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Fooladi, M., Golmohammadi, M. H., Safavi, H. R., Mirghafari, R.,Akbari, H., (2021) Trend Analysis of Hydrological and Water Quality Variables to Detect Anthropogenic Effects and ..., J HYDRO-ENVIRON RES., doi: 10.1016/j.jher.2021.01.001.

Trend Analysis of Hydrological and Water Quality Variables to Detect Anthropogenic Effects and Climate Variability on a River Basin Scale: A Case Study of Iran

Mahmood Fooladi, Mohammad H. Golmohammadi, Hamid R. Safavi, Rasoul Mirghafari, Hassan Akbari


In recent years, climate changeability, hydrologic regime conditions, and human interventions have become crucial issues to be assessed. In this research, two annually recorded datasets were collected to trend analysis. The first set is comprised of precipitation, streamflow, and water quality variables including Total Dissolved Solids (TDS), pH, cation, and anion and the second one contains the mean groundwater level and agricultural water demand of four main stations of Shahpour River basin in the south of Iran. To recognize the fluctuating patterns, the Mann-Kendall Trend Test (MKTT), KPSS Stationary Test, and Pettit Homogeneity Test (PHT) of statistical methods were utilized at a 5% significance level. The Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) were subsequently employed to detect the hydrological drought patterns. According to the statistical analysis, the streamflow and water quality depicted intensive varying trends, while there were slight decreasing trends for the precipitation series. Afterward, the abrupt changing points were identified in the first and second datasets between the years 2004 to 2007. The results of this study clarified that human activity effects (as a major factor) and climate variability (as a minor factor) have been affecting the Shahpour River basin. These effects are able to disrupt water chemical balance (the relationship between cations and anions) and hydrological regimes (increasing drought drivers) and consequently menace the health of the watershed.


Trend analysis, statistical methods, changing point, human activity, climate variability.


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