Trend Assessment of Land Use Changes Using Remote Sensing Technique and its Relationship with Streamflows Trend (Case Study: The East Sub-Basins of Urmia Lake)

آب و خاک

Article 17, Volume 27, Issue 3, July 2013, Pages 642-655   

Document Type: Research Article

DOI: 10.22067/jsw.v0i0.26091

Authors

F. Fathian^* ; S. Morid; S. Arshad

Abstract

The drawdown trend of the water level in Urmia Lake poses a serious problem for northwestern Iran that will have a negative impact on the agriculture and industry. This research investigated the possible causes of this adversity by estimating trends in the time series of hydro-climatic variables of the basin as well as tracking changes in the land use of the study area, using satellite images. Four non-parametric statistical tests, the Mann-Kendall, Theil-Sen, Spearman Rho and Sen's T test, were applied to estimate the trends in the annual time series of streamflow, precipitation and temperature at 18 stations throughout the case study. Furthermore, by using the LANDSAT satellite images of 1976, 1989, 2002 and 2011, land use classification was determined using maximum likelihood, minimum distance and mahalanobis distance methods. The results showed significant increasing temperature trend throughout the region and an area-specific precipitation trend. The trend tests also confirmed a general decreasing trend in region streamflows that was more pronounced in the downstream stations. The results showed that the classification by the maximum likelihood method wass associated with minimum error. The results of processing the images showed that the irrigated crops, horticultural and dry lands have increased during last 35 years by 412, 485 and 672 percent, respectively. But, the pasture area is decreased by 34 percent. Finally, correlation between streamflow changes with simultaneous changes in climatic variables and land use showed it is significant in case of temperature and land use; and insignificant in case of precipitation. However, the determination coefficient of land use is higher than temperature.

Keywords

Trend; Non-parametric methods; land use; Remote sensing; Urmia Lake Basin