Analysis of Long-Term Trend of Stream Flow and Interaction Effect of Land Use and Land Cover on Water Yield by SWAT Model and Statistical Learning in Part of Urmia Lake Basin, Northwest of Iran

Author:

Sakizadeh Mohamad1,Milewski Adam2ORCID,Sattari Mohammad Taghi34ORCID

Affiliation:

1. Department of Environmental Sciences, Shahid Rajaee Teacher Training University, Shahid Shabanlou Avenue, Lavizan, Tehran 16785-163, Iran

2. Department of Geology, University of Georgia, 210 Field Street, Athens, GA 30602, USA

3. Department of Water Engineering, Agriculture Faculty, University of Tabriz, Tabriz 51666-16471, Iran

4. Department of Agricultural Engineering, Faculty of Agriculture, Ankara University, Ankara 06100, Turkey

Abstract

The water yield produced at the outlet of a sub-basin is the combination of multiple interacting land uses. In the majority of previous research, while accounting for the effect of land use and land cover (LULC) on water yield, the hydrologic components of a watershed have been attributed to the dominant land use class within that sub-basin. We adopted an approach to investigate the interaction effect of LULC on water yield (WYLD) using the Johnson–Neyman (JN) method. The soil and water assessment tool (SWAT) model was employed in the Urmia Lake Basin (ULB) to estimate the WYLD following successful calibration and validation of the model by stream flow. It was found that in each sub-basin, the effect of the soil class on the WYLD was statistically significant only when the area of rangeland was less than 717 ha and when the area of agricultural lands was less than 633 ha. On the other hand, the trend of stream flow was assessed over 70 years at two stations in the Urmia Lake Basin (ULB) using the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST). The year 1991 turned out to be the most likely change point in both stations. A significant decrease in Urmia Lake’s water level started in 1995, which indicated that part of this shrinkage was most likely caused by water inflow reduction over a 4-year time delay. Besides identifying the most probable seasonal and trend change points, this method has the additional capability to analyze the uncertainty of estimated points, which was lacking in earlier methods.

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

Reference68 articles.

1. Nonparametric tests against trend;Mann;Econometrica,1945

2. Kendall, M.G. (1984). Rank Correlation Methods, Charles Griffin.

3. A contextual Mann-Kendall approach for the assessment of trend significance in image time series;Neeti;Trans. GIS,2011

4. A non-parametric approach to the change-point problem;Pettitt;J. Roy. Stat. Soc. C App.,1979

5. Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm;Zhao;Remote Sens. Environ.,2019

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