Determination of yield and quality parameters of energy crops applying laboratory and field spectroscopy

A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.

Digitales stochastisches Magnetfeld-Sensorarray

Digitales stochastisches Magnetfeld-Sensorarray Stefan Rohrer Im Rahmen eines mehrjährigen Forschungsprojektes, gefördert von der Deutschen Forschungsgesellschaft (DFG), wurden am Institut für Mikroelektronik (IPM) der Universität Kassel digitale Magnetfeldsensoren mit einer Breite bis zu 1 µm entwickelt. Die vorliegende Dissertation stellt ein aus diesem Forschungsprojekt entstandenes Magnetfeld-Sensorarray vor, das speziell dazu entworfen wurde, um digitale Magnetfelder schnell und auf minimaler Fläche mit einer guten räumlichen und zeitlichen Auflösung zu detektieren. Der noch in einem 1,0µm-CMOS-Prozess gefertigte Test-Chip arbeitet bis zu einer Taktfrequenz von 27 MHz bei einem Sensorabstand von 6,75 µm. Damit ist er das derzeit kleinste und schnellste digitale Magnetfeld-Sensorarray in einem Standard-CMOS-Prozess. Konvertiert auf eine 0,09µm-Technologie können Frequenzen bis 1 GHz erreicht werden bei einem Sensorabstand von unter 1 µm. In der Dissertation werden die wichtigsten Ergebnisse des Projekts detailliert beschrieben. Basis des Sensors ist eine rückgekoppelte Inverter-Anordnung. Als magnetfeldsensitives Element dient ein auf dem Hall-Effekt basierender Doppel-Drain-MAGFET, der das Verhalten der Kippschaltung beeinflusst. Aus den digitalen Ausgangsdaten kann die Stärke und die Polarität des Magnetfelds bestimmt werden. Die Gesamtanordnung bildet einen stochastischen Magnetfeld-Sensor. In der Arbeit wird ein Modell für das Kippverhalten der rückgekoppelten Inverter präsentiert. Die Rauscheinflüsse des Sensors werden analysiert und in einem stochastischen Differentialgleichungssystem modelliert. Die Lösung der stochastischen Differentialgleichung zeigt die Entwicklung der Wahrscheinlichkeitsverteilung des Ausgangssignals über die Zeit und welche Einflussfaktoren die Fehlerwahrscheinlichkeit des Sensors beeinflussen. Sie gibt Hinweise darauf, welche Parameter für das Design und Layout eines stochastischen Sensors zu einem optimalen Ergebnis führen. Die auf den theoretischen Berechnungen basierenden Schaltungen und Layout-Komponenten eines digitalen stochastischen Sensors werden in der Arbeit vorgestellt. Aufgrund der technologisch bedingten Prozesstoleranzen ist für jeden Detektor eine eigene kompensierende Kalibrierung erforderlich. Unterschiedliche Realisierungen dafür werden präsentiert und bewertet. Zur genaueren Modellierung wird ein SPICE-Modell aufgestellt und damit für das Kippverhalten des Sensors eine stochastische Differentialgleichung mit SPICE-bestimmten Koeffizienten hergeleitet. Gegenüber den Standard-Magnetfeldsensoren bietet die stochastische digitale Auswertung den Vorteil einer flexiblen Messung. Man kann wählen zwischen schnellen Messungen bei reduzierter Genauigkeit und einer hohen lokalen Auflösung oder einer hohen Genauigkeit bei der Auswertung langsam veränderlicher Magnetfelder im Bereich von unter 1 mT. Die Arbeit präsentiert die Messergebnisse des Testchips. Die gemessene Empfindlichkeit und die Fehlerwahrscheinlichkeit sowie die optimalen Arbeitspunkte und die Kennliniencharakteristik werden dargestellt. Die relative Empfindlichkeit der MAGFETs beträgt 0,0075/T. Die damit erzielbaren Fehlerwahrscheinlichkeiten werden in der Arbeit aufgelistet. Verglichen mit dem theoretischen Modell zeigt das gemessene Kippverhalten der stochastischen Sensoren eine gute Übereinstimmung. Verschiedene Messungen von analogen und digitalen Magnetfeldern bestätigen die Anwendbarkeit des Sensors für schnelle Magnetfeldmessungen bis 27 MHz auch bei kleinen Magnetfeldern unter 1 mT. Die Messungen der Sensorcharakteristik in Abhängigkeit von der Temperatur zeigen, dass die Empfindlichkeit bei sehr tiefen Temperaturen deutlich steigt aufgrund der Abnahme des Rauschens. Eine Zusammenfassung und ein ausführliches Literaturverzeichnis geben einen Überblick über den Stand der Technik.

Experimentelle und numerische Untersuchungen zur Dispersion von Dichteströmungen in einem stochastischen Modellaquifer

Es ist bekannt, dass die Dichte eines gelösten Stoffes die Richtung und die Stärke seiner Bewegung im Untergrund entscheidend bestimmen kann. Eine Vielzahl von Untersuchungen hat gezeigt, dass die Verteilung der Durchlässigkeiten eines porösen Mediums diese Dichteffekte verstärken oder abmindern kann. Wie sich dieser gekoppelte Effekt auf die Vermischung zweier Fluide auswirkt, wurde in dieser Arbeit untersucht und dabei das experimentelle sowohl mit dem numerischen als auch mit dem analytischen Modell gekoppelt. Die auf der Störungstheorie basierende stochastische Theorie der macrodispersion wurde in dieser Arbeit für den Fall der transversalen Makodispersion. Für den Fall einer stabilen Schichtung wurde in einem Modelltank (10m x 1.2m x 0.1m) der Universität Kassel eine Serie sorgfältig kontrollierter zweidimensionaler Experimente an einem stochastisch heterogenen Modellaquifer durchgeführt. Es wurden Versuchsreihen mit variierenden Konzentrationsdifferenzen (250 ppm bis 100 000 ppm) und Strömungsgeschwindigkeiten (u = 1 m/ d bis 8 m/d) an drei verschieden anisotrop gepackten porösen Medien mit variierender Varianzen und Korrelationen der lognormal verteilten Permeabilitäten durchgeführt. Die stationäre räumliche Konzentrationsausbreitung der sich ausbreitenden Salzwasserfahne wurde anhand der Leitfähigkeit gemessen und aus der Höhendifferenz des 84- und 16-prozentigen relativen Konzentrationsdurchgang die Dispersion berechnet. Parallel dazu wurde ein numerisches Modell mit dem dichteabhängigen Finite-Elemente-Strömungs- und Transport-Programm SUTRA aufgestellt. Mit dem kalibrierten numerischen Modell wurden Prognosen für mögliche Transportszenarien, Sensitivitätsanalysen und stochastische Simulationen nach der Monte-Carlo-Methode durchgeführt. Die Einstellung der Strömungsgeschwindigkeit erfolgte - sowohl im experimentellen als auch im numerischen Modell - über konstante Druckränder an den Ein- und Auslauftanks. Dabei zeigte sich eine starke Sensitivität der räumlichen Konzentrationsausbreitung hinsichtlich lokaler Druckvariationen. Die Untersuchungen ergaben, dass sich die Konzentrationsfahne mit steigendem Abstand von der Einströmkante wellenförmig einem effektiven Wert annähert, aus dem die Makrodispersivität ermittelt werden kann. Dabei zeigten sich sichtbare nichtergodische Effekte, d.h. starke Abweichungen in den zweiten räumlichen Momenten der Konzentrationsverteilung der deterministischen Experimente von den Erwartungswerten aus der stochastischen Theorie. Die transversale Makrodispersivität stieg proportional zur Varianz und Korrelation der lognormalen Permeabilitätsverteilung und umgekehrt proportional zur Strömungsgeschwindigkeit und Dichtedifferenz zweier Fluide. Aus dem von Welty et al. [2003] mittels Störungstheorie entwickelten dichteabhängigen Makrodispersionstensor konnte in dieser Arbeit die stochastische Formel für die transversale Makrodispersion weiter entwickelt und - sowohl experimentell als auch numerisch - verifiziert werden.

Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes apriori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y'Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is applied for real data. The corresponding outcomes are compared with the results of other methods for the same data. Thereby, the special BAIQUE, which estimates the general variance of the data, achieves a very close result to the classical empirical variance.

Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

Das Einzugsgebiet der Fulda - Untersuchung der Methoden der Hochwasserstatistik im Zeichen des Klimawandels

Numerous studies have proven an effect of a probable climate change on the hydrosphere’s different subsystems. In the 21st century global and regional redistribution of water has to be expected and it is very likely that extreme weather phenomenon will occur more frequently. From a global view the flood situation will exacerbate. In contrast to these discoveries the classical approach of flood frequency analysis provides terms like “mean flood recurrence interval”. But for this analysis to be valid there is a need for the precondition of stationary distribution parameters which implies that the flood frequencies are constant in time. Newer approaches take into account extreme value distributions with time-dependent parameters. But the latter implies a discard of the mentioned old terminology that has been used up-to-date in engineering hydrology. On the regional scale climate change affects the hydrosphere in various ways. So, the question appears to be whether in central Europe the classical approach of flood frequency analysis is not usable anymore and whether the traditional terminology should be renewed. In the present case study hydro-meteorological time series of the Fulda catchment area (6930 km²), upstream of the gauging station Bonaforth, are analyzed for the time period 1960 to 2100. At first a distributed catchment area model (SWAT2005) is build up, calibrated and finally validated. The Edertal reservoir is regulated as well by a feedback control of the catchments output in case of low water. Due to this intricacy a special modeling strategy has been necessary: The study area is divided into three SWAT basin models and an additional physically-based reservoir model is developed. To further improve the streamflow predictions of the SWAT model, a correction by an artificial neural network (ANN) has been tested successfully which opens a new way to improve hydrological models. With this extension the calibration and validation of the SWAT model for the Fulda catchment area is improved significantly. After calibration of the model for the past 20th century observed streamflow, the SWAT model is driven by high resolution climate data of the regional model REMO using the IPCC scenarios A1B, A2, and B1, to generate future runoff time series for the 21th century for the various sub-basins in the study area. In a second step flood time series HQ(a) are derived from the 21st century runoff time series (scenarios A1B, A2, and B1). Then these flood projections are extensively tested with regard to stationarity, homogeneity and statistical independence. All these tests indicate that the SWAT-predicted 21st-century trends in the flood regime are not significant. Within the projected time the members of the flood time series are proven to be stationary and independent events. Hence, the classical stationary approach of flood frequency analysis can still be used within the Fulda catchment area, notwithstanding the fact that some regional climate change has been predicted using the IPCC scenarios. It should be noted, however, that the present results are not transferable to other catchment areas. Finally a new method is presented that enables the calculation of extreme flood statistics, even if the flood time series is non-stationary and also if the latter exhibits short- and longterm persistence. This method, which is called Flood Series Maximum Analysis here, enables the calculation of maximum design floods for a given risk- or safety level and time period.

Effects of plant diversity on bioenergy parameters in grassland biomass

Extensive grassland biomass for bioenergy production has long been subject of scientific research. The possibility of combining nature conservation goals with a profitable management while reducing competition with food production has created a strong interest in this topic. However, the botanical composition will play a key role for solid fuel quality of grassland biomass and will have effects on the combustion process by potentially causing corrosion, emission and slagging. On the other hand, botanical composition will affect anaerobic digestibility and thereby the biogas potential. In this thesis aboveground biomass from the Jena-Experiment plots was harvested in 2008 and 2009 and analysed for the most relevant chemical constituents effecting fuel quality and anaerobic digestibility. Regarding combustion, the following parameters were of main focus: higher heating value (HHV), gross energy yield (GE), ash content, ash softening temperature (AST), K, Ca, Mg, N, Cl and S content. For biogas production the following parameters were investigated: substrate specific methane yield (CH4 sub), area specific methane yield (CH4 area), crude fibre (CF), crude protein (CP), crude lipid (CL) and nitrogen-free extract (NfE). Furthermore, an improvement of the fuel quality was investigated through applying the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Through the specific setup of the Jena-Experiment it was possible to outline the changes of these parameters along two diversity gradients: (i) species richness (SR; 1 to 60 species) and (ii) functional group (grasses, legumes, small herbs and tall herbs) presence. This was a novel approach on investigating the bioenergy characteristic of extensive grassland biomass and gave detailed insight in the sward-composition¬ - bioenergy relations such as: (i) the most relevant SR effect was the increase of energy yield for both combustion (annual GE increased by 26% from SR8→16 and by 65% from SR8→60) and anaerobic digestion (annual CH4 area increased by 22% from SR8→16 and by 49% from SR8→60) through a strong interaction of SR with biomass yield; (ii) legumes play a key role for the utilization of grassland biomass for energy production as they increase the energy content of the substrate (HHV and CH4 sub) and the energy yield (GE and CH4 area); (iii) combustion is the conversion technique that will yield the highest energy output but requires an improvement of the solid fuel quality in order to reduce the risk of corrosion, emission and slagging related problems. This was achieved through applying the IFBB-procedure, with reductions in ash (by 23%), N (28%), K (85%), Cl (56%) and S (59%) and equal levels of concentrations along the SR gradient.

Downscaling and Modeling the Effects of Climate Change on Hydrology and Water Resources in the Upper Blue Nile River Basin, Ethiopia

The Upper Blue Nile River Basin (UBNRB) located in the western part of Ethiopia, between 7° 45’ and 12° 45’N and 34° 05’ and 39° 45’E has a total area of 174962 km2 . More than 80% of the population in the basin is engaged in agricultural activities. Because of the particularly dry climate in the basin, likewise to most other regions of Ethiopia, the agricultural productivity depends to a very large extent on the occurrence of the seasonal rains. This situation makes agriculture highly vulnerable to the impact of potential climate hazards which are about to inflict Africa as a whole and Ethiopia in particular. To analyze these possible impacts of future climate change on the water resources in the UBNRB, in the first part of the thesis climate projection for precipitation, minimum and maximum temperatures in the basin, using downscaled predictors from three GCMs (ECHAM5, GFDL21 and CSIRO-MK3) under SRES scenarios A1B and A2 have been carried out. The two statistical downscaling models used are SDSM and LARS-WG, whereby SDSM is used to downscale ECHAM5-predictors alone and LARS-WG is applied in both mono-model mode with predictors from ECHAM5 and in multi-model mode with combined predictors from ECHAM5, GFDL21 and CSIRO-MK3. For the calibration/validation of the downscaled models, observed as well as NCEP climate data in the 1970 - 2000 reference period is used. The future projections are made for two time periods; 2046-2065 (2050s) and 2081-2100 (2090s). For the 2050s future time period the downscaled climate predictions indicate rise of 0.6°C to 2.7°C for the seasonal maximum temperatures Tmax, and of 0.5°C to 2.44°C for the minimum temperatures Tmin. Similarly, during the 2090s the seasonal Tmax increases by 0.9°C to 4.63°C and Tmin by 1°C to 4.6°C, whereby these increases are generally higher for the A2 than for the A1B scenario. For most sub-basins of the UBNRB, the predicted changes of Tmin are larger than those of Tmax. Meanwhile, for the precipitation, both downscaling tools predict large changes which, depending on the GCM employed, are such that the spring and summer seasons will be experiencing decreases between -36% to 1% and the autumn and winter seasons an increase of -8% to 126% for the two future time periods, regardless of the SRES scenario used. In the second part of the thesis the semi-distributed, physically based hydrologic model, SWAT (Soil Water Assessment Tool), is used to evaluate the impacts of the above-predicted future climate change on the hydrology and water resources of the UBNRB. Hereby the downscaled future predictors are used as input in the SWAT model to predict streamflow of the Upper Blue Nile as well as other relevant water resources parameter in the basin. Calibration and validation of the streamflow model is done again on 1970-2000 measured discharge at the outlet gage station Eldiem, whereby the most sensitive out the numerous “tuneable” calibration parameters in SWAT have been selected by means of a sophisticated sensitivity analysis. Consequently, a good calibration/validation model performance with a high NSE-coefficient of 0.89 is obtained. The results of the future simulations of streamflow in the basin, using both SDSM- and LARS-WG downscaled output in SWAT reveal a decline of -10% to -61% of the future Blue Nile streamflow, And, expectedly, these obviously adverse effects on the future UBNRB-water availibiliy are more exacerbated for the 2090’s than for the 2050’s, regardless of the SRES.

Numerical Feasibility Study for Treated Wastewater Recharge as a Tool to Impede Saltwater Intrusion in the Coastal Aquifer of Gaza – Palestine

The ongoing depletion of the coastal aquifer in the Gaza strip due to groundwater overexploitation has led to the process of seawater intrusion, which is continually becoming a serious problem in Gaza, as the seawater has further invaded into many sections along the coastal shoreline. As a first step to get a hold on the problem, the artificial neural network (ANN)-model has been applied as a new approach and an attractive tool to study and predict groundwater levels without applying physically based hydrologic parameters, and also for the purpose to improve the understanding of complex groundwater systems and which is able to show the effects of hydrologic, meteorological and anthropogenic impacts on the groundwater conditions. Prediction of the future behaviour of the seawater intrusion process in the Gaza aquifer is thus of crucial importance to safeguard the already scarce groundwater resources in the region. In this study the coupled three-dimensional groundwater flow and density-dependent solute transport model SEAWAT, as implemented in Visual MODFLOW, is applied to the Gaza coastal aquifer system to simulate the location and the dynamics of the saltwater–freshwater interface in the aquifer in the time period 2000-2010. A very good agreement between simulated and observed TDS salinities with a correlation coefficient of 0.902 and 0.883 for both steady-state and transient calibration is obtained. After successful calibration of the solute transport model, simulation of future management scenarios for the Gaza aquifer have been carried out, in order to get a more comprehensive view of the effects of the artificial recharge planned in the Gaza strip for some time on forestall, or even to remedy, the presently existing adverse aquifer conditions, namely, low groundwater heads and high salinity by the end of the target simulation period, year 2040. To that avail, numerous management scenarios schemes are examined to maintain the ground water system and to control the salinity distributions within the target period 2011-2040. In the first, pessimistic scenario, it is assumed that pumping from the aquifer continues to increase in the near future to meet the rising water demand, and that there is not further recharge to the aquifer than what is provided by natural precipitation. The second, optimistic scenario assumes that treated surficial wastewater can be used as a source of additional artificial recharge to the aquifer which, in principle, should not only lead to an increased sustainable yield of the latter, but could, in the best of all cases, revert even some of the adverse present-day conditions in the aquifer, i.e., seawater intrusion. This scenario has been done with three different cases which differ by the locations and the extensions of the injection-fields for the treated wastewater. The results obtained with the first (do-nothing) scenario indicate that there will be ongoing negative impacts on the aquifer, such as a higher propensity for strong seawater intrusion into the Gaza aquifer. This scenario illustrates that, compared with 2010 situation of the baseline model, at the end of simulation period, year 2040, the amount of saltwater intrusion into the coastal aquifer will be increased by about 35 %, whereas the salinity will be increased by 34 %. In contrast, all three cases of the second (artificial recharge) scenario group can partly revert the present seawater intrusion. From the water budget point of view, compared with the first (do nothing) scenario, for year 2040, the water added to the aquifer by artificial recharge will reduces the amount of water entering the aquifer by seawater intrusion by 81, 77and 72 %, for the three recharge cases, respectively. Meanwhile, the salinity in the Gaza aquifer will be decreased by 15, 32 and 26% for the three cases, respectively.

Interrelatedness of grazing livestock with vegetation parameters and farmers’ livelihoods in the Mahafaly region, southwestern Madagascar

The study aims to get deeper insight into the highly extensive system of animal husbandry in the Mahafaly region of southwestern Madagascar. It tries to understand the major drivers for pastoral dynamics, land and resource use along a gradient in altitude and vegetation to consider the area’s high spatial and temporal heterogeneity. The study also analyzes the reproductive performance of local livestock as well as the owners’ culling strategies to determine herd dynamics, opportunities for economic growth, and future potential for rural development. Across seasons, plateau herds from both livestock species covered longer distances (cattle 13.6±3.02 km, goats 12.3±3.48 km) and were found further away from the settlements (cattle 3.1±0.96 km, goats 2.8±0.98 km) than those from the coastal plain (walking_dist: cattle 9.5±3.25 km, goats 9.2±2.57 km; max_dist: cattle 2.6±1.28 km, goats 1.8±0.61 km). Transhumant cattle were detected more vulnerable through limited access to pasture land and water resources compared to local herds. Seasonal water shortage has been confirmed as a key constraint on the plateau while livestock keeping along the coast is more limited by dry season forage availability. However, recent security issues and land use conflicts with local crop farmers are gaining importance and force livestock owners to adapt their traditional grazing management, resulting in spatio-temporal variation of livestock numbers and in the impending risk of local overgrazing and degradation of rangelands. Among the 133 plant species consumed by livestock, 13 were determined of major importance for the animals’ nutrition. The nutritive value and digestibility of the natural forage, as well as its abundance in the coastal zone, substantially decreased over the course of the dry season and emphasized the importance of supplementary forage plants, in particular Euphorbia stenoclada. At the same time, an unsustainable utilization and overexploitation of its wild stocks may raise the pressure on the vegetation and pasture resources within the nearby Tsimanampetsotsa National Park. Age at first parturition was 40.5±0.59 months for cattle and 21.3±0.63 months for goats. Both species showed long parturition intervals (cattle 24.2±0.48 months, goats 12.4±0.30 months), mostly due to the maintenance of poorly performing breeding females within the herds. Reported offspring mortality, however, was low with 2.5% of cattle and 18.8% of goats dying before reaching maturity. The analysis of economic information revealed higher than expected market dynamics, especially for zebus, resulting in annual contribution margins of 33 € per cattle unit and 11 € per goat unit. The application of the PRY Herd Life model to simulate herd development for present management and two alternate scenarios confirmed the economic profitability of the current livestock system and showed potential for further productive and economic development. However, this might be clearly limited by the region’s restricted carrying capacity. Summarizing, this study illustrates the highly extensive and resources-driven character of the livestock system in the Mahafaly region, with herd mobility being a central element to cope with seasonal shortages in forage and water. But additional key drivers and external factors are gaining importance and increasingly affect migration decisions and grazing management. This leads to an increased risk of local overgrazing and overexploitation of natural pasture resources and intensifies the tension between pastoral and conservation interests. At the same time, it hampers the region’s agronomic development, which has not yet been fully exploited. The situation therefore demonstrates the need for practical improvement suggestions and implication measures, such as the systematic forestation of supplemental forage plant species in the coastal zone or a stronger integration of animal husbandry and crop production, to sustain the traditional livestock system without compromising peoples’ livelihoods while at the same time minimizing the pastoral impact on the area’s unique nature and environment.