<p>This research set out to assess the Kan-Karaj River's water quality as a vital water supply for the cities of Karaj and Tehran, as well as to ascertain how land development affected the river's water quality. Data on water quality measures, such as turbidity, NO<sub>3</sub>, SO<sub>4</sub>, EC, TDS, COD, and total coliform bacteria (TC), were gathered from the output of 20 sub-watersheds for this purpose. Based on two independent and continuous methodologies, the area of land-use classes in each sub-watershed was estimated, and then correlation analysis, multivariate statistical regression, and redundancy analysis were performed to examine the link between land-use and water quality. The findings of the cluster analysis of the monitoring stations, which indicated that the region might be split into two parts—the southern portion with poor water quality and the northern half with higher quality—were validated by the spatial pattern of water quality parameters. Regression analysis showed that, in the independent method, farmland land-use predicts NO<sub>3</sub>, TC, FC, and IRWQIs (R<sup>2</sup> values are 0.42, 0.70, 0.66, and 0.60, respectively), while built-up and rangeland land-uses explain SO<sub>4</sub> (R<sup>2</sup> = 0.67). built-up and farmland land-uses are used to determine EC and TDS (R<sup>2</sup> = 0.81).The land uses that had the most impact on water quality were, generally speaking, farmland land-use in a continuous approach and built-up and rangeland land-use in an independent approach. Redundancy analysis results also indicated that farmland had a greater influence on the parameters of NO<sub>3</sub>, FC, and TC, whereas built-up and farmland land-uses had an impact on EC, TDS, and SO<sub>4</sub>. However, the independent strategy outperformed the continuous approach in demonstrating the influence of land use on water quality indicators. Smaller-scale land-use data may provide a more accurate picture of the impact on water quality in future researches.</p>

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Assessing the relationship between land-use pattern and spatial variation of surface water quality in the Kan-Karaj River basin, Iran

  • Maryam Alizadeh,
  • Rouhollah Mirzaei,
  • Seyed Hossein Kia,
  • Mohamad Sakizadeh

摘要

This research set out to assess the Kan-Karaj River's water quality as a vital water supply for the cities of Karaj and Tehran, as well as to ascertain how land development affected the river's water quality. Data on water quality measures, such as turbidity, NO3, SO4, EC, TDS, COD, and total coliform bacteria (TC), were gathered from the output of 20 sub-watersheds for this purpose. Based on two independent and continuous methodologies, the area of land-use classes in each sub-watershed was estimated, and then correlation analysis, multivariate statistical regression, and redundancy analysis were performed to examine the link between land-use and water quality. The findings of the cluster analysis of the monitoring stations, which indicated that the region might be split into two parts—the southern portion with poor water quality and the northern half with higher quality—were validated by the spatial pattern of water quality parameters. Regression analysis showed that, in the independent method, farmland land-use predicts NO3, TC, FC, and IRWQIs (R2 values are 0.42, 0.70, 0.66, and 0.60, respectively), while built-up and rangeland land-uses explain SO4 (R2 = 0.67). built-up and farmland land-uses are used to determine EC and TDS (R2 = 0.81).The land uses that had the most impact on water quality were, generally speaking, farmland land-use in a continuous approach and built-up and rangeland land-use in an independent approach. Redundancy analysis results also indicated that farmland had a greater influence on the parameters of NO3, FC, and TC, whereas built-up and farmland land-uses had an impact on EC, TDS, and SO4. However, the independent strategy outperformed the continuous approach in demonstrating the influence of land use on water quality indicators. Smaller-scale land-use data may provide a more accurate picture of the impact on water quality in future researches.