Title :
Mapping of Interception Loss of Vegetation in the Heihe River Basin of China Using Remote Sensing Observations
Author :
Yaokui Cui ; Li Jia ; Guangcheng Hu ; Jie Zhou
Author_Institution :
State Key Lab. of Remote Sensing Sci., Inst. of Remote Sensing & Digital Earth, Beijing, China
Abstract :
Interception loss is an important component of the regional water balance for the Heihe River Basin which is an inland basin with limited precipitation. We used a modified Gash analytical model by combining remote sensing observations to estimate the interception loss of several vegetation types, e.g., grass, crop, forest and shrub for the years 2003-2012 in the Heihe River Basin. The estimated monthly interception ratio (in percent) was compared with field measurements made in Dayekou and Pailugou forest hydrology experimental sites and the results showed reasonable accuracy with RMSE of 5.0% and 4.3% at the two sites, respectively. The regional distribution of the interception loss showed strong spatial and temporal variability at monthly scale. At annual scale, the interception ratio could be treated as a stable indicator for long-term water balance research. The annual average interception loss is about 7.2% of gross rainfall for the vegetation covered area in the Heihe River Basin.
Keywords :
rain; remote sensing; rivers; vegetation mapping; AD 2003 to 2012; China; Dayekou forest hydrology experimental site; Heihe River Basin; Pailugou forest hydrology experimental site; RMSE accuracy; annual average interception loss; annual scale; crop; estimated monthly interception ratio; field measurement; forest; grass; gross rainfall; inland basin; interception loss regional distribution; limited precipitation; long-term water balance research stable indicator; modified Gash analytical model; monthly scale spatial variability; monthly scale temporal variability; regional water balance component; remote sensing observation; shrub; vegetation covered area; vegetation type interception loss mapping; Agriculture; Indexes; Mathematical model; Remote sensing; Rivers; Vegetation; Vegetation mapping; Heihe River Basin; RS-Gash model; interception loss; remote sensing;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2014.2324635