A GIS Analysis of Potential Wetland Mitigation Opportunities in the Brandywine Creek Watershed, Chester County, Pennsylvania

Wetlands provide innumerous functions and values that are beneficial to both the natural environment and economic systems. Historically these habitats have suffered significant losses and it is crucial to preserve existing wetlands and plan for future restoration opportunities. This research examines six sub-watersheds within the Brandywine Creek watershed within Chester County, Pennsylvania to determine where potential wetland mitigation opportunities occur. Using a Geographic Information Systems (GIS) analysis, three wetland characteristics including watercourse locations, existing National Wetlands Inventory (NWI) wetlands, and hydric soils were mapped throughout each of the watersheds. Areas of agricultural easements and steep slopes were used to exclude areas from the study. Based on the occurrence of these characteristics, eight sites were selected for ground-truthing investigations. To support findings from these processes, a review of aerial imagery was performed to understand how the site and surrounding landscape have changed over time. Of the eight selected sites, two were deemed suitable for immediate potential wetland mitigation opportunities, four were determined to have the potential for wetland mitigation pending further analysis, and two were determined to be unsuitable for wetland mitigation. The lack of access to private property, presence of agricultural activities, and availability of GIS data provided limitations for a complete and thorough study. This research shows that GIS analysis could be a useful tool in determining where potential wetland mitigation opportunities lie and can serve to benefit future wetland mitigation planning activities, regulating agencies, conservation organizations, as well as the natural and human environments

Unmanned Aerial Vehicle (UAV) photogrammetry produces accurate high-resolution orthophotos, point clouds and surface models for mapping wetlands

Unmanned Aerial Vehicle (UAV) photogrammetry has recently become a powerful tool that offers a viable alternative to traditional remote sensing systems, particularly for applications covering relatively small spatial extents. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool for the mapping of wetlands. A multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. The survey of the 100ha study area at the Kameelzynkraal farm, Gauteng Province, South Africa took about 2½ hours and the generation of the point cloud about 18 hours. Ground control points (GCPs) were positioned across the site to achieve geometrical precision and georeferencing accuracy. Structure from Motion (SfM) computer vision techniques were used to reconstruct the camera positions, terrain features and to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The results of the geometric accuracy of the data based on the 20 GCPs were 0.018m for the overall and 0.0025m for the vertical root mean squared error (RMSE). The results exceeded our expectations and provided valuable, rapid and accurate mapping of wetlands that can be used for wetland studies and thereby support and enhance associated decision making to secure our future

Remote sensing based assessment of small wetlands in East Africa

Small wetlands in East Africa have in the past few decades become focal points of a broad spectrum of agricultural production and other land-uses. Climate change and population growth are the major factors attributing to increasing use and change of the wetlands. This study aimed at detecting the distribution and extent of small wetlands in Tanzania and Kenya, classifying them into different types, identifying their use patterns and quantifying changes that have taken place from 1976 to 2003. Field and aerial surveys were conducted; microwave (ALOS-PALSAR, ENVISAT-ASAR, and TerraSAR-X) and optical (LANDSAT and aerial photographs) data, were used to detect spatial distribution of the wetlands using automated and semi automated techniques. Time series LANDSAT images were applied in classification and change detection by post classification comparison (PCC), change vector analysis (CVA) and land use change mapper (LCM). Maps and socio-economic data were also gathered. Driving forces of change were determined qualitatively using group discussions with key informants. Two types of small wetlands were mainly identified, inland valleys located in the humid highlands and covering 87% of the total surveyed area as well as floodplains in sub-humid lowlands and semi-arid highlands covering the remaining 13%. Eight major land cover and uses were identified with accuracies between 82.76 and 95.17%. Cropland was a dominant land use occupying 57% of the inland valleys and 35% in the flood plains; others included open water, floating vegetation, permanent papyrus swamps, semi-natural vegetation, grazing, shrubs, settlements and bare land. The cover and uses are unevenly distributed between the types and sites. The major change detected was expansion of cropped land at the expense of natural vegetation. This accounted for 56% of the change in the highland flood plain and 52% in the lowland floodplain. Shrubs proliferated in all wetlands, which is indicated by more than 50% compared to their area coverage in 1976. Climate change, population increase, unemployment, market access, wetland physical access and insufficient knowledge on the use are among the proximate causes of the wetland changes. Underlying factors like poor enforcement of wetland law and policy in Kenya and lack of the same in Tanzania have accelerated these changes. Combinations of remote sensing data and image processing methods played an important role in achieving the objectives of the study. Optical data proved to be very useful in delineation of small wetlands while microwave data delineated larger areas. The spatial resolution of the images has also proved to be a key factor in studies of small wetlands. To ameliorate the wetlands, it is recommended that a balance is attained between the use and conservation. Policy formulation and law enactment in Tanzania and enforcement of the existing policy and law in Kenya is seen to support wise use. Awareness creation is also important to lessen the over and inappropriate utilization of the wetlands

Remote sensing and wetland ecology: a South African case study

Remote sensing offers a cost efficient means for identifying and monitoring wetlands over a large area and at different moments in time. In this study, we aim at providing ecologically relevant information on characteristics of temporary and permanent isolated open water wetlands, obtained by standard techniques and relatively cheap imagery. The number, surface area, nearest distance, and dynamics of isolated temporary and permanent wetlands were determined for the Western Cape, South Africa. Open water bodies (wetlands) were mapped from seven Landsat images (acquired during 1987 – 2002) using supervised maximum likelihood classification. This study has indicated that ecologically relevant data can be generated for the larger wetlands through relatively cheap imagery and standard techniques, despite the relatively low resolution of Landsat and Envisat imagery. For the characterisation of very small wetlands, high spatial resolution optical or radar images are needed. This study exemplifies the benefits of integrating remote sensing and ecology and hence stimulates interdisciplinary research of isolated wetlands

An assessment of the impacts of climate and land use/cover changes on wetland extent within Mzingwane catchment, Zimbabwe

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy(Geography and Environmental Science). Johannesburg, June 2018.Wetlands ecosystems are amongst the most diverse and valuable environments which provide a number of goods and services pertinent to human and natural systems functioning yet they are increasingly threatened by anthropogenic and climatic changes. This thesis, examines the impact of climatic trends and variations, and land use/land (LU/LC) cover changes on wetland extent within Mzingwane catchment, south-western of Zimbabwe. An attempt is made to establish how the two stressors (climate and LU/LC changes) modify areal extents of wetlands over time, grounded on the hypothesis that, climate and LU/LC related changes impact on wetland ecosystems resulting in their degradation, shrinking in size and in some cases overall loss. To achieve the broader objective of the study, a number of parametric and non-parametric statistical analyses were employed to quantify and ascertain climate variability and change in Mzingwane catchment through the use of historic and current climatic trends in rainfall and temperature (T). Remote sensing data was used for wetland change analysis for the period between 1984 and 2015as well as future land cover predictions based on CA-Markov Chain model. LU/LC changes on nested wetlands were modelled at catchment level. In addition the study simulated future rainfall and extreme events and their implications on wetland dynamics using Regional Climate Models derived from CORDEX data. Trends in annual Tmax significantly increased (p=1mm) has decreased by 34%, thus suggesting much more concentrated and increased rainfall intensity. A notable shift in both the onset and cessation dates of the rainy season is recorded, particularly during the 21st century, which has resulted in a significant reduction (p<0.05) in the length of the rainy season. Land change analysis results show a decline in woodland and wetland cover which could be resulting from both human and natural factors. Major conversions are from wetland cover to crop field, suggesting agricultural encroachment onto wetland areas. Wetland area thus significantly decreased by 60.16% (236, 52 ha) in the last 30 years (p < 0.05). CA-Markov model results for the years 2025, 2035 and 2045 predicted an overall increase in the crop field areas at the expense of woodland and wetland areas. LU/LC modelling results suggest that LU/LC changes modify wetland hydrology which consequently influences wetland areal extent. Trend results for projected rainfall suggest a significant decreasing trend in future rainfall (2016-2100) at p<0.05. In addition, a general decreasing trend in the number of rainy days is projected for the future climate although the significance and magnitude varied with station location. Regional Climate Models projections suggest an increased occurrence of future extreme events particularly towards the end of this century. The findings are important for developing appropriate sustainable and adaptive strategies given climate changes as well as designing catchment level wetland management approaches aimed at sustaining wetland ecosystems for the current and future generations. Any future efforts towards protection of the remaining wetlands should be combined with developing a sustainable relationship between social and ecological systems which will enable communities to adapt to the effects of changing climates.LG201

Mapping decadal land cover changes in the woodlands of north eastern Namibia from 1975 to 2014 using the Landsat satellite archived data

Woodlands and savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to subsistence and intensive agriculture or urbanized. This study investigates changes in land cover over four administrative regions of North Eastern Namibia within the Kalahari woodland savannah biome, covering a total of 107,994 km2. Land cover is mapped using multi-sensor Landsat imagery at decadal intervals from 1975 to 2014, with a post-classification change detection method. The dominant change observed was a reduction in the area of woodland savannah due to the expansion of agriculture, primarily in the form of small-scale cereal and pastoral production. More specifically, woodland savannah area decreased from 90% of the study area in 1975 to 83% in 2004, and then increased to 86% in 2014, while agricultural land increased from 6% to 12% between 1975 and 2014. We assess land cover changes in relation to towns, villages, rivers and roads and find most changes occurred in proximity to these. In addition, we find that most land cover changes occur within land designated as communally held, followed by state protected land. With widespread changes occurring across the African continent, this study provides important data for understanding drivers of change in the region and their impacts on the distribution of woodland savannahs

Assessing processes of long-term land cover change and modelling their effects on tropical forest biodiversity patterns – a remote sensing and GIS-based approach for three landscapes in East Africa: Assessing processes of long-term land cover change and modelling their effects on tropical forest biodiversity patterns – a remote sensing and GIS-based approach for three landscapes in East Africa

The work describes the processing and analysis of remote sensing time series data for a comparative assessment of changes in different tropical rainforest areas in East Africa. In order to assess the effects of the derived changes in land cover and forest fragmentation, the study made use of spatially explicit modelling approaches within a geographical information system (GIS) to extrapolate sets of biological field findings in space and time. The analysis and modelling results were visualised aiming to consider the requirements of three different user groups. In order to evaluate measures of forest conservation and to derive recommendations for an effective forest management, quantitative landscape-scale assessments of land cover changes and their influence on forest biodiversity patterns are needed. However, few remote sensing studies have accounted for all of the following aspects at the same time: (i) a dense temporal sequence of land cover change/forest fragmentation information, (ii) the coverage of several decades, (iii) the distinction between multiple forest formations and (iv) direct comparisons of different case studies. In regards to linkages of remote sensing with biological field data, no attempts are known that use time series data for quantitative statements of long-term landscape-scale biodiversity changes. The work studies three officially protected forest areas in Eastern Africa: the Kakamega-Nandi forests in western Kenya (focus area) and Mabira Forest in south-eastern Uganda as well as Budongo Forest in western Uganda (for comparison purposes). Landsat imagery of in total eight or seven dates in regular intervals from 1972/73 to 2003 was used. Making use of supervised multispectral image classification procedures, in total, 12 land cover classes (six forest formations) were distinguished for the Kakamega-Nandi forests and for Budongo Forest while for Mabira Forest ten classes could be realised. An accuracy assessment via error matrices revealed overall classification accuracies between 81% and 85%. The Kakamega-Nandi forests show a continuous decrease between 1972/73 and 2001 of 31%, Mabira Forest experienced an abrupt loss of 24% in the late 1970s/early 1980s, while Budongo Forest shows a relatively stable forest cover extent. An assessment of the spatial patterns of forest losses revealed congruence with areas of high population density while a spatially explicit forest fragmentation index indicates a strong correlation of forest fragmentation with forest management regime and forest accessibility by roads. For the Kenyan focus area, three sets of biological field abundance data on keystone species/groups were used for a quantitative assessment of the influence of long-term changes in tropical forests on landscape-scale biodiversity patterns. For this purpose, the time series was extended with another three land cover data sets derived from aerial photography (1965/67, 1948/(52)) and old topographic maps (1912/13). To predict the spatio-temporal distribution of the army ant Dorylus wilverthi and of ant-following birds, GIS operators (i.e. focal and local functions) and statistical tests (i.e. OLS or SAR regression models) were combined into a spatial modelling procedure. Abundance data on three guilds of birds differing in forest dependency were directly extrapolated to five forest cover classes as distinguished in the time series. The results predict declines in species abundances of 56% for D. wilverthi, of 58% for ant-following birds and an overall loss of 47% for the bird habitat guilds, which in all three cases greatly exceed the rate of forest loss (31%). Additional extrapolations on scenarios of deforestation and reforestation confirmed the negative ecological consequences of splitting-up contiguous forest areas but also showed the potential of mixed indigenous forest plantings. The visualisation of the analysis and modelling results produced a mixture of different outcomes. Map series and a matrix of maps both showing species distributions aim to address scientists and decision makers. The results of the land cover change analysis were synthesised in a map of land cover development types for each study area, respectively. These maps are designed mainly for scientists. Additional maps of change, limited to a single class of forest cover and to three dates were generated to ensure an easy-to-grasp communication of the major forest changes to decision makers. Additionally, an easy-to-handle visualisation tool to be used by scientists, decision makers and local people was developed. For the future, an extension of this study towards a more complete assessment including more species/groups and also ecosystem functions and services would be desirable. Combining a framework for land cover simulation with a framework for running empirical extrapolation models in an automated manner could ideally result in a GIS-based, integrated forest ecosystem assessment tool to be used as regional spatial decision support system.Die Arbeit beschreibt die Prozessierung und Analyse von Fernerkundungs-Zeitreihendaten für eine vergleichende Abschätzung von Veränderungen verschiedener tropischer Waldökosysteme Ostafrikas. Um Effekte der Veränderungen bzgl. Landbedeckung und Waldfragmentierung auf Biodiversitätsmuster abzuschätzen, wurden verschiedene räumlich explizite Modellierungssätze innerhalb eines geographischen Informationssystems (GIS) zur räumlichen und zeitlichen Extrapolation biologischer Felderhebungsdaten benutzt. Die Visualisierung der Analyse- und Modellierungsergebnisse erfolgte unter Berücksichtigung der Bedürfnisse von drei verschiedenen Nutzergruppen. Um Waldschutzmaßnahmen zu evaluieren und Empfehlungen für ein effektives Waldmanagement abzuleiten, sind quantitative Abschätzungen von Landbedeckungsveränderungen sowie von deren Einfluss auf tropische Waldbiodiversitätsmuster nötig. Wenige fernerkundungsbasierte Studien haben jedoch bislang alle der folgenden Faktoren berücksichtigt: (i) Informationen zu Veränderungen von Landbedeckung und Waldfragmentierung in dichter zeitlicher Sequenz, (ii) die Abdeckung mehrerer Jahrzehnte, (iii) die Unterscheidung zwischen mehreren Waldformationen, und (iv) direkte Vergleiche von unterschiedlichen Fallstudien. Hinsichtlich Verknüpfungen von Fernerkundung mit biologischen Felddaten sind bisher keine Studien bekannt, die Zeitreihendaten für quantitative Aussagen zu Langzeitveränderungen von Biodiversität auf Landschaftsebene verwenden. Die Arbeit untersucht drei offiziell geschützte Gebiete: die Kakamega-Nandi forests in Westkenia (Hauptuntersuchungsgebiet) sowie Mabira Forest in Südost-Uganda und Budongo Forest in West-Uganda (zu Vergleichszwecken). Es wurden Landsat-Daten für insgesamt acht bzw. sieben Zeitpunkte zwischen 1972/73 und 2003 in ungefähr gleichen Abständen erworben. Mit Hilfe von überwachten, multispektralen Klassifizierungsverfahren wurden für die Kakamega-Nandi forests und Budongo Forest jeweils 12 Landbedeckungsklassen (sechs Waldformationen) und für Mabira Forest zehn Klassen unterschieden. Eine Genauigkeitsprüfung mit Hilfe von Fehlermatrizen ergab Gesamtklassifizierungsgenauigkeiten zwischen 81% und 85%. Die Kakamega-Nandi forests sind durch eine kontinuierliche Waldabnahme von 31% zwischen 1972/73 und 2001 gekennzeichnet, Mabira Forest zeigt einen abrupten Waldverlust von 24% in den späten 1970ern/frühen 1980ern, während die Ergebnisse für Budongo Forest eine relativ stabile Waldbedeckung ausweisen. Während eine Abschätzung der räumlichen Muster von Waldverlusten eine hohe Deckungsgleichheit mit Gebieten hoher Bevölkerungsdichte ergab, deutet die Anwendung eines räumlich expliziten Waldfragmentierungsindexes auf eine starke Korrelation von Waldfragmentierung mit der Art von Waldmanagement sowie mit der Erreichbarkeit von Wald über Straßen hin. Um den Einfluss von Langzeit-Landbedeckungsveränderungen auf Biodiversitätsmuster auf Landschaftsebene für das kenianische Hauptuntersuchungsgebiet quantitativ abzuschätzen wurden drei Datensätze mit biologischen Felderhebungen zur Abundanz von Schlüsselarten/-gruppen verwendet. Zu diesem Zweck wurde die Zeitreihe zunächst um drei weitere Landbedeckungs-Datensätze ergänzt, die aus Luftbildern (1965/67, 1948/(52)) bzw. alten topographischen Karten (1912/13) gewonnen wurden. Zur Vorhersage der raum-zeitlichen Verteilung der Treiberameise Dorylus wilverthi wurden GIS-Operatoren und statistische Tests (OLS bzw. SAR Regressionsmodelle) in einem räumlichen Modellierungsablauf kombiniert. Abundanzdaten von drei sich hinsichtlich ihrer Abhängigkeit von Wald unterscheidenden Vogelgilden wurden direkt auf fünf Waldbedeckungsklassen hochgerechnet, die in der Zeitreihe unterschieden werden konnten. Die Ergebnisse prognostizieren Abundanzabnahmen von 56% für D. wilverthi, von 58% für Ameisen-folgende Vögel und einen Gesamtverlust von 47% für die Vogelgilden, was in allen drei Fällen eine deutliche Überschreitung der Waldverlustrate von 31% darstellt. Zusätzliche Extrapolationen basierend auf Szenarien bestätigten die negativen ökologischen Konsequenzen der Zerteilung zusammenhängender Waldflächen bzw. zeigten andererseits das Potential von Aufforstungen mit einheimischen Arten auf. Die Visualisierung der Analyse- bzw. Modellierungsergebnisse führte zu unterschiedlichen Darstellungen: mit einer Reihe von nebeneinander positionierten Einzelkarten sowie einer Matrix von Einzelkarten, die jeweils Artenverteilungen zeigen, sollen Wissenschaftler und Entscheidungsträger angesprochen werden. Aus den Ergebnissen der Landbedeckungsanalyse für die drei Untersuchungsgebiete wurden Landbedeckungsveränderungstypen generiert und jeweils in einer synthetischen Karte dargestellt, die hauptsächlich für Wissenschaftler gedacht sind. Um die wesentlichen Waldveränderungen auch auf einfache Weise zu den Entscheidungsträgern zu kommunizieren, wurden zusätzliche Karten erstellt, die nur eine aggregierte Klasse „Waldbedeckung“ zeigen und jeweils auf drei Zeitschritte der Zeitreihen begrenzt sind. Zusätzlich wurde ein leicht zu bedienendes Visualisierungstool entwickelt, das für Wissenschaftler, Entscheidungsträger und die lokale Bevölkerung gedacht ist. Für die Zukunft wäre eine umfassendere Abschätzung unter Berücksichtigung zusätzlicher Arten/-gruppen sowie auch Ökosystemfunktionen und –dienstleistungen wünschenswert. Die Verknüpfung einer Applikation zur Landbedeckungsmodellierung mit einer Applikation zur Ausführung von empirischen Extrapolationsmodellen (in stärkerem Maße automatisiert als in dieser Arbeit) könnte im Idealfall in ein GIS-basiertes Tool zur integrativen Bewertung von Waldökosystemen münden, das dann als räumliches Entscheidungsunterstützungssystem verwendet werden könnte

Mapping and monitoring the Akagera wetland in Rwanda

Wetland maps are a prerequisite for wetland development planning, protection, and restoration. The present study aimed at mapping and monitoring Rwanda's Akagera Complex Wetland by means of remote sensing and geographic information systems (GIS). Landsat data, spanning from 1987 to 2015, were acquired from different sensor instruments, considering a 5-year interval during the dry season and the shuttle radar topographic mission (SRTM) digital elevation model (30-m resolution) was used to delineate the wetland. The mapping and delineation results showed that the wetland narrowly extends along the Rwanda-Tanzania border from north to south, following the course of Akagera River and the total area can be estimated at 100,229.76 ha. After waterbodies that occupy 30% of the wetland's surface area, hippo grass and Cyperus papyrus are also predominant, representing 29.8% and 29%, respectively. Floodplain and swamp forest have also been inventoried in smaller proportions. While the wetland extent has apparently remained stable, the inhabiting waterbodies have been subject to enormous instability due to invasive species. Lakes, such as Mihindi, Ihema, Hago and Kivumba have been shrinking in extent, while Lake Rwanyakizinga has experienced a certain degree of expansion. This study represents a consistent decision support tool for Akagera wetland management in Rwanda

Estuarine geomorphodynamic assessment of environmental change and stressor impacts: a geographic information systems and remote sensing (geoinformatic) modelling approach for sustainable management of southeast Australian coastal ecosystems

Increased habitation and global warming is posing growing threats to the coastal zone and estuarine settings through direct and indirect environmental and anthropogenic modification of sensitive coastal systems and their relevant catchments. It is essential to understand the impact of the different stressors on the coastal environment under current conditions and within the historical record in order to predict future responses of estuaries and coastal wetlands. Short-term remote sensing and GIS modelling and field assessment have made a significant contribution to our knowledge on estuarine and coastal wetland dynamism within the last few decades. This thesis assesses the potential impacts of anthropogenic modifications, climatic factors and sea level rise on estuarine eco-geomorphic intertidal sedimentary landforms and their associated coastal wetlands in southeastern Australia based on three estuarine systems on the south coast of NSW: the estuarine Comerong Island, Wandandian deltaic estuary, and Towamba estuary. The thesis’ short-term evaluation approach shows that the degradation levels on estuarine platforms are dependent on catchment development, sediment characteristics, ecosystem stability and sea level rise inundation. During anticipated climate change and rising sea level conditions, estuaries depend on their sediment source areas, especially on modifications to their river catchment. Catchments with high anthropogenic modification levels, like the dam infrastructure in the Shoalhaven River catchment, influence sediment availability and transportation with clear impacts on eco-geomorphic coastal platform losses. In contrast, mostly unmodified but high-sloped catchments, such as the Towamba example, may have other negative effects on the estuary since the sediments are poorly sorted and coarser noncohesive quartz-dominated particles cause the geomorphic landforms and associated ecosystems to be more vulnerable to erosion and lead to less stable vegetation. Regions with small moderately modified catchments, such as the Wandandian site, allow ideal geomorphic processes to occur. Here, sediment is weathered slowly and moved downstream naturally to a secure inner estuarine deltaic setting where fine sandy/silty particles accumulate and provide more geomorphic stability. Associated vegetation assemblages ensure the progradation and steady growth of the deltaic eco-geomorphic system. The thesis assessment shows the eco-geomorphic-dynamism of the Towamba estuary, which has a mostly unmodified catchment surface (only 14% anthropogenic modifications), has grown a total of 0.17 km2 since 1949. This growth rate indicates that the Towamba estuary future scenarios will mostly be filled at the completion of the 21st Century. In comparison, the partially modified (22.1%) catchment has prograded the Wandandian deltaic shorelines resulting in the total growth of 0.24 km2 during the study period (1949-2016). However, results on Comerong Island show significant changes in the spatial extent, elevation, and shorelines with total net losses of 0.3 km2 over the investigated timespan (1949-2014). Changes included northern accretion (0.4 km2), and western, middle and southern erosion (0.7 km2) of the island. The thesis emphasises the dynamic character of the estuarine eco-geomorphic system, particularly using Normalised Difference Vegetation Index (NDVI) as a vegetation canopy assessment approach. This approach illustrates the significant correlations between vegetation and climatic and geomorphic influences at the study sites, indicating that these factors are the main drivers of vegetation canopy disturbance on intertidal sedimentary landforms during the 21st Century. Locally, map-algebra expression shows the spatial distribution of the NDVI identifies areas that need to be managed in relation to the causes and drivers. This modelling confirms the LiDAR-DEMs-driven character of the existing situations to their influencing factors, which also control the estimated future-scenarios and illustrate clear inundatable landform zones at the study sites by 2100. Results indicate that the rise of sea level will have tremendous effects on the coastal eco-geomorphic systems, particularly wetlands, throughout southeastern Australia and equivalent systems overseas by the end of this century. This thesis develops possible mitigation and adaptation strategies and sustainable solutions that might be utilized to minimize the indirect devastating consequences of climate change and anthropogenic modifications, particularly damming rivers, which cause direct sedimentation problems as implied by the Tallowa Dam case study. The thesis shows that intertidal sedimentary landforms will have a future negative or positive vegetarian response according to their evolving morphological character. Within a short-term timescale, the whole eco-geomorphic system will interact with many environmental and anthropogenic variables (particularly sedimentation rates) to evolve its own character over a longer timescale. Therefore, the long term assessment approach can be directed by having a better understanding of the existing situation and accurately identifying the past drivers. Future projections indicate that indirect anthropogenic-induced global warming will have a great effect on estuaries and coastal wetlands in the 21st Century. This research helps to provide an important framework for quantifying the current situation, future stressors and vulnerability responses during any intensification of natural and artificial coastal hazards, which may be of concern to the general public and environmental scientists who are currently focusing their attention on the best way to preserve estuaries and their wetland ecosystems at the current stage of global warming and human settlement