Accurate identification of nitrate (NO3−) sources is critical to addressing groundwater pollution, especially in highly vulnerable karst aquifers. The groundwater hydrochemistry and δ15NNO3 and δ18ONO3 isotopes were analyzed in samples taken from the Jinan Spring Catchment, which has been affected by urbanization and agricultural activities. The study highlighted the use of hydrochemistry, environmental isotopes, and a multisource linear mixed model for NO3− source identification and apportionment. The results showed that, controlled by carbonate rocks, the hydrochemical types in both rainy and dry seasons were highly consistent, and HCO3·SO4−Ca was the dominant type, accounting for 60%. Except for Ca2+, Mg2+ and HCO3−, the coefficients of variation of other ions were all greater than 0.5 in rainy and dry seasons. The chemical composition of groundwater was mainly controlled by water–rock interaction. Ca2+ and HCO3− were mainly derived from carbonate rock dissolution; K+, Na+, SO42−, NO3− and Cl− were partially derived from atmospheric precipitation. The IsoSource model quantitatively revealed that the majority of the groundwater and surface water was influenced by manure and sewage (M&S) contributing 39.3% and 52.3% in the rainy season, and 37.1% and 56.9% in the dry season, respectively. The NO3− source fraction rates were in the order M&S > SON > AF > CF > AD. In addition, nitrate pollution control measures and suggestions for different areas are put forward. In rural residential areas, the free discharge of livestock manure and sewage should be strictly controlled. In agricultural planting areas, chemical fertilizers and pesticides should be used rationally to prevent non-point source pollution. In urban areas, the centralized treatment of industrial and residential sewage should be strengthened to prevent point source pollution.
Water measurement through standard cross-section is one of the main methods of water measuring of irrigation canal. This paper takes Zhejiang Province as an example, and calibrates 16 canal standard cross-sections of 5 irrigation areas, and uses the curve of water level-discharge relation and the power function formula to fit coefficient “K” and index “u”, and applies the linear regression method to analyze the influence of canal width, slope and lining type on the flow parameters. The results show that the coefficient “K” of canal standard cross-section range from 0.6986 to 4.7035, and the index “u” range from 1.3334 to 2.6376. The discharge parameters are positively correlated with canal width and slope, and are negatively correlated with canal roughness.
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