Mahsa Polroudimoghadam; Saeid Hamzeh; Madjid Vazifehdoust
Abstract
Abstract
Nowadays, considering the reduction of water resources and the existing water crisis, it is necessary and important to pay attention to the proper and integrated water resources management, especially in border areas. One of the basic measures in this field is to know the amount of rainfall ...
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Abstract
Nowadays, considering the reduction of water resources and the existing water crisis, it is necessary and important to pay attention to the proper and integrated water resources management, especially in border areas. One of the basic measures in this field is to know the amount of rainfall and runoff and the trend of its changes in the watershed basins.
However, the lack of access to sufficient field data in the border areas poses a major problem. Remotely sensing data and global land models can be used to overcome this problem. The aim of this research is to investigate the trend of rainfall-runoff changes in the Doosti dam basin - which is important to decision–makers in Iran- using the Global Land Surface Model System (GLDAS). For this purpose GLDAS data were used in 7 pixels 1.5*1.5 degree between the Latitudes of 35-36.5 N and Longitude of 59.5-67 W. The type of changes and trend of model data were investigated seasonally and annually through simulation, Pearson correlation coefficient, Mann-Kendall and Mann-Kendall sequential tests over a period of 10 years from 2004 to 2013. The results of data analysis showed that the correlation between rainfall and runoff is weaker in the East and the Southeast of the studied basin than in other areas. Also, at 95% of the confidence level for annual rainfall data, the trend for the rainfall is negative only in pixel 7 and for runoff in pixels 6 and 7. Regarding seasonal data, the trend was detected to be negative for the rainfall only in spring in pixels 5 and 7, and for the runoff in winter and summer in pixel 7. The results of this model show that the GLDAS model can be very useful and practical for studying rainfall-runoff in areas with difficult access to terrestrial data because it is possible to study vast areas at low cost.