The aim of this research is to investigate the application of nonlinear programming techniques to multipurpose reservoir systems. A multipurpose multiple reservoir operation problem is a typical nonlinear large scale optimization problem. The currently applied techniques overcome the nonlinearity and dimensionality problems through simplification. To model the problem more closely, a successful trial is made in this study to apply the most efficient and suitable nonlinear programming techniques. Although research in large scale nonlinear optimization has been in recent'years a major subject of interest within the mathematical programming community, its application to reservoir systems is very limited. As a result of these activities software packages, as Lancelot, have been developed. Lancelot is a general purpose software package designed for solving large-scale nonlinear optimization problems. It uses Augmented Lagrangian and Conjugate Gradient methods. This software is used here successfully to solve an optimization problem formulated for a major river system, the Blue Nile in Sudan. The system has two in series reservoirs used for hydropower generation, maintaining minimum downstream flows and irrigation. For optimization, some features of the system have been modelled. These are sedimentation, evaporation, demand and flow. To represent the effect of sedimentation a model is fitted and verified. To include the effect of evaporation a model that estimates the total evaporation losses is fitted using Penman approach and verified using water balance. To cope with flow uncertainty the Blue Nile flow has been modelled. ARMA(1,1) has given the best fitting. Irrigation requirements have been estimated using Penman- Monteith approach. Efficiency of water use has been investigated and other possible demand scenarios resulting from efficient water use are obtained. The results of flow and demand modelling are used as direct input to the optimization model while sedimentation and evaporation models are incorporated in the model. The objective of this model is to maximise power benefits on condition that certain irrigation and downstream requirements be met. To solve this problem a double precision version of Lancelot was installed in a hp-UNIX system. For the problem a specification and a standard input format, SEF, files were written and put under the same directory with Lancelot to run the program. The problem was solved successfully in few minutes. The solution includes values for the objective function, decision variables (releases and storage volumes), penalty parameter, Lagrange multipliers and slack variables. The optimization output is affected by reservoir sedimentation. Therefore the developed optimization and sedimentation models have been linked to investigate sedimentation effect on optimization on output along the course of reservoir operation. Results have shown that this approach can be used to investigate the effect of sedimentation on reservoir optimum output. In, a multipurpose reservoir system, the optimization output for one purpose is affected by the efficiency of water use for other purposes. Therefore the effect of efficient water use in irrigation on power benefits is investigated. Results have shown an increment in benefits due to using irrigation water efficiently. This approach can be applied to systems where priority is given for one purpose over the others.

On the Blue Nile in Sudan, near the Ethiopian border, there is a measurement station named El Deim. The discharge assessments carried out at this station are crucial for the water resource management in Sudan. Due to changed conditions, caused by a heightening of the downstream-located Roseires dam, new methods for discharge assessment are needed. The objective of the present study was to examine possibilities and methodologies to assess the discharge at this station. The flow dynamics was examined through steady state as well as dynamic hydraulic modeling by use of the Mike 11 modeling software package. By simulating possible future scenarios, in the aspect of discharge variations in the Blue Nile and water level variations in the reservoir, the effects from the raised dam on El Deim could be studied. The model was based on bathymetrical data in form of cross sections. As boundary conditions for the simulation, measured and synthetic data series of discharge and water levels were used. The known measured water levels at El Deim were compared with the simulated water levels at El Deim for the same discharge scenarios. The modeled value corresponds well to the measured values. The existing discrepancies between the simulated and measured values are likely caused by insufficient bathymetrical data.   Simulation results show that the flow dynamics at El Deim are highly dependent on the water level of the reservoir and the discharge’s rate of variation. Accordingly, rating curves were created for a range of water levels at the reservoir. With the use of these curves, and tables/equations based on them, the discharge can be rated by knowing the water level at the Roseires dam and El Deim. However, the results from this study are more a description of the principles of how the discharge ratings could be performed. If the methodology and rating tools from this study are planned to be implemented the model must be improved with more bathymetrical data. The improvements are needed to create more accurate curves, tables and equations for discharge rating. Discharge ratings can then be produced and enable better operation of Roseires dam and a more efficient use of the valuable water resources in Sudan. In order to test the applicability of the created model and produced rating tools they should be compared with new measurement data from El Deim with the heightened Roseires dam fully implemented.   It is possible to assess the discharge at El Deim even when backwater effects affect the station. The methodology developed in this thesis would be applicable for similar studies at other locations.

No description available.

Frequent climatic shocks have presented challenges for rainfed agriculture in sub-Saharan Africa. Appropriate water management practices are among the solutions to the challenges. The role of water harvesting in achieving sustainable agricultural intensification and specified resilience was explored. Suitable areas for water harvesting in the Upper Blue Nile basin were identified. The usefulness of the Curve Number method for surface runoff estimation was evaluated, and was found to perform satisfactorily. The impact of climate change in the Lake Tana sub-basin was studied. A decision support system was developed for locating and sizing of water harvesting ponds in the SWAT model. Methodological developments enabled analysis of the implications of water harvesting intensification in a meso-scale watershed in the Lake Tana sub-basin. Results suggest that water harvesting can increase agricultural productivity, sustain ecosystems and build specified resilience, and thereby contribute to sustainable agricultural intensification. There is considerable potential for water harvesting in the Upper Blue Nile Basin. Rainfall may increase in the Lake Tana sub-basin due to climate change. Supplementary irrigation from water harvesting ponds and better nutrient application increased staple crop production by up to three-fold. Moreover, a substantial amount of cash crop was produced using dry seasonal irrigation. Water harvesting altered the streamflow regime, and reduced sediment loss from the watershed.       Water harvesting can play an important role in food security. It showed potential to buffer climatic variability. In the watershed studied, water harvesting will not compromise the environmental water requirements. Instead, increased low flows, and reduced flooding and sediment loss may benefit the social-ecological systems. The adverse effects of disturbance of the natural flow variability and sediment influx to certain riverine ecosystems warrant detailed investigation. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript. Paper 5: Epub ahead of print. Paper 6: Manuscript.</p> / Water resources management and social-ecological resilience

<p>Land and water resources degradation are the major problems on the Ethiopian highlands. Poor land use practices and improper management systems have played a significant role in causing high soil erosion rates, sediment transport and loss of agricultural nutrients. So far limited meas-ures have been taken to combat the problems. In this study a physically based watershed model, SWAT2005 was applied to the Northern Highlands of Ethiopia for modelling of the hydrology and sediment yield. The main objective of this study was to test the performance and feasibility of SWAT2005 model to examine the influence of topography, land use, soil and climatic condi-tion on streamflows, soil erosion and sediment yield. The model was calibrated and validated on four tributaries of Lake Tana as well as Anjeni watershed using SUFI-2, GLUE and ParaSol algo-rithms. SWAT and GIS based decision support system (MCE analysis) were also used to identify the most erosion prone areas in the Lake Tana Basin. Streamflows are more sensitive to the hy-drological response unites definition thresholds than subbasin discretization. Prediction of sedi-ment yield is highly sensitive to subbasin size and slope discretization. Baseflow is an important component of the total discharge within the study area that contributes more than the surface runoff. There is a good agreement between the measured and simulated flows and sediment yields with higher values of coefficients of determination and Nash Sutcliffe efficiency. The an-nual average measured sediment yield in Anjeni watershed was 24.6 tonnes/ha. The annual aver-age simulated sediment yield was 27.8 and 29.5 tonnes/ha for calibration and validation periods, respectively. The SWAT model indicated that 18.5 % of the Lake Tana Basin is erosion potential areas. Whereas the MCE result indicated that 25.5 % of the basin are erosion potential areas. The calibrated model can be used for further analysis of the effect of climate and land use change as well as other different management scenarios on streamflows and soil erosion. The result of the study could help different stakeholders to plan and implement appropriate soil and water conser-vation strategies.</p>

Following the hierarchical nature of forest resource management, the present work focuses on the natural forest cover at various abstraction levels of details, i.e. categorical land use/land cover (LU/LC) level and a continuous empirical estimation of local operational level. As no single sensor presently covers absolutely all the requirements of the entire levels of forest resource assessment, multisource imagery (i.e. RapidEye, TERRA ASTER and LANDSAT TM), in addition to other data and knowledge have been examined. To deal with this structure, an object-based image analysis (OBIA) approach has been assessed in the destabilized Blue Nile region of Sudan as a potential solution to gather the required information for future forest planning and decision making. Moreover, the spatial heterogeneity as well as the rapid changes observed in the region motivates the inspection for more efficient, flexible and accurate methods to update the desired information. An OBIA approach has been proposed as an alternative analysis framework that can mitigate the deficiency associated with the pixel-based approach. In this sense, the study examines the most popular pixel-based maximum likelihood classifier, as an example of the behavior of spectral classifier toward respective data and regional specifics. In contrast, the OBIA approach analyzes remotely sensed data by incorporating expert analyst knowledge and complimentary ancillary data in a way that somehow simulates human intelligence for image interpretation based on the real-world representation of the features. As the segment is the basic processing unit, various combinations of segmentation criteria were tested to separate similar spectral values into groups of relatively homogeneous pixels. At the categorical subtraction level, rules were developed and optimum features were extracted for each particular class. Two methods were allocated (i.e. Rule Based (RB) and Nearest Neighbour (NN) Classifier) to assign segmented objects to their corresponding classes. Moreover, the study attempts to answer the questions whether OBIA is inherently more precise at fine spatial resolution than at coarser resolution, and how both pixel-based and OBIA approaches can be compared regarding relative accuracy in function of spatial resolution. As anticipated, this work emphasizes that the OBIA approach is can be proposed as an advanced solution particulary for high resolution imagery, since the accuracies were improved at the different scales applied compare with those of pixel-based approach. Meanwhile, the results achieved by the two approaches are consistently high at a finer RapidEye spatial resolution, and much significantly enhanced with OBIA. Since the change in LU/LC is rapid and the region is heterogeneous as well as the data vary regarding the date of acquisition and data source, this motivated the implementation of post-classification change detection rather than radiometric transformation methods. Based on thematic LU/LC maps, series of optimized algorithms have been developed to depict the dynamics in LU/LC entities. Therefore, detailed change “from-to” information classes as well as changes statistics were produced. Furthermore, the produced change maps were assessed, which reveals that the accuracy of the change maps is consistently high. Aggregated to the community-level, social survey of household data provides a comprehensive perspective additionally to EO data. The predetermined hot spots of degraded and successfully recovered areas were investigated. Thus, the study utilized a well-designed questionnaire to address the factors affecting land-cover dynamics and the possible solutions based on local community's perception. At the operational structural forest stand level, the rationale for incorporating these analyses are to offer a semi-automatic OBIA metrics estimates from which forest attribute is acquired through automated segmentation algorithms at the level of delineated tree crowns or clusters of crowns. Correlation and regression analyses were applied to identify the relations between a wide range of spectral and textural metrics and the field derived forest attributes. The acquired results from the OBIA framework reveal strong relationships and precise estimates. Furthermore, the best fitted models were cross-validated with an independent set of field samples, which revealed a high degree of precision. An important question is how the spatial resolution and spectral range used affect the quality of the developed model this was also discussed based on the different sensors examined. To conclude, the study reveals that the OBIA has proven capability as an efficient and accurate approach for gaining knowledge about the land features, whether at the operational forest structural attributes or categorical LU/LC level. Moreover, the methodological framework exhibits a potential solution to attain precise facts and figures about the change dynamics and its driving forces. / Da das Waldressourcenmanagement hierarchisch strukturiert ist, beschäftigt sich die vorliegende Arbeit mit der natürlichen Waldbedeckung auf verschiedenen Abstraktionsebenen, das heißt insbesondere mit der Ebene der kategorischen Landnutzung / Landbedeckung (LU/LC) sowie mit der kontinuierlichen empirischen Abschätzung auf lokaler operativer Ebene. Da zurzeit kein Sensor die Anforderungen aller Ebenen der Bewertung von Waldressourcen und von Multisource-Bildmaterialien (d.h. RapidEye, TERRA ASTER und LANDSAT TM) erfüllen kann, wurden zusätzlich andere Formen von Daten und Wissen untersucht und in die Arbeit mit eingebracht. Es wurde eine objekt-basierte Bildanalyse (OBIA) in einer destabilisierten Region des Blauen Nils im Sudan eingesetzt, um nach möglichen Lösungen zu suchen, erforderliche Informationen für die zukünftigen Waldplanung und die Entscheidungsfindung zu sammeln. Außerdem wurden die räumliche Heterogenität, sowie die sehr schnellen Änderungen in der Region untersucht. Dies motiviert nach effizienteren, flexibleren und genaueren Methoden zu suchen, um die gewünschten aktuellen Informationen zu erhalten. Das Konzept von OBIA wurde als Substitution-Analyse-Rahmen vorgeschlagen, um die Mängel vom früheren pixel-basierten Konzept abzumildern. In diesem Sinne untersucht die Studie die beliebtesten Maximum-Likelihood-Klassifikatoren des pixel-basierten Konzeptes als Beispiel für das Verhalten der spektralen Klassifikatoren in dem jeweiligen Datenbereich und der Region. Im Gegensatz dazu analysiert OBIA Fernerkundungsdaten durch den Einbau von Wissen des Analytikers sowie kostenlose Zusatzdaten in einer Art und Weise, die menschliche Intelligenz für die Bildinterpretation als eine reale Darstellung der Funktion simuliert. Als ein Segment einer Basisverarbeitungseinheit wurden verschiedene Kombinationen von Segmentierungskriterien getestet um ähnliche spektrale Werte in Gruppen von relativ homogenen Pixeln zu trennen. An der kategorische Subtraktionsebene wurden Regeln entwickelt und optimale Eigenschaften für jede besondere Klasse extrahiert. Zwei Verfahren (Rule Based (RB) und Nearest Neighbour (NN) Classifier) wurden zugeteilt um die segmentierten Objekte der entsprechenden Klasse zuzuweisen. Außerdem versucht die Studie die Fragen zu beantworten, ob OBIA in feiner räumlicher Auflösung grundsätzlich genauer ist als eine gröbere Auflösung, und wie beide, das pixel-basierte und das OBIA Konzept sich in einer relativen Genauigkeit als eine Funktion der räumlichen Auflösung vergleichen lassen. Diese Arbeit zeigt insbesondere, dass das OBIA Konzept eine fortschrittliche Lösung für die Bildanalyse ist, da die Genauigkeiten - an den verschiedenen Skalen angewandt - im Vergleich mit denen der Pixel-basierten Konzept verbessert wurden. Unterdessen waren die berichteten Ergebnisse der feineren räumlichen Auflösung nicht nur für die beiden Ansätze konsequent hoch, sondern durch das OBIA Konzept deutlich verbessert. Die schnellen Veränderungen und die Heterogenität der Region sowie die unterschiedliche Datenherkunft haben dazu geführt, dass die Umsetzung von Post-Klassifizierungs- Änderungserkennung besser geeignet ist als radiometrische Transformationsmethoden. Basierend auf thematische LU/LC Karten wurden Serien von optimierten Algorithmen entwickelt, um die Dynamik in LU/LC Einheiten darzustellen. Deshalb wurden für Detailänderung "von-bis"-Informationsklassen sowie Veränderungsstatistiken erstellt. Ferner wurden die erzeugten Änderungskarten bewertet, was zeigte, dass die Genauigkeit der Änderungskarten konstant hoch ist. Aggregiert auf die Gemeinde-Ebene bieten Sozialerhebungen der Haushaltsdaten eine umfassende zusätzliche Sichtweise auf die Fernerkundungsdaten. Die vorher festgelegten degradierten und erfolgreich wiederhergestellten Hot Spots wurden untersucht. Die Studie verwendet einen gut gestalteten Fragebogen um Faktoren die die Dynamik der Änderung der Landbedeckung und mögliche Lösungen, die auf der Wahrnehmung der Gemeinden basieren, anzusprechen. Auf der Ebene des operativen strukturellen Waldbestandes wird die Begründung für die Einbeziehung dieser Analysen angegeben um semi-automatische OBIA Metriken zu schätzen, die aus dem Wald-Attribut durch automatisierte Segmentierungsalgorithmen in den Baumkronen abgegrenzt oder Cluster von Kronen Ebenen erworben wird. Korrelations- und Regressionsanalysen wurden angewandt, um die Beziehungen zwischen einer Vielzahl von spektralen und strukturellen Metriken und den aus den Untersuchungsgebieten abgeleiteten Waldattributen zu identifizieren. Die Ergebnisse des OBIA Rahmens zeigen starke Beziehungen und präzise Schätzungen. Die besten Modelle waren mit einem unabhängigen Satz von kreuz-validierten Feldproben ausgestattet, welche hohe Genauigkeiten ergaben. Eine wichtige Frage ist, wie die räumliche Auflösung und die verwendete Bandbreite die Qualität der entwickelten Modelle auch auf der Grundlage der verschiedenen untersuchten Sensoren beeinflussen. Schließlich zeigt die Studie, dass OBIA in der Lage ist, als ein effizienter und genauer Ansatz Kenntnisse über die Landfunktionen zu erlangen, sei es bei operativen Attributen der Waldstruktur oder auch auf der kategorischen LU/LC Ebene. Außerdem zeigt der methodischen Rahmen eine mögliche Lösung um präzise Fakten und Zahlen über die Veränderungsdynamik und ihre Antriebskräfte zu ermitteln.

The government of Ethiopia has initialized an investment in the agricultural sector in order to secure food production for a growing population. The Koga Irrigation and Water Management Project is a pilot project and hopes are that crop production will double. Water quality is an important factor to meet these expectations. The aim of this study is to assess the irrigation water’s biological and chemical quality by using locally available methods and compare the results with international water quality standards pertaining to agricultural use as well as human and animal consumption. The water was sampled and analyzed for biological, chemical and physical parameters. The most important parameters were thermotolerant coliforms, electrical conductivity and turbidity. The first part of the thesis was a literature study dealing with the Koga project and the water use in the area. The second part focuses on 17 water samples that were taken within an individual command area: irrigation canals, fish pond and drinking water well. The samples were then analyzed at the water quality and treatment lab at the University of Bahir Dar. The results were compared to guideline values for livestock, crop, fish and human use recommended by the World Health Organization (WHO). All water samples, including the drinking water from the groundwater well, were contaminated with thermotolerant coliforms and had a relatively high turbidity. Additionally, the irrigation water contained levels of boron which were higher than recommended for crop production. Electrical conductivity values were overall satisfactory. These results give only an idea of the overall water quality within the Koga Irrigation Project. More samples need to be taken in order to draw any concrete conclusions and provide any recommendations.

Summary Fresh water availability and distribution have been declining over time due to population increase, climate change and variability, emerging new demands due to economic growth, and changing consumption patterns. Spatial and temporal changes in environmental changes, such as climate and land use/cover (LULC) dynamics have an enormous impact on water availability. Food and energy security, urbanization and industrial growth, as well as climate change (CC) will pose critical challenges on water resources. Climate variability and change may affect both the supply and demand sides of the balance, and thus add to the challenges. Land-cover changes are vastly prominent in the developing countries that are characterized by agriculture-based economies and rapidly increasing human population. The consequent changes in water availability and increase in per capita water demand will adversely affect the food, water and energy security of those countries. Therefore, evaluating the response of the catchment to environmental changes is crucial in the critical part of the basin for sustainable water resource management and development. In particular, assessing the contribution of individual LULC classes to changes in water balance components is vital for effective water and land resource management, and for mitigation of climate change impacts. The dynamic water balance of a catchment is analyzed by hydrological models that consider spatio-temporal catchment characteristics. As a result, hydrological models have become indispensable tools for the study of hydrological processes and the impacts of environmental stressors on the hydrologic system. Physically-based distributed hydrological models are able to explicitly account for the spatial variability of hydrological process, catchment characteristics such as climatic parameters, and land use/cover changes. For improved illustration of physical processes in space and time, the distributed hydrological models need serially complete and homogenized rainfall and temperature data. However, observed rainfall and temperature data are neither serially complete nor homogeneous, particularly in developing countries. Using inhomogeneous climatological data inputs to hydrological models affects the output magnitude of climate and land use/cover change impacts and, hence, climate change adaptation. The Nile River Basin, one of the transboundary river flows through 11 riparian states, serves the livelihoods of millions of people in the basin (nearly 20 per cent of the African population) and covers one-tenth of the land cover of Africa. The basin is characterized by high population growth and high temporal variability in the river flow and rainfall patterns. The Blue Nile river basin, which contributes 62% of the annual main Nile flow, has faced serious land degradation. This has led to increased soil erosion and loss of soil fertility. The most overwhelming challenge that the basin faces is food insecurity caused by subsistence farming and rain-fed agriculture (over 70% of the basin’s population), together with high rainfall variability. Drought and floods are also critical issues in the Blue Nile basin, with the potential for exacerbation by environmental changes. Understanding how LULC and climate changes influence basin hydrology will therefore enable decision makers to introduce policies aimed at reducing the detrimental effects of future environmental changes on water resources. Understanding types and impacts of major environmental stressors in representative and critical regions of the basin is crucial for developing of effective response strategies for sustainable land- and water-resource management in the Eastern Nile Basin in general, and at the Tana and Beles watersheds in particular. In this study, serially completed and homogenized rainfall and temperature dataset are maintained from 1980 to 2013 to fill-in the gap which characterized previous studies on trend analyses. The new hydroclimatic data revealed that the climate the study region has become wetter and warmer. The proportional contribution of main rainy season rainfall to annual total rainfall has increased. This might result in high runoff and ultimately flooding as well as erosion and sedimentation in the source region of the Blue Nile, and siltation in the downstream reservoirs unless soil and water conservation measures are taking place. In the Tana sub-basin, it is found that expansion of cultivation land and decline in woody shrub are the major contributors to the rise in surface run-off and to the decline in the groundwater component from 1986 to 2010. Similarly, decline of woodland and expansion of cultivation land are found to be the major contributors to the increase in surface run-off and water yield. They also contributed to the decrease in groundwater and actual evapotranspiration components in the Beles watershed. Increased run-off and reduced baseflow and actual evapotranspiration would have negative impacts on water resources, especially in relation to erosion and sedimentation in the upper Blue Nile River Basin. As a result, expansion of cultivation land and decline in woody shrub/woodland appear to be major environmental stressors affecting local water resources. GCMs simulated near-future annual total rainfall and average temperature were used to investigate the sensitivity of the catchment to near-future CC. The results showed an increase in streamflow in the annual and the main rainy season, but decrease in the dry period when compared to the baseline period. Catchment response for future LULC scenario showed opposite effect to that of near-future CC. The combined effects of climate change and LULC dynamics can be quite different from the effects resulting from LULC or CC alone. At the outlet of the Tana watershed, streamflow response is amplified under concurrent land cover and climate change scenarios compared to the baseline scenario; but the streamflow has an augmenting response at the outlet of the Beles watershed under future climate change and land use scenarios compared to that of current period. The important inference from these findings is that it could be possible to alleviate intense floods or droughts due to future climate change by planning LULC to achieve particular hydrological effects of land cover in the basin. Continuing expansion of cultivation land and decrease in natural vegetation, coupled with increased rainfall due to climate change, would result in high surface runoff in the main rainy season, which would subsequently increase flooding, erosion and sedimentation in already degraded lands. Sound mitigation measures should therefore be applied to reduce these adverse environmental consequences. On the other hand, the simulated climate and land-use change impacts on the Tana watershed hydrological regime might increase the availability of streamflow to be harnessed by water-storage structures. In conclusion, the present study has developed an innovative approach to identify the major environmental stressors of critical source region of the Blue Nile River in order to effectively managing the water resources and climate risk. Understanding the catchment responses to environmental changes improves sustainability of the water resources management particularly given that the hydropower and the irrigation schemes are recently established for energy and food security.:TABLE OF CONTENTS LIST OF ABBREVIATIONS LIST OF FIGURES LIST OF TABLES 1. General Introduction 2. The study area 3. Gap Filling and Homogenization of Climatological Datasets in the Headwater Region of the Upper Blue Nile Basin, Ethiopia Abstract 3.1. Introduction 3.1.1. Data 3.2. Methodology 3.2.1. Quality control and gap filling 3.2.2. Homogenization 3.3. Results and Discussion 3.3.1. Gap filling 3.3.2. Homogeneity 3.3.3. Verification of the homogenization 3.3.4. Impact of homogenization on the rainfall and temperature series 3.4. Conclusions Acknowledgements 4. Revisiting trend analysis of hydroclimatic data in the Upper Blue Nile basin based on homogenized data Abstract 4.1 Introduction 4.2 Data and Methodology 4. 2.1 Data 4. 2.2 Linear trend 4. 2.3 Trend magnitude 4.3 Results and Discussions 4.3.1. Linear mean climate trends 4.3.1.1. Rainfall 4.3.1.2. Maximum Temperature (Tmax) 4.3.1.3. Minimum Temperature (Tmin) 4.3.1.4. Mean temperature (Tmean) 4.3.1.5. Diurnal temperature range (DTR) 4.3.1.6. Streamflow 4.3.2. Effect of homogenization on Tmax, Tmin, Tmean and DTR linear trends 4.3.3. Linear extreme climate trends 4.3.1. Temperature 4.3.2. Precipitation 4.4 Conclusions Acknowledgements 5. Recent Changes in Land Use/Cover in the Headwater Region of the Upper Blue Nile Basin, Ethiopia 85 Abstract 5.1 Introduction 5.2 Materials and Methods 5.2.1 Data used and image pre-processing 5.2.2 Classification accuracy assessment 5.2.3 Extent and rate of change 5.2.4 Detecting the most systematic transitions (dominant signals of change) 5.4 Results and Discussion 5.4.1 Accuracy assessment 5.4.2 Extent and rate of LULC changes 5.4.3 Rate of land use and land cover change 5.4.4 Detection of most systematic transitions 5.5 Conclusions Acknowledgements 6. Hydrological Responses to Land use/cover Changes in the Tana and Beles Watersheds, the Upper Blue Nile, Ethiopia Abstract 6.1 Introduction 6.2 Method 6.2.1 Hydrological modeling 6.2.2 Partial least squares regression 6.3 Results and Discussion 6.3.1 Calibration and validation of SWAT 6.3.2 Impacts of LULC changes on hydrology at the basin scale 6.3.3 Contribution of changes in individual LULCs to hydrological components 6.4 Conclusions Acknowledgements 7. Combined Impact of Climate and Land Use Changes on Hydrology in the Tana and Beles Sub-Basins, Upper Blue Nile, Ethiopia Abstract 7.1 Introduction 7.2 Methodology 7.2.1 Simulation 7.2.2 Climate change scenarios 7.2.3 LULC change scenarios 7.3 Results and Discussion 7.3.1 Future versus current LULC impact on the basin hydrology 7.3.2 Future versus baseline climate 7.3.3 Impact of combined future climate and LULC changes on hydrology 7.4 Uncertainties and Limitations 7.5 Conclusions Acknowledgements 8. Overall Conclusions, Recommendations and Future Research Directions 8.1. Overall Conclusions 8.2 Recommendations and Directions for further research References

Following the hierarchical nature of forest resource management, the present work focuses on the natural forest cover at various abstraction levels of details, i.e. categorical land use/land cover (LU/LC) level and a continuous empirical estimation of local operational level. As no single sensor presently covers absolutely all the requirements of the entire levels of forest resource assessment, multisource imagery (i.e. RapidEye, TERRA ASTER and LANDSAT TM), in addition to other data and knowledge have been examined. To deal with this structure, an object-based image analysis (OBIA) approach has been assessed in the destabilized Blue Nile region of Sudan as a potential solution to gather the required information for future forest planning and decision making. Moreover, the spatial heterogeneity as well as the rapid changes observed in the region motivates the inspection for more efficient, flexible and accurate methods to update the desired information. An OBIA approach has been proposed as an alternative analysis framework that can mitigate the deficiency associated with the pixel-based approach. In this sense, the study examines the most popular pixel-based maximum likelihood classifier, as an example of the behavior of spectral classifier toward respective data and regional specifics. In contrast, the OBIA approach analyzes remotely sensed data by incorporating expert analyst knowledge and complimentary ancillary data in a way that somehow simulates human intelligence for image interpretation based on the real-world representation of the features. As the segment is the basic processing unit, various combinations of segmentation criteria were tested to separate similar spectral values into groups of relatively homogeneous pixels. At the categorical subtraction level, rules were developed and optimum features were extracted for each particular class. Two methods were allocated (i.e. Rule Based (RB) and Nearest Neighbour (NN) Classifier) to assign segmented objects to their corresponding classes. Moreover, the study attempts to answer the questions whether OBIA is inherently more precise at fine spatial resolution than at coarser resolution, and how both pixel-based and OBIA approaches can be compared regarding relative accuracy in function of spatial resolution. As anticipated, this work emphasizes that the OBIA approach is can be proposed as an advanced solution particulary for high resolution imagery, since the accuracies were improved at the different scales applied compare with those of pixel-based approach. Meanwhile, the results achieved by the two approaches are consistently high at a finer RapidEye spatial resolution, and much significantly enhanced with OBIA. Since the change in LU/LC is rapid and the region is heterogeneous as well as the data vary regarding the date of acquisition and data source, this motivated the implementation of post-classification change detection rather than radiometric transformation methods. Based on thematic LU/LC maps, series of optimized algorithms have been developed to depict the dynamics in LU/LC entities. Therefore, detailed change “from-to” information classes as well as changes statistics were produced. Furthermore, the produced change maps were assessed, which reveals that the accuracy of the change maps is consistently high. Aggregated to the community-level, social survey of household data provides a comprehensive perspective additionally to EO data. The predetermined hot spots of degraded and successfully recovered areas were investigated. Thus, the study utilized a well-designed questionnaire to address the factors affecting land-cover dynamics and the possible solutions based on local community's perception. At the operational structural forest stand level, the rationale for incorporating these analyses are to offer a semi-automatic OBIA metrics estimates from which forest attribute is acquired through automated segmentation algorithms at the level of delineated tree crowns or clusters of crowns. Correlation and regression analyses were applied to identify the relations between a wide range of spectral and textural metrics and the field derived forest attributes. The acquired results from the OBIA framework reveal strong relationships and precise estimates. Furthermore, the best fitted models were cross-validated with an independent set of field samples, which revealed a high degree of precision. An important question is how the spatial resolution and spectral range used affect the quality of the developed model this was also discussed based on the different sensors examined. To conclude, the study reveals that the OBIA has proven capability as an efficient and accurate approach for gaining knowledge about the land features, whether at the operational forest structural attributes or categorical LU/LC level. Moreover, the methodological framework exhibits a potential solution to attain precise facts and figures about the change dynamics and its driving forces. / Da das Waldressourcenmanagement hierarchisch strukturiert ist, beschäftigt sich die vorliegende Arbeit mit der natürlichen Waldbedeckung auf verschiedenen Abstraktionsebenen, das heißt insbesondere mit der Ebene der kategorischen Landnutzung / Landbedeckung (LU/LC) sowie mit der kontinuierlichen empirischen Abschätzung auf lokaler operativer Ebene. Da zurzeit kein Sensor die Anforderungen aller Ebenen der Bewertung von Waldressourcen und von Multisource-Bildmaterialien (d.h. RapidEye, TERRA ASTER und LANDSAT TM) erfüllen kann, wurden zusätzlich andere Formen von Daten und Wissen untersucht und in die Arbeit mit eingebracht. Es wurde eine objekt-basierte Bildanalyse (OBIA) in einer destabilisierten Region des Blauen Nils im Sudan eingesetzt, um nach möglichen Lösungen zu suchen, erforderliche Informationen für die zukünftigen Waldplanung und die Entscheidungsfindung zu sammeln. Außerdem wurden die räumliche Heterogenität, sowie die sehr schnellen Änderungen in der Region untersucht. Dies motiviert nach effizienteren, flexibleren und genaueren Methoden zu suchen, um die gewünschten aktuellen Informationen zu erhalten. Das Konzept von OBIA wurde als Substitution-Analyse-Rahmen vorgeschlagen, um die Mängel vom früheren pixel-basierten Konzept abzumildern. In diesem Sinne untersucht die Studie die beliebtesten Maximum-Likelihood-Klassifikatoren des pixel-basierten Konzeptes als Beispiel für das Verhalten der spektralen Klassifikatoren in dem jeweiligen Datenbereich und der Region. Im Gegensatz dazu analysiert OBIA Fernerkundungsdaten durch den Einbau von Wissen des Analytikers sowie kostenlose Zusatzdaten in einer Art und Weise, die menschliche Intelligenz für die Bildinterpretation als eine reale Darstellung der Funktion simuliert. Als ein Segment einer Basisverarbeitungseinheit wurden verschiedene Kombinationen von Segmentierungskriterien getestet um ähnliche spektrale Werte in Gruppen von relativ homogenen Pixeln zu trennen. An der kategorische Subtraktionsebene wurden Regeln entwickelt und optimale Eigenschaften für jede besondere Klasse extrahiert. Zwei Verfahren (Rule Based (RB) und Nearest Neighbour (NN) Classifier) wurden zugeteilt um die segmentierten Objekte der entsprechenden Klasse zuzuweisen. Außerdem versucht die Studie die Fragen zu beantworten, ob OBIA in feiner räumlicher Auflösung grundsätzlich genauer ist als eine gröbere Auflösung, und wie beide, das pixel-basierte und das OBIA Konzept sich in einer relativen Genauigkeit als eine Funktion der räumlichen Auflösung vergleichen lassen. Diese Arbeit zeigt insbesondere, dass das OBIA Konzept eine fortschrittliche Lösung für die Bildanalyse ist, da die Genauigkeiten - an den verschiedenen Skalen angewandt - im Vergleich mit denen der Pixel-basierten Konzept verbessert wurden. Unterdessen waren die berichteten Ergebnisse der feineren räumlichen Auflösung nicht nur für die beiden Ansätze konsequent hoch, sondern durch das OBIA Konzept deutlich verbessert. Die schnellen Veränderungen und die Heterogenität der Region sowie die unterschiedliche Datenherkunft haben dazu geführt, dass die Umsetzung von Post-Klassifizierungs- Änderungserkennung besser geeignet ist als radiometrische Transformationsmethoden. Basierend auf thematische LU/LC Karten wurden Serien von optimierten Algorithmen entwickelt, um die Dynamik in LU/LC Einheiten darzustellen. Deshalb wurden für Detailänderung "von-bis"-Informationsklassen sowie Veränderungsstatistiken erstellt. Ferner wurden die erzeugten Änderungskarten bewertet, was zeigte, dass die Genauigkeit der Änderungskarten konstant hoch ist. Aggregiert auf die Gemeinde-Ebene bieten Sozialerhebungen der Haushaltsdaten eine umfassende zusätzliche Sichtweise auf die Fernerkundungsdaten. Die vorher festgelegten degradierten und erfolgreich wiederhergestellten Hot Spots wurden untersucht. Die Studie verwendet einen gut gestalteten Fragebogen um Faktoren die die Dynamik der Änderung der Landbedeckung und mögliche Lösungen, die auf der Wahrnehmung der Gemeinden basieren, anzusprechen. Auf der Ebene des operativen strukturellen Waldbestandes wird die Begründung für die Einbeziehung dieser Analysen angegeben um semi-automatische OBIA Metriken zu schätzen, die aus dem Wald-Attribut durch automatisierte Segmentierungsalgorithmen in den Baumkronen abgegrenzt oder Cluster von Kronen Ebenen erworben wird. Korrelations- und Regressionsanalysen wurden angewandt, um die Beziehungen zwischen einer Vielzahl von spektralen und strukturellen Metriken und den aus den Untersuchungsgebieten abgeleiteten Waldattributen zu identifizieren. Die Ergebnisse des OBIA Rahmens zeigen starke Beziehungen und präzise Schätzungen. Die besten Modelle waren mit einem unabhängigen Satz von kreuz-validierten Feldproben ausgestattet, welche hohe Genauigkeiten ergaben. Eine wichtige Frage ist, wie die räumliche Auflösung und die verwendete Bandbreite die Qualität der entwickelten Modelle auch auf der Grundlage der verschiedenen untersuchten Sensoren beeinflussen. Schließlich zeigt die Studie, dass OBIA in der Lage ist, als ein effizienter und genauer Ansatz Kenntnisse über die Landfunktionen zu erlangen, sei es bei operativen Attributen der Waldstruktur oder auch auf der kategorischen LU/LC Ebene. Außerdem zeigt der methodischen Rahmen eine mögliche Lösung um präzise Fakten und Zahlen über die Veränderungsdynamik und ihre Antriebskräfte zu ermitteln.

Land and water resources degradation are the major problems on the Ethiopian highlands. Poor land use practices and improper management systems have played a significant role in causing high soil erosion rates, sediment transport and loss of agricultural nutrients. So far limited meas-ures have been taken to combat the problems. In this study a physically based watershed model, SWAT2005 was applied to the Northern Highlands of Ethiopia for modelling of the hydrology and sediment yield. The main objective of this study was to test the performance and feasibility of SWAT2005 model to examine the influence of topography, land use, soil and climatic condi-tion on streamflows, soil erosion and sediment yield. The model was calibrated and validated on four tributaries of Lake Tana as well as Anjeni watershed using SUFI-2, GLUE and ParaSol algo-rithms. SWAT and GIS based decision support system (MCE analysis) were also used to identify the most erosion prone areas in the Lake Tana Basin. Streamflows are more sensitive to the hy-drological response unites definition thresholds than subbasin discretization. Prediction of sedi-ment yield is highly sensitive to subbasin size and slope discretization. Baseflow is an important component of the total discharge within the study area that contributes more than the surface runoff. There is a good agreement between the measured and simulated flows and sediment yields with higher values of coefficients of determination and Nash Sutcliffe efficiency. The an-nual average measured sediment yield in Anjeni watershed was 24.6 tonnes/ha. The annual aver-age simulated sediment yield was 27.8 and 29.5 tonnes/ha for calibration and validation periods, respectively. The SWAT model indicated that 18.5 % of the Lake Tana Basin is erosion potential areas. Whereas the MCE result indicated that 25.5 % of the basin are erosion potential areas. The calibrated model can be used for further analysis of the effect of climate and land use change as well as other different management scenarios on streamflows and soil erosion. The result of the study could help different stakeholders to plan and implement appropriate soil and water conser-vation strategies. / QC 20101123