measurement and model data during 1961-1990 show systematic bias and differing statistical characteristics between the two data types; thus the model data requires preliminary correction before use. A critical point is the corrections´ impact on extreme event data that are applied in extreme value statistics for structure design, e.g. for retention basins. Different characteristics of the analysed rainfall data and correction procedures are described.
Abstract
Water management and environmental protection is vulnerable to extreme low flows during streamflow droughts. During the last decades, in most rivers of Central Europe summer runoff and low flows have decreased. Discharge projections agree that future decrease in runoff is likely for catchments in Brandenburg, Germany. Depending on the first-order controls on low flows, different adaption measures are expected to be appropriate. Small catchments were analyzed because they are expected to be more vulnerable to a changing climate than larger rivers. They are mainly headwater catchments with smaller ground water storage. Local characteristics are more important at this scale and can increase vulnerability.
This thesis mutually evaluates potential adaption measures to sustain minimum runoff in small catchments of Brandenburg, Germany, and similarities of these catchments regarding low flows. The following guiding questions are addressed: (i) Which first-order controls on low flows and related time scales exist? (ii) Which are the differences between small catchments regarding low flow vulnerability? (iii) Which adaption measures to sustain minimum runoff in small catchments of Brandenburg are appropriate considering regional low flow patterns?
Potential adaption measures to sustain minimum runoff during periods of low flows can be classified into three categories: (i) increase of groundwater recharge and subsequent baseflow by land use change, land management and artificial ground water recharge, (ii) increase of water storage with regulated outflow by reservoirs, lakes and wetland water management and (iii) regional low flow patterns have to be considered during planning of measures with multiple purposes (urban water management, waste water recycling and inter-basin water transfer). The question remained whether water management of areas with shallow groundwater tables can efficiently sustain minimum runoff. Exemplary, water management scenarios of a ditch irrigated area were evaluated using the model Hydrus-2D. Increasing antecedent water levels and stopping ditch irrigation during periods of low flows increased fluxes from the pasture to the stream, but storage was depleted faster during the summer months due to higher evapotranspiration. Fluxes from this approx. 1 km long pasture with an area of approx. 13 ha ranged from 0.3 to 0.7 ls-1 depending on scenario. This demonstrates that numerous of such small decentralized measures are necessary to sustain minimum runoff in meso-scale catchments.
Differences in the low flow risk of catchments and meteorological low flow predictors were analyzed. A principal component analysis was applied on daily discharge of 37 catchments between 1991 and 2006. Flows decreased more in Southeast Brandenburg according to meteorological forcing. Low flow risk was highest in a region east of Berlin because of intersection of a more continental climate and the specific geohydrology. In these catchments, flows decreased faster during summer and the low flow period was prolonged. A non-linear support vector machine regression was applied to iteratively select meteorological predictors for annual 30-day minimum runoff in 16 catchments between 1965 and 2006. The potential evapotranspiration sum of the previous 48 months was the most important predictor (r2 = 0.28). The potential evapotranspiration of the previous 3 months and the precipitation of the previous 3 months and last year increased model performance (r2 = 0.49, including all four predictors). Model performance was higher for catchments with low yield and more damped runoff. In catchments with high low flow risk, explanatory power of long term potential evapotranspiration was high.
Catchments with a high low flow risk as well as catchments with a considerable decrease in flows in southeast Brandenburg have the highest demand for adaption. Measures increasing groundwater recharge are to be preferred. Catchments with high low flow risk showed relatively deep and decreasing groundwater heads allowing increased groundwater recharge at recharge areas with higher altitude away from the streams. Low flows are expected to stay low or decrease even further because long term potential evapotranspiration was the most important low flow predictor and is projected to increase during climate change. Differences in low flow risk and runoff dynamics between catchments have to be considered for management and planning of measures which do not only have the task to sustain minimum runoff.
Information about possible changes of extreme wave heights are essential for the future safe design of coastal and flood protection structures likes dykes, flood protection dunes, revetments etc. In this study, scenarios of regional climate change up to 2100 are used for the evaluation of changes of wave conditions. Analyses on calculated significant wave heights derived from extreme value statistics are showing a different signal of change for the selected locations along the German Baltic Sea Coast. The results are showing that extreme wave heights with a return level of 200 years can increase up to +14%. But also a decrease of down to -14% were found compared to actual conditions, depending on the location and climate change scenario applied. At the location of Warnemünde a slight increasing trend for the change of extreme wave heights could be found for 3 of 4 scenario runs with a maximum increase of +7%.
Feedback of forest distribution on the simulated climate of the metropolitan region of Hamburg
(2013)
