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Tagebau(folge)landschaften bieten gute Möglichkeiten den Wandel ökohydrologische Systeme aufgrund veränderter Umweltbedingungen zu untersuchen: Im Zuge des Tagebaubetriebs wird die Vegetation vollständig entfernt, nach dem Tagebau wächst die Vegetation entweder durch aktive Rekultivierung oder natürliche Sukzession wieder auf. Von Interesse ist, ob und wie bzw. wie schnell sich die Tagebauflächen von der Störung erholen und ähnliche Bedingungen wie vor dem Tagebau bzw. auf ungestörten Flächen herrschen. Klimatische,
geomorphologische und ökologische Gegebenheiten sowie die Rekultivierungsstrategie spielen eine große Rolle in der Phase der Rehabilitation und bestimmen die Rate der Wiederbesiedlung
mit Pflanzen bzw. deren Wachstum. Der NDVI (normalisierter differenzierter Vegetationsindex) bietet die Möglichkeit generelle Muster der Vegetation quantitativ zu detektieren, um die Regenerationsrate der Vegetation für verschiedene Klima- und Ökoregionen abzuschätzen. Wir analysierten den MODIS Terra NDVI (achttägliche Werte) für Tagebaulandschaften verschiedener Klimate (äquatoriale, trockene, warm gemäßigte und Schnee-Klimate nach Köppen-Geiger) im Zeitraum 2001 bis 2015. Es wurden Kohletagebaue
betrachtet, da diese gut definierte Chronosequenzen der Störung erzeugen. Bei der Analyse der NDVI-Zeitreihen sollten Charakteristiken der Rehabilitationsphase erfasst werden. Um
die räumliche Heterogenität der Zellen (ca. 250 x 250 m²) der Tagebaulandschaft abzubilden, wurde je Tagebau eine hierarchische Clusteranalyse durchgeführt. Die einzelnen Zeitreihen der Cluster wurden mit einer Methode zur Detektion von Bruchpunkten und zur Zeitreihenzerlegung auf Konsistenz bezüglich Eigenschaften der Zeitreihen (Beginn des Tagebaus, Ende des Tagebaus/Beginn der Rehabilitation, Rate der Rehabilitation) untersucht. Die Clusteranalyse führt zu einer Einordnung der Zellen in vom Tagebau nicht direkt beeinflusste Flächen, aktiven Tagebau und in der Rehabilitation befindliche Fläche verschiedenen Alters
bzw. rehabilitierte Flächen. Das Zeitfenster der Entfernung der Vegetation kann im NDVI-Signal identifiziert werden, es zeigt sich meist in einer abrupten Änderung des NDVI. Die Rehabilitationsphase hingegen verläuft graduell und kann mehrere Jahre bis Jahrzehnte
andauern. Die Zeitreihenzerlegung zeigt auf, dass in der Rehabilitationsphase der Trend dominiert, während mit Voranschreiten der Rehabilitation die Saisonalität im NDVI-Signal vorherrschend wird. Durch die ermittelte Rate der Rehabilitation können die Flächen innerhalb eines Tagebaus miteinander verglichen werden. Die mittlere Rehabilitationsrate der Tagebaue kann in Zusammenhang mit den vorherrschenden hydroklimatischen Bedingungen der Klimazonen und mit Rekultivierungsstrategien gebracht werden. Zudem ist auch eine
Betrachtung hydrometeorologischer Größen zur Erkennung von kurzzeitigen Veränderungen des Pflanzenwachstums im NDVI-Signal möglich.
Studien zum Einfluss des zukünftigen Klimawandels auf das Abflussgeschehen fokussieren oft auf die Fortpflanzung von Unsicherheiten in Modellkaskaden, berücksichtigen meist jedoch
die Wasserressourcenbewirtschaftung nur ungenügend. Wir untersuchten den Einfluss der Wasserressourcenbewirtschaftung auf die Abflussvariabilität und die Fortpflanzung von Unsicherheiten von Klimaprojektionen auf Abflusssimulationen in den Einzugsgebieten von
Spree (bis Pegel Große Tränke: 6200 km²) und Schwarzer Elster (5700 km²). Die Einzugsgebiete ähneln sich hinsichtlich Klima, Topographie, Boden und Landnutzung, jedoch ist das Spreeeinzugsgebiet stärker durch den Braunkohletagebau und die damit verbundenen Bewirtschaftung geprägt und durch einen höheren Speicherausbaugrad gekennzeichnet. Um zwischen Bewirtschaftungseinflüssen und meteorologischen Einflüssen zu separieren, wurden für den Zeitraum 1961-2005 beobachtete Abflüsse mit durch das Modell SWIM rekonstruierten natürlichen (d.h. ohne Bewirtschaftungseinfluss) Abflüssen der Vergangenheit verglichen. Mögliche Einflüsse des Klimawandels wurden für den Zeitraum 2018-2052 auf Grundlage von 3 Szenarien des statistischen Regionalmodells STAR (je 100 Realisierungen) mit SWIM (natürliche Abflüsse) und dem Langfristbewirtschaftungsmodell WBalMo (bewirtschaftete Abflüsse) modelliert. Die Analyse erfolgte mit Fokus auf Saisonalität, Oszillation, Verteilung und räumliche Variabilität der Abflüsse. Der Vergleich zwischen beobachteten
und natürlichen Abflüssen der vergangenen Jahrzehnte zeigt, dass die zwischenjährliche Abflussvariabilität im Spreeeinzugsgebiet stärker durch Grubenwassereinleitungen als durch natürliche hydrologische Prozesse bestimmt wurde. Zusätzlich führt der höhere Speicherausbaugrad dazu, dass die kurzzeitliche und saisonale Variabilität im Spreeeinzugsgebiet geringer als im Einzugsgebiet der Schwarzen Elster ist. Simulationen mit Klimaszenarien, welche
steigende Jahresmitteltemperaturen und einen Rückgang der Niederschlagsjahressummen enthalten, führen zu deutlichen Abflussrückgängen. Die Unterschiede der natürlichen Abflüsse
beider Einzugsgebiete sind gering, die Unsicherheiten der Klimaprojektionen werden durch die hydrologische Modellierung verstärkt. Die natürlichen und bewirtschafteten Abflüsse
der Schwarzen Elster unter Klimawandel unterscheiden sich kaum. Im Spreeeinzugsgebiet zeigt sich eine deutliche Verringerung der Variabilität und Unsicherheiten unter Klimawandel von den natürlichen zu den bewirtschafteten Abflüssen. Die Analysen zeigen, dass effektive Wasserressourcenbewirtschaftung die Abflussvariabilität verringern kann und damit auch
dazu beitragen kann, die sich aus Klimawandelprojektionen ergebenden Unsicherheiten zu vermindern. Einzugsgebiete mit einem hohen Ausbaugrad weisen weniger Vulnerabilität bezüglich klimatischer Änderungen auf. Dies unterstreicht die Bedeutung von Wasserresourcenbewirt-schaftungfür die Anpassung an den Klimawandel.
In landscapes with heterogeneous vegetation structure, interception and throughfall patterns produce spatiotemporal
variability of soil moisture. This variability is important for eco-hydrological processes, in particular on
small spatial scales up to the catchment scale. Throughfall depends on vegetation structure, whereas vegetation
development is presumably co-determined by the spatio-temporal distribution of throughfall itself. In addition
to vegetation structure, meteorological factors like wind speed and rainfall intensity also have an impact on
throughfall.
The objective of this study is to quantify the influence of vegetation structure and meteorological variables
on spatial (and in the long run the temporal) variability of throughfall. For that purpose, we developed an
approach combining field methods, image analysis and multivariate statistics. The 6-ha constructed catchment
‚Hühnerwasser‘ (aka Chicken Creek, southern Brandenburg, Germany) offers ideal conditions for the investigation
of eco-hydrological feedback processes. After more than 10 years of development, vegetation structure on the
catchment is spatially heterogeneous and evolves through natural succession. Furthermore, complementary
meteorological data are available on-site.
Throughfall was measured using 50 tipping-bucket rain gauges, which are aligned along two transects in 0.5
and 1 m heights, covering the dominating vegetation types on the catchment (e.g., robinia, sallow thorn, reed,
reedgrass, herbs). The spatial distribution of vegetation structures around each measurement site was recorded
with hemispheric photographs, which were subsequently analyzed using image processing techniques. Two
weather stations provide reference values for precipitation and relevant meteorological variables for wind speed
and direction, air humidity, temperature and irradiation.
The amount and distribution of precipitation measured in scarcely vegetated areas of the catchment widely
correspond with values from the reference weather stations. Under dense vegetation, very heterogeneous values
were recorded, which can be explained by i) canopy interception, and ii) fetching effects. The results of this study
can serve as basis for interception models and may also contribute to complex eco-hydrological models.
Climate change impact studies are associated with error propagation and amplification of uncertainties through model chains from global climate models down to impact (e.g. hydrological) models. The effect of water management, which reduces discharge variability, is often not considered in climate change impact studies. Here, we investigated how water resources management influences discharge variability and uncertainty propagation of climate change scenarios by combining the analyses of observed flow records and model-based climate change impact simulations. Two neighbouring catchments, the Schwarze Elster River (Germany) and the Spree River (Germany and Czech Republic) which are similar in climate, topography and land use, but different in terms of water resources management were chosen as study area. The intense water resources management in the Spree River catchment includes a high reservoir capacity, water use in terms of mining discharges and water withdrawals by power plants as well as water transfers.
The analysis of historical flow records focusses on variability indices (Parde index, Richards-Baker-Flashiness Index, Interquartile Ratio and Baseflow Index). The climate change impact simulations were carried out using a model cascade of (i) the statistical regional model STAR (100 stochastically generated realizations each for 3 scenarios with different prescribed temperature trend), (ii) the hydrological models SWIM and EGMO, and (iii) the water resources management model WBalMo.
The analysis of the observed discharges reveals that the annual discharge variability in the Spree catchment is dominated by mining activities rather than natural rainfall-runoff processes. Due to the high reservoir capacity in the Spree catchment its discharge is characterised by less seasonality and short-term variability compared to the Schwarze Elster. Simulations with climate change scenarios assuming increasing temperature and decreasing precipitation result in pronounced reductions of discharge in both catchments. The differences in potential natural discharges between the Schwarze Elster and the Spree catchments as projected by the hydrological models SWIM and EGMO are marginal. The uncertainties related to the climate projection are propagated through the hydrological models. In the Schwarze Elster catchment, the managed discharges simulated by WBalMo are comparable to the potential natural discharges. In the Spree River however, the short-term variability is moderated by water resources management and managed discharge under climate change is less affected by amplification of uncertainties through model chains.
The results of the study, which combines the analyses of observed flow records and model-based climate change impact simulations, imply that generally, effective water resources management reducing discharge variability hence also reduces uncertainty related to climate change impacts on river discharge. Catchments with a high storage ratio are thus less vulnerable to changing climate conditions. This underlines the role of water resources management in coping with climate change impacts. Yet, due to decreasing reservoir volumes in drought periods, reservoir management alone cannot compensate strong changes in climate conditions over long time periods.
Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff,
erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution.
We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model.
The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes.
Assessing ecohydrological systems that undergo state transitions due to environmental change is becoming
increasingly important. One system that can be used to study severe disturbances are post-mining landscapes as they usually are associated with complete removal of vegetation and afterwards subsequent ecosystem restoration or spontaneous rehabilitation in line with natural succession.
Within this context it is of interest, whether and how (fast) the land cover in these areas returns to conditions
comparable to those in the undisturbed surrounding or those prior mining. Many aspects of mine site rehabilitation
depend on climatic, geomorphic and ecological settings, which determine at which rate vegetation may be reestablished. In order to identify general patterns of vegetation establishment, we propose to use NDVI (Normalized Difference Vegetation Index) time series for mine affected land to estimate rate of recovery across climate regions and ecoregions. In this study we analysed the MODIS Terra Satellite 8 day-composite NDVI for areas influenced by surface mining in different climates from 2001 to 2015. The locations have been chosen based on their extent and the
data availability of mining and rehabilitation activities. We selected coal extraction as a case study as strip mining
generates well-defined chronosequences of disturbance. The selected mining areas are located in equatorial, arid, warm temperate or snow climates with different precipitation and temperature conditions according to the Köppen-Geiger classification. We analysed the NDVI time series regarding significant characteristics of the re-vegetation phase. We applied hierarchical cluster analysis to capture the spatial heterogeneity between different pixels (ca. 250 * 250 m2 each) in and around each open cast mine. We disentangled seasonality, trend and residual components in the NDVI time
series by Seasonal and Trend decomposition using LOESS.
As expected the time of the removal of vegetation can be clearly identified from the NDVI time series and provides
the starting point of disturbance. The cluster analysis allowed us to distinguish between the non-mining land, the
mine and the restored land of different ages. Based on these clusters, the time series decomposition revealed the
dominance of the trend of increasing NDVI in areas undergoing the restoration process as well as the prevailing
seasonality of the oldest restored sites. The determined phase of a dominant trend component, lasting until the
NDVI is in the range of the surrounding landscape or the pre-mining conditions, is in the scale of a decade. The impacts of different hydroclimatic regimes and different rehabilitation strategies on long term NDVI development are currently being investigated. Furthermore, coherence analysis will be applied to quantify short term influences of hydrometeorological variables on vegetation development.
Due to the flooding of former open-pit mines, Europe’s largest artificial lake district is created in Eastern Germany. Between 1990 and 2006 more than 80 km² of new lakes have already been formed. These large-scale land cover changes may impact regional meteorological characteristics, therefore it is of interest, whether effects of the mining lakes can already be observed. We especially focus on whether the evaporation from the mining pit lakes leads to a higher precipitation on their lee side. To detect changes in the precipitation patterns, we analysed daily precipitation data (1980-2014) of 25 stations in an area of 10 000 km² widely around the lake district. Under the assumption that the influences of the lakes should be detectable either directly as trends in the observed data or as a deviation from a general measure for precipitation we combined statistical tests and principal component analysis (PCA). We applied pre-whitening Mann-Kendall tests to detect precipitation trends and Mann-Whitney tests to detect differences between split samples (before and after the flooding of most of the lakes). The PCA was applied based on the correlation matrix of daily precipitation at the different stations.
As the daily precipitation can sufficiently be explained by the first five principal components, the recombination of these five principal components was used as a general measure of precipitation in the region. By regression trees (random forests) a relation between the eigenvectors of the first five principal components and physiogeographic characteristics of the stations (e.g. altitude) was shown.
Both the observed data and the deviations between the measurements and the recombination of the first five principal components showed divergent trends with high spatial variability and also interannual variability, but a pattern consistent with the lee side of the lake could not be detected. Therefore, it has been demonstrated that the emerging lakes had no influence on the daily precipitation at the stations considered in this study. This may be explained by the coarse spatial and also temporal resolution of precipitation measurements. Still, the approach presented here can be applied to (i) detect changes in the spatial pattern of climate variables by a combination of statistical tests and PCA and (ii) to analyse the relationships between such changes and physiogeographic characteristics by regression trees.
In evolving initial landscapes, vegetation development depends on a variety of feedback effects. One of the less understood feedback loops is the interaction between throughfall and plant canopy development. The amount of throughfall is governed by the characteristics of the vegetation canopy, whereas vegetation pattern evolution may in turn depend on the spatio-temporal distribution of throughfall. Meteorological factors that may influence throughfall, while at the same time interacting with the canopy, are e.g. wind speed, wind direction and rainfall intensity. Our objective is to investigate how throughfall, vegetation canopy and meteorological variables interact in an exemplary eco-hydrological system in its initial development phase, in which the canopy is very heterogeneous and rapidly changing. For that purpose, we developed a methodological approach combining field methods, raster image analysis and multivariate statistics. The research area for this study is the Hühnerwasser (‘Chicken Creek’) catchment in Lower Lusatia, Brandenburg, Germany, where after eight years of succession, the spatial distribution of plant species is highly heterogeneous, leading to increasingly differentiated throughfall patterns. The constructed 6-ha catchment offers ideal conditions for our study due to the rapidly changing vegetation structure and the availability of complementary monitoring data.Throughfall data were obtained by 50 tipping bucket rain gauges arranged in two transects and connected via a wireless sensor network that cover the predominant vegetation types on the catchment (locust copses, dense sallow thorn bushes and reeds, base herbaceous and medium-rise small-reed vegetation, and open areas covered by moss and lichens). The spatial configuration of the vegetation canopy for each measurement site was described via digital image analysis of hemispheric photographs of the canopy using the ArcGIS Spatial Analyst, GapLight and ImageJ software. Meteorological data from two on-site weather stations (wind direction, wind speed, air temperature, air humidity, insolation, soil temperature, precipitation) were provided by the ‘Research Platform Chicken Creek’. Data were combined and multivariate statistical analysis (PCA, cluster analysis, regression trees) were conducted using the R-software to i) obtain statistical indices describing the relevant characteristics of the data and ii) to identify the determining factors for throughfall intensity. The methodology is currently tested and results will be presented. Preliminary evaluation of the image analysis approach showed only marginal, systematic deviation of results for the different software tools applied, which makes the developed workflow a viable tool for canopy characterization. Results from this study will have a broad spectrum of possible applications, for instance the development / calibration of rainfall interception models, the incorporation into eco-hydrological models, or to test the fault tolerance of wireless rainfall sensor networks.
While there are hints that biological soil crusts (BSCs) can constitute physical barriers for the emergence of vascular plants, a conceptual approach for the quantitative evaluation of these effects is still missing. Here we present an experimental design to test the emergence of seedlings in situ with (i) capping natural intact, (ii) destroyed and (iii) removed BSC. The selected field site is directly adjacent to the constructed Hühnerwasser catchment (Lusatia,
Germany). This site exists since the end of 2008 and consists of loamy sand. Serving as proxy for seedling thrust, we inserted pre-germinated seeds of three confamiliar plant species with different seed masses (members of the Fabaceae family: Lotus corniculatus
L., Ornithopus sativus Brot., and Glycine max
(L.) Merr.). In each treatment as well as in the control group planting depths were 10 mm. We took care that experimental plots had identical crust thickness, slightly less than 4 mm, serving as proxy for mechanical resistance.
A plot became established as follows: Firstly, the pristine crusted surface was vertically cut. To the windward side the BSC remained intact (i: “with BSC” stripe). To the downwind side soil material was temporarily excavated for laterally inserting the seeds beneath the surface of the first stripe. Then at the thereby disturbed second stripe pulverised BSC material became filled as a top layer (ii: “BSC mix” stripe). From the next stripe the BSC was removed (iii : “no BSC” stripe). Thus each plot had each experimental group in spatial contiguity (within 50 cm * 50 cm). The overall 50 plots were distributed across an area of 40 m * 12 m. When individuals of a species either emerged at all stripes, “XXX”, or at no stripe of a plot, “– – –“, there was no reason to suppose any effect of a crust. The “–XX” emergence pattern (depicting the appearance of seedlings in both stripes possessing manipulated surfaces) points towards hindrance more clearly than “–X–” or “– - X”. Altogether eight possible combinations exist. Combinatorial analysis turned out that seedling emergence had been notably impeded for light-weighted seeds but little for heavy seeds. Repeated recordings enable to account for adaptable emergence of seedlings according to varying crust conditions – in spatial as well as temporal terms. The proposed experimental procedure hence is highly recommended as a viable instrument to further investigate filter and facilitation processes between BSCs and vascular plants.
Abschätzung möglicher Folgen des Klimawandels auf die regionalen Wasserressourcen der Lausitz
(2013)
Das ökohydrologische Modell SWIM wurde für die Gesamteinzugsgebiete der Dahme, der
Schwarzen Elster und die Einzugsgebiete der Spree bis zum Pegel Große Tränke und der Lausitzer
Neiße bis zum Pegel Steinbach aufgebaut und parametrisiert. Aufgrund starker anthropogener
Beeinflussung durch Braunkohleförderung und Wasserbewirtschaftung ist der klassische
Ansatz der Kalibrierung hydrologischer Modelle an den Endpegeln der Einzugsgebiete nicht
möglich. Der in dieser Studie genutzte Ansatz ist daher, SWIM für Teileinzugsgebiete zu kalibrieren
und zu validieren und die sensitivsten Modellparameter zu regionalisieren. Zur Verifizierung
der Kalibrierung wurden für unbeeinflusste Teileinzugsgebiete Modellergebnisse von SWIM mit
denen von WaSim-ETH und HBV light verglichen. Der Regionalisierungsansatz wurde durch
Vergleich mit diesen Modellen in einem anthropogen stärker beeinflussten Teileinzugsgebiet und
unter Berücksichtigung langjähriger natürlicher und naturalisierter Abflüsse verifiziert. Zwischen
den Simulationsergebnissen von SWIM, HBV light und WaSim-ETH zeigen sich unter Antrieb
der Szenarien WettReg A1B und STAR 2K nur geringe Unterschiede. Hingegen wirkt sich die
Wahl des Regionalen Klimamodells deutlich auf die Simulationsergebnisse aus. Simulationen für
die Gesamteinzugsgebiete im Untersuchungsgebiet zeigen einen deutlichen Rückgang von Abfluss
und Grundwasserneubildung für WettReg A1B. Das Szenario STAR 0K führt zu sehr geringen
Änderungen dieser Wasserhaushaltskomponenten in den Einzugsgebieten der Dahme, der
Schwarzen Elster und der Spree, während die Szenarien STAR 2K und STAR 3K zu deutlichen
Rückgängen beider Größen führen. Im Einzugsgebiet der Lausitzer Neiße wird für die STARSzenarien
ein Anstieg des Abflusses bei Verringerung der Grundwasserneubildung simuliert.
Lusatia is one of the driest regions in Germany: already under current climate conditions the climatic water balance is negative. Due to excessive open-cast lignite mining activities the water balance of the catchments of the rivers Spree, Schwarze Elster, and Lusatian Neisse is profoundly disturbed. Potential changes of future climate and land use conditions will certainly impact the natural hydrologic conditions and consequently water management measures have to be adjusted in order to alleviate the water tense situation. Simulations of the Soil and Water Integrated Model (SWIM) for subcatchments without influence of lignite mining and water management driven by scenarios of the Statistical Analogue Resampling scheme (STAR) assuming a further temperature increase of 0 K, 2 K and 3 K, respectively, showed an aggravation of the situation: Due to higher potential evaporation natural discharge is decreased especially in the vegetation period.
The objective of this study is to assess potential climate change impact for the catchments of the rivers Spree, Schwarze Elster, and Lusation Neisse. Due to the strong anthropogenic impact on the discharge, the traditional approach of calibrating hydrological models based on time series of observed discharges is constrained. In order to estimate potential climate and land use change impacts for the named river catchments SWIM was first calibrated for subcatchments without influence of mining activities and water management. In a second step, the model was set up for the all catchments using model parameter regionalization. Climate change impacts were estimated using climate scenarios STAR (3 scenarios, 100 realisations each) and WettReg (3 scenarios, 10 realisations each). Land use change was considered for several scenarios focusing on the reduction of the groundwater depression cone caused by lignite mining and on a potentially increased cultivation of agricultural energy crops. Both, changes in quasi-natural river discharges at certain gauge stations and temporally and spatially distributed changes of water balance components, were analyzed in order to estimate whether climate or land use changes will be the dominant reason for potential changes of water resources. The simulated discharges will later be used as input data for the long term water management model WBalMo in order to assess potential climate and land use change impacts on water users and managed discharges as a prerequisite for climate and land use change adaptation strategies.
The water balance of the Rivers Spree, Schwarze Elster and Lusatian Neisse is profoundly disturbed due to large-scale open-cast lignite mining activities and water management. Together with continental climate conditions this affects
water resources and water users in the region. Driven by scenarios of the regional climate model STAR which assume increasing temperature and decreasing precipitation, two hydrological models, the Soil and Water Integrated Model
SWIM and the catchment model EGMO simulate declining natural discharges in the region. Thus, decreasing managed discharges are simulated with the long term water management model WBalMo. The refinement of the simulation time step of WBalMo from months to weeks improves the consideration of climate variability and is also associated with higher simulated managed discharges in
early summer. Management scenarios in terms of a reduced outlet capacity of a mining lake reservoir result in higher releases from other reservoirs and slightly
reduced summer discharges in downstream river sections.
Highly disturbed soils and substrates used in land rehabilitation undergo rapid changes after the first wetting events which in turn can lead to ecosystem degradation. Such changes were detected during the early development of the
constructed Hühnerwasser (“Chicken Creek”) catchment in Lusatia, Germany. Surface substrates consisting of
quaternary sandy sediments formed surface seals during the first rainfall events leading to reduced infiltration and
substantially increased surface runoff. Subsequently biological soil crusts formed and stabilised the surface. The
aim of this study is to investigate the factors that cause the hydraulic conductivity to decrease using undisturbed
and disturbed soil samples. Based on the hypothesis that physical and biological crusts lower the hydraulic conductivity, the first set of experiments with undisturbed soil cores from the Hühnerwasser catchment were carried out to measure the saturated hydraulic conductivity using the constant head method. Measurements were done with intact cores and repeated after the surface crust was removed. As the quaternary glacial sediments tend to display hard setting behaviour, we further hypothesised that the mobilisation of fine particles within the cores lead to pore clogging and that wet-dry cycles will therefore decrease hydraulic conductivity. A second set of experiments using the same methodology consisted of five
repeated measurements of hydraulic conductivity after each drying cycle. These measurements were done with
undisturbed core samples as well as repacked cores in order to assess how dry packing affects the dynamics of the
hydraulic conductivity somewhat similar to the situation during the first wetting after completion of the catchment
construction. For all experiments, the temporal evolution of hydraulic conductivity was measured and the turbidity
of the effluent was recorded. The results clearly demonstrated that the substrate is highly unstable. The first set of experiments showed that the removal of the crust lead generally to a decrease in hydraulic conductivity. The process of crust removal represented a severe disturbance of the surface soil which to our understanding causes particle mobilisation and subsequent pore clogging. The first hypothesis could neither be rejected nor accepted. The second set of
experiments showed that the hydraulic conductivity significantly dropped in particular after the first drying event. This was observed for both undisturbed and repacked samples. The following drying cycles further decreased the
hydraulic conductivity in the repacked samples. The decrease in hydraulic conductivity was positively correlated to turbidity values in the effluent of the samples, indicating particle mobilisation in all samples. The results imply that hydraulic properties in such substrates undergo rapid changes that depend on the temporal dynamics of atmospheric drivers, precipitation and evaporative demand, controlling the degree of wetness and the rate and degree of drying during the very early stage after placement. Associated with the dynamics of the atmospheric drivers are the biological changes due to the formation of biological soil crusts and the establishment of vegetation, both of them contributing to the stabilisation of hydraulic properties.
Klimawandelimpaktstudien, welche durch eine Vielzahl von Unsicherheiten gekennzeichnet sind, stellen die Voraussetzung für die Entwicklung von praxistauglichen Anpassungsmaßnahmen an den Klimawandel dar. Dieser Beitrag zeigt Möglichkeiten zur Berücksichtigung von Unsicherheiten in Klimawandelimpaktstudien auf, welche einen modellgestützten Ensembleansatz sowie Trenduntersuchungen an Messwerten beinhalten. Aufgrund der zum Teil gegensätzlichen Entwicklung in der Abflussbildung,
welche insbesondere auf Basis der unterschiedlichen regionalen Klimamodelle simuliert wird, kann die Analyse der Veränderungen der Vergangenheit Aufschluss über gesicherte und weniger gesicherte zukünftige Veränderungen geben. Darüber hinaus ermöglicht die integrierte Betrachtung von vergangenen und zukünftigen Veränderungen den Erwerb eines erweiterten Prozessverständnisses,
welches insbesondere bei der Entwicklung von Anpassungsmaßnahmen erforderlich ist.
Auswirkungen von Unsicherheiten in Klimaszenarien auf die regionale Wassermengenbewirtschaftung
(2014)
In den Lausitzer Flusseinzugsgebieten von Schwarzer Elster, Dahme, Spree und Lausitzer Neiße zeigen sich durch Braunkohlebergbau und vielfältige Bewirtschaftungseinflüsse deutliche Unterschiede zwischen natürlichem Abflussgeschehen und bewirtschafteten Abflüssen. Die möglichen Auswirkungen klimatischer Änderungen werden durch eine Klimawandelimpaktstudie mit dem statistischen Regionalen Klimamodell STAR (3 Klimaszenarien), den hydrologischen Modellen SWIM und EGMO
sowie dem Langfristbewirtschaftungsmodell WBalMo untersucht. Durch niedrigere natürliche Abflüsse und den angenommenen Rückgang der Sümpfungswassermengen aus dem Braunkohlebergbau werden mit WBalMo abnehmende bewirtschaftete Abflüsse simuliert. Unsicherheiten bestehen dabei auf Grund der genutzten Klimaszenarien und hydrologischen Modelle, sowie hinsichtlich der Annahmen
zur zukünftigen wirtschaftlichen Entwicklung (u.a. Braunkohleförderung und –verstromung).
Climate change is expected in Brandenburg, eastern Germany, in terms of increasing annual temperature and changes in climate variability, as well as the number of extreme weather events. Since agroforestry systems have a planning horizon of several decades, long-term yield assessments are required in order to evaluate the economic profitability and environmental sustainability of such systems. Accordingly, our aim was to simulate the tree growth of poplar trees (Populus nigra x P. maximowiczii) in an agroforestry system in Brandenburg for the next forty years. For this purpose, we used the process-oriented Yield-SAFE model, a parameter-sparse, biophysical model developed for the simulation of plant growth in agroforestry systems. For the investigated period from 2011 to 2014, the validation simulations showed clear correlations with the observed values for woody tree biomass. For the unfolding period from 2015 to 2055, a variety of possible climate changes (including higher evaporation requirements and reduced water availability) and their uncertainties were incorporated into our assessment. The tree yield sensitivity to future climatic conditions was evaluated using 100 realizations of a scenario of the statistical regional climate model Statistical Analogue Resampling Scheme (STAR), which assumes an increase in annual temperature of 2K, as well as decreasing annual precipitation by 30–40 mm. The Yield-SAFE model responded sensitively to changes in the meteorological input data, showing that (1) shifts in temperature and/or precipitation would have a directly proportional influence on tree growth and (2) the impact of potential climate changes on tree growth must be assessed in terms of the complex interaction of various influencing factors. This was evidenced, for example, by the fact that higher average annual temperatures could either increase the tree growth due to a prolonged vegetation period or, on the contrary, decrease the tree growth due to higher potential evapotranspiration. The model results are important for the sustainable planning and management of agroforestry systems, upcoming risk assessments, and example analysis of adaptation scenarios in the near and distant future.
Experimental catchments with well-known boundaries and characteristics may contribute valuable data to hydrological, critical zone and landscape evolution research. One of the most well-established and largest constructed catchments is the Chicken Creek catchment (6 ha area including a 0.4 ha pond, Brandenburg, Germany) representing an initial ecosystem undergoing a highly dynamic ecological development starting from clearly defined starting conditions. The water balance dynamics of the catchment was calculated using a simple mass balance approach to reveal the impact of ecological development during 12 years. Water storage in the catchment was calculated from a 3D-model of groundwater volumes, soil moisture measurements and water level recordings of the pond. The catchment water balance equation was resolved for evapotranspiration, the only part that was not measured directly. Due to the known boundary conditions and the inner structure of the catchment, we were able to quantify the different storage compartments and their role in hydrologic response. Our results indicate that for small catchments with a highly dynamic ecological development like the Chicken Creek, the knowledge about saturated and unsaturated storage volumes enables a good estimate and closure of the water balance using a rather simple approach, at least in annual resolution. We found a significant relationship between vegetation cover in the catchment and calculated ET. Time series of meteorological, hydrological, soil and vegetation data over 12 years enabled us to characterize the transient development of the catchment and to evaluate the effect of different feedback mechanisms on catchment hydrology. The dataset from the Chicken Creek catchment indicate at least three phases in ecosystem development, where initial abiotic feedbacks (e.g. erosion) were followed by more and
more biotic controls (e.g. biological soil crusts, vegetation succession and growth). Data from Chicken Creek in high spatial and temporal resolution provide a valuable database underlining the high importance of abiotic/biotic feedback effects that change the hydrologic functioning and response of the catchment more than the water balance itself revealed and thus have to be included in catchment models.
The constructed Hühnerwasser (“Chicken Creek”) catchment is an ecohydrological system in an initial state of development. The catchment with an area of 6 ha was built up from quaternary sediments in the post-mining landscape of Lusatia in Eastern Germany and serves as a critical zone observatory for detecting ecosystem transition. The soil substrate is characterized as sands to loamy sands with low carbonate contents but significant amounts of gypsum in the sediments of the catchment. The catchment undergoes a strong transition from an abiotic system in the initial years to a system with growing influence of biota. Concerning the hydrology, a regime shift from surface runoff to groundwater flow dominated processes is significant. It is of interest, whether the catchment transition is also reflected by hydrogeochemical indicators. We assume gypsum dissolution as dominant process at the catchment scale. In order to investigate the hydrogeochemical evolution of the catchment we analysed electric conductivity, calcium and sulphate concentrations and pH-values of biweekly composite samples from 2007-2013 of the atmospheric deposition, of runoff and soil water. The two observation points in the flowing water represent surface runoff and groundwater discharge respectively. Soil
water has been analysed at four soil pits in three depths. The monitoring data were provided by the Research
Platform Chicken Creek. From the macroscopic data analysis we found an exponential decay of the electric conductivity, calcium and sulphate concentrations in the flowing waters and some of the soil pits. In the flowing water, the decrease slope of the electric conductivity and the calcium and sulphate concentrations is almost identical. The calcium / sulphate molar ratio as an indicator of gypsum dissolution is almost equal to one up to 2010, afterwards more calcium than sulphate is released. The pH-values in the flowing and soil water are generally higher than in the atmospheric deposition, they do show variabilites but no trend behaviour. The time series analyses showed that the interannual variability of the hydrogeochemical properties is less pronounced in the first years of ecosystem development than in the later years. This leads to the conclusion, that in the first years, gypsum dissolution is the major source for calcium and sulphate in the soil and the flowing waters. The increasing interannual variability and changes in the calcium / sulphate ratio in the later years might be interpreted as hydrogeochemical response to the development of vegetation and acidification due to the development of the rhizosphere.