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- W4281792136 abstract "Nitrate nitrogen (NO3−-N) from agricultural activities and in industrial wastewater has become the main source of groundwater pollution, which has raised widespread concerns, particularly in arid and semi-arid river basins with little water that meets relevant standards. This study aimed to investigate the performance of spatial and non-spatial regression models in modeling nitrate pollution in a semi-intensive farming region of Iran. To perform the modeling of the groundwater's NO3−-N concentration, both natural and anthropogenic factors affecting groundwater NO3−-N were selected. The results of Moran's I test showed that groundwater nitrate concentration had a significant spatial dependence on the density of wells, distance from streams, total annual precipitation, and distance from roads in the study area. This study provided a way to estimate nitrate pollution using both natural and anthropogenic factors in arid and semi-arid areas where only a few factors are available. Spatial regression methods with spatial correlation structures are effective tools to support spatial decision-making in water pollution control." @default.
- W4281792136 created "2022-06-13" @default.
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- W4281792136 date "2022-09-01" @default.
- W4281792136 modified "2023-10-04" @default.
- W4281792136 title "Modeling groundwater nitrate concentrations using spatial and non-spatial regression models in a semi-arid environment" @default.
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- W4281792136 cites W1929923454 @default.
- W4281792136 cites W1968111533 @default.
- W4281792136 cites W1972448450 @default.
- W4281792136 cites W1973199320 @default.
- W4281792136 cites W1976764790 @default.
- W4281792136 cites W1977356088 @default.
- W4281792136 cites W1983513512 @default.
- W4281792136 cites W1992874753 @default.
- W4281792136 cites W1993488142 @default.
- W4281792136 cites W1995068819 @default.
- W4281792136 cites W1996051870 @default.
- W4281792136 cites W1997159081 @default.
- W4281792136 cites W2002667357 @default.
- W4281792136 cites W2002848730 @default.
- W4281792136 cites W2008435275 @default.
- W4281792136 cites W2015061762 @default.
- W4281792136 cites W2015327201 @default.
- W4281792136 cites W2016520855 @default.
- W4281792136 cites W2017007384 @default.
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- W4281792136 cites W2024695206 @default.
- W4281792136 cites W2028573940 @default.
- W4281792136 cites W2035660303 @default.
- W4281792136 cites W2035982120 @default.
- W4281792136 cites W2038913727 @default.
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- W4281792136 cites W2621614687 @default.
- W4281792136 cites W2743040512 @default.
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- W4281792136 doi "https://doi.org/10.1016/j.wse.2022.05.002" @default.
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