ENVIRONMENT AND CLIMATE ANALYSIS IN LAKES, NORTHERN BAHR EL GHAZAL AND WARRAP STATES SOUTH SUDAN

Transcription

1 ENVIRONMENT AND CLIMATE ANALYSIS IN LAKES, NORTHERN BAHR EL GHAZAL AND WARRAP STATES SOUTH SUDAN Preliminary Analysis Report As part of the Building Resilience and Adaptation to Climate Extremes and Disasters Programme (BRACED) October 2014

2 CONTENTS SUMMARY... 3 Maps and Figures... 5 Acronyms... 5 Geographic Classifications... 5 METHODOLOGY... 7 FINDINGS... 7 RAINFALL PATTERN... 7 HISTORICAL FLOODING EXTENTS... 9 LAND COVER CHANGE RECOMMENDATIONS CONCLUSION About REACH REACH is a joint initiative of two international non-governmental organizations ACTED and IMPACT Initiatives and the UN Operational Satellite Applications Programme (UNOSAT). REACH was created in 2010 to facilitate the development of information tools and products that enhance the capacity of aid actors to make evidencebased decisions in emergency, recovery and development contexts. All REACH activities are conducted in support to and within the framework of inter-agency aid coordination mechanisms. For more information, please visit: You can write to us at: geneva@reach-initiative.organd follow 2

3 SUMMARY South Sudan has a largely rural, agro-pastoralist population who is significantly vulnerable to climate change, particularly climate shocks such as excessive rainfall or droughts. For aid actors working in South Sudan, being informed about the relationship between the environment and the community is vital for the design, planning and implementation of appropriate and efficacious programmes. Understanding this important relationship first requires information about trends in the environment and climate over time. To gain a greater understanding of environmental and climatic features, as well as what types of changes have occurred in the climate and the environment of South Sudan, REACH undertook this preliminary research for Lakes, Northern Bahr el Ghazal and Warrap states, the objective of which was to obtain a better understanding of the climate and seasonality in the region. The report focuses on these three states to provide greater contextual understanding of potential challenges to the proposed activities in the Building Resilience and Adaptation to Climate Extremes and Disasters programme (BRACED), funded by the United Kingdom s Department for International Development (DFID), planned for these three states from The goal of the research is to provide background knowledge to BRACED partners in the inception phase, to improve planning by identifying specific environmental and climactic features in the three implementation states at the local level. During BRACED project implementation, a more in-depth analysis will be conducted at state level. The report analyses rainfall patterns, historical extents of flooding and changes in land coverage, using data and satellite image analysis representing the period The research yielded the following results for Lakes, Northern Bahr el Ghazal and Warrap states: Rainfall pattern An average year sees very little rain in December, January and February; rainfall then generally increases gradually from March until it peaks in August. The median rainfall for each month varies seasonally from 0.05 mm/day in January to 6.4 mm/day in August. The amount of rain in the wet months can vary substantially; for example, rainfall estimates for the month of August range from 5.7 mm/day in August 2013 to 8.5 mm/day in August A 10 year analysis of rainfall reveals subtle annual variances in the timing of the first and last rains of the wet season. Historical flooding extents Over 40 per cent of land has been classified as inundated in all but one of the counties in both Lakes and Warrap states. Flooding in this region of South Sudan commonly occurs in the later part of the rainy season, from July to December, and is known to cause issues with accessibility especially in the north of Warrap State. The inundated areas in Northern Bahr el Ghazal State are concentrated mainly in Aweil South County, adjacent to the flood-prone areas in the north of Warrap State. Page 3

4 Land Cover During the rainy season, this part of South Sudan is generally characterised by flat grassland and tropical savannah, with moderate to dense coverage of vegetation across all three states. In contrast, the landscape in the dry season is predominantly sparse, with moderate vegetation around the Nile and on the border with Unity state. In the dry season of 2013, dense vegetation constituted 16 per cent of land cover in Warrap State, 16 per cent in Lakes State and only 2 per cent in Northern Bahr el Ghazal State. In 2013, the region appears the same or greener compared to the 10-year average ( ) 31 per cent of Warrap State is classified as greener, 35 per cent in Lakes State and 41 per cent Northern Bahr el Ghazal State. There are several areas where vegetation is noticeably less vigorous than expected. Most noticeable are the two large areas in Warrap State, one to the north of Kuajok measuring over 6 km wide and the second to the south of the state, likely due to extensive burning in the region. The above-mentioned environmental and climate features, as well as changes to them over time, will be relevant for all humanitarian actors operating in Lakes, Northern Bahr el Ghazal and Warrap states in the coming months and years. To mitigate the negative impact of these challenges, and to support the most vulnerable communities, BRACED partners should consider the trends and critical points identified herein when planning the locations, content and timing of BRACED activities. Page 4

5 Maps and Figures Figure 1: Monthly Rainfall Statistics ( ) Figure 2: Daily Rainfall Trends ( )... 7 Figure 3: Percentage of Land Classified as Inundated by County Figure 4: emodis NDVI Image, Displaying Vegetation Coverage, October Figure 5: emodis NDVI Image, Displaying Vegetation Coverage, January Figure 6: emodis NDVI Image, Comparing Vegetation Coverage, October 2013 to 10 Year Average Figure 7: A Classification of Landsat 7 Satellite Image of Northern Bahr el Ghazal State Map 1: BRACED Areas of Implementation... 4 Map 2: UNOSAT Africa Inundation Map... 9 Map 3: South Sudan Administrative Boundaries and Livelihood Zones Acronyms AFIS BRACED DFID DMSP FAO GIS GOES GPCP MODIS NDVI NOAA SPOT UN UNOSAT USGS Agriculture and Food Information System Building Resilience and Adaptation to Climate Extremes and Disasters programme Department for International Development Defense Meteorological Program Food and Agriculture Organization for the United Nations Geographic Information Systems Geostationary Satellite Server Global Precipitation Climatology Project Moderate Resolution Imaging Spectroradiometer Normalised Difference Vegetation Index National Oceanic and Atmospheric Administration Système Pour l Observation de la Terre United Nations United Nations Operational Satellite Applications Programme United States Geological Survey Geographic Classifications Boma Payam County State Lowest level of local government administration Intermediate administrative level including several bomas Primary administrative level below the state including several payams Highest form of governance below the national level Page 5

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7 METHODOLOGY The research for this report was conducted in two parts: satellite imagery analysis and a desk review from June 15 August 15, A team of REACH Geographic Information System (GIS) specialists based in Upper Nile State, South Sudan and Nairobi, Kenya analysed satellite imagery related to rainfall patterns, historical flooding extents and land cover change. As the technical methods used to conduct each analysis are unique, a more specific description of the methodology accompanies the relevant maps and results. The second research method for this report is a desk review, conducted in Juba, South Sudan. The purpose of this desk review is to facilitate the production of this brief report which provides BRACED activity implementers with background information on the environmental and climate features of Lakes, Northern Bahr el Ghazal and Warrap states. This desk review also allows the REACH team and other BRACED partners the opportunity to identify information gaps and to determine potential adaptions to planned BRACED activities and subsequent areas of future research. It is important to note that the analyses herein were conducted as a preliminary assessment of environmental conditions in the BRACED implementation areas. They are not a comprehensive analysis of the available data, rather, the analyses in this report were created for an initial pilot phase for BRACED programming. The goal of this report is to share the findings of these preliminary assessments and to determine the utility of these methodologies and findings in informing future BRACED activities. For this reason, the future research section provides specific details for how to further build on each methodology mentioned in the report. It is also important to note that the results and trends observed through remote sensing in this report have not been validated at field level. Recommendations for field validation are included in this report. FINDINGS This section presents the main findings from the analysis pertaining to rainfall patterns, historical flooding extents, and land cover change. The sub-section comprise the methodology applied to collect and analysis data for each specific theme, as well as the subsequent results. RAINFALL PATTERN To gain an understanding of how variations in the environment and climate may affect BRACED programming, REACH undertook an analysis of rainfall patterns across Lakes, Northern Bahr el Ghazal and Warrap states. The research used satellite image analysis to explore the amount of rainfall over the period of 1999 to The first component analyses the variation in level of rainfall throughout the year, displaying which time of year sees the heaviest amount of precipitation in BRACED implementing areas. The second component of the rainfall pattern analysis looks at how the timing of the wet season has varied from year-to-year. This section gives a brief overview of the technical methodology used to conduct the analysis, followed by a description of the results of the research regarding rainfall pattern. Page 7

8 Methodology The REACH team downloaded satellite-derived estimates of rainfall as part of the GPCP Version 2.2 Combined Precipitation Data Set produced by the Global Precipitation Climatology Project (GPCP). The product draws from many different sources including passive microwave emission and scattering algorithms using data from the Defense Meteorological Program (DMSP) and cloud-top temperature estimates from infrared sensors on-board the GOES geostationary satellite and NOAA-series polar-orbiting satellites. Monthly precipitation were averaged for the whole region under study in South Sudan (25E-32E, 5N-9N). The dataset used for this analysis does include data collected prior to 1999, yet this research used data beginning in that year as the scope is introductory and therefore not comprehensive. There is significantly more analysis that can be conducted with this dataset, yet in the interest of time, relevance for BRACED activities, and consistency with the data time frame in the next section on historical flooding extents, this analysis used data from the period of Results The average rainfall in the past 15 years for the region is 2.9 mm/day with a standard deviation of 2.5 mm/day. Monthly rainfall data from 1999 to 2013 is summarised in the box-and-whisker plot in Figure 1. The median rainfall for each month varies seasonally from 0.05 mm/day in January to 6.4 mm/day in August. An average year sees very little rain in December, January and February; rainfall then generally increases gradually from March until it peaks in August. The amount of rain in the wet months can vary substantially; for example, rainfall estimates for the month of August range from 5.7 mm/day in August 2013 to 8.5 mm/day in August Figure 1: Monthly Rainfall Statistics Derived from the GPCP v2.2 Combined Precipitation Data Set ( ) Figure 2 below shows the monthly precipitation results between 1999 and The regular seasonal trend is clear, peaking in August and dipping in December. Closer inspection of the data reveals subtle annual variances in the timing and amount of rainfall during the wet season. For example, the average rainfall in July to September 2002 was less than average, but the 2002 wet season lasted longer than expected with 2mm/day more rain than average for October. The 2004 wet season was also particularly dry. Analysis of monthly anomalies revealed that the start of the 2004 wet season (May-July) experienced 2 m/day less rain than average for those three months. Page 8

9 Figure 2: Daily Rainfall Trends from 1999 to 2013 HISTORICAL FLOODING EXTENTS In addition to an understanding of rainfall patterns, BRACED activity planning can be supported by a greater understanding of historical flooding extents in Lakes, Northern Bahr el Ghazal and Warrap states. The research uses satellite image analysis to discover areas covered by water over the period of 1999 to The goal of this analysis is to determine locations in the BRACED area of implementation that may be particularly vulnerable to flooding. The first component of the research creates a map of the three BRACED states and the surrounding area that displays the extent to which the land has historically been covered by water. The second component of the analysis displays the percentage land inundated by water in each county in the three BRACED states. This section gives a brief overview of the technical methodology used to conduct the analysis, followed by a description of the results of the research regarding historical flooding extents in the three states. Methodology The following section assesses areas of water inundation across South Sudan with the use of historical satellite imagery. The analysis detected small water bodies, wetlands and other humid areas via the SPOT satellite (Système Pour l Observation de la Terre) using its VEGETATION sensor between 1999 (the first year of the dataset) and SPOT satellite images were acquired every 10 days for almost 14 years with a spatial resolution of 1 km. The Geoland Consortium compiled a spatial database containing over five hundred of these SPOT images to produce the UNOSAT Africa Inundation dataset, presented in Figure 3. During post-processing, the results were verified and calibrated using a base-map of the region and the data re-scaled so dark blue pixels in the map equate to areas that were inundated or had wetland conditions 100 per cent of the time and lighter blues indicate areas that were less frequently wet. Results Analysis conducted by REACH in 2013using the UNOSAT Inundation Map identified 151 potentially flood-prone villages in Warrap State, as outlined in the report Flood Vulnerability and Contingency Plan (REACH, 2013). 1 These villages were located mainly in the north of Warrap State, primarily in Twic and Gogrial West counties. The villages there reported both an increase in the frequency and the severity of flooding between 2008 and They also considered dyke and water channel construction as the most efficient preparedness strategies. 1 REACH Initiative, Flood Vulnerability and Contingency Plan: Warrap State, South Sudan, December, 2013 Page 9

10 Map 2: The UNOSAT Africa Inundation Map Represents Small Water Bodies, Wetlands and Other Humid Areas in the Region between 1999 and 2012 The above inundation map shows wet zones present in all three states under study: 49 per cent of Warrap State area is classified as inundated in the map, 39 per cent in Lakes State and 21 per cent in Northern Bahr el Ghazal State. Figure 3 below presents a breakdown of the inundation data by county. Over 40 per cent of the land has been classified as inundated in all but one of the counties in both Lakes and Warrap states. The inundated areas in Northern Bahr el Ghazal State are concentrated mainly in Aweil South County, adjacent to the flood-prone areas in the north of Warrap State. This is the area where the seasonal Jur River joins the Bahr el Ghazal River, to the west of the Sudd wetlands, before flowing into the Nile. Other counties that experienced prolonged inundation include Awerial and Yirol East on the banks of the Nile River. Flooding in this region of South Sudan commonly occurs in the later part of the rainy season, from July to December. When this occurs, swamps and stagnant water can make access difficult. 2 In 2008, the entire Twic County was affected by severe flooding. 2 UNDP, Warrap Stabilization Programme Joint Programme Document. Sudan Recovery Fund South Sudan, Page 10

11 Figure 3: Percentage of Land Classified as Inundated by County LAND COVER CHANGE Following a description of rainfall patterns and historical flooding extents, the REACH team also analysed the changes in land cover. The REACH team used remote sensing analysis to ascertain the extent and vigour of vegetation that covers Lakes, Northern Bahr el Ghazal and Warrap states. The initial analysis yields two maps; the first displays the extent and vigour of vegetation across the region at the end of the rainy season (October), and the second displays the extent and vigour of vegetation across the region at the peak of the dry season (January). The next component of the analysis first determines a 10 year average of land cover across the area from 2001 to It then compares this average to that of October 2013 to identify specific anomalies at the State level. The final component of the analysis uses Landsat satellite imagery for Northern Bahr el Ghazal State only to analyse different types of land cover there. This section gives a brief overview of the technical methodology used to conduct the analysis, followed by a description of the results of the analysis of land coverage during the rainy season and the dry season, and a comparison of this land coverage to a 10-year average in the three states. Methodology Green vegetation is mapped using the Normalised Difference Vegetation Index (NDVI) based on the red and near-infra-red reflectance from the earth s surface. The following section uses maps of vegetation that were produced by the U.S. Geological Survey (USGS). The emodis NDVI data products were produced from MODIS L1B Terra surface reflectance data and corrected for molecular scattering, ozone absorption and aerosols using MODIS Science Team algorithms. Page 11

12 10-day maximum value composites were produced at 250 m spatial resolution to coincide with both the dry season (January 2013) and the end of the rainy season (October 2013). An anomaly image was also produced by subtracting the mean NDVI values for a 10-year period ( ) from values for the same period in A weighted least squares linear regression approach was used to correct observations that are poor quality due to atmospheric contamination. 3 The anomaly image contains negative pixels portraying less vigorous vegetation than average and positive values that represent areas that are more vigorous in Results Normalised Difference Vegetation Index (NDVI) The area comprised of Lakes, Northern Bahr el Ghazal and Warrap states is generally characterised by flat grassland and tropical savannah. Figure 4 below shows that all three states have moderate to dense vegetation coverage. In contrast, the landscape in the dry season is predominantly sparse to moderate, as displayed in Figure 5. Figure 4: emodis NDVI Image Displaying Sparse, Moderate and Dense Vegetation Coverage in October Swets, D.L., Reed, B.C., Rowland, J.D. & Marko, S.E. (1999). A weighted least-squares approach to temporal NDVI smoothing. In: 1999 ASPRS Annual Conference: From Image to Information, Portland, Oregon, May Page 12

13 Figure 5: emodis NDVI Image Displaying Sparse, Moderate and Dense Vegetation Coverage, January 2013 In the dry season of 2013, dense vegetation constituted 16 per cent of land cover in Warrap State, 16 per cent in Lakes State and only 2 per cent in Northern Bahr el Ghazal State. The green zones present in the dry season map coincide closely with the inundated areas displayed in the UNOSAT Inundation map shown in Map 2. These marsh and swampland areas extend from both sides of the Nile River on the border of Unity and Jonglei states between Bor and Bentiu. The marshland also extends west to Rumbek in Lakes State, and across the northern part of Warrap State to Aweil in Northern Bahr el Ghazal State. The anomaly image in Figure 6 below displays the difference in vegetation cover measured in October 2013 to that of a 10-year average between 2001 and Areas of more vigorous vegetation are shown in shades of green and areas of less vigorous vegetation are represented as browns. Overall, the region appears greener or comparable to the 10-year average 31 per cent of Warrap State is classified as greener, 35 per cent in Lakes State and 41 per cent Northern Bahr el Ghazal State. There are several areas where vegetation is noticeably less vigorous than expected. Most prominent are the two large areas in Warrap State, one to the north of Kuajok measuring over 6 km wide and the second to the south of the state. Visual analysis of high spatial-resolution satellite imagery suggests this vegetation loss was due to extensive burning in the region. Less vigorous levels of vegetation were also measured either side of the river between Kuajok and Wau, most likely as a result of flooding. Page 13

14 Figure 6: emodis NDVI Anomaly Image Displaying the Difference in Vegetation Coverage in October 2013 Compared to a 10-year Average between 2001 and Figure 7: A 9-class Supervised Classification of Landsat 7 Satellite Image of Northern Bahr el Ghazal State Showing Vegetation, Wet, Burnt and Bare Ground. Page 14

15 Landsat Satellite Image Classification: A Sample for Northern Bahr El Ghazal More advanced spectral analysis of land cover can provide a deeper understanding of land dynamics. Figure 7 presents a 9-class land cover map of Northern Bahr el Ghazal State produced by the REACH team from the classification of Landsat 7 satellite imagery. The classes were developed after a Tasselled Cap Transformation was applied to the image to highlight areas of wetness, greenness and brightness. Landsat imagery can be used to identify various classes of vegetation. Wet ground and open water are observable around Aweil, mirroring patterns displayed in the UNOSAT Inundation map in Figure 3. Various stages of burning are also classified in the northwest part of the state. Due to challenges related to imagery access and time constraints, the REACH GIS team conducted the Landsat Satellite Image Classification for Northern Bahr el Ghazal only. If the analysis herein is found to be valuable beyond the BRACED inception phase, the research can be repeated for Lakes and Warrap States. RECOMMENDATIONS While the initial findings tell us about environmental and climactic conditions in the three states, there are a number of important and relevant areas of research that fall outside the scope of this report. This section identifies key recommendations for further research and analysis related to environment and climate assessment, namely, further improvements on spatial analysis, desk research on human-environment interaction, and field level primary data collection. The second section puts forth recommendations on how to improve BRACED programming by engagement with a variety of environmental and climate actors. FURTHER RESEARCH Spatial Analysis More detailed spatial analysis is recommended; this might focus on particular geographical areas of interest, including areas of intervention, by utilising higher spatial resolution datasets including that of the USGS s Landsat satellite series. The integration of suitable ground-derived datasets would also likely lead to more detailed, context-specific results and products. The acquisition of more detailed time-series datasets would also allow a deeper historical analysis of rainfall, flooding and land cover change in the region. For example, this might be through the analysis of flooding and land cover change following particular climatic events. Comparing satellite imagery of the worst flooding events and normal flooding events would contribute to a richer analysis. Integrating datasets that represent elevation and soil/geology could also be used to further explore flooding hazards and risk. Datasets used for rainfall patterns go back further in time than the research conducted for this report allowed. While the data for historical flooding extents only began in 1999, researchers may be able to find alternative sources of flooding data prior to this, but they may be less reliable. Human-Environment Interaction The next phase of research should address the impact of human behaviour on the environment. As seen in Map 6, the livelihood zone known as the Western Flood Plain covers most of Lakes, Northern Bahr el Ghazal and Warrap states; where the predominant livelihood is agro-pastoralism. According to the National Bureau of Statistics, this area has northern highlands, which are considered highly fertile and not susceptible to flooding. Page 15

16 In the southern part of the zone, soils are predominantly black cotton and the farm sizes are larger. 4 More research on the way in which this land has been used historically, particularly at the sub-state level, will be extremely helpful to BRACED partners. Map 3: South Sudan Administrative Boundaries and Livelihood Zones The research in this report would be greatly enhanced by an exploration of how environmental change corresponds to changing trends in human behaviour. Human activities such as changes in farming technique, increased burning of grasslands (related to agriculture or cultural practices), population influxes or new cattle grazing migration patterns may have affected some of the findings herein. On a related note, a comparison of how the environment has changed with civil war events may offer interesting findings. For example, the NDVI maps show green areas in northern Warrap State and central Lakes State, both areas known for cattle raiding. This is particularly relevant given the current conflict that began on December 15, The next step in the analysis should use the aforementioned more detailed datasets to target areas identified in this report as particularly sensitive, or for which implementers have gaps in information. Prior to conducting future spatial analysis, a secondary data review can identify existing, albeit knowingly limited, historical environmental and climate data on these three states. 4 Southern Sudan Centre for Census, Statics and Evaluation, (now known as the National Bureau of Statics),Southern Sudan Livelihood Profiles, January Page 16

17 Field Validation Another key element of future research must be field validation of identified trends. Following more detailed spatial analysis, the research should next focus on primary data collection at field level in a sample of affected villages. Primary data collection on flooding, for example, will allow BRACED partners to gather information on the living conditions, flood mitigation and preparedness methods, and perceptions of communities in flood prone areas. This data collection can be conducted through the use of two complementary data collection methods direct observation and community discussion. Furthermore, there is likely a link between the variation in land cover identified in the NDVI and agricultural areas, but the current lack of ground data that could inform exactly where these projects are shows further need for field data collection. Further Analysis In addition to spatial analysis, desk research on human-environment interaction, and primary data collection in BRACED implementation areas, further analysis could be done in the development of predictive models, and a more in-depth shock analysis. Mapping historic patterns of climate events can be used to anticipate changing and emerging environmental risks through the development of predictive models. Models can identify both the type and extent of risks likely to impact the target communities, as well as specific areas that may be exposed to higher levels of vulnerability. The development or refinement of existing climate change models can also tell us more about the future impact of climate change on floods and droughts. Partners can conduct special data collection exercises that analyse both the immediate and longer-term consequences of climate shocks. For example, the impact of flooding on areas with dense vegetation in the days and months following the event. This can help inform aid workers about the level of resiliency within target communities, as well as provide realistic timelines for recovery and response activities. ENGAGEMENT In addition to the aforementioned recommendations for future research, this section identifies a number of ways in which BRACED actors can support additional climate and environment change initiatives by engaging with administrative actors and supporting data collection and monitoring mechanisms. In this way, BRACED partners can reinforce existing structures and build local and national capacity for environment and climate change programming and understanding. Engage with Administrative Actors The unique nature of South Sudan s short history as a nation makes it extremely difficult to find reliable historical data at the national level. The Government of Sudan captured data on historical floods and droughts and much of the information is not easily available in South Sudan. BRACED partners should engage with the South Sudan Ministry of Humanitarian Affairs and Disaster to see if this information is accessible and the extent to which it can be used to inform BRACED programming or analysis. When relevant, BRACED partners should also engage with the Ministry of Agriculture, Forestry, Cooperatives and Rural Development and the Ministry of Animal Resources and Fisheries, with whom the Food and Agriculture Organization for the United Nations (FAO), a partner of BRACED, has an existing relationship in Lakes, Northern Bahr el Ghazal and Warrap states. Page 17

18 Support Data Collection and Monitoring Mechanisms Since the outbreak of the conflict in December 2013, the food security situation across South Sudan has deteriorated considerably. In mid-2013, FAO launched a two-year project in South Sudan known as the Agriculture and Food Information System (AFIS). AFIS supports state- and national-level data information systems on food security. According to FAO, AFIS will build on an existing FAO project that developed improved information systems on crop and livestock monitoring and forecasting, crop and livestock markets, and natural resources, and it hopes to further improve the scope, representativeness, performance, reliability and timeliness of these systems at the state level. 5 BRACED implementing partners should familiarize the types of data and information AFIS collects at the state level and all partners should participate in the data collection mechanisms when relevant. BRACED actors should also contribute to data collection and analysis for the Integrated Food Security Phase Classification (IPC), a national measure of food security. BRACED partners may be able to contribute valuable information on the impact of floods and droughts on communities at the local level. The technical stakeholder meetings will also provide BRACED partners with the opportunity to engage with other actors on climate effects in their specific area of implementation. CONCLUSION The population of Lakes, Northern Bahr el Ghazal and Warrap states is largely agro-pastoralist, and therefore has livelihoods largely dependent on the natural environment. Changes in the environment or climate, particularly shocks such as extreme droughts or excessive rainfall, have a severe impact on the well-being of these communities. This report provided a brief review of the environmental and climatic conditions in Lakes, Northern Bahr el Ghazal and Warrap states using satellite-derived datasets. The results of this report represent a preliminary analysis only. The findings from this research on rainfall patterns, historical flooding extents and land cover change provide helpful information for program development and planning by BRACED consortium partners. Examples of ways in which the data from this assessment can inform BRACED programming include: The identification of peak rainy season (August) and dry season (December), which can guide the activity timelines of BRACED projects, including a greater understanding of infrastructure access (seasonal road cut-offs) and related challenges to the pre-positioning of supplies due to high monthly rainfall potential. The data on which counties have the greatest percentage of land that suffers prolonged flooding: Awerial, Yirol and Rumbek East counties in Lakes State; Aweil South County in Northern Bahr el Ghazal State; and Twic, Gogrial East and Tonj North counties in Warrap State; can inform geographic areas of concentration for BRACED activities that focus on flood preparedness. The detection of areas of low vegetation, likely due to human activity, such as the suspected large-scale land burning in the north-west and southern parts of Warrap State, identifies key land-use behaviours that may inform programmatic priorities or deepen the understanding of various community needs and practices. The above list offers only few examples of the different ways in which this research can support BRACED programme decision-making and planning. Each partner in the BRACED consortium may find different uses for the data herein, and will hopefully offer local field-based context to future analyses. 5 FAO, FAO Expands Support For National Food Security Systems in South Sudan, May 24, Page 18