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Declining groundwater levels in some forested regions in Northeast Germany indicate a reduction in groundwater recharge. Various interlinked aspects, such as changes in climate conditions and changes in forest structure, have been considered as the main factors affecting the regional level of groundwater recharge.
For this study, the water balance model WaSiM-ETH was used to calculate groundwater recharge in a 104 km(2) area between 1958 and 2007. Climate impact analysis was driven by observed data from neighbouring meteorological stations. Changes in forest stands were reconstructed from the current status and literature studies.
The model-based analysis showed that the average groundwater recharge under forest areas decreased from 1958 to 2007, with a trend of 2.3 mm/yr(2). The most important effect was changing climatic boundary conditions, which made up 53% of the decrease. Declining precipitation is identified as the main factor. Changes in tree age distribution caused 18% of the decrease, and the change of ground vegetation under pines (Pinus sylvestris) accounts for 29%.
In respect of the complexity and the interconnectivity of the processes of groundwater recharge, the necessity of using process-oriented distributed models such as WaSiM-ETH is discussed.
We conclude that changes in forest stands affecting groundwater recharge could play a significant role in the water balance, especially in regions with a priori low total runoff, this has up to now often remained unquantified.
The classification of small catchments with respect to low flow risk is needed by water and environmental managers to plan adaptation measures for freshwater streams. In this study a new approach is presented to assess the risk of seasonal low flow in the Pleistocene landscape of the Federal State of Brandenburg in Germany. Seasonal low flow and drought in small streams is very common in this region and is predicted to increase due to climate change within the next decades. Data of 15 years (1991-2006) of daily discharge at 37 small catchments (<500 km(2)) and rainfall data from the same region were used. Principal component analyses were applied to the two data sets separately.
The first five principal components of the discharge data, principal components of a precipitation data set covering the same catchments and catchment characteristics were used to explain the patterns found. The first five discharge components explained 72.9% of the total variance in the data set. The first component reflected the general regional discharge pattern. Components 2 and 3 of the discharge data could be related to spatial patterns of precipitation. Components 4 and 5 of the discharge data reflected geohydrologic processes within the catchments. In order to identify catchments with high risk with respect to low flows, component three and five were important as they both identified catchments with faster decrease of flows during summer. These components were used to estimate low flow risk. Catchments located in the northeast of Brandenburg, especially those in the Barnim highlands north and east of Berlin, were identified to be prone to seasonal low flow. There water management measures to adapt to climate change are needed the most.
In the young moraine landscape in Northeast Germany, small glacially created ponds, the so-called kettle holes, are very abundant. They exhibit large spatial heterogeneity, seemingly rendering each kettle hole unique. However, this would not be consistent with any scientific approach. Thus, a classification scheme has been developed for kettle holes in Northeast Germany based on morphology, hydrodynamics and connection to stream networks of the kettle holes as well as size, topography and land use of the respective catchment. These indices are assumed to be related both to water quality as well as to biological issues of the kettle holes. Starting in the mid-1990s, an extensive monitoring program has been established in the federal state of Brandenburg, Germany. In this study, a subset comprising 1,316 samples from 79 kettle holes was analysed, where 21 parameters had been determined. Sampling intervals varied widely, and were between bi-weekly and three-monthly at most sites. A nonlinear principal component analysis was performed. The first four components explained 90% of the variance. These components seem to provide quantitative measures of phosphorus release from the sediments during hypoxic periods, agricultural solute input, algae primary production, and geogenic compounds. This allowed differentiating between the natural and anthropogenic impact factors on water quality. In addition, scores of single components were related to properties of the kettle holes and their environments. The results contribute to a better understanding of biological and biogeochemical processes and can be used to verify the effects of conservation and management strategies for kettle holes.
Reliable hydrological monitoring is the basis for sound water management in drained wetlands. Since statistical methods cannot be employed for unobserved or sparsely monitored areas, the primary design (first set-up) may be arbitrary in most instances. The objective of this paper is therefore to provide a guideline for designing the initial hydrological monitoring network. A scheme is developed that handles different parts of monitoring and hydrometry in wetlands, focusing on the positioning of surface water and groundwater gauges. For placement of the former, control units are used which correspond to areas whose water levels can be regulated separately. The latter are arranged depending on hydrological response units, defined by combinations of soil type and land use, and the chosen surface water monitoring sites. A practical application of the approach is shown for an investigation area in the Spreewald region in north-east Germany. The presented scheme leaves a certain degree of freedom to its user, allowing the inclusion of expert knowledge or special concerns. Based on easily obtainable data, the developed hydrological network serves as a first step in the iterative procedure of monitoring network optimisation. Copyright (c) 2013 John Wiley & Sons, Ltd.
Due to increasing demands and competition for high quality groundwater resources in many parts of the world, there is an urgent need for efficient methods that shed light on the interplay between complex natural settings and anthropogenic impacts. Thus a new approach is introduced, that aims to identify and quantify the predominant processes or factors of influence that drive groundwater and lake water dynamics on a catchment scale. The approach involves a non-linear dimension reduction method called Isometric feature mapping (Isomap). This method is applied to time series of groundwater head and lake water level data from a complex geological setting in Northeastern Germany. Two factors explaining more than 95% of the observed spatial variations are identified: (1) the anthropogenic impact of a waterworks in the study area and (2) natural groundwater recharge with different degrees of dampening at the respective sites of observation. The approach enables a presumption-free assessment to be made of the existing geological conception in the catchment, leading to an extension of the conception. Previously unknown hydraulic connections between two aquifers are identified, and connections revealed between surface water bodies and groundwater. (C) 2014 Elsevier B.V. All rights reserved.
Deep seepage estimation is important for water balance investigations of groundwater and the vadose zone. A simplified Buckingham-Darcy method to assess time series of deep seepage fluxes was proposed by Schindler and Muller (1998). In the method dynamics of water fluxes are calculated by a soil hydraulic conductivity function. Measured soil moistures and matric heads are used as input data. Resulting time series of flux dynamics are scaled to realistic absolute levels by calibrating the method with the areal water balance. An assumption of the method is that water fluxes at different positions exhibit identical dynamics although their absolute values can differ. The aim of this study was to investigate uncertainties of that method depending on the particle size distribution and textural heterogeneity in non-layered soils. We performed a numerical experiment using the two-dimensional Richards Equation. A basic model of transient water fluxes beneath the root and capillary zone was setup and used to simulate time series of soil moisture, matric head, and seepage fluxes for 4221 different cases of particle size distribution and intensities of textural heterogeneity. Soil hydraulic parameters were predicted by the pedotransfer function Rosetta. Textural heterogeneity was modeled with Miller and Miller scaling factors arranged in spatial random fields. Seepage fluxes were calculated with the Buckingham-Darcy method from simulated soil moisture and matric head time series and compared with simulated reference fluxes. The median of Root Mean Square Error was about 0.026 cm d(-1) and the median of maximum cross correlation was 0.96 when the method was calibrated adequately. The method's performance was mainly influenced by (i) the soil textural class and (ii) the time period used for flux calibration. It performed best in sandy loam while hotspots of errors occurred in sand and silty texture. Calibrating the method with time periods that exhibit high variance of seepage fluxes yielded the best performance. The geostatistical properties of the Miller and Miller scaling field influenced the performance only slightly. However, the Miller and Miller scaling procedure generated heterogeneous flow fields that were addressed as main reason for mismatches of simulated reference fluxes and fluxes obtained with the Buckingham-Darcy method.
Hydrology is rich in methods that use information theory to evaluate monitoring networks. Yet in most existing studies, only the available data set as a whole is used, which neglects the intraannual variability of the hydrological system. In this paper, we demonstrate how this variability can be considered by extending monitoring evaluation to subsets of the available data. Therefore, we separately evaluated time windows of fixed length, which were shifted through the data set, and successively extended time windows. We used basic information theory measures and a greedy ranking algorithm based on the criterion of maximum information/minimum redundancy. The network investigated monitored surface and groundwater levels at quarter-hourly intervals and was located at an artificially drained lowland site in the Spreewald region in north-east Germany. The results revealed that some of the monitoring stations were of value permanently while others were needed only temporally. The prevailing meteorological conditions, particularly the amount of precipitation, affected the degree of similarity between the water levels measured. The hydrological system tended to act more individually during periods of no or little rainfall. The optimal monitoring setup, its stability, and the monitoring effort necessary were influenced by the meteorological forcing. Altogether, the methodology presented can help achieve a monitoring network design that has a more even performance or covers the conditions of interest (e.g., floods or droughts) best.
In this paper we report on a series of replicated tracer experiments with deuterium conducted under controlled, steady stormflow conditions at the Gardsjon G1 catchment in south-western Sweden. In five different years, these experiments were carried out in a subcatchment of G1. Deuterium was applied as a narrow pulse so that distributions of water transit times could be directly inferred from the observed tracer breakthrough curves. Significantly different transit times of water were observed under similar experimental conditions. Coefficients of variation for estimated mean transit times were greater than 60%, which can be understood as a measure of the interannual variability for this type of experiments. Implications for water transit times under more natural flow conditions as wells as for future experimentation are discussed. Copyright (c) 2015 John Wiley & Sons, Ltd.
Stream restoration aims at an enhancement of ecological habitats, an increase of water retention within a landscape and sometimes even at an improvement of biogeochemical functions of lotic ecosystems. For the latter, good exchange between groundwater and stream water is often considered to be of major importance. In this study hydraulic connectivity between river and aquifer was investigated for a four years period, covering the restoration of an old oxbow after the second year. The oxbow became reconnected to the stream and the clogging layer in the oxbow was excavated. We expected increasing hydraulic connectivity between oxbow and aquifer after restoration of the stream, and decreasing hydraulic connectivity for the former shortcut due to increased clogging. To test that hypothesis, the spatial and temporal characteristics of the coupled groundwater-stream water system before and after the restoration were analysed by principal component analyses of time series of groundwater heads and stream water levels. The first component depicted between 53% and 70% of the total variance in the dataset for the different years. It captured the propagation of the pressure signal induced by stream water level fluctuations throughout the adjacent aquifer. Thus it could be used as a measure of hydraulic connectivity between stream and aquifer. During the first year, the impact of stream water level fluctuations decreased with distance from the regulated river (shortcut), whereas the hydraulic connection of the oxbow to the adjacent aquifer was very low. After restoration of the stream we observed a slight but not significant increase of hydraulic connectivity in the oxbow in the second year after restoration, but no change for the former shortcut. There is some evidence that the pattern of hydraulic connectivity at the study site is by far more determined by the natural heterogeneity of hydraulic conductivities of the floodplain sediments and the initial construction of the shortcut rather than by the clogging layer in the oxbow. (C) 2015 The Authors. Published by Elsevier B.V.
Runoff, especially during summer months, and low flows have decreased in Central and Eastern Europe during the last decades. A detailed knowledge on predictors and dependencies between meteorological forcing, catchment properties and low flow is necessary to optimize regional adaption strategies to sustain minimum runoff. The objective of this study is to identify low flow predictors for 16 small catchments in Northeast Germany and their long-term shifts between 1965 and 2006. Non-linear regression models (support vector machine regression) were calibrated to iteratively select the most powerful low flow predictors regarding annual 30-day minimum flow (AM(30)). The data set consists of standardized precipitation (SPI) and potential evapotranspiration (SpETI) indices on different time scales and lag times. The potential evapotranspiration of the previous 48 and 3 months, as well as the precipitation of the previous 3 months and last year were the most relevant predictors for AM(30). Pearson correlation (r(2)) of the final model is 0.49 and if for every year the results for all catchments are averaged r(2) increases to 0.80 because extremes are smoothing out. Evapotranspiration was the most important low flow predictor for the study period. However, distinct long-term shifts in the predictive power of variables became apparent. The potential evapotranspiration of the previous 48 months explained most of the variance, but its relevance decreased during the last decades. The importance of precipitation variables increased with time. Model performance was higher at catchments with a more damped discharge behavior. The results indicate changes in the relevant processes or flow paths generating low flows. The identified predictors, temporal patterns and patterns between catchments will support the development of low flow monitoring systems and determine those catchments where adaption measures should aim more at increasing groundwater recharge. (C) 2014 Elsevier B.V. All rights reserved.
Does textural heterogeneity matter? Quantifying transformation of hydrological signals in soils
(2015)
Textural heterogeneity causes complex water flow patterns and soil moisture dynamics in soils that hamper monitoring and modeling soil hydrological processes. These patterns can be generated by process based models considering soil texture heterogeneities. However, there is urgent need for tools for the inverse approach, that is, to analyze observed dynamics in a quantitative way independent from any model approach in order to identify effects of soil texture heterogeneity. Here, studying the transformation of hydrological input signals (e.g., rainfall, snow melt) propagating through the vadose zone is a promising supplement to the common perspective of mass flux considerations. In this study we applied a recently developed new approach for quantitative analysis of hydrological time series (i) to investigate the effect of soil texture on the signal transformation behavior and (ii) to analyze to what degree soil moisture dynamics from a heterogeneous profile can be reproduced by a corresponding homogenous substrate. We used simulation models to generate three data sets of soil moisture time series considering homogeneous substrates (HOM), homogeneous substrates with noise added (NOISE), and heterogeneous substrates (HET). The soil texture classes sand, loamy sand, clay loam and silt were considered. We applied a principal component analysis (also called empirical orthogonal functions) to identify predominant functional patterns and to measure the degree of signal transformation of single time series. For the HOM case 86.7% of the soil moisture dynamics were reproduced by the first two principal components. Based on these results a quantitative measure for the degree of transformation of the input signal was derived. The general nature of signal transformation was nearly identical in all textures, but the intensity of signal damping per depth interval decreased from fine to coarse textures. The same functional patterns occurred in the HET data set. However, here the signal damping of time series did not increase monotonically with soil depth. The analysis succeeded in extracting the same signal transformation behavior from the NOISE data set compared to that of the HOM case in spite of being blurred by random noise. Thus, principal component analysis proved to be a very robust tool to disentangle between independent effects and to measure the degree of transformation of the input signal. The suggested approach can be used for (i) data processing, including subtracting measurement noise (ii) identification of factors controlling soil water dynamics, (iii) assessing the mean signal transformation in heterogeneous soils based on observed soil moisture time series, and (iv) model building, calibration and evaluation. (C) 2015 Elsevier B.V. All rights reserved.
Effects of data and model simplification on the results of a wetland water resource management model
(2016)
This paper presents the development of a wetland water balance model for use in a large river basin with many different wetlands. The basic model was primarily developed for a single wetland with a complex water management system involving large amounts of specialized input data and water management details. The aim was to simplify the model structure and to use only commonly available data as input for the model, with the least possible loss of accuracy. Results from different variants of the model and data adaptation were tested against results from a detailed model. This shows that using commonly available data and unifying and simplifying the input data is tolerable up to a certain level. The simplification of the model has greater effects on the evaluated water balance components than the data adaptation. Because this simplification was necessary for large-scale use, we suggest that, for reasons of comparability, simpler models should always be applied with uniform data bases for large regions, though these should only be moderately simplified. Further, we recommend using these simplified models only for large-scale comparisons and using more specific, detailed models for investigations on smaller scales.
Monitoring the phase space of ecosystems: Concept and examples from the Quillow catchment, Uckermark
(2016)
Ecosystem research benefits enormously from the fact that comprehensive data sets of high quality, and covering long time periods are now increasingly more available. However, facing apparently complex interdependencies between numerous ecosystem components, there is urgent need rethinking our approaches in ecosystem research and applying new tools of data analysis. The concept presented in this paper is based on two pillars. Firstly, it postulates that ecosystems are multiple feedback systems and thus are highly constrained. Consequently, the effective dimensionality of multivariate ecosystem data sets is expected to be rather low compared to the number of observables. Secondly, it assumes that ecosystems are characterized by continuity in time and space as well as between entities which are often treated as distinct units. Implementing this concept in ecosystem research requires new tools for analysing large multivariate data sets. This study presents some of them, which were applied to a comprehensive water quality data set from a long-term monitoring program in Northeast Germany in the Uckermark region, one of the LTER-D (Long Term Ecological Research network, Germany) sites. Short-term variability of the kettle hole water samples differed substantially from that of the stream water samples, suggesting different processes generating the dynamics in these two types of water bodies. However, again, this seemed to be due to differing intensities of single processes rather than to completely different processes. We feel that research aiming at elucidating apparently complex interactions in ecosystems could make much more efficient use from now available large monitoring data sets by implementing the suggested concept and using corresponding innovative tools of system analysis. (C) 2015 Elsevier Ltd. All rights reserved.
Effects of Data and Model Simplification on the Results of a Wetland Water Resource Management Model
(2016)
This paper presents the development of a wetland water balance model for use in a large river basin with many different wetlands. The basic model was primarily developed for a single wetland with a complex water management system involving large amounts of specialized input data and water management details. The aim was to simplify the model structure and to use only commonly available data as input for the model, with the least possible loss of accuracy. Results from different variants of the model and data adaptation were tested against results from a detailed model. This shows that using commonly available data and unifying and simplifying the input data is tolerable up to a certain level. The simplification of the model has greater effects on the evaluated water balance components than the data adaptation. Because this simplification was necessary for large-scale use, we suggest that, for reasons of comparability, simpler models should always be applied with uniform data bases for large regions, though these should only be moderately simplified. Further, we recommend using these simplified models only for large-scale comparisons and using more specific, detailed models for investigations on smaller scales.
Landscapes can be viewed as spatially heterogeneous areas encompassing terrestrial and aquatic domains. To date, most landscape carbon (C) fluxes have been estimated by accounting for terrestrial ecosystems, while aquatic ecosystems have been largely neglected. However, a robust assessment of C fluxes on the landscape scale requires the estimation of fluxes within and between both landscape components. Here, we compiled data from the literature on C fluxes across the air–water interface from various landscape components. We simulated C emissions and uptake for five different scenarios which represent a gradient of increasing spatial heterogeneity within a temperate young moraine landscape: (I) a homogeneous landscape with only cropland and large lakes; (II) separation of the terrestrial domain into cropland and forest; (III) further separation into cropland, forest, and grassland; (IV) additional division of the aquatic area into large lakes and peatlands; and (V) further separation of the aquatic area into large lakes, peatlands, running waters, and small water bodies These simulations suggest that C fluxes at the landscape scale might depend on spatial heterogeneity and landscape diversity, among other factors. When we consider spatial heterogeneity and diversity alone, small inland waters appear to play a pivotal and previously underestimated role in landscape greenhouse gas emissions that may be regarded as C hot spots. Approaches focusing on the landscape scale will also enable improved projections of ecosystems’ responses to perturbations, e.g., due to global change and anthropogenic activities, and evaluations of the specific role individual landscape components play in regional C fluxes. WIREs Water 2016, 3:601–617. doi: 10.1002/wat2.1147
Solute concentration variability is of fundamental importance for the chemical and ecological state of streams. It is often closely related to discharge variability and can be characterized in terms of a solute export regime. Previous studies, especially in lowland catchments, report that nitrate is often exported with an accretion pattern of increasing concentrations with increasing discharge. Several modeling approaches exist to predict the export regime of solutes from the spatial relationship of discharge generating zones with solute availability in the catchment. For a small agriculturally managed lowland catchment in central Germany, we show that this relationship is controlled by the depth to groundwater table and its temporal dynamics. Principal component analysis of groundwater level time series from wells distributed throughout the catchment allowed derivation of a representative groundwater level time series that explained most of the discharge variability. Groundwater sampling revealed consistently decreasing nitrate concentrations with an increasing thickness of the unsaturated zone. The relationships of depth to groundwater table to discharge and to nitrate concentration were parameterized and integrated to successfully model catchment discharge and nitrate export on the basis of groundwater level variations alone. This study shows that intensive and uniform agricultural land use likely results in a clear and consistent concentration-depth relationship of nitrate, which can be utilized in simple approaches to predict stream nitrate export dynamics at the catchment scale. (C) 2016 Elsevier Ltd. All rights reserved.
Carbon and nutrient cycling in kettle hole sediments depending on hydrological dynamics: a review
(2016)
Kettle holes as a specific group of isolated, small lentic freshwater systems (LFS) often are (i) hot spots of biogeochemical cycling and (ii) exposed to frequent sediment desiccation and rewetting. Their ecological functioning is greatly determined by immanent carbon and nutrient transformations. The objective of this review is to elucidate effects of a changing hydrological regime (i.e., dry-wet cycles) on carbon and nutrient cycling in kettle hole sediments. Generally, dry-wet cycles have the potential to increase C and N losses as well as P availability. However, their duration and frequency are important controlling factors regarding direction and intensity of biogeochemical and microbiological responses. To evaluate drought impacts on sediment carbon and nutrient cycling in detail requires the context of the LFS hydrological history. For example, frequent drought events induce physiological adaptation of exposed microbial communities and thus flatten metabolic responses, whereas rare events provoke unbalanced, strong microbial responses. Different potential of microbial resilience to drought stress can irretrievably change microbial communities and functional guilds, gearing cascades of functional responses. Hence, dry-wet events can shift the biogeochemical cycling of organic matter and nutrients to a new equilibrium, thus affecting the dynamic balance between carbon burial and mineralization in kettle holes.
This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease (P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.