Estimating the Extent of Degradation in the Bounfum Forest Reserve, Ghana, Using Historical Remotely Sensed Data and Landscape Fragmentation Indices

Land use and land cover changes, especially deforestation and forest degradation and its driving factors, are key factors hindering sustainable forest management. Currently, there is limited knowledge concerning the detection of the extent and interpretation of the spatial and temporal pattern of forest cover dynamics in the Bounfum Forest Reserve, which when available will inform sustainable policies. Using the Landsat TM image of 1986, Landsat ETM+ image of 2002 and Landsat 8 OLI image of 2014, the study identified and quantified the forest cover dynamics in the Bounfum Forest Reserve from 1986 to 2014. The ERDAS maximum likelihood classification algorithm was used to classify the pixels into five major land cover classes namely, bare/built areas, farmlands, closed forest, open forest and shrub/grassland. The Kappa coefficients of 0.83 (1986), 0.72 (2002) and 0.75 (2014) respectively were obtained for the classified images. The findings showed that the closed forests decreased by 3.5% (563.90 ha) per annum whilst the open forests and farm lands increased by 19.5% (385.60 ha) and 2.9% (65.00 ha) per annum within the 28-year period. This implies that the Bounfum forest reserve has been highly degraded over the past 28 years, evident through the trends of its patch densities and the number of patches. Collaborative forest management is required in the management of the forest reserve to conserve the socio-ecological and economic benefits derived from the resource on sustainable basis. Keywords: Land use and land cover change, Bounfum forest reserve, deforestation, forest degradation, remote sensing, sustainable forest managemen

Dynamique du couvert végétal à la périphérie du Parc W du Burkina Faso

L’objectif de cette étude est d’analyser la dynamique du couvert végétal du Parc W du Burkina Faso et sa périphérie à travers les images Landsat et NDVI. Les données utilisées sont des images Landsat de 1984, 1999 et 2015 de résolution 30 mètres et une série temporelle d’images MODIS NDVI-250 mètres de la période 2001-2015. Des données de références collectées à l’aide d’un GPS et des connaissances locales ont permis une classification supervisée des images Landsat à l’aide de l’algorithme de maximum de vraisemblance. Le test de Mann-Kendall a été appliqué à la série d’images NDVI pour évaluer la tendance évolutive de la végétation.Les résultats montrent que dans la zone hors parc, le couvert végétal a connu une nette régression. Cette régression s’est faite au profit des champs dont les superficies ont plus que doublé, passant de 20,2 % à 46,4 % entre 1984 et 2015. Ainsi, 88,1 %, 48,3 % et 52,2 % des superficies respectives de Botou, Diapaga et Tansarga sont affectées par la dégradation du couvert végétal. Selon le test de Mann-Kendal, 16,82 % de la zone d’étude ont une tendance négative significative de la végétation. Cette tendance est principalement localisée dans les zones à emprise agropastorale, puisque 7,88 % de ces superficies sont localisées dans des champs.The objective of this study is to analyse the dynamics of the vegetation cover of Burkina Faso’s W Park and its periphery through Landsat and NDVI images. The data used are Landsat images from 1984, 1999 and 2015 with a resolution of 30 meters and a time series of MODIS NDVI-250 meters images from the period 2001-2015. Reference data collected using GPS and local knowledge allowed a supervised classification of the Landsat images with the maximum likelihood algorithm. The Mann-Kendall test was applied to the NDVI time series to assess the vegetation trend.The results showed that in the area outside the park, the vegetation cover has clearly regressed. This regression was in favour of croplands whose area has more than doubled from 20.2% to 46.4% between 1984 and 2015. Thus, vegetation cover declined in 88.1%, 48.3% and 52.2% of the areas of Botou, Diapaga and Tansarga respectively. According to the Mann-Kendal test, 16.82% of the study area has a significant negative vegetation trend. This trend is mainly localized in the agropastoral zones, since 7.88% of these areas are located in fields

Modeling water availability for smallholder farming in inland valleys under climate and land use / land cover change in Dano, Burkina Faso

Effective water management in inland valley catchments is crucial for adaptation to the adverse impact of climate change and land use and land cover change (LULCC) on smallholder farming systems, poverty reduction, attaining food security, and ecosystem preservations in the West African region. An intensive hydrological instrumentation of four sparse data catchments (Bankandi-Loffing, Mebar, Moutori, and Fafo in Dano, Burkina Faso) has been undertaken in order to better understand hydrological processes which control water availability, to calibrate and validate the physically-based and spatially distributed water balance simulation model WaSiM, to assess the impact of climate and land use and land cover change on water resources, and subsequently to derive strategies for improving the capacity of smallholder farmers to cope with water scarcity and climate variabilities. The instrumentation of the catchment helped to achieve three years (2014-2016) of high temporal and spatial resolution data. The temporal resolutions of meteorological and stream flow data were 5 min to 10 min, six hours to a week for piezometric data, and 30 min to a week for soil moisture data. Five rain recorders, seven stream gauges, 64 piezometers in shallow groundwater (2). Additionally, the groundwater tables of three relatively deep wells (6 m, 16 m, and 25 m deep) were monitored. The analyses of hydrographs and the flow duration curves (FDC) using observed discharge show less discharge in the headwater sub-catchments compared to the downstream sub-catchments. This is due to the low contribution of base flow in the headwater sub-catchments. The decomposition of total runoff using observed hydrographs and stream electric conductivity suggests that interflow is the major contributor to total discharge. The calibration and validation of the Bankandi-Loffing catchment achieved a good model performance using the coefficient of determination (R2), the Nash-Sutcliffe efficiency (NSE), the Kling-Gupta efficiency (KGE), and the percent bias (Pbias). The R2 ranges from 0.47 to 0.95, NSE from 0.40 to 0.95, and KGE from 0.57 to 0.84 between the observed and simulated discharge. The numerical performance for soil moisture modeling is 0.70 for both R2 and NSE, and 0.80 for KGE while for the groundwater table modeling the results are 0.30, 0.20, and 0.5 for R2, NSE, and KGE, respectively. The fact that the transfer of the parameter set from Bankandi-Loffing to Mebar catchment without recalibration resulted in a good model performance (R2: 0.93, NSE: 0.92, and KGE: 0.84 in 2014-2015; R2: 0.65, NSE: 0.64, and KGE: 0.59) suggests the strong robustness of WaSiM in the investigated area. The resulting water balance shows that evapotranspiration is quantitatively the most important hydrological process, physical evaporation dominates the evapotranspiration, and 14% of rainfall runs out of the catchment as discharge. Interflow dominates runoff at the headwater sub-catchments whereas base flow is the major runoff component in the downstream area where the inland valley bottoms are located. The conversion of savanna to cropland leads to an increase of surface runoff. This is potentially associated with an exacerbation of soil erosion and soil fertility loss. Therefore, supplementing the current erosion technique (stone-belt) with agroforestry and/or mulching will reduce the negative effects of land cover change. Two scenarios were considered during the impact assessment. The first scenario evaluated exclusively the climate change impact by utilizing five regional climate models (RCMs) using land use and land cover (LULC) of the year 2013 for both the reference period (1971-2000) and the projection period (2021-2050). Each RCM is composed of the representative concentration pathways (RCPs) 4.5 and 8.5. The results indicate large uncertainty in the discharge projection for the future. Three RCMs predict an increase of total runoff for the projection period compared to the reference period. The mean total runoff increase is +61% (standard deviation Std= 31%) compared to the reference period. However, two RCMs project a decrease of total runoff. The mean total runoff decrease is -34% (Std= 10%) compared to the reference period. The second scenario utilizes the five RCMs and LULC 2013 for the reference period and LULC 2030 for the projection period in order to assess the combined impact of climate change and LULCC. The results suggest that LULCC exacerbates the increase of total runoff in combination with the three RCMs with a mean increase in total runoff by +108% (Std= 38%) compared to the reference period (versus mean= +61% in the first scenario). However, for the two RCMs predicting a decrease of total runoff, LULCC reduces the decrease of total runoff. The mean decrease is -20% (Std= 10%) compared to the reference period (versus mean= -34% in the first scenario). The results of this study can be used as input to water management models in order to derive strategies to cope with present and future water scarcities for smallholder farming in the investigated area.Modélisation de la disponibilité de l'eau pour les petites exploitations agricoles des bas-fonds sous l’influence du changement climatique, d’utilisation des sols / couverture végétale à Dano, Burkina Faso La gestion efficiente des ressources en eau dans les bassins versants des bas-fonds est indispensable non seulement pour l’adaptation aux impacts néfastes du changement climatique, utilisation sols / couverture végétale sur les petites exploitations agricoles, mais aussi pour réduire la pauvreté, l’insécurité alimentaire et préserver les écosystèmes en Afrique de l’Ouest. Une instrumentation hydrologique intensive de quatre (04) bassins versants pourvus de très peu de données (Bankandi-Loffing, Mebar, Moutori et Fafo situés à Dano, Burkina Faso) a été entreprise afin de mieux comprendre les processus hydrologiques qui contrôlent la disponibilité en ressources hydrologiques. Le modèle WaSiM (modèle à base physique distribué) a été utilisé, pour évaluer les impacts du changement climatique, d’utilisation des sols et de couverture végétale sur les ressources en eau. Cette étude pourra aider à développer des stratégies d’amélioration de la capacité des petits exploitants agricoles à surmonter les problèmes de manque d’eau et de variabilités climatiques. L'équipement hydrologique des bassins versants a permis d'obtenir durant trois (03) années (2014-2016) de données de hautes précisions temporelles et spatiales. Les précisions temporelles des données météorologiques et des données de débit des cours d'eau étaient de 5 à 10 minutes. Ces précisions étaient de 6 heures à une semaine pour les données piézométriques et de 30 minutes et une semaine pour les données sur l'humidité du sol. Cinq (05) pluviomètres, sept (07) station limnimétriques, soixante-quatre (64) piézomètres captant la nappe phréatique (< 5 m de profondeur), soixante-quatre (64) points de mesures de l'humidité du sol à trois profondeurs (5 cm, 30 cm et 50 cm) ont été installés et rendus opérationnels sur les quatre bassins versants (leur superficie total est d’environ 65 km2;). De plus, le niveau de la nappe phréatique a été régulièrement mesuré dans trois puits relativement profonds (6 m, 16 m et 25 m de profondeurs respectivement). Les analyses des hydrogrammes et des courbes de débits classés à partir des débits observés révèlent des débits plus faibles dans les sous-bassins en amont par rapport aux sous-bassins en aval. Cela s’explique en partie par la faible contribution des écoulements de base dans les sous-bassins en amont. La décomposition de l’écoulement à l'aide des hydrogrammes de débits observés et de la conductivité électrique des cours d'eau suggère que l'écoulement hypodermique est le principal contributeur des écoulements. La calibration et la validation de WaSiM pour le bassin versant de Bankandi-Loffing ont permis d'obtenir une bonne performance du modèle en utilisant le coefficient de détermination (R2), l'efficacité de Nash-Sutcliffe (NSE), l'efficacité de Kling-Gupta (KGE), et le pourcentage de biais (Pbias). R2 varie de 0,47 à 0,95, NSE de 0,40 à 0,95 et KGE de 0,57 à 0,84 entre les débits observés et les débits simulés. La performance numérique pour la modélisation de l'humidité du sol est de 0,70 pour les deux paramètres de performance R2 et NSE, et de 0,80 pour KGE. Concernant la modélisation du niveau de la nappe phréatique, les résultats sont de 0,30, 0,20 et 0,5 pour R2, NSE et KGE, respectivement. Le fait que le transfert du jeu de paramètres de Bankandi-Loffing au bassin versant de Mebar sans recalibration ait donné lieu à une bonne performance du modèle (R2: 0,93, NSE: 0,92, et KGE: 0,84 en 2014-2015 ; R2: 0,65, NSE: 0,64, et KGE: 0,59 en 2016) dénote une forte robustesse du modèle WaSiM pour la zone d’étude. Le bilan hydrique qui résulte de la modélisation montre que l'évapotranspiration est le processus hydrique le plus important quantitativement. L'évaporation physique est plus importante que la transpiration et 14% des précipitations s'écoulent du bassin versant sous forme d'écoulement de surface. Le ruissellement de surface domine les écoulements dans les sous-bassins en amont, tandis que l'écoulement de base est la principale composante des écoulements dans les sous-bassins en aval où se situent les bas-fonds. La conversion des savanes en terres cultivées entraîne une augmentation du ruissellement de surface. Ceci est potentiellement associé à une exacerbation de l'érosion et à la perte de fertilité des sols. Par conséquent, il serait envisageable de compléter les techniques anti-érosives actuelles (ceinture de pierres) par de l'agroforesterie et/ou du paillage. Deux scénarii ont été considérés lors de l’étude d'impact. Le premier scénario a évalué uniquement l'impact du changement climatique en se servant de cinq (05) modèles climatiques régionaux (RCMs) et de la carte d’utilisation des sols / couverture végétale de l'année 2013 (LULC 2013) pour la période de référence (1971-2000) et pour les projections futures (2021-2050). Chaque RCM est composé de profils représentatifs d’évolution des concentrations (RCPs) 4.5 et 8.5.  Les résultats indiquent une grande incertitude des projections de débits d’écoulement pour l'avenir. Trois RCMs prévoient une augmentation moyenne annuelle de débits de +61% (écart-type Std = 31%) par rapport à la période de référence. En revanche deux RCMs prévoient une diminution des débits de -34% (Std = 10%) en moyenne par rapport à la période de référence. Le deuxième scénario a utilisé les cinq RCMs et le LULC 2013 pour la période de référence et le LULC 2030 pour le futur afin d'évaluer l'impact combiné du changement climatique et de le LULCC. Les résultats suggèrent que le LULCC accentue l'augmentation des débits quand il est combiné avec les trois modèles prévoyant l’augmentation des débits. L'augmentation moyenne des débits est de +108% (Std = 38%) par rapport à la période de référence (contre +61% en moyenne dans le premier scénario). Cependant, pour les deux RCMs qui prévoient une diminution des débits, le LULCC attenue le changement de débit. La diminution moyenne de débit est de -20% (Std = 10%) par rapport à la période de référence (contre –34% en moyenne dans le premier scénario). Les résultats de cette étude pourront servir de données d’entrée aux modèles de gestion des ressources en eau afin d’élaborer des stratégies pour faire face aux pénuries d’eau actuelles et futures pour les petites exploitations agricoles dans la zone d’étude

Assessment of Spatio-Temporal Changes of Land Use and Land Cover over South-Western African Basins and Their Relations with Variations of Discharges

West African basins play a vital role in the socio-economic development of the region. They are mostly trans-boundary and sources of different land use practices. This work attempts to assess the spatio-temporal land use and land cover changes over three South Western African basins (Volta, Mono and Sassandra basins) and their influence on discharge. The land use and land cover maps of each basin were developed for 1988, 2002 and 2016. The results show that all the studied basins present an increase in water bodies, built-up, agricultural land and a decline in vegetative areas. These increases in water bodies and land use are as a result of an increase in small reservoirs, of dugouts and of dam constructions. However, the decline in some vegetative clusters could be attributed to the demographic and socio-economic growth as expressed by the expansion of agriculture and urbanization. The basic statistical analysis of precipitation and discharge data reveals that the mean annual discharge varies much more than the total annual precipitation at the three basins. For instance, in the entire Volta basin, the annual precipitation coefficient of variation (CV) is 10% while the annual discharge CV of Nawuni, Saboba and Bui are 43.6%, 36.51% and 47.43%, respectively. In Mono basin, the annual precipitation CV is 11.5% while the Nangbeto and Athieme annual discharge CV are 37.15% and 46.60%, respectively. The annual precipitation CV in Sassandra basin is 7.64% while the annual discharge CV of Soubre and Dakpadou are 29.41% and 37%, respectively. The discharge varies at least three times much more than the precipitation in the studied basins. The same conclusion was found for all months except the driest months (December and January). We showed that this great variation in discharge is mainly due to land use and land cover changes. Beside the hydrological modification of the land use and land cover changes, the climate of the region as well as the water quality and availability and the hydropower generation may be impacted by these changes in land surfaces conditions. Therefore, these impacts should be further assessed to implement appropriate climate services and measures for a sustainable land use and water management

SPATIAL ANALYSES AND REMOTE SENSING FOR LAND COVER CHANGE DYNAMICS: ASSESSING IN A SPATIAL PLANNING

ABSTRACT (EN) Spatial planning is a crucial discipline for the identification and implementation of sustainable development strategies that take into account the environmental impacts on the soil. In recent years, the significant development of technology, like remote sensing and GIS software, has significantly increased the understanding of environmental components, highlighting their peculiarities and criticalities. Geographically referenced information on environmental and socio-economic components represents a fundamental database for identifying and monitoring vulnerable areas, also distinguishing different levels of vulnerability. This is even more relevant considering the increasingly significant impact of land transformation processes, consisting of rapid and frequent changes in land use patterns. In order to achieve some of the Sustainable Development Goals of the 2030 Agenda, the role of environmental planning is crucial in addressing spatial problems, such as agricultural land abandonment and land take, which cause negative impacts on ecosystems. Remote sensing, and in general all Earth Observation techniques, play a key role in achieving SDG 11.3 and 15.3 of Agenda 2030. Through a series of applications and investigations in different areas of Basilicata, it has been demonstrated how the extensive use of remote sensing and spatial analysis in a GIS environment provide a substantial contribution to the results of the SDGs, enabling an informed decisionmaking process and enabling monitoring of the results expected, ensuring data reliability and directly contributing to the calculation of SDG objectives and indicators by facilitating local administrations approaches to work in different development and sustainability sectors. In this thesis have been analyse the dynamics of land transformation in terms of land take and soil erosion in sample areas of the Basilicata Region, which represents an interesting case example for the study of land use land cover change (LULCC). The socio-demographic evolutionary trends and the study of marginality and territorial fragility are fundamental aspects in the context of territorial planning, since they are important drivers of the LULCC and territorial transformation processes. In fact, in Basilicata, settlement dynamics over the years have occurred in an uncontrolled and unregulated manner, leading to a constant consumption of land not accompanied by adequate demographic and economic growth. To better understand the evolution and dynamics of the LULCCs and provide useful tools for formulating territorial planning policies and strategies aimed at a sustainable use of the territory, the socio-economic aspects of the Region were investigated. A first phase involved the creation of a database and the study and identification of essential services in the area as a fundamental parameter against which to evaluate the quality of life in a specific area. The supply of essential services can be understood as an assessment of the lack of minimum requirements with reference to the urban functions exercised by each territorial unit. From a territorial point of view, the level of peripherality of the territories with respect to the network of urban centres profoundly influences the quality of life of citizens and the level of social inclusion. In these, the presence of essential services can act as an attractor capable of generating discrete catchment areas. The purpose of this first part of the work was above all to create a dataset of data useful for the calculation of various socio-economic indicators, in order to frame the demographic evolution and the evolution of the stock of public and private services. The first methodological approach was to reconstruct the offer of essential services through the use of open data in a GIS environment and subsequently estimate the peripherality of each municipality by estimating the accessibility to essential services. The study envisaged the use of territorial analysis techniques aimed at describing the distribution of essential services on the regional territory. It is essential to understand the role of demographic dynamics as a driver of urban land use change such as, for example, the increase in demand for artificial surfaces that occurs locally. Social and economic analyses are important in the spatial planning process. Comparison of socio-economic analyses with land use and land cover change can highlight the need to modify existing policies or implement new ones. A particular land use can degrade and thereby destroy other land resources. If the economic analysis shows that the use is beneficial from the point of view of the land user, it is likely to continue, regardless of whether the process is environmentally friendly. It is important to understand and investigate which drivers have been and will be in the future the most decisive in these dynamics that intrinsically contribute to land take, agricultural abandonment and the consequent processes of land degradation and to define policies or thresholds to mitigate and monitor the effects of these processes. Subsequently, the issues of land take and abandonment of agricultural land were analysed by applying models and techniques of remote sensing, GIS and territorial analysis for the identification and monitoring of abandoned agricultural areas and sealed areas. The classic remote sensing methods have also been integrated by some geostatistical analyses which have provided more information on the investigated phenomenon. The aim was the creation of a quick methodology that would allow to describe the monitoring and analysis activities of the development trends of soil consumption and the monitoring and identification of degraded areas. The first methodology proposed allowed the automatic and rapid detection of detailed LULCC and Land Take maps with an overall accuracy of more than 90%, reducing costs and processing times. The identification of abandoned agricultural areas in degradation is among the most complicated LULCC and Land Degradation processes to identify and monitor as it is driven by a multiplicity of anthropic and natural factors. The model used to estimate soil erosion as a degradation phenomenon is the Revised Universal Soil Loss Equation (RUSLE). To identify potentially degraded areas, two factors of the RUSLE have been correlated: Factor C which describes the vegetation cover of the soil and Factor A which represents the amount of potential soil erosion. Through statistical correlation analysis with the RUSLE factors, on the basis of the deviations from the average RUSLE values and mapping of the areas of vegetation degradation, relating to arable land, through statistical correlation with the vegetation factor C, the areas were identified and mapped that are susceptible to soil degradation. The results obtained allowed the creation of a database and a map of the degraded areas to be paid attention to

Remote sensing of land use-land cover change and climate variability on hydrological processes in Sub-Saharan Africa: Key scientific strides and challenges

The impact of land use land cover (LULC) change and climatevariability on water resources poses as a major threat in semi-aridenvironments, especially in the sub-Saharan Africa. Countries insub-Saharan Africa are vulnerable to water scarcity. Hence, thereis an urgent need for understanding the various methods forLULC change and climate variability assessment, to aid in waterresources management at various scales. Various studies havemodelled and assessed the effect of LULC change and climatevariability on hydrological responses, using different approaches.In this regard, this paper provides a detailed review on the pro-gress of various remote sensing techniques in modelling andassessing the effect of LULC change and climate variability onhydrological processes

Remote sensing and multispectral imaging of hydrological responses to land use/land cover and climate variability in contrasting agro-ecological systems in Mountainous catchment, Western Cape

>Magister Scientiae - MScWater is a fundamental resource and key in the provision of energy, food and health. However, water resources are currently under severe pressure as a consequence of climate change and variability, population growth and economic development. Two driving factors that affect the availability of water resources are land use land cover (LULC) change and climate variability. Increasing population influences both LULC change and climate variability by inducing changes in key hydrological parameters such as interception rates, evapotranspiration (ET), run-off, surface infiltration, soil moisture, water quality and groundwater availability thereby affecting the watershed hydrology. The effects of LULC change and climate variability on hydrologic parameters have been extensively studied

Application of machine learning to quantify forest cover loss in the Congo Basin and its implications for large mammal habitat suitability

Machine learning (ML) models are a powerful tool for land use and land cover (LULC) mapping. In the African tropics, and particularly in the Congo Basin, there is a need to better assess the performance and reliability of ML-based LULC classification using coarse-resolution satellite images. In the context of ongoing climate change and socioeconomically-driven forest disturbances, it is important to understand and quantify the extent of forest cover loss in the Congo Basin, as well as the impact of this loss on suitable habitat for key wildlife species. In this dissertation, I address these key issues in three manuscript-based chapters. In Chapter 2, I compared the classification performance of four ML algorithms (k-nearest neighbor (kNN), support vector machines (SVM), artificial neural networks (ANN), and random forests (RF)) for LULC mapping within a tropical region in Central Africa (the Mayo Rey department of northern Cameroon). All four classification algorithms produced high accuracy (overall classification accuracy > 80%), with the RF model (> 90% classification accuracy) outperforming the other algorithms. In Chapter 3, I used the RF model, together with the Idrissi TerrSet land change modeler, to map and project LULCC for the Congo Basin under historical and future scenarios of socioeconomic impacts and climate change. I found that over 352642 km2 of dense forests have been lost in this region between 1990 and 2020, with projected continued loss of about 174860 - 204161 km2 by the year 2050. In Chapter 4, I produced spatially explicit species distribution models to map habitat suitability for great apes (chimpanzees and gorillas) and elephants within the Dzanga Sangha Protected Areas (DSPA) of the Congo Basin. I found that priority habitat areas for the three mammal species mostly occurred and overlapped spatially within the DSPA national parks. However, priority habitat areas for the three species declined by 4, 4.5 and 9.8 percentage points respectively between 2015 and 2020, mostly due to increased human pressures. This research provides a new understanding of the extend and implications of forest cover loss in the Congo Basin, highlighting the critical conservation challenges that remain in this region

Modeling climate and land use change impacts on water resources in the dano catchment (Burkina Faso, West africa)

This study investigated the impacts of climate and land use changes on water resources in the Dano catchment combining hydrological processes understanding, hydrological simulations and climate and land use scenarios application. The catchment covers about 195 km2 and is located in the Southwest of Burkina Faso in West Africa. The study area is characterized by an annual population growth of about 3% over the past decades. Based on intensive field investigations on soil hydraulic properties, instrumentation and monitoring of hydro-meteorological variables such as discharge, soil moisture, groundwater level, precipitation, temperature etc. the distributed and physically based hydrological simulation model WaSiM was successfully calibrated and validated for the catchment. Achieved model statistical quality measures (R2, NSE and KGE) ranged between 0.6 and 0.9 for total discharge, soil moisture, and groundwater level, indicating a good agreement between observed and simulated variables. Land use change assessment in the catchment over the period of 1990-2013 exhibited a decrease of natural and semi-natural vegetation at an annual rate of about 2%. Conversely, cropland, and to a lesser extend urban areas, have increased. Land conversion was attributed to population growth, changing in farming practices and environmental conditions. Four land use maps were used to build land use scenarios corresponding to different levels of land use change in the catchment. Application of the land use scenarios to the calibrated and validated hydrological model indicated that, compared to the land use status in 1990, the current situation leads to an increase in total discharge of about 17% and a decrease of actual evapotranspiration of about 5%. The results of simulations further showed that the increase in total discharge is related to high peak flow, suggesting an alteration of flood risk. Following field measurements that showed infiltration rates 1.2 times higher under semi-natural vegetation compared to cropland, land use change related effects on soil infiltration rate was integrated in the modeling of LULC change impact assessment. Model results with a refined soil (integrating this additional information) and a classic soil indicated similar trends in water balance components as a result of land use change. However slight differences of 0.5 to 20 mm/year in the water balance component were noticed between the two soil parameterization approaches. The integration of land use related effects on soil properties was suggested to render LULC change scenarios more plausible. The projected climate change signal in the catchment was analyzed using the representative concentration pathways 4.5 and 8.5 of six datasets of the COordinated Regional climate Downscaling Experiment-project. Compared to the reference period of 1971-2000, the climate models ensemble consistently projects an increased temperature of 0.1 to 2.6°C over the period 2021-2050. However, an agreement was not found among climate models with regards to precipitation change signal as projections for annual rainfall ranged between -13 and +18%. The application of the climate models ensemble in WaSiM showed future discharge change signals very similar to the projected precipitation change. Individual climate models showed opposite annual discharge change signals ranging from -40 to +50 %. On average, the climate models ensemble suggested a 7 % increase in annual discharge under RCP4.5 and a 2 % decrease under RCP8.5. The analysis of the catchment sensitivity to precipitation and temperature change indicated that discharge is more related to precipitation than to temperature as the environmental system of the catchment is water limited and not energy limited

Assessment of soil erosion based on clustered geoinformatics approaches: a case study of Tyume River Catchment, Eastern Cape, South Africa

This research centres on the holistic assessments of spatial and temporal dimensions of soil erosion zones based on the parameters of geomorphometry, hydro-statistics, and land use/cover dynamics. The study used a case study approach based on a clustered framework model of soil erosion parameters in the Tyume River basin in Eastern Cape, South Africa. The methods adopted for the investigation are, namely; non-parametric time-series assessment of streamflow dataset, semidecadal assessment of land use/cover (LU/C) dynamics, geospatial analysis of geomorphometric variables, vulnerability analysis of soil erosion zones, regression analysis of determination coefficient, and Receiver Operating Characteristic Curve (ROC). The delineation of soil erosion zones was based on the integrated analysis of the parameters of geomorphometry, geology, hydrology, and land use/ cover. The result of the hydro-statistical analysis of the Tyume River reports a major decline in the inter-annual regime frequency of storm flow based on the Mann- Kendall (MK) test and Sen’s slope assessment in 1992 (p-value = 0.031), 1997 (p-value = 0.045), 2003 (p-value = 0.021), 2008 (p-value = 0.003), and 2016 (p-value = 0.002). The MK test depicted a recurrence of peak streamflow acceleration in every three years based on low-flow and highflow transition. The sensitivity of LU/C to temporal dynamics of streamflow trends shown by the coefficient of correlation of trends of the LU/C water bodies with streamflow semi-decadal acceleration indicates a moderately relevant relationship, R = 0.76. The temporal analysis of LU/C and hydro-statistical analysis shows that the Tyume basin was highly vulnerable to soil erosion by water in 1999, 2009, and 2019. The vulnerability of the Tyume River basin in 2019 is exceptional and this is due to the conversion of forested area (woodland) into a built-up environment and farmland, with a high vulnerability in 2019 due to the slump in the rate of change of woodland and precipitation, and the increase in the rate of built-up and agricultural activities. The soil erosion vulnerability mapping divides the river basin into the critical high, high, moderate, low, nonvulnerable zones that cover 40 km2, 135 km2, 209 km2, and 186 km2 respectively. Regression analysis shows that the areas of soil erosion in the Tyume basin are moderately represented by the model (R2 = 56) while the model performance assessment based on success rate and prediction rate estimation from the area under the ROC curve shows that the model is good, Area Under Curve of the ROC = 0.899, and 0.897. The analysis suggests that soil erosion is driven by the impact of land use/land cover change, particularly in areas of high drainage density. Significantly, high vegetation density played a vital role in lowering high-flow on the hill-slope and low topographic wetness area as well as in areas with erodible geologic properties. The study, therefore, recommends the advocacy of crop rotation method of agricultural practice in the highly critical areas of soil erosion and recommends the development of riparian forests around the Tyume River. The study provides important information for environmental stakeholders on degradable areas which may require the urgent implementation of sustainable development measures.Thesis (MPhil) -- Faculty of Science and Agriculture, 202