科技报告详细信息
A Predictive Model for Lake Chad Total Surface Water Area Using Remotely Sensed and Modeled Hydrological and Meteorological Parameters and Multivariate Regression Analysis
Policelli, Frederick [Point of Contact] ; Hubbard, Alfred ; Jung, Hahn Chul ; Zaitchik, Ben ; Ichoku, Charles
关键词: LAKES;    SAHARA DESERT (AFRICA);    SURFACE WATER;    AREA;    ANNUAL VARIATIONS;    EVAPOTRANSPIRATION;    REGRESSION ANALYSIS;    ESTIMATES;    METEOROLOGICAL PARAMETERS;    PRECIPITATION (METEOROLOGY);    FLOODS;   
RP-ID  :  GSFC-E-DAA-TN64340
美国|英语
来源: NASA Technical Reports Server
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【 摘 要 】

Lake Chad is an endorheic lake in the Sahel region of Africa at the southern edge of the Sahara Desert. The lake, which is well known for its dramatic decrease in surface area during the 1970s and 1980s, experiences an annual flood resulting in a maximum total surface water area generally during February or March, though sometimes earlier or later. People along the shores of Lake Chad make their living fishing, farming, and raising livestock and have a vested interest in knowing when and how extensive the annual flooding will be, particularly those practicing recession farming in which the fertile ground of previously flooded area is used for planting crops. In this study, the authors investigate the relationship between lake and basin parameters, including rainfall, basin evapotranspiration, lake evapotranspiration, lake elevation, total surface water area, and the previous year’s total surface water area, and develop equations for each dry season month (except November) linking total surface water area to the other parameters. The resulting equations allow the user to estimate the December average monthly total surface water area of the lake in late November, and to make the estimates for January to May in early December. Based on the results of a Leave One Out Cross Validation analysis, the equations for lake area are estimated to have an average absolute error ranging from 5.3 percent (for February estimates) to 7.6 percent (for May estimates).

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