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Remote regions, remote data: A spatial investigation of precipitation, dynamic land covers, and conflict in the Sudd wetland of South Sudan
Abstract
Though wetlands are recognized for their wide range of ecosystem services, the sustainable management of wetlands is hindered by a lack of data, especially in large transnational river systems in less-developed countries. The Sudd wetland of South Sudan is the largest freshwater wetland on the Nile River and supports transhumant pastoral cultures and wildlife migrations; yet, it is understudied in terms of its regional hydrologic controls and corresponding changes in land cover. To assess the use of remote data derived from remote sensing systems, the wetland extent between 2000 and 2014 was delineated using MODIS thermal infrared data and baseline changes in the wetland land cover extents were mapped using NDVI products. The upper White Nile basin was subdivided into seven natural sub-basins and correlations between sub-basin precipitation amounts and wetland extents were determined. Areas of high spatial variability in land cover were related to the spatial distribution of conflict in South Sudan. Results indicate that downstream sub-basins, which have largely been ignored, display high correlations (0.58–0.74) with the wetland extent and appear to be major sources of water for the wetland. Precipitation patterns in the Lake Kyoga sub-basin, instead of the neighboring torrent sub-basin that has previously been cited, correspond to inter-annual changes in wetland extents. Land cover transitions in years of reduced flow amounts varied depending upon the precipitation in upstream and downstream sub-basins. Because the downstream sub-basins appear to have a higher influence than previously anticipated, a reduction in water from the upstream sub-basins didn't necessarily lead to a reduced wetland extent. The most highly variable regions of land cover changes correspond not only to locations of conflict, but also to ethnic boundary lines. Though the conflict in this region makes in-situ data collection difficult, the conflict only increases the need for scientific assessments in order to predict changes in ecosystem services.
... These habitats appear "largely intact and largely unaffected by industrial development" (South Sudan Ministry of Culture, Youth and Sports 2017). These wetlands are also crucial for many people's livelihoods, ecosystem services, and water resources although information on the area's hydrology, ecology, and conservation is deficient (e.g., Mohamed and Savenije 2014;Sosnowski et al. 2016). ...
... Increasing trends in the daily maximum and minimum temperature in the Sudd have been recorded whereas relative humidity and solar radiation have decreased significantly (Mohamed and Savenije 2014). These changes have been correlated with large-scale climatic patterns, such as the increase of rainfall over Lake Victoria in the early 1960s (Mohamed and Savenije 2014), or local ecological changes such as changes in water flow that are related to high spatial variability in land cover which in turn is related to the spatial distribution of conflict in South Sudan (Sosnowski et al. 2016). Rural communities depending on climate sensitive resources such as fisheries generally have a high capacity to recognize changes in local climate (Howe and Leiserowitz 2013). ...
The Sudd in South Sudan, formed by the White Nile's Baḥr al-Jabal section, is one of the largest and most important wetlands in the world. Communities in the region almost exclusively depend on fisheries for food and livelihoods. Although threatened by over-exploitation and habitat changes, fish populations are also affected by climate change. Using semi-structured questionnaires, we assessed fisherfolk’s opinions of how recent variation in climate affected their livelihoods and the environment. Fisherfolk perceived that climate had changed in the past decade and were negatively impacted by this. Interviewees reported average higher temperatures, a greater frequency of floods and droughts, unpredictable timing of seasons, and erratic rainfall. Destruction of fishing villages/camps, loss and damage of fishing equipment, shifts in the fishing
calendar, reduction of fish trade, fish catch declines as well as psycho-social problems were given as the major consequences of climate change. Causes of climate change and variability were perceived to be linked to uncontrolled harvest of forest resources, anger of G-d and ancestors, and natural variability in climate. Most respondents expressed a desire to adopt more responsible behavior such as plantings trees and establishing community nurseries, being educated on climate change risks and sustainable fisheries management. Our results show that fisherfolk in the Sudd are troubled by climate change impacts on their livelihoods and on fish populations. Based on our information, further research and more focused conservation management of the Sudd wetlands are needed to achieve the Sustainable Development Goals.
... Flood waters that may be lost to infiltration were computed through the Soil Conservation Service's Curve Number (SCS-CN) method developed by the US Department of Agriculture (USDA-SCS 1985). This method is suitable for humid, semi-arid, and arid conditions [6,12,20]. Surface runoff ...
... Flood waters that may be lost to infiltration were computed through the Soil Conservation Service's Curve Number (SCS-CN) method developed by the US Department of Agriculture (USDA-SCS 1985). This method is suitable for humid, semi-arid, and arid conditions [6,12,20]. Surface runoff occurs after rainfall surpasses an initial abstraction (l a ) value. Rainfall excess (Q) is associated with the effective precipitation, (p − l a ), through a maximum potential retention value (S) as follows: ...
Flash floods are classified among the Earth’s most deadly and destructive natural hazards, particularly in arid regions. Wadi El-Ambagi, one of the largest drainage basins in the Eastern Desert of Egypt, is frequently subjected to severe flash flood damage following intense, short-lived rainstorms. This wadi is home to one of the few road networks which connects the Nile River Valley to the Red Sea Coast. At its outlet lies Quseir, one of the major coastal towns in the area. Quseir is a developing tourism and scuba diving town, and is known for its historical importance as an ancient port; thus, efforts are in place to preserve the town’s heritage. The lack of hydrological and meteorological data in this region necessitates the use of a hydrological modeling approach to predict the spatial extent, depth, and velocity of the flood waters, and hence locate sites at risk of flood inundation. This was accomplished by understanding the characteristics of surface runoff through modeled hydrographs. Here, elevation data were extracted from Shuttle Radar Topography Mission (SRTM) and a two-meter digital elevation model (DEM) derived from WorldView-2 stereo pair imagery. The land use/land cover and soil properties were mapped from fused ASTER multispectral and ALOS-PALSAR Synthetic Aperture Radar (SAR) data to produce a hybrid image that combines spectral properties and surface roughness, respectively. The results showed that storm events with rainfall intensities of 30 mm and ~60 mm over a two-hour period would generate maximum peak flows of 165 m3 s−1 and 875 m3 s−1 , respectively. The latter peak flow would generate floods with depths of up to 2 m within the town of Quseir. A flood of this magnitude would inundate 217 buildings, 7 km of the highway, and 1.43 km of the railroad in the downstream area of Wadi El-Ambagi. Findings from this work indicate that the integration of remote sensing and hydrological modeling can be a practical and quick approach to predict flash flood hazards in arid regions where data are scarce.
... The properties of water allow for increased potential with thermal imagery because night and day images can be compared using the diurnal differences of land and surface temperatures. This technique has been used in many regions worldwide, including the Everglades [16], the continent of Africa [17], an agricultural region of Germany [18], the Sudd wetlands of South Sudan [19], and the Xinjiang Autonomous Region of China [20]. The MODIS Terra and Aqua sensors are able to collect thermal data of a sufficiently high temporal resolution for night and day differencing techniques. ...
... Khan et al. [7] and Sakamoto et al. [6] demonstrated that MODIS can successfully distinguish between flooded and non-flooded pixels. The lower spatial resolution that MODIS offers is sufficient for mapping in larger regional areas [21], especially transnational water systems [19] in wetland areas [22]. The diurnal temperature difference is extremely detectable in semi-arid areas, such as southern Africa, where the surrounding landscape is devoid of localized water or heavy vegetation that may influence flood detection. ...
The Chobe River Basin (CRB), a sub-basin of the Upper Zambezi Basin shared by Namibia and Botswana, is a complex hydrologic system that lies at the center of the world's largest transfrontier conservation area. Despite its regional importance for livelihoods and biodiversity, its hydrology, controlled by the timing and relative contributions of water from two regional rivers, remains poorly understood. An increase in the magnitude of flooding in this region since 2009 has resulted in significant displacements of rural communities. We use an innovative approach that employs time-series of thermal imagery and station discharge data to model seasonal flooding patterns, identify the driving forces that control the magnitude of flooding and the high population density areas that are most at risk of high magnitude floods throughout the watershed. Spatio-temporal changes in surface inundation determined using NASA Moderate-resolution Imaging Spectroradiometer (MODIS) thermal imagery (2000–2015) revealed that flooding extent in the CRB is extremely variable, ranging from 401 km 2 to 5779 km 2 over the last 15 years. A multiple regression model of lagged discharge of surface contributor basins and flooding extent in the CRB indicated that the best predictor of flooding in this region is the discharge of the Zambezi River 64 days prior to flooding. The seasonal floods have increased drastically in magnitude since 2008 causing large populations to be displaced. Over 46,000 people (53% of Zambezi Region population) are living in high magnitude flood risk areas, making the need for resettlement planning and mitigation strategies increasingly important.
... The segmentation was compiled using nine Landsat images as a preprocessing step for image classification. The main idea behind segmentation is to use the collection of the raster scenes obtained from the archives of the United States Geological Survey (USGS) for the detection of landscape patches to map flooded areas of the Sudd wetlands which experience spatio-temporal changes over time [69][70][71]. To demonstrate the value of image segmentation techniques, we use them as priors in image classification and object detection as land cover classes. ...
This paper presents the object detection algorithms GRASS GIS applied for Landsat 8-9 OLI/TIRS data. The study area includes the Sudd wetlands located in South Sudan. This study describes a programming method for the automated processing of satellite images for environmental analytics, applying the scripting algorithms of GRASS GIS. This study documents how the land cover changed and developed over time in South Sudan with varying climate and environmental settings, indicating the variations in landscape patterns. A set of modules was used to process satellite images by scripting language. It streamlines the geospatial processing tasks. The functionality of the modules of GRASS GIS to image processing is called within scripts as subprocesses which automate operations. The cutting-edge tools of GRASS GIS present a cost-effective solution to remote sensing data modelling and analysis. This is based on the discrimination of the spectral reflectance of pixels on the raster scenes. Scripting algorithms of remote sensing data processing based on the GRASS GIS syntax are run from the terminal, enabling to pass commands to the module. This ensures the automation and high speed of image processing. The algorithm challenge is that landscape patterns differ substantially, and there are nonlinear dynamics in land cover types due to environmental factors and climate effects. Time series analysis of several multispectral images demonstrated changes in land cover types over the study area of the Sudd, South Sudan affected by environmental degradation of landscapes. The map is generated for each Landsat image from 2015 to 2023 using 481 maximum-likelihood discriminant analysis approaches of classification. The methodology includes image segmentation by ‘i.segment’ module, image clustering and classification by ‘i.cluster’ and ‘i.maxlike’ modules, accuracy assessment by ‘r.kappa’ module, and computing NDVI and cartographic mapping implemented using GRASS GIS. The benefits of object detection techniques for image analysis are demonstrated with the reported effects of various threshold levels of segmentation. The segmentation was performed 371 times with 90% of the threshold and minsize = 5; the process was converged in 37 to 41 iterations. The following segments are defined for images: 4515 for 2015, 4813 for 2016, 4114 for 2017, 5090 for 2018, 6021 for 2019, 3187 for 2020, 2445 for 2022, and 5181 for 2023. The percent convergence is 98% for the processed images. Detecting variations in land cover patterns is possible using spaceborne datasets and advanced applications of scripting algorithms. The implications of cartographic approach for environmental landscape analysis are discussed. The algorithm for image processing is based on a set of GRASS GIS wrapper functions for automated image classification.
... The satellite sensors observing the Earth provide remote sensing data which allow one to highlight the links between the hydrological and climate processes leading to desertification and vegetation responses in environmental studies. The importance of the use of remote sensing data and advanced methods of image processing was raised in earlier studies [6][7][8][9]. Satellite images can be used to analyse the links between complex hydrological and climate processes and vegetation responses that lead to desertification. For example, Landsat images are known to be a reliable source of data for relatively accurate techniques for classifying time-series and detecting forest and land cover types [10][11][12][13], computing vegetation indices [14][15][16] and specifically desertification [17] to show the advance or retreat of arid areas using the analysis of satellite images. ...
Desertification is one of the most destructive climate-related issues in the Sudan–Sahel region of Africa. As the assessment of desertification is possible by satellite image analysis using vegetation indices (VIs), this study reports on the technical advantages and capabilities of scripting the ‘raster’ and ‘terra’ R-language packages for computing the VIs. The test area which was considered includes the region of the confluence between the Blue and White Niles in Khartoum, southern Sudan, northeast Africa and the Landsat 8–9 OLI/TIRS images taken for the years 2013, 2018 and 2022, which were chosen as test datasets. The VIs used here are robust indicators of plant greenness, and combined with vegetation coverage, are essential parameters for environmental analytics. Five VIs were calculated to compare both the status and dynamics of vegetation through the differences between the images collected within the nine-year span. Using scripts for computing and visualising the VIs over Sudan demonstrates previously unreported patterns of vegetation to reveal climate–vegetation relationships. The ability of the R packages ‘raster’ and ‘terra’ to process spatial data was enhanced through scripting to automate image analysis and mapping, and choosing Sudan for the case study enables us to present new perspectives for image processing.
... The Sudd is one of the world's largest freshwater ecosystems and the largest in the Nile Basin, draining much of Eastern Africa, including water from Lake Victoria (Sutcliffe and Brown, 2018). This outflow from Lake Victoria leads to strong seasonal inundation, characterised by annual flood pulses (Rebelo et al., 2012), that is further modified by local precipitation and evaporation (Mohamed and Savenije, 2014), leading to highly complex and seasonal behaviour (Sosnowski et al., 2016). Previous work (Parker et al., 2020a;Lunt et al., 2021;Pandey et al., 2021) has detailed the importance of understanding and characterising the CH 4 emissions from the Sudd wetlands given their sensitivity to large-scale climate drivers. ...
Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model (UKESM) and is capable of generating estimates of wetland methane emissions. In this study, we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 and 0.88 for most regions; however, the seasonal cycle amplitude is typically underestimated (by between 1.8 and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data are found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration outperforms the other, but this does lead to poor performance in some regions. We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1, 19.5 and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to explicitly represent river and floodplain water dynamics and find that these JULES-CaMa-Flood simulations are capable of providing a wetland extent that is more consistent with observations in this regions, highlighting this as an important area for future model development.
... Through qualitative and quantitative methods, the evidence for Sudan and South Sudan suggests that variations in the geographical distribution of water and vegetative resources (De Juan, 2015), and temperature anomalies (Maystadt et al., 2014a), are associated with the risk of violent conflict. Olsson and Siba (2013) show that militia attacks are more common in villages near floodplains, while, according to Sosnowski et al. (2016), the dry season and the reduced water flow from the Victoria Lake correspond to an increase in violent clashes between the Dinka and Nuer ethnic groups. Despite the increased attention on this region (Assal, 2006;Chavunduka and Bromley, 2011a;Leff, 2009;Rowhani et al., 2012), the relationship between climate variations, population dynamics, conflict and organised violence remains rather complex, with quantitative analyses at the sub-national level often yielding inconclusive results on the significance and causality of the link, and the mechanisms underlying the nexus remaining largely overlooked (Eberle et al., 2020). ...
This publication is a Technical report by the Joint Research Centre (JRC), the European Commission's science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. For information on the methodology and quality underlying the data used in this publication for which the source is neither Eurostat nor other Commission services, users should contact the referenced source. The designations employed and the presentation of material on the maps do not imply the expression of any opinion whatsoever on the part of the European Union concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.
... Climate-induced migration and the issue of climate refugees are particularly of concern in global climate governance. In the past, abrupt hydroclimatic changes or frequent occurrences of droughts/ oods led to turmoil periods in human history (Meier et al., 2007;Sosnowski et al., 2016;Zhang et al., 2008;Büntgen et al., 2011). As a cradle of the ancient cultures, Europe featured several episodes of climate deterioration over the past millennia, which have been discussed as triggers of diseases (Appleby, 1980), population decrease (Patterson et al., 2010), and migrations (Thompson et al., 1999). ...
Times of turmoil in Europe during past millennia have been linked to hydroclimate variability. The invasion of foreign peoples that hastened the collapse of the Roman Empire, for example, was suggested to have been triggered by precipitation minima. However, the climate evolution of central-east Europe, the cradle of these tribes, remains elusive, thus limiting our understanding of how ancient civilizations responded to climate change. In this study, we present a 3000-year-long winter temperature and precipitation record inferred from a stalagmite in central Slovakia with dating uncertainties as small as ±6 yr. The data reveal that this region experienced seven 100-200 year-long cold intervals during the past three millennia. Three of these intervals with wet winters centered at 350 BC, and 400 and 900 AD coincided with historic invasion events in eastern Europe. These cold intervals were likely triggered by a weakened North Atlantic circulation and concomitant atmospheric blockings over western Europe.
... Such unreliable climatic changes have resulted to water shortage for agricultural production and lack of pasture for cattle. also, the occasional flooding is one of the climatic challenges leading to displacement of communities, both animals and human diseases and destruction of agricultural production especially in Jonglei and Upper Nile to mention but are few [23,38]. Changes in weather has also led to internal and even inter-state conflict, for instance the disclosed Sudan conflict with her neighbors on the Nile water [39], ...
South Sudan has agriculture as one of the main contributors of her economy since the vast majority of the households engage in different agricultural activities. Among which is Livestock and it is mostly done on small scale. Cattle keepers are faced with challenges like political instability, civil conflicts, cattle raiding, Continuous uncontrolled pastoralism and poor record keeping by stakeholder with less or no initiatives from gov't to combat the above short comings. The above loopholes among others retard the improvement of the livestock sector. This paper however is meant to highlight the most challenges affecting livestock production, and possible suggestions that can be of use for the organization and the improvement of the livestock sectors. Although South Sudan is considered to be one of the highest Cattle keeping country in Africa, this may be just a mirth once the above issues aren't timely addressed.
... 160 It can also be considered as linked to the Sudd Wetland. 161 The catchment of the Bahr el Ghazal covers an area of approximately 645 000 km2 and is an important tributary of the White Nile system. 162 The Bahr el Ghazal wetlands are seasonally flooded, supporting biodiversity and pastoral livelihoods. ...
The Horn of Africa is a region exposed to the risks of water insecurity due to population growth and the impact of climate change. Growing water stress complicates many of the region’s social, political and economic difficulties, including weak governance and societal tensions between ethnic, regional or religious groups. The double impact of climate stress and violent conflict has led to increased social vulnerability and political fragility, which in turn affects the region’s prospects for adapting to changing environmental conditions. Cooperation over water resources as a policy option to address such challenges has been high on the research and policy agenda for decades. International and national policymakers are particularly interested in how different forms of water cooperation can mitigate the drivers of conflict, prevent the escalation of tensions, and build resilience to better respond to the impacts of climate change.
Previous research has identified that water cooperation is relevant both in different forms and at different levels, which calls for a better understanding of informal arrangements at the local level. This joint SIPRI–CIWA report aims to help to fill this research gap by exploring the role of local-level cooperative initiatives in improving water resource challenges in the Horn of Africa. The report draws on three illustrative case studies of transboundary basins in cross-border regions: the Sio–Malaba–Malakishi Basin; the Dawa River and Aquifer; and the Bahr el Ghazal Basin and the Baggara Basin Aquifer. In doing so, it provides lessons learned from existing cooperative initiatives.
... Through qualitative and quantitative methods (Assal 2006;Chavunduka and Bromley 2011;Leff 2009;Rowhani et al. 2012), evidence for Sudan and South Sudan suggests that variations in the geographical distribution of water and vegetative resources (De Juan 2015) and temperature anomalies (Maystadt et al. 2015) are positively associated with the risk of violent conflict. Militia attacks have been found to be more common in villages near floodplains (Olsson and Siba 2013), and the drier season with the reduced flow of water from Lake Victoria coincided with an increase in fighting between the Dinka and Nuer ethnic groups in the wetlands of Sudan (Sosnowski et al. 2016). Despite the growing attention on the climate-conflict nexus, this remains a complex and context-specific phenomenon 45 See https://thinkhazard.org/en/. ...
The report quantifies exposed and vulnerable populations to climate change in Africa based on climate, demographic and socio-economic scenarios and analyses past trends, to detect statically significant associations between net migration and climate. It follows a spatial demographic approach and covers the entire territory of Africa with data and projections at high geographical resolution spanning from 1975 to 2100. These macro analyses are complemented by case studies looking at the relation between climate change displacement and urbanization in Egypt, drought migration in the Sahel regions and the role of conflicts in Sudan and South Sudan. Finally, the report considers individual perspectives using survey data on the perceptions in Africa about climate change and the desire to migrate. The findings of this report support the ongoing integration of EU policymaking on climate change, adaptation and migration. Specifically, it highlights the importance of further mainstreaming an understanding of climate change processes into demographic processes and adaptation actions at a local level.
... Cyperus papyrus, Phragmites communis, Vossia cuspidata, Typha domingensis and Eichornia crassipes (water hyacinth) are common along open water channels and dominate the permanent swamp areas, which are surrounded by floodplains and seasonally flooded grasslands characterized by Oryza longistaminata and Echinochloa pyramidalis. Previous wetland research in the area tended to focus on hydrological regime (Rebelo et al., 2011;Sosnowski et al., 2016;Sutcliff and Brown, 2018) and effects of hydrocarbon contamination on soils (Ruley et al., 2019) while soil seed bank studies have largely been neglected thus curtailing deeper understanding of soil seed banks in the Sudd wetlands of South Sudan. Moreover, there has been limited research in wetlands in the surroundings of Juba City which are experiencing increasing human population growth estimated at 4.61% per annum (Fernando and Garvey, 2013). ...
Soil seed banks are important for regeneration of degraded wetlands ecosystems. The Sudd wetlands of Juba city have long been encroached for crop cultivation. Seedling germination was monitored in a greenhouse to establish possible natural regeneration in Mindiari, Rejaf and Roton wetlands in the Sudd. Sixty-four species germinated from the soil seed bank of which 12.5% were dominated by Cyperus difformis and Typha capensis. The findings showed that median wetland species richness in Mindiari was 1.5 (interquartile range = 0.75?3.5), Rejaf 2.5 (interquartile range = 1.0 ? 4.0), Roton 3 (interquartile range = 1.0 ? 5.0) while median Shannon-Wiener diversity was 1.5 (1.14 ?1.73), 1.43 (1.01?1.66), 1.15 (0.98?1.67) for Mindiari, Rejaf and Roton respectively. Both the median seed species richness and diversity were not significantly different among the study wetlands. The median of seed density (56.1) was significantly higher in Roton than in Mindiari (36.7) and Rejaf (29.4) wetlands. The NMDS results showed that species composition of Mindiari and Rejaf was different from Roton. It is concluded that growing crops in wetlands did not influence species richness and diversity but it reduced seed density and altered species composition. Although wetland species were not significantly different in the three-wetland categories, dominance of canopy species belonging to Typhaceae and Cyperaceae indicates that these species are resilient to cultivation and could facilitate natural regeneration of cultivated wetlands edges of the Sudd region in Juba. Further research should examine effect of cultivation duration and flooding regimes on soil seed bank species richness, diversity, and density and composition.
... Uncategorized sensors covered 7% of the biomes, aerial photographs, and Lidar ALS sensor stands out within this segment (e.g., Note et al., 2018). Finally, coarse sensors (>250 m) covered 6% of the biomes in which MODIS sensor was the most outstanding (e.g., Gorsevski et al., 2012;Hecht and Saatchi, 2007;Sánchez-Cuervo and Aide, 2013;Sosnowski et al., 2016) (Fig. 5). Table 3 was obtained after crossing the data between the study area type of biome and the satellite imagery sensors used for RS. ...
Armed conflicts not only affect human populations but can also cause considerable damage to the environment. Its consequences are as diverse as its causes, including; water pollution from oil spills, land degradation due to the destruction of infrastructure, poisoning of soils and fields, destruction of crops and forests, over-exploitation of natural resources and paradoxically and occasionally reforestation. In this way, the environment in the war can be approached as beneficiary, stage, victim or/and spoil of war.
Although there are few papers that assess the use of remote sensing methods in areas affected by warfare, we found a gap in these studies, being both outdated and lacking the correlation of remote sensing analysis with the causes-consequences, biome features and scale. Thus, this paper presents a methodical approach focused on the assessment of the existing datasets and the analysis of the connection between geographical conditions (biomes), drivers and the assessment using remote sensing methods in areas affected by armed conflicts. We aimed to find; weaknesses, tendencies, patterns, points of convergence and divergence. Then we consider variables such as biome, forest cover affectation, scale, and satellite imagery sensors to determine the relationship between warfare drivers with geographical location assessed by remote sensing methods. We collected data from 44 studies from international peer-reviewed journals from 1998 to 2019 that are indexed using scientific search engines. We found that 62% of the studies were focused on the analysis of torrid biomes as; Tropical Rainforest, Monsoon Forest / Dry Forest, Tree Savanna and Grass Savanna, using the 64% Moderate-resolution satellite imagery sensors as; Landsat 4-5 TM and Landsat 7 ETM+. Quantitative analysis of the trends identified within these areas contributes to an understanding of the reasons behind these conflicts.
... These human-induced modifications have significant impacts on waterbird species (Liang et al., 2018b;Liang et al., 2021;Mei et al., 2015). The ecological status of lakes in many regions are reported to be affected by water conservancy projects, such as the Amur Basin (Jia et al., 2020), the semi-arid rivers in Colorado, USA (Diehl et al., 2020), and the Sudd wetland of South Sudan (Sosnowski et al., 2016). Dam constructions dramatically change hydrological regimes of global river systems. ...
Hydrology-climate changes and food availability are expected to be the primary drivers that result in a loss of waterbirds diversity. Non-biological factors are vital to food availability in interconnected river-lake systems, so in addition to identifying the ecological response to drivers, it is also important to analyze and quantify relationships between drivers. In order to explore the impacts of these drivers on the wintering waterbirds, we selected Dongting Lake (DTL) as a study area, which is a typical interconnected river-lake system in the middle and lower reaches of the Yangtze River Floodplain. The Anatidae species, most of which are herbivorous, were chosen as the representative waterfowl. The Pearson correlation coefficient was applied to select variables related to the timing of water recession and food availability, which have significant influences on the Anatidae. Then, the structural equation model (SEM) was carried out to quantify the relationships among the food availability, hydrological variables, and climatic variables. The results showed that unseasonably early or late water recession had a negative impact on the diversity of the Anatidae, and in particular affected population dynamics of the Lesser White-fronted goose Anser erythropus. Significant changes in Anatidae populations in DTL occurred in response to maximum NDVI (r=0.53, p<0.01) and the interval time of water recession (r=-0.43, p<0.1). Water level, flow, and interval time of water recession explained 71% of maximum NDVI in DTL. In addition, hydraulic interactions between the mainstream and each lake jointly affected the inundation pattern and the vegetation growth stage of the lake after the flood season, thus affecting foraging suitability. Our findings suggest that water compensation should be carried out within an appropriate range of hydraulic gradient to optimize the time of water recession and improve the suitability of the habitat effectively.
... South Sudan has a production capacity of 298,000/390,000 barrels per day [8,9] including Sudd wetland. Sudd is the largest wetland in the whole world and covers 57,000 Km 2 that makes up approximately 5% of the total land area of the Republic of South Sudan (648,000 Km 2 ) [10,11]. e area of the wetland is larger than countries such as Switzerland, Belgium, the Netherlands, and Singapore [12]. ...
The Sudd wetland is one of the oil-rich regions of South Sudan where environmental pollution resulting from oil extraction activities has been unprecedented. Although phytoremediation is the most feasible technique, its efficacy reduces at high TPH concentration in soil. This has made rhizoremediation the most preferred approach. Rhizoremediation involves use of a combination of phytoremediation and biostimulation. The process is catalyzed by the action of rhizobacteria. Therefore, the objective of this study is to characterize rhizobacteria communities prevalent in phytoremediation species growing in hydrocarbon-contaminated soils biostimulated with cattle manure. The treatments studied were plant species only (T1), plant species and hydrocarbons (T2), plant species and manure (T3), and plant species, manure, and hydrocarbons (T4). The rhizobacteria communities were determined using pyrosequencing of 16S rRNA. In the treatment with phytoremediation species, hydrocarbons 75 g · kg−1soil, and cattle manure 5 g · kg−1soil (T4), there was a significant increase (p
... Such unreliable climatic changes have resulted to water shortage for agricultural production and lack of pasture for cattle. also, the occasional flooding is one of the climatic challenges leading to displacement of communities, both animals and human diseases and destruction of agricultural production especially in Jonglei and Upper Nile to mention but are few [23,38]. Changes in weather has also led to internal and even inter-state conflict, for instance the disclosed Sudan conflict with her neighbors on the Nile water [39], ...
South Sudan has agrıculture as one of the main contributors of her economy since the vast majority of the households engage in different agricultural activities. Among which is Livestock and it is mostly done on small scale. Cattle keepers are faced with challenges like political instability, civil conflicts, cattle raiding, Continuous uncontrolled pastoralism and poor record keeping by stakeholder with less or no initiatives from gov’t to combat the above short comings. The above loopholes among others retard the improvement of the livestock sector. This paper however is meant to highlight the most challenges affecting livestock production, and possible suggestions that can be of use for the organization and the improvement of the livestock sectors. Although South Sudan is considered to be one of the highest Cattle keeping country in Africa, this may be just a mirth once the above issues aren’t timely addressed.
... Our finding is consistent with previous works which have determined an increase in the spatial extent of the Sudd using MODIS LST diurnal temperature difference (Sosnowski et al., 2016) and MODIS land surface reflectance data (Vittorio and Georgakakos, 2018). Both studies indicate that the flooded extent of the Sudd was particularly small in 2009-2010 in both wet and dry seasons, with seasonally flooded vegetation that was constrained to be very close to the White Nile river itself. ...
Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5∘×0.625∘) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74–78) to 80 (78–82) Tg yr−1, depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, depending on the CO2 data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.
... Our finding is consistent with previous works which have determined an increase in the spatial extent of the Sudd using MODIS LST diurnal temperature difference (Sosnowski et al., 2016), and MODIS land surface reflectance data (Vittorio and Georgakakos, 2018). Both studies indicate that the flooded extent of the Sudd was particularly small in 2009-2010 in both wet and dry seasons, with seasonally flooded vegetation that was constrained to be very close to the White Nile river itself. ...
Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing SATellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5 × 0.625) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010–2016 range from 75 (72–78) Tg yr−1 to 80 (78–83) Tg yr−1, dependent on the proxy XCH4 data used, with larger differences in northern hemisphere Africa than southern hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our seven-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, dependent on the CO2 data product used in the proxy retrieval. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data we find this increase in CH4 emission is consistent with an increase in wetland extent due to increased inflow from the White Nile. We find a strong seasonality in emissions across northern hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.
... These two uses also pose considerable issues. Firstly, the need to ensure passable navigation channels, whilst essential economically within many large river basins, may lead to concerns regarding hydrologi- cally sensitive regions, and especially wetlands such as the Sudd on the Nile River in Southern Sudan 165 and the Pantanal on the Paraná River in Paraguay [166][167][168] , that could be adversely affected by dredging or flow diversions. Secondly, sediment mining ( Supplementary Fig. 6) may contribute significantly to decreasing downstream sediment flux, which may exacerbate the effects of subsidence in river del- tas, as well as causing scour around in-channel engineering struc- tures 169-171 and potentially triggering channel incision 172 and bank failures. ...
The world’s big rivers and their floodplains were central to development of civilization and are now home to c. 2.7 billion people. They are economically vital whilst also constituting some of the most diverse habitats on Earth. However, a number of anthropogenic stressors, including large-scale damming, hydrological change, pollution, introduction of non-native species and sediment mining, challenge their integrity and future, as never before. The rapidity and extent of such change is so great that large-scale, and potentially irreparable, transformations may ensue in periods of years to decades, with ecosystem collapse being possible in some big rivers. Prioritizing the fate of the world’s great river corridors on an international political stage is imperative. Future sustainable management, and establishment of environmental flow requirements for the world’s big rivers, must be supported through co-ordinated international funding, and trans-continental political agreement to monitor these rivers, finance their continual upkeep and help ameliorate increasing anthropogenic pressures. To have any effect, all of these must be set within an inclusive governance framework across scales, organizations and local populace. © 2018, The Author(s), under exclusive licence to Springer Nature Limited.
... For digital topographic data, the 30 m SRTM and the 12.5 m ALOS PALSAR terrain dataset were used. Drainages were extracted based on a procedure by [25], with drainage pathways and flow accumulation delineated with the widely used 8D flow direction algorithm [17,26]. Drainage networks were generated using a threshold of 2000 cells and were then compared against the actual subsurface channels revealed in Sentinel-1 and PALSAR radar scenes. ...
This work communicates the discovery of a sandy buried 10.5 km diameter near-circular structure in the eastern part of the Great Sahara in North Africa. Rimaal, meaning “sand” in Arabic, is given as the name for this structure since it is largely concealed beneath the Sahara Aeolian sand. Remote sensing image fusion and transformation of multispectral data (from Landsat-8) and synthetic aperture radar (from Sentinel-1 and ALOS PALSAR), of dual wavelengths (C and L-bands) and multi-polarization (HV, VV, HH, and HV), were adopted in this work. The optical and microwave hybrid imagery enabled the combining of surface spectral properties and subsurface roughness information for better understanding of the Rimaal structure. The long wavelength of the radar, in particular, enabled the penetration of desert sands and the revealing of the proposed structure. The structure exhibits a clear outer rim with traces of concentric faults, an annular flat basin and an inner ring surrounding remnants of a highly eroded central peak. Radar imagery clearly shows the interior wall of the structure is incised with radial pattern gullies that originate at or near the crater periphery, implying a much steeper rim wall in the past. In addition, data reveals a circumferential of a paleoriver course that flows along a curved path parallel to the crater’s western margin indicating the plausible presence of a concentric ring graben related to the inferred structure. The defined crater boundary is coincident with a shallow semi-circular-like basin in the SRTM elevation data. The structure portrays considerable modifications by extensive long-term Aeolian and fluvial erosion. Residing in the Cretaceous Nubian Sandstone formation suggests an old age of ≤65 Ma for the structure. If proven to be of an impact origin, the Rimaal structure could help in understanding the early evolution of the landscape of the Eastern Sahara and holds promise for hosting economically valuable ore deposits and hydrocarbon resources in the region.
... Furthermore, the swamp and surface water land types were combined to highlight changes in the presence and absence of vegetation relative to water-logged landscapes (Fig. 11). Our results showed that the grasslands exhibited a very little fluctuation relative to the highly fluctuating one conformed by the water swamp class in the Hamoun wetland area, but in other wetlands, vegetation cover is entitled as a main factor for LCCs (Munyati 2000;Tareq et al. 2004;Sosnowski et al. 2016). We considered that grasslands were not the best indicators for analyzing dynamics of Hamoun wetland, because no significantly changes were observed during a long-term period (Fig. 6d). ...
The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987–2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R² = 0.94) than fall and spring (R² = 0.58) seasons. Before 2000, ~ 50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.
... The rainfall regime in Pariang and Maban is unimodal with a single rainy season from May to October (Chen, Guo, Zhang, & Xu, 2013;Sosnowski, Ghoneim, Burke, Hines, & Halls, 2016). According to Climate-data.org ...
Mass population displacements put additional stress on the ecosystems and often lead to conflicts with the host communities, especially in the case of large refugee or Internally Displaced Person (IDP) camps. Therefore, there is need for the assessment of environmental impacts and, based on this, the sustainable management of natural resources between host and refugee communities. We propose a method based on high (Landsat 5,7 and 8) and very high (WorldView-2) resolution Earth Observation data to establish forest inventories combining the analysis of remote sensing satellite data along with ground-based observations in South Sudan. The resulting forest inventory mapping comprises map products on vegetation cover, tree species, and vegetation changes. We distinguished between the vegetation types grassland, shrub/tree savanna, savanna woodland, and woodland. For savanna woodland and woodland, we furthermore applied a tree species classification, differentiating between Red acacia, Desert date tree, Silak, and Doum palm. The tree species classification yielded in mean accuracies of about 61.0% for both the Landsat and WorldView based classifications, with the best results achieved for Desert palm tree and red acacia with average accuracies of 88% and 53%, respectively. The product about vegetation changes indicates a decrease of vegetation up to 50% within and in the surroundings of the refugee camps/settlement. The resulting maps can serve to estimate accessible wood resources and to identify potential harvest areas. In addition, they can support the definition of a sustainable use of wood for construction and cooking purposes for the refugee and host communities based on a community forest management.
... Migration can lead to ethnic tensions that result in violent conflict, particularly when migrants and residents come from different ethnic groups that have a history of violence (Reuveny 2007, 657). By moving their herds to areas that are richer in water and pasture, pastoralists may also end up closer to other groups, inciting competition over shared resources or making them more vulnerable to attack by hostile groups (Leff 2009;Hundie 2010;Adem et al. 2012;Ember et al. 2012Ember et al. , 2014Detges 2014;Sosnowski et al. 2016). Second, and related to the first mechanism, migration and changing pastoral mobility patterns bring communities together that may lack shared conflict resolution institutions. ...
How does climate change affect the risk and dynamics of violent conflict? Existing research shows that climate change can increase the risk of violent conflict and significantly alter the dynamics of existing conflicts. Less is known about the exact mechanisms through which climate change affects violent conflict. In this article, we address this lacuna in light of the first systematic review of both quantitative and qualitative scholarship. Through an analysis of forty-three peer-reviewed articles on climate-related environmental change and violent conflict in East Africa published 1989–2016, we evaluate to what extent the literature provides coherent explanations that identify relevant mechanisms, actors, and outcomes. In addition, we discuss the expected temporal and spatial distribution of violence and the confounding political factors implied in the literature. Against this background, we offer a number of suggestions for how future climate-conflict research can theorize and explore mechanisms. Future research should distinguish between explanations that focus on causes and dynamics of climate-related violent conflict, theoretically motivate when and where violence is most likely to occur, systematically examine the role of state policies and intervention, and explore the implications of each explanation at the microlevel.
... While the long-term evolution of the wetland has been studied from remote sensing images, studies have not provided information about how to select either appropriate time periods or images. Various other studies (Chen et al., 2014;Romshoo and Rashid, 2014;Sosnowski et al., 2016) adopted time periods that were considered sensible but otherwise were chosen without a firm scientific basis. ...
There is wide concern about the evolution of wetlands, an important component of the global ecosystem. The Honghe National Nature Reserve (HNNR) is an internationally important marsh wetland in China that is at risk of degradation. To gain an improved understanding of how the HNNR wetland developed from 1975 to 2014, typical years, including 1975, 1988, 1996, 2002 and 2014, were selected based on precipitation date. And land cover types of the different years were classified using TM images. The results showed that the wetland evolution mainly reflects transformations between the meadow and wetland land cover types. The landscape index suggests the wetland is degrading. The main drivers of wetland evolution were a warmer and drier climate, the establishment of an irrigation system, and a decrease in the groundwater level. These factors resulted in changes in the quantity of water in the HNNR. We can therefore say that the evolution was driven by changes in the water quantity. Because there have been very few hydrogeological studies in the HNNR, we examined the relationships among precipitation, surface water, and groundwater, all of which significantly influence water quantity. We found that precipitation was the only source of surface water and, while there was certain amount of surface water recharge into the shallow groundwater, the recharge range was limited, which increased the vulnerability of the wetlands. Thus, it is difficult to recharge surface water but easy to lose surface water from the HNNR, which suggests that efforts need to be directed at maintaining the surface water at the optimal level to prevent degradation of the wetland.
The development of biofilms and the microbial biofilm adherence into the production equipment and facilities used in the dairy industry is a critical issue that needs to be addressed. Biofilms lead to the contamination of food by pathogenic and spoilage m/os. The microbes cause both company loses due to unsafe spoilt products, equipment depreciation and death of consumers under severe pathogenic out breaks. Biofilms may also lead to a failure of anti- microbial therapy hence major threats to modern medicine. Biofilm formation however is a dynamic process with different mechanisms involved in the biofilm growth. Raw milk provides an ideal medium for the formation of a biofilm as it contains bacteria and is nutrient-rich. This paper gives highlights regarding microbial sources, challenges, biofilm control strategies that include but not limited to physical, mechanical, enzymatic and chemical methods for the effective control of formation and or eradicate biofilm in the dairy industry.
Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model and is capable of generating estimates of wetland methane emissions. In this study we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 to 0.88 for most regions, however the seasonal cycle amplitude is typically underestimated (by between 1.8 ppb and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data is found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration out-performs the other but this does lead to poor performance in some regions. We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1 ppb, 19.5 ppb and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the CaMa-Flood model to explicitly represent river and floodplain water dynamics and find these JULES-CaMa-Flood simulations are capable of providing wetland extent more consistent with observations in this regions, highlighting this as an important area for future model development.
Flash floods are among the most common natural hazards in Egypt. Wadi El-Darb, one of the vastest drainage catchment in the Eastern Desert of Egypt, is considerably subjected to severe flash flood events. The coastal city of Ras Gharib is located at the outlet of this Wadi, which consequently makes it susceptible to the flash flood hazard. Ras Gharib has a strategic importance to Egypt that it produces 65% of the petroleum requirement; therefore, the government seeks hard to protect the city. Using hydrological modeling approach was necessary, especially in case of the lack of hydrological and meteorological data in the region, to simulate the spatial extent, depth, and speed of the floodwater and then identify the sites at risk of flooding. The elevation data were extracted from digital elevation models (SRTM and ALOS PALSAR). The soil texture properties can be derived from Sentinel-1 radar images fused with geological data to produce the hybrid land cover map containing the rock types and their texture information. Sentinel-2 imagery was used to map the land use/land cover (LULC) in the downstream area of the basin. The results showed that the rainstorm with 51 mm of precipitation intensity would cause, at the outlet of the Wadi El-Darb basin, peak discharge rate of 852.73 m3/s, and the flash flood water can reach Ras Gharib city within 4 h, with an average flood depth of 1.69 m. Also, the flash flood impacts concentrated in the midtown covering about 2.93 km2, about 342 houses, 33.35 km of Ras Ghareb-Minya highway, and 55.9-km long of the internal road network were inundated. The hydrologic modeling results were validated using Jaccard coefficient (= 0.72), based on the integration of Sentinel-2 images along with aerial photos (captured post the flood), Google Earth images, and Open Street Map (OSM). Accordingly, this work provides the developing countries with a practical and quick technique to predict flash flood hazards in arid regions where data are scarce.
The history of the Nile in Africa offers useful lessons for civil engineers seeking to build a sustainable future in which climate change is an existential challenge. For thousands of years, communities along the river have sought greater water security at the interface of technical possibility, politics and unpredictable nature. Large projects such as the Grand Ethiopian Renaissance dam and Jonglei canal in South Sudan continue to be controversial, but both show how civil engineers might help to address climate-change challenges. Once again, Nile communities need civil engineers to find and implement innovative, politically acceptable and sustainable development initiatives.
In the version of this Review originally published, the author name ‘Arthington’ was misspelt in refs 216 and 218. Further, in the sentence that starts “Global warming has also been linked to potentially significant increases in the flow of Russia’s three great Artic rivers..”, ‘Artic’ should have been ‘Arctic’. These errors have now been corrected.
This report establishes a framework for environmental transboundary management in the Nile Basin and, within this framework, constructs principles for assessing environmental aspects of proposed projects. The report addresses current environmental conditions and the forces affec- ting change; it also addresses transboundary environmental factors that are important in apprais- ing proposed programs or projects, and develops criteria for determining priorities among envi- ronmental transboundary programs or projects.
Our article contributes to the emerging micro-level strand of the literature on the link between local variations in weather
shocks and conflicts by focusing on a pixel-level analysis for North and South Sudan between 1997 and 2009. Temperature anomalies
are found to strongly affect the risk of conflict, whereas the risk is expected to magnify in a range of 24–31% in the future
under a median scenario. Our analysis also sheds light on the competition over natural resources, in particular water, as
the main driver of such relationship in a region where pastoralism constitutes the dominant livelihood.
The Sudd wetland is a huge swampy area (30,000–40,000 km2), with vegetation composed mainly of papyrus, water hyacinth and grasslands. It is located in South Sudan, and is of vital importance for livelihoods, ecosystem services and water resources. Half of the White Nile flow evaporates when passing through the Sudd (~16,000 106 m3/year). Historically, this phenomenon triggered several water conservation projects in the Nile region (the Jonglei Canal Project). However, the available information on the hydrology of the Sudd is very limited, and mostly outdated. This paper investigates the long term dynamics of the Sudd hydroclimatology (water balance components), and how it affects the wetland areal extent. The water balance results show that the extent of the Sudd wetland area is determined both by the regional climate (outflow from Lake Victoria) and the local climate, represented by precipitation and evaporation over the wetland itself. The long term trends of the Sudd hydrology from 1900 to 2000 have been analyzed with the Mann–Kendall test statistics. The water flows into and out of the Sudd demonstrate a statistically significant increasing trends during the last 100 years. This can be attributed to increasing rainfall over Lake Victoria in the early 1960s. The daily maximum and minimum temperature in the Sudd shows an increasing trend of 0.6 and 1.5 °C, respectively, over the last 100 years. However, this has not caused any change of the wetland actual evaporation (open water evaporation plus plant transpiration). The impact of the temperature rise has likely been compensated by a reduction of the relative humidity and solar radiation over the wetland. The statistical test shows that both relative humidity and solar radiation (sunshine hours) has significantly decreased, each reduced by 10 % over the last 50 year. The precipitation over the Sudd showed no significant change during the last 100 years. On the other hand, the areal extent of the Sudd wetland increased by 19,000 km2 (80 %) during the last 100 years, as a result of the increased inflows. The long term variability of the Sudd areal extent provides new results and deeper insights of the two-way land surface climate feedbacks, and informs wetland conservation and water resources management for this important tropical wetland.
Characterising hydroperiod and vegetation for flood-pulsed wetlands is a critical first step towards understanding their ecology. In large, data-poor wetlands such as Botswana’s Okavango Delta, quantifying hydrology and ecology presents great logistic and financial challenges, yet relationships between hydrology and floodplain ecology are essential inputs to management. This paper describes an approach to improving ecological understanding by seeking relationships between archival remote sensing data and floodplain vegetation data. We produced a high spatial resolution (30 × 30 m) time series of annual flood frequency from Landsat 5TM imagery for the period 1989–2009. A second, lower spatial resolution (250 × 250 m) series of monthly flood extent was developed from a band 1 (0.62–0.67 μm) threshold of MODIS (MOD09Q1) imagery for the period 2000–2012. Vegetation composition and abundance was sampled in 30 floodplain sites, using a modified Braun-Blanquet approach. Interpreted flood extent from MODIS was 92 % accurate compared to the Landsat interpretation, and 89 % accurate when assessed against field data. Three major classes of floodplain vegetation were identified from ordination and cluster analysis: Occasionally flooded savanna, Seasonally flooded grassland, and Seasonally flooded sedgeland. Relationships identified between hydroperiod and vegetation communities were tested against five validation sites, in four of which indicator species occurrence was predicted with ≥60 % accuracy. The methods used are simple, objective, repeatable and inexpensive. Relating floodplain vegetation to hydrological history provides a means of predicting shifts in species composition and abundance for given changes in hydrology.
Wetlands, such as those of the Tana River Delta in Kenya, are vital but
threatened ecosystems. The flooding characteristics of wetlands largely
determine their physical, chemical and biological properties, so their
quantification is crucial for wetland management. This quantification
can be achieved through hydrological modelling. In addition, the
analysis of satellite imagery provides essential hydrological data to
monitor floods in poorly gauged zones. The objective of
this study was to quantify the main water fluxes and flooding
characteristics (extent, duration and number of floods) in the poorly
gauged Tana River Delta in East Africa during 2002-2011. To do so, we
constructed a lumped hydrological model (the Tana Inundation Model, TIM)
that was calibrated and validated with MODIS data. Further analysis of
the MYD09A1 500 m composite product provided a map of the empirical
probability of flooded state. In non-extreme years and for the current
topology of the delta, the flood extent exceeded 300 km2.
Floods over 200 km2 occurred on average once a year, with a
mean duration of 18 days. River discharge from the upper basin counted
for over 95% of the total water inflow. The results are discussed in the
light of possible improvements of the models and wetland management
issues. This study provides the first known quantification
of spatial and temporal flooding characteristics in the Tana River
Delta. As such, it is essential for the water and natural resource
management of the Tana River basin. The water balance approach was
pertinent to the study of this system, for which information on its
internal properties and processes is limited. The methodology, a
combination of hydrological modelling and flood mapping using MODIS
products, should be applicable to other areas, including those for which
data are scarce and cloud cover may be high, and where a medium spatial
resolution is required.
Reconstruction of the inundation history in the floodpulsed
12000 km2 wetland of the Okavango Delta is a
prerequisite for the calibration of hydrological models,
development of ecological models, and improved
understanding of gemorphological dynamics of this
system. Although flood mapping has been previously
done based on NOAA AVHRR data, there is a need for
higher resolution inundation maps. Fourteen Landsat
TM5 and TM+ coverages (4 scenes each), depicting the
largest annual inundation extent for the periods 1989-
1990, 1992-2002 and 2005 are analysed in this study.
Initial analyses indicated that separatibility of “dry” and
“inundated” Landsat TM spectral signatures is affected
by the presence of extensive floating Cyperus papyrus
mats that entirely cover underlying water, and the
presence of evergreen riverine forests. These render
inapplicable such classic methods of land/water
discrimination as thresholding of Tasseled Cap wetness
product and the thermal band. Additionally, the
dynamics of the system prohibit ground-truthing of
classification results of historic imagery. To overcome
these difficulties, a classification procedure has been
devised that is based on a combination of supervised
and unsupervised classification of multispectral data and
indices (band 5 and 2 ratio), and contextual analyses.
Wetlands are important ecosystems on Earth. However, global wetland
coverage is being reduced due to both anthropogenic and natural effects.
Thus, assessment of temporal changes in vegetative coverage, as a
measure of the wetland health, is critical to help implement effective
management plans and provide inputs for climate-related research. In
this work, 596 moderate-resolution imaging spectroradiometer (MODIS)
250-m resolution images of the Hongze Lake national wetland nature
reserve from 2000 to 2009 were used to study the vegetative coverage
(above the water surface) of the reserve. Three vegetation indices
[normalized difference vegetation index (NDVI), enhanced VI (EVI), and
floating algae index (FAI)] were compared to evaluate their
effectiveness in assessing relative changes. FAI was less sensitive than
NDVI and EVI to aerosol effects and showed less statistical error than
NDVI and EVI. Long-term FAI data revealed clear seasonal cycles in
vegetative coverage in the 113-km2 core area of the reserve,
with annual maximal coverage relatively stable after 2004. This suggests
that the national wetland nature reserve was well protected through the
study period. However, vegetative coverage decreased due to the flooding
event in 2003. Moreover, correlation analysis showed that annual
sunshine duration collectively played a significant role in affecting
the wetland vegetative coverage.
Located on the Bahr el Jebel in South Sudan, the Sudd is one of the largest floodplain wetlands in the world. Seasonal inundation drives the hydrologic, geomorphological, and ecological processes, and the annual flood pulse is essential to the functioning of the Sudd. Despite the importance of the flood pulse, various hydrological interventions are planned upstream of the Sudd to increase economic benefits and food security. These will not be without consequences, in particular for wetlands where the biological productivity, biodiversity, and human livelihoods are dependent on the flood pulse and both the costs and benefits need to be carefully evaluated. Many African countries still lack regional baseline information on the temporal extent, distribution, and characteristics of wetlands, making it hard to assess the consequences of development interventions. Because of political instability in Sudan and the inaccessible nature of the Sudd, recent measurements of flooding and seasonal dynamics are inadequate. Analyses of multitemporal and multisensor remote sensing datasets are presented in this paper, in order to investigate and characterize flood pulsing within the Sudd wetland over a 12-month period. Wetland area has been mapped along with dominant components of open water and flooded vegetation at five time periods over a single year. The total area of flooding (both rain and river fed) over the 12 months was 41 334 km2, with 9176 km2 of this constituting the permanent wetland. Mean annual total evaporation is shown to be higher and with narrower distribution of values from areas of open water (1718 mm) than from flooded vegetation (1641 mm). Although the exact figures require validation against ground-based measurements, the results highlight the relative differences in inundation patterns and evaporation across the Sudd.
The split-window land surface brightness temperature (LSTb) algorithm of Coll and Caselles (1994) is one of the first approaches to estimate LSTb applied for large surface areas. In this article, we describe a calibrated and validated version of the Coll and Caselles (1994) algorithm applied for the retrieval of land surface air temperature (LSTa) - equivalent to standard WMO (World Meteorological Organization) temperature measurements - for the province of Xinjiang (PR of China). Locally received MODIS (Moderate Resolution Imaging Spectroradiometer) imagery (Fukang receiving station) is used as the input data stream for the so-called AMSL (Aqua MODIS SWA LSTa) algorithm. The objective to develop this algorithm is that it is an input for a distributed hydrological model as well as a soil moisture content retrieval algorithm. In the Xinjiang province with an abundance of arid to semi-arid regions, a highly continental climate, irrigated crop fields and mountain ranges of 6000 m and higher, one typically deals with the spatio-temporally complex conditions, making a high-accuracy retrieval of LSTa quite a challenge. The calibration and validation of the AMSL LSTa product (LSTa, amsl) - using the Jackknife method - is performed using LSTa measurements (LSTa, tmb) from 49 meteorological stations managed by the Tarim Meteorological Bureau (TMB). These stations are distributed relatively homogeneously over the province. The TMB stations' temperature data are split into 40 calibration LSTa, tmb data sets and 9 validation LSTa,tmb data sets. We can observe that when validated, the LSTa,amsl versus LSTa,(tmb) validation relationship elicits a high correlation, a slope very close to 1 and an intercept very close to 0. The validated LSTa,amsl estimates demonstrate an estimation accuracy of 0.5 K. The results presented in this article suggest that the LSTa,amsl product is suitable to estimate the land surface air temperature spatio-temporal
To conserve and manage wetland resources, it is important to inventoryand monitor wetlands and their adjacent uplands. Satellite remote sensing hasseveral advantages for monitoring wetland resources, especially for largegeographic areas. This review summarizes the literature on satellite remotesensing of wetlands, including what classification techniques were mostsuccessful in identifying wetlands and separating them from other land covertypes. All types of wetlands have been studied with satellite remote sensing.Landsat MSS, Landsat TM, and SPOT are the major satellite systems that have beenused to study wetlands; other systems are NOAA AVHRR, IRS-1B LISS-II and radarsystems, including JERS-1, ERS-1 and RADARSAT. Early work with satellite imageryused visual interpretation for classification. The most commonly used computerclassification method to map wetlands is unsupervised classification orclustering. Maximum likelihood is the most common supervised classificationmethod. Wetland classification is difficult because of spectral confusion withother landcover classes and among different types of wetlands. However,multi-temporal data usually improves the classification of wetlands, as doesancillary data such as soil data, elevation or topography data. Classifiedsatellite imagery and maps derived from aerial photography have been comparedwith the conclusion that they offer different but complimentary information.Change detection studies have taken advantage of the repeat coverage andarchival data available with satellite remote sensing. Detailed wetland maps canbe updated using satellite imagery. Given the spatial resolution of satelliteremote sensing systems, fuzzy classification, subpixel classification, spectralmixture analysis, and mixtures estimation may provide more detailed informationon wetlands. A layered, hybrid or rule-based approach may give better resultsthan more traditional methods. The combination of radar and optical data providethe most promise for improving wetland classification.
The Digital Elevation Model that has been derived from the February 2000 Shuttle Radar Topography Mission (SRTM) has been one of the most important publicly available new spatial data sets in recent years. However, the 'finished' grade version of the data (also referred to as Version 2) still contains data voids (some 836,000 km 2)—and other anomalies—that prevent immediate use in many applications. These voids can be filled using a range of interpolation algorithms in conjunction with other sources of elevation data, but there is little guidance on the most appropriate void-filling method. This paper describes: (i) a method to fill voids using a variety of interpolators, (ii) a method to determine the most appropriate void-filling algorithms using a classification of the voids based on their size and a typology of their surrounding terrain; and (iii) the classification of the most appropriate algorithm for each of the 3,339,913 voids in the SRTM data. Based on a sample of 1304 artificial but realistic voids across six terrain types and eight void size classes, we found that the choice of void-filling algorithm is dependent on both the size and terrain type of the void. Contrary to some previous findings, the best methods can be generalised as: kriging or inverse distance weighting interpolation for small and medium size voids in relatively flat low-lying areas; spline interpolation for small and medium-sized voids in high-altitude and dissected terrain; triangular irregular network or inverse distance weighting interpolation for large voids in very flat areas, and an advanced spline method (ANUDEM) for large voids in other terrains.
The normalized difference vegetation index (NDVI) has been widely used for remote sensing of vegetation for many years. This index uses radiances or reflectances from a red channel around 0.66 μm and a near-IR channel around 0.86 μm. The red channel is located in the strong chlorophyll absorption region, while the near-IR channel is located in the high reflectance plateau of vegetation canopies. The two channels sense very different depths through vegetation canopies. In this article, another index, namely, the normalized difference water index (NDWI), is proposed for remote sensing of vegetation liquid water from space. NDWI is defined as , where ϱ represents the radiance in reflectance units. Both the 0.86-μm and the 1.24-μm channels are located in the high reflectance plateau of vegetation canopies. They sense similar depths through vegetation canopies. Absorption by vegetation liquid water near 0.86 μm is negligible. Weak liquid absorption at 1.24 μm is present. Canopy scattering enhances the water absorption. As a result, NDWI is sensitive to changes in liquid water content of vegetation canopies. Atmospheric aerosol scattering effects in the 0.86–1.24 μm region are weak. NDWI is less sensitive to atmospheric effects than NDVI. NDWI does not remove completely the background soil reflectance effects, similar to NDVI. Because the information about vegetation canopies contained in the 1.24-μm channel is very different from that contained in the red channel near 0.66 μm, NDWI should be considered as an independent vegetation index. It is complementary to, not a substitute for NDVI. Laboratory-measured reflectance spectra of stacked green leaves, and spectral imaging data acquired with Airborne Visible Infrared Imaging Spectrometer (AVIRIS) over Jasper Ridge in California and the High Plains in northern Colorado, are used to demonstrate the usefulness of NDWI. Comparisons between NDWI and NDVI images are also given.
This book presents an account of the hydrology of the whole Nile basin, dealing with each tributary in turn but drawing attention to links between reaches. The Nile is shown to be a set of very different tributaries which came together by geological accident. Nevertheless, evidence from one part of the basin often throws light on a different area. Recent changes are discussed, in particular the dramatic change of regime of Lake Victoria and other lakes that occurred post-1961. The relationship between hydrology and vegetation affects the important wetlands of the White Nile Basin and discussion of this relationship includes the effect of increased lake flows. The authors draw on records collected throughout the basin to paint a detailed hydrological picture of the Nile. The book is illustrated with over 100 diagrams and photographs.
Monitoring spatio-temporal dynamics of hydrology in seasonally-flooded wetlands is important for water management and biodiversity conservation. Spectral data and derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) have been used for hydrological monitoring of large wetlands. However, comparable studies for small wetlands (<25 km2) are lacking. Our aims are to examine whether MODIS-derived indices at 500-m spatial resolution can perform this task for small wetlands, and to compare the performance of various indices. First we evaluated if water levels are a good indicator for wetland inundation extent. A high correlation between water level and Landsat-derived inundation extent was found (R
2 = 0.957). Secondly, we compared 10 years of water level fluctuations with seven spectral indices at a 16-day interval. The Tasseled Cap brightness index (TCBI) had the highest correlation with water level for the complete time series including dry and wet years. Thirdly, we analyzed how these indices behave for areas with different inundation characteristics. Again TCBI showed a consistently accurate performance, which was independent of inundation frequency. We therefore conclude that TCBI is the best-suited index for monitoring of hydrological variability in small seasonally-flooded wetlands such as the Fuente de Piedra lake in southern Spain. We recommend testing this index further for other seasonally-flooded wetlands in semi-arid areas.
Construction of the Jonglei Canal began in 1977 to reduce absorption and evaporation from the White Nile, and to provide water for irrigation and hydroelectric power in the wetland area of southern Sudan. Based on scientific studies carried out in the early 1950s and in 1978 and 1983, the book aims to present a multi-disciplinary survey of the complex interrelated hydrological, ecological, biological and human problems involved with the scheme. Construction was halted in 1983 by civil war, and the book is intended to provide a foundation upon which further research can proceed with minimum delay should political circumstances allow work on the canal and development of the area to begin again. -after Publisher
Wetlands provide a vital resource to ecosystem services and associated rural livelihoods but their extent, geomorphological heterogeneity and flat topography make the representation of their hydrological functioning complex. A semi automated method exploiting 526 MODIS (Moderate Resolution Imaging Spectroradiometer) 8-day 500 m resolution images was developed to study the spatial and temporal dynamics of the annual flood across the Niger Inner Delta over the period 2000–2011. A composite band ratio index exploiting the Modified Normalised Difference Water Index (MNDWI) and Normalised Difference Moisture Index (NDMI) with fixed thresholds provided the most accurate detection of flooded areas out of six commonly used band ratio indices. K-means classified Landsat images were used to calibrate the thresholds. Estimated flooded surface areas were evaluated against additional classified Landsat images, previous studies and field stage data for a range of hydrological units: river stretches, lakes, floodplains and irrigated areas. This method illustrated how large amounts of MODIS images may be exploited to monitor flood dynamics with adequate spatial and temporal resolution and good accuracy, except during the flood rise due to cloud presence. Previous correlations between flow levels and flooded areas were refined to account for the hysteresis as the flood recedes and for the varying amplitude of the flood. Peak flooded areas varied between 10 300 km2 and 20 000 km2, resulting in evaporation losses ranging between 12 km3 and 21 km3. Direct precipitation assessed over flooded areas refined the wetland’s water balance and infiltration estimates. The knowledge gained on the timing, duration and extent of the flood across the wetland and in lakes, floodplains and irrigated plots may assist farmers in agricultural water management. Furthermore insights provided on the wetland’s flood dynamics may be used to develop and calibrate a hydraulic model of the flood in the Niger Inner Delta.
Time-series remote sensing data, such as Moderate Resolution Imaging Spectroradiometer (MODIS) data hold considerable promise for investigating long-term dynamics of land use/cover change (LUCC), given their significant advantages of frequent temporal coverage and free cost. However, because of the complex ecological environment of wetlands, the applicability of these data for studying temporal dynamics of wetland-related land-cover types is limited. This is especially so for the Poyang Lake, China's largest freshwater lake, which has active seasonal and inter-annual dynamics. The primary objective of this study is to investigate the suitability of MODIS 250-m maximum value composite (MVC) vegetation indexes (VIs) for dynamics monitoring of the Poyang Lake. We applied time-series16-day MODIS NDVI from 2000 to 2012 and developed a method to classify wetland cover types based on timing of inundation. We combined techniques of applying iterative self-organizing data analysis (ISODATA) with varying numbers of clusters and a transformed divergence (TD) statistic, to implement annual classification of smoothed time-series NDVI. In addition, we propose a decision tree based on features derived from NDVI profiles, to characterize phenological differences among clusters. Supported by randomly generated validation samples from TM images and daily water level records, we obtained a satisfactory accuracy assessment report. Classification results showed various change patterns for four dominant land cover types. Water area showed a non-significant declining trend with average annual change rate 33.25 km2, indicating a drier Poyang lake, and emergent vegetation area had weak change over the past 13 years. Areas of submerged vegetation and mudflat expanded, with significant average annual change rate 23.51 km2 for the former. The results suggest that MODIS’ 250-m spatial resolution is appropriate and the classification method based on timing of inundation useful for mapping general land cover patterns of Poyang Lake.
In this study, the maximum likelihood supervised classification and the
post-classification comparison change detection are applied in order to
monitor the wetlands by assessing and quantifying the wetland cover
changes in the Nile swamps of southern Sudan, called the Sudd, by using
the ERDAS IMAGINE software. Three multispectral satellite imageries,
acquired in the wet season from 1986 to 2006 by Landsat TM and Landsat
ETM+ images, are classified into five main land cover classes namely
water, vegetation, urban, wetland-vegetation, and wetland-no vegetation,
by using the maximum likelihood supervised classification. A
pixel-by-pixel comparison was then performed over the classified
thematic map images. The post-classification change detection results
show a 3.69% decrease in the wetland-vegetation areas and a 2.68%
decrease in the wetland-no vegetation areas within the period 1986 to
1999. In addition, a noticeable increase is observed in the
wetland-vegetation areas within the period 1999 to 2006 in the Sudd area
as 14.95% of the land cover classes' areas, excluding the
wetland-vegetation areas are changed into wetland-vegetation areas while
there was a decrease of 5.18% in the wetland-no vegetation areas within
the period 1999 to 2006. The objective of this paper is to introduce
precedence in studying the wetland cover changes over the Sudd area
which can help the output planners develop water resources management
projects leading to enhance the life conditions in the Sudd region.
In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objectives of this study are to develop, demonstrate and validate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near real-time at the African continental scale as a first step towards global scale coverage. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. Two different validations were done at the continental scale over Africa: i) The algorithm validation checked the ability of the proposed algorithm to perform as effectively as human interpretation of the image: it showed an accuracy of 96.6% and no commission errors. ii) The product validation was carried out by using an independent dataset derived from high resolution imagery: the continental permanent water surface product showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at the African continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties.
The Great Artesian Basin springs (Australia) are unique groundwater dependent wetland ecosystems of great significance, but are endangered by anthropogenic water extraction from the underlying aquifers. Relationships have been established between the wetland area associated with individual springs and their discharge, providing a potential means of monitoring groundwater flow using measurements of vegetated wetland area. Previous attempts to use this relationship to monitor GAB springs have used aerial photography or high resolution satellite images and gave sporadic temporal information. These “snapshot” studies need to be placed within a longer and more regular context to better assess changes in response to aquifer draw-downs. In this study we test the potential of 8 years of Moderate Resolution Imaging Spectroradiometer Normalised Difference Vegetation Index data as a long-term tracer of the temporal dynamics of wetland vegetation at the Dalhousie Springs Complex of the Great Artesian Basin. NDVI time series were extracted from MODIS images and phenologies of the main wetland vegetation species defined. Photosynthetic activity within wetlands could be discriminated from surrounding land responses in this medium resolution imagery. The study showed good correlation between wetland vegetated area and groundwater flow over the 2002–2010 period, but also the important influence of natural species phenologies, rainfall, and anthropogenic activity on the observed seasonal and inter-annual vegetation dynamics. Declining trends in the extent (km2) of vegetated wetland areas were observed between 2002 and 2009 followed by a return of wetland vegetation since 2010. This study underlines the need to continue long-term medium resolution satellite studies of the GAB to fully understand variability and trends in the spring-fed wetlands. The MODIS record allows a good understanding of variability within the wetlands, and gives a high temporal-frequency context for less frequent higher spatial resolution studies, therefore providing a strong baseline for assessment of future changes.
Lake Chad at the border of the Sahara desert in central Africa, is well known for its high sensitivity to hydroclimatic events. Gaps in in situ data have so far prevented a full assessment of the response of Lake Chad to the ongoing prolonged drought that started in the second half of the 20th century. Like many other wetlands and shallow lakes, the 'Small' Lake Chad includes large areas of water under aquatic vegetation which needs to be accounted for to obtain the total inundated area. In this paper, a methodology is proposed that uses Meteosat thermal maximum composite data (Tmax) to account for water covered by aquatic vegetation and provide a consistent monthly time series of total inundated area estimates for Lake Chad. Total inundation patterns in Lake Chad were reconstructed for a 15-yr period (1986-2001) which includes the peak of the drought (86-91) and therefore provides new observations on the hydrological functioning of the 'Small' Lake Chad. During the study period, Lake Chad remained below 16,400 km(2) (third quartile similar to 8800 km(2)). The variability of the inundated area observed in the northern pool (standard deviation sigma(northern pool) = 1980 km(2)) is about 60% greater than that of the southern pool (sigma(southern pool) 1250 km(2)). The same methodology could be applied to other large wetlands and shallow lakes in semi-arid or arid regions elsewehere using Meteosat (e.g. Niger Inland Delta, Sudd in Sudan, Okavango Delta) and other weather satellites (e.g., floodplains of the Lake Eyre Basin in Australia and Andean Altiplano Lakes in South America).
A two-dimensional (2D) hydrodynamic assessment of the Nile swamps in southern Sudan has been carried out using DHI MIKE 21 software based on a ground referenced and corrected Shuttle Radar Topography Mission (SRTM) digital elevation model. The model was set up and calibrated using available historical information as well as newly measured data. The results show the model capable of representing the hydraulic conditions in the swamps, allowing the assessment of different flow conditions and their effects on the swamp. The study has established water-level gradients, flow directions and velocities in the swamp, as well as on the seasonal flood plains, and describes the importance of evapotranspiration for losses in the system.Citation Petersen, G. & Fohrer, N. (2010) Two-dimensional numerical assessment of the hydrodynamics of the Nile swamps in southern Sudan. Hydrol. Sci. J.55(1), 17–26.
This study aimed to develop simple remote-sensing techniques suitable for mapping and monitoring
wetlands, using Landsat TM imagery of inland wetland sites in Victoria and New South Wales. A range
of classification methods was examined in attempts to map the location and extent of wetlands and their
vegetation types. Multi-temporal imagery (winter/spring and summer) was used to display seasonal
variability in water regime and vegetation status. Simple density slicing of the mid-infrared band (TM5)
from imagery taken during wet conditions was useful for mapping the location and extent of inundated
areas. None of the classification methods tested reproduced field maps of dominant vegetation species;
however, density slicing of multi-temporal imagery produced classes based on seasonal variation in
water regime and vegetation status that are useful for reconnaissance mapping and for examining
variability in previously mapped units. Satellite imagery is unlikely to replace aerial photography for
detailed mapping of wetland vegetation types, particularly where ecological gradients are steep, as in
many riverine systems. However, it has much to offer in monitoring changes in water regime and in
reconnaissance mapping at regional scales.
THE NILE FLOOD PLAIN AT THE SOUTHERN MARGIN OF THE SUDD REGION PROVIDES A SERIES OF BASINS WHICH ACT AS RESERVOIRS.AN ANALYSIS OF FLOW RECORDS ALLOWS THE STORAGE VOLUME IN A SAMPLE REACH TO BE RELATED TO THE RIVER INFLOW.THE VEGETATION DISTRIBUTION ON THE FLOOD PLAIN IS CONTROLLED BY SEASONAL FLOODING AND THE FORM OF CONTROL IS DEDUCED BY RELATING THIS DISTRIBUTION TO ELEVATION AND THUS TO HYDROLOGICAL CONDITIONS.THE VARIATIONS IN THE LOCAL ECONOMY ARE IN TURN RELATED TO RIVER REGIME.THE PAPER IS BASED ON THE SURVEYS OF THE JONGLEI INVESTIGATION TEAM IN 1954.(A.)
River discharge as well as lake and wetland storage of water are critical terms in the surface water balance, yet they are poorly observed globally and the prospects for improvement from in-situ networks are bleak [e.g., Shiklomanov et al., 2002; IAHS, 2001; Stokstad, 1999]. Indeed, given our basic need for fresh water, perhaps the most important hydrologic observations that can be made in a basin are of the temporal and spatial variations in discharge. Gauges measuring discharge rely on flow converging from the upstream catchment to a singular in-channel cross-section. This approach has successfully monitored many of the world's densely inhabited and typically heavily engineered basins for well over a century. However, much of the globally significant discharge occurs in sparsely gauged basins, many with vast wetlands that lack flow convergence (e.g., Figures 1 and 2), thus leading to poorly defined values of runoff at local, regional, and continental scales. The Surface Water Working Group is funded by NASA's Terrestrial Hydrology Program and is an outgrowth of a mission planning process summarized in a July 1999 white paper [Vörösmarty et al., 1999]. Based on the white paper and discussions at working group meetings over the last 2 years, we are focused on the following critical hydrologic questions. (1) What are the observational and data assimilation requirements for measuring surface storage and river discharge that will allow us to understand the dynamics of the land surface branch of the global hydrologic cycle, and in particular, to predict the consequences of global change on water resources? (2) What are the roles of wetlands, lakes, and rivers as regulators of biogeochemical cycles (e.g., carbon and nutrients) and in creating or ameliorating water-related hazards of relevance to society?
Software tools have been developed at the U.S. Geological Survey's EROS Data Center to extract topographic structure and to delineate watersheds and overland flow paths from digital elevation models. The tools are special purpose FORTRAN programs interfaced with general-purpose raster and vector spatial analysis and relational data base management packages. The first phase of analysis is a conditioning phase that generates three data sets: the original DEM with depressions filled, a data set indicating the flow direction for each cell, and a flow accumulation data set in which each cell receives a value equal to the total number of cells that drain to it. The original DEM and these three derivative data sets can then be processed in a variety of ways.
Due to the increase in urban and agricultural activities in arid regions, the exploration of new locations of possible groundwater discharge and accumulation is required to augment the limited water resources. In order to locate such discharge areas, it is necessary first to identify zones of high recharge potentials. In such an arid region, like the northern United Arab Emirates (UAE), one of the ways to predict areas of potential groundwater recharge is by understanding the hydrological response of its drainage basins to rainfall events. Due to the scarcity of basic hydrological data, a hydrological model driven mainly by information on the physiographic characteristics, drainage network properties (generated from DEM), and surface cover distribution (generated from satellite images) was used to comprehend the dynamics of surface runoff through hydrographs, and hence water loss in the study area. Results show that the northern UAE is drained by 48 drainage basins emerging from the Oman Mountains. Two‐thirds of these basins drain easterly toward the Gulf of Oman, and one‐third drain westerly toward the Arabian Gulf. These basins are found to be structurally controlled by three major fault trends, which are the NE trend (Dibba zone), NW trend (Ham Zone), and WNW trend (Hatta zone).The hydrological response of a basin is correlated with its morphological characteristics. Based on these characteristics, and through the application of a cluster analysis, it was feasible to classify the largest basins in the region into four groundwater potentiality groups in accordance with the magnitude of their peak discharges. From this study, it became evident that the downstream area of the two major basins of Ar‐Rafiah and Limhah, and their vicinities are the most probable sites for groundwater accumulation. The drainage systems of these two basins, especially those controlled by major fault lines, play a vital role in transmitting surface–subsurface rainwater from the Oman Mountains, the recharge zone, into the western desert plain, the discharge zone, where freshwater accumulates underground. The study also revealed that a large volume of groundwater is dissipated into the sea along the eastern coast. A detailed examination of MODIS thermal data supports this by revealing cool surface anomalies issuing from the mountain range toward both the western desert plain and the Gulf of Oman following major rainfall events. Thus, the technique used facilitates the prediction of new locations of optimum groundwater resources in the northern UAE. Such a technique could be adopted, with appropriate modifications, elsewhere in arid regions, where groundwater is restricted and subject to greater complexity.
A water balance model of the Nile is described, working in terms of dry season flows. The main use of the modelling studies was to extend flows back to the start of observations at Aswan in 1869, and hence to estimate the levels of Lake Victoria during the high flow event of the 1870s. New estimates of Lake Victoria levels and outflows for the period 1870–1895 are deduced, extending the length of the observed data for Lake Victoria by some 25%. Crucially, the analysis includes the major flood event of 1878, which historical evidence suggests was the highest since 1860 or earlier. The modelling results are compared with previous estimates and a detailed examination of historical evidence. Some prospects for future levels are considered, taking into account the reconstructed levels of the late nineteenth century.
The water balance of the Sudd is represented by a hydrological model which uses measured inflows and outflows and estimates of rainfall and evaporation to reproduce volumes and areas of flooding over the historical period 1905–1980. Predicted outflows based on inflows are then substituted for measured outflows so that the proposed diversions through the Jonglei Canal can be incorporated in the model in order to predict the effects of the canal on areas of flooding. RESUME Le bilan hydrologique du Sudd est représenté par un modèle hydrologique utilisant les debits entrants et sortants mesurés et les pluies et évaporations estimées pour reproduire les volumes et les superficies inondées pendant la période historique 1905–1980. Les débits sortants estimés à partir des débits entrants sont ensuite substitués de sorte que les dérivations des eaux proposées par le canal de Jonglei peuvent être introduites dans le modèle pour estimer les effets du canal sur les superficies inondées.
A coupled heat and moisture flux model was used to study the influence
of soil physical parameters and moisture content on diurnal surface
temperature fluctuations. The study was performed for a grass cover
under summer and autumn conditions for four soil types, ranging from
sand to clay. The results show that it may be possible to use the daily
maximum and minimum surface temperature measurements to discriminate
several soil physical characteristics, including soil moisture. Further,
ignoring the lower boundary heat flux, as is usually done in thermal
inertia mapping but which can vary substantially in relation to
different hydrological recharge and discharge areas, may lead to
significant errors in the interpretation of soil moisture, thermal
inertia, and transpiration.
An analysis of the vast wetland of the Sudd swamps in southern Sudan was designed to assess and describe interdependencies between morphology and hydrology. Findings based on field survey and remote sensing data include an assessment of the effect of ground slopes and morphological features on spill and flooding of the seasonally flooded grasslands. Through bathymetric surveys and analysis of Landsat images, depth profiles and cross-sectional depth and flow distributions were established. Data from remote sensing, field survey and historical sources were correlated and correction factors established; the SRTM was found to be partly unsuitable for further assessments. Further analysis of remote sensing data was used to investigate the Sudd's inland delta as well as the question of spill into the Bahr el Ghazal basin. Copyright © 2008 John Wiley & Sons, Ltd.
Previous research on environment and security has contested the existence, nature and significance of a climate driver of conflict. In this study, we have focused on small-scale conflict over East Africa where the link between resource availability and conflict is assumed to be more immediate and direct. Using the parameter of rainfall variability to explore the marginal influence of the climate on conflict, the article shows that in locations that experience rebel or communal conflict events, the frequency of these events increases in periods of extreme rainfall variation, irrespective of the sign of the rainfall change. Further, these results lend support to both a ‘zero-sum’ narrative, where conflicting groups use force and violence to compete for ever-scarcer resources, and an ‘abundance’ narrative, where resources spur rent-seeking/wealth-seeking and recruitment of people to participate in violence. Within the context of current uncertainty regarding the future direction of rainfall change over much of Africa, these results imply that small-scale conflict is likely to be exacerbated with increases in rainfall variability if the mean climate remains largely unchanged; preferentially higher rates of rebel conflict will be exhibited in anomalously dry conditions, while higher rates of communal conflict are expected in increasingly anomalous wet conditions.
This article presents ACLED, an Armed Conflict Location and Event Dataset. ACLED codes the actions of rebels, governments, and militias within unstable states, specifying the exact location and date of battle events, transfers of military control, headquarter establishment, civilian violence, and rioting. In the current version, the dataset covers 50 unstable countries from 1997 through 2010. ACLED's disaggregation of civil war and transnational violent events allow for research on local level factors and the dynamics of civil and communal conflict. Findings from subnational conflict research challenges conclusions from larger national-level studies. In a brief descriptive analysis, the authors find that, on average, conflict covers 15% of a state's territory, but almost half of a state can be directly affected by internal wars.
The water balance of the upper Nile swamps, in particular, the Sudd, has been the topic of debate for many years. Surface Energy Balance Algorithm for Land (SEBAL) is a parameterization scheme of surface heat fluxes based on spectral satellite measurements. The SEBAL scheme has been applied to derive the energy balance components from National Oceanic Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) images over the extensive swamps in the upper Nile. The study area covers the swamps of the Sudd, Bahr el Ghazal and the Sobat sub-basins. The actual evaporation and soil moisture for an area between 2–12°N and 26–36°E (approximately 1000 km×1000 km) have been investigated. Monthly (actual) evaporation and soil moisture maps for the year 2000 have been generated. The evaporation results were verified against longer-term averaged rainfall and flow data of the three sub-basins. A close resemblance was obtained for the Sudd (1.8% error) and the Sobat Basin (5.7% error), while the balance lacks closure for the Ghazal basin (27%) due to un-gauged or inadequately gauged inflow from the upper catchments. It is concluded that soil moisture availability controls the monthly evaporation rates for all areas that are not saturated with water, and that a significant dry-down in the winter period occurs. It is concluded that the evaporation for the Sudd wetlands is 20% less and the average area occupied by the wetlands is 74% larger than assumed in earlier hydrological studies (e.g. Jonglei canal studies). The derived results can serve as a sound basis to support the widely debated evaporation losses from the Sudd, as well as form an input to regional scale climate models for studying atmospheric circulation patterns over Africa and the Nile Basin.
The recently available Shuttle Radar Topography Mission (SRTM) data, with ∼90 m horizontal resolution, are used to delineate the entire Tushka mega-watershed. It is calculated that the watershed covers an area of 150 000 km2 and composed of four subwatersheds. This study indicates that the Tushka basin is a closed hydrological system independent of the Nile hydro-system, the Qena Valley system, and the Chad basin as well. More importantly, the study demonstrates that this basin drains northeasterly toward the westernmost of the recently flooded lakes in the Tushka depression, west of Lake Nasser. The hydrological activities within the basin resulted in the formation of the largest paleo-lake deposit in Egypt at Bir-Tarfawi. The vast sand sheets that cover the Tushka basin accentuate the theory of El-Baz [1982. Genesis of the Great Sand Sea, Western Desert of Egypt. International Association of Sediment, 11th International Conference, Hamilton, Ontario, Canada, p. 68], which relates sand accumulations within basins in today's deserts to previous fluvial activities. The present study illustrates the capability of the SRTM in penetrating desert sand surfaces and mapping the ancient drainage networks, which remarkably correlate with subsurface channels detected in Radarsat-1 images.
Information regarding the spatial extent and timing of flooding in the world's major wetlands is important to a wide range of research questions including global methane models, water management, and biodiversity assessments. The Florida Everglades is one of the largest wetlands in the US, and is subject to substantial development and pressures that require intensive hydrological modeling and monitoring. The Moderate Resolution Imaging Spectrometer (MODIS) is a global sensor with high frequency repeat coverage and significant potential for mapping wetland extent and dynamics at moderate spatial resolutions. In this study, empirical models to predict surface inundation in the Everglades were estimated using MODIS data calibrated to water stage data from the South Florida Water Management District for the calendar year 2004. The results show that hydropatterns in the Florida Everglades are strongly correlated to a Tasseled Cap wetness index derived from MODIS Nadir Bidirectional Reflectance Function Adjusted Reflectance data. Several indices were tested, including the Normalized Difference Wetness Index and the diurnal land surface temperature difference, but the Tasseled Cap wetness index showed the strongest correlation to water stage data across a range of surface vegetation types. Other variables included in the analysis were elevation and percent tree cover present within a pixel. Using logistic regression and ensemble regression trees, maps of water depth and flooding likelihood were produced for each 16-day MODIS data period in 2004. The results suggest that MODIS is useful for dynamic monitoring of flooding, particularly in wetlands with sparse tree cover.
The cross-tabulation matrix is a fundamental starting point in the analysis of land change, but many scientists fail to analyze the matrix according to its various components and thus fail to gain as much insight as possible concerning the potential processes that determine a pattern of land change. This paper examines the cross-tabulation matrix to assess the total change of land categories according to two pairs of components: net change and swap, as well as gross gains and gross losses. Analysis of these components can distinguish between a clearly systematic landscape transition and a seemingly random landscape transition. Multiple resolution analysis provides additional information concerning the distances over which land change occurs. An example of change among four land categories in central Massachusetts illustrates the methods. These methods enable scientists to focus on the strongest signals of systematic landscape transitions, which is necessary ultimately to link pattern to process.