A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques

2019 ◽  
Vol 35 (9) ◽  
pp. 954-975
Author(s):  
Olutoyin Adeola Fashae ◽  
Rotimi Oluseyi Obateru ◽  
Adeyemi Oludapo Olusola
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
River Basin ◽  
Remote Sensing And Gis ◽  
Water Balance Model ◽  
Balance Model ◽  
Gis Techniques

scholarly journals Estimation of flooded area in the Bahr El-Jebel basin using remote sensing techniques

2006 ◽  
Vol 3 (4) ◽  
pp. 1851-1877 ◽  
Author(s):  
M. A. H. Shamseddin ◽  
T. Hata ◽  
A. Tada ◽  
M. A. Bashir ◽  
T. Tanakamaru
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Lake Victoria ◽  
Open Water ◽  
Unsupervised Classification ◽  
Water Balance Model ◽  
Balance Model ◽  
Water Evaporation ◽  
Flooded Area ◽  
Remote Sensing Techniques

Abstract. In spite of the importance of Sudd (swamp) area estimation for any hydrological project in the southern Sudan, yet, no abroad agreement on its size, due to the inaccessibility and civil war. In this study, remote sensing techniques are used to estimate the Bahr El-Jebel flooded area. MODIS-Terra (Moderate Resolution Imaging Spectroradiometer) level 1B satellite images are analyzed on basis of the unsupervised classification method. The annual mean of Bahr El-Jebel flooded area has been estimated at 20 400 km2, which is 96% of Sutcliffe and Park (1999) estimation on basis of water balance model prediction. And only, 53% of SEBAL (Surface Energy Balance Algorithm for Land) model estimation. The accuracy of the classification is 71%. The study also found the swelling and shrinkage pattern of Sudd area throughout the year is following the trends of Lake Victoria outflow patterns. The study has used two evaporation methods (open water evaporation and SEBAL model) to estimate the annual storage volume of Bahr El-Jebel River by using a water balance model. Also the storage changes due time is generated throughout the study years.

Coupling remote sensing with a water balance model for soybean yield predictions over large areas

2019 ◽  
Vol 13 (2) ◽  
pp. 345-359 ◽  
Author(s):  
Daniela F. Silva Fuzzo ◽  
Toby N. Carlson ◽  
Nektarios N. Kourgialas ◽  
George P. Petropoulos
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Balance Model ◽  
Balance Model ◽  
Soybean Yield
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