lake chad hydrological modeling analysis final2

Lake Chad Basin Data Research and Analysis

Serena Emanuel and Haley Kujawa

Presentation Overview:

1. Background Research/Literature Review2. Data Acquisition3. Data Analysis 4. Watershed Delineation and Mapping5. Basin Trends and Conclusions

Directly affected countries:• Chad, Niger, Nigeria, Cameroon

Indirectly affected countries:• Central African Republic• Sudan• Algeria

Part 1: Background Research and Literature Review

History of Lake Chad


Low adaptive capacity of arid regions


Decreased lake size could be due to decreased inflow


IPCC GCM report on water and climate change

Regions experiencing significant increases or decreases in precipitation – The Lake Chad Basin (LCB) marked by a significant decrease


On the causes of shrinking Lake Chad


Model of inflow for Lake Chad to return to pre-1960s levels


Impact of droughts, split, and irrigation model


Historical Lake Levels show cause could bepart of a natural cycle


Part 2: Data AcquisitionGRDC: River Discharge Data• Application process• Received daily and monthly data• Daily Data Includes:

• Lake Chad Basin• 11 Nigeria Stations• 21 Central African Republic Stations• 12 Chad Stations

• Congo River Basin (for future diversion impact study)• 44 stations

NOAA Precipitation and Temperature Data• Daily and monthly data for:

• Cameroon (3 stations)• Nigeria (10 stations)• Central African Republic (17 stations)• Chad (11 stations)

Part 2: Data Acquisition

Part 3: Data Research and Analysis

KEY

Precipitation Station: Date Range

Flow Station: Date Range

Justifying data selectionCriteria for evaluating monotonic trends• Minimum of 5 years monthly data• Data gaps less than 1/3 the total data

Climatic analysis of data• Minimum of 50 years preferable• For lack of consistent data, 30 years of data was considered useful in this

study


Flow Large Data RangesFlow Selected Stations:Ndjamena: 1976-1991 Ouli Bangala: 1978-1990Hadejia: 1963-2006Wudil: 1963-2005Bossangoa: 1986-1992Bangui: 1935-2007


Precipitation Large Date RangesPrecipitation Selected Stations:Ndjamena: 1950-2016 (67%)Bousso: 1952-1978 (91%)Magaria: 1980-1992 (90%)Moundou: 1950-2016 (62%)Pala: 1952-1978 (92%)Garoua: 1973-2016 (71%)Bour: 1950-1980 (94%)N Guigni: 1926-2016 (79%)Sarh: 1950-2016 (64%)Bouca: 1950-1965 (96%)Bangui: 1950-1980 (93%)


Part 4: Watershed Delineation• Accessed 90 m accuracy data from

CGIAR-CSI GeoPortal• Downloaded about 20 DEM

files/squares that encompass the Watershed• Use GIS to delineate watershed and

sub-basins• Can determine which stations we

have data for and where these stations are located in the sub-basins

Lake Chad Basin• Huge area2,500,000 km^2 at 90

m accuracy• Too large for even ArcGIS to

handle • Must decrease accuracy while still

maintaining correct watershed

Part 4: Watershed Delineation

Problem Solving: Lake Chad Basin Delineation

• Use CIMA watershed delineation to determine correct Lake Chad Basin boundaries

• Used AutoCAD to outline basin, and then used previous CIMA file to correctly scale and locate the basin

CIMA Watershed Boundaries

AutoCAD tracing of watershed


Problem Solving: Lake Chad Basin Delineation• Imported AutoCAD basin

outline and DEM files into Global Mapper, to chop data to watershed size and reduce cell size, further decreasing the size of the data• Exported the cropped DEM

files and imported them into WMS• Used WMS functions in order

to delineate watershed and sub-basins


Global Mapper

WMS

Lake Chad Basin Delineation


Comparison between WMS Delineation (left) and CIMA delineation (right)

Lake Chad Basin Delineation: Adding the Lake


• Used GIS raster calculator to add 290 m elevation lake (historic size) and 280 m elevation lake (2008 size)

• Compared with Google Earth to check accuracy of raster calculator/elevation method

Lake Chad Basin Delineation using WMS

Sub-Basin 1Sub-Basin 2Sub-Basin 3Sub-Basin 4Sub-Basin 5Overall Basin


Part 5: Basin Trends and Conclusions

Key:PrecipitationFlow

Mann-Kendall analysis

Part 5: Basin Trends and Conclusion

Sen slope; estimate of rate of change in the trend

Test statistic; large absolute value indicates a trend

β0 is the null hypothesis (no trend); when non-zero, the null hypothesis is rejected

n = number of data points

Tau statistic; similar to correlation coefficient

Linear regression of the data Significance Equations

Relative Factor• Used to fill missing data• Stations with spatial relations could be plotted on x (station A) and y-

axis (station B) to determine a linear fit• If R>0.8, the linear relationship between the data can be used to

transform data from station A to station B



Ndjamena

Moundou

Bangui

Bossangoa

Wudil

Hadejia

Station Precipitation Date Range

Flow Date Range

Ndjamena 1950-1978 1953-2009

Bangui -------- 1935-2007

Bossangoa -------- 1951-1972

Hadejia -------- 1963-2005

Wudil -------- 1963-1991

Moundou 1950-1978 ----------

Significant: CI>90%

Seasonal Trend Analysis: Rainy season

Conclusion of Data Analysis and Results• Map of trends concludes decrease in flow

and precipitation could be a significant cause of the shrinking of the Lake Chad

• Conclusion coincides with background research


Data Discussion• Historically, countries around Lake Chad haven’t focused on

investments in data collection• Data is sporadic and infrequent, many sets are missing too large of

gaps to run Mann-Kendall analysis• Relative analysis was able to fill some of the data gaps• Using only one month out of the year may produce a more

continuous series of data to run in the Mann-Kendall (i.e. August or September, during the rainy season)


Future Work• Further analysis and organization of the data must be done• Collection of more data sets to verify and fill gaps in the data• More research on and a better understanding of the Mann-Kendall

analysis• Finding more data for stations in upper sub-basins (Sahel region)• Using historical data to project future trends• Analyzing impact of the basin transfer project on the the Lake Chad

Basin and Congo River Basin


Thank you!

Any questions?

Special thanks to: Dr. Guo, Bibi, David, Mr. Song, Yang, and all others who have graciously helped with our project and our internship

lake chad hydrological modeling analysis final2

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