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Groundwater monitoring at the watershed scale: An evaluation of recharge and nonpoint source pollutant loading in the Clear Creek Watershed, Iowa

机译:流域尺度的地下水监测:爱荷华州Clear Creek流域的补给和面源污染物负荷评估

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Determining the groundwater contribution of nonpoint source pollution at a watershed scale is a challenging issue. In this study, we utilized a top-down approach to characterize representative groundwater response units (GRUs) based on land use and landscape position (e.g., upland, sideslope, or floodplain) in the 275-km(2) Clear Creek Watershed, Iowa. Groundwater monitoring wells were then established along downslope transects in representative GRUs. This unique combination of top-down/bottom-up approaches allowed us to estimate groundwater pollutant loads at the watershed scale with minimal monitoring. For the 2015 study period, results indicated that more groundwater recharge occurred in the floodplain (404 mm) compared to the uplands or sideslopes (281 and 165 mm, respectively), irrespective of land use. Recharge in the floodplains consisted of 37% of the annual precipitation, whereas upland wells averaged 26% and sideslopes averaged 15% of the annual precipitation. Less recharge was found to occur beneath perennial grass compared to row crop and urbanized areas. Baseflow discharge accounted for 69% of the total NO3-N exported from the Clear Creek Watershed, with row crop areas contributing approximately 95% of the annual load. Orthophosphorus (OP) yields were approximately 0.72 kg/ha beneath urban and suburban areas, three times higher than those in row crop or perennial areas. Urban and suburban areas accounted for 21.4% of groundwater orthophosphorus and chloride loads in the watershed compared to only 8.5% of the land area. Overall, the groundwater load allocation model for baseflow nutrient discharge to Clear Creek can be used to target future nonpoint source load reduction strategies at the watershed scale. The use of GRUs can pinpoint better areas of concern for controlling nutrient loads.
机译:在流域范围内确定非点源污染对地下水的贡献是一个具有挑战性的问题。在这项研究中,我们使用了一种自上而下的方法,根据衣阿华州275公里(2)克利尔克里克流域的土地利用和景观位置(例如高地,边坡或洪泛区)来表征代表性的地下水响应单位(GRU)。 。然后在代表性的GRU中沿着下坡样线建立地下水监测井。自上而下/自下而上的方法的独特组合使我们能够以最少的监测来估算流域范围内的地下水污染物负荷。对于2015年研究期,结果表明,与高地或边坡(分别为281和165毫米)相比,洪泛区(404毫米)的地下水补给量更多,而与土地用途无关。洪泛区的补给量占年降水量的37%,而旱井平均为年降水量的26%,边坡平均为年降水量的15%。与大田作物和城市化地区相比,多年生草下的补给较少。基流排放量占Clear Creek流域出口的NO3-N总量的69%,其中排田面积约占年负荷量的95%。在城市和郊区以下,正磷(OP)产量约为0.72千克/公顷,是大田作物或多年生地区的三倍。城市和郊区占流域地下水正磷和氯化物负荷的21.4%,而土地面积仅占8.5%。总体而言,用于清除河溪的基流养分排放的地下水负荷分配模型可用于确定流域尺度上未来的非点源负荷减少策略。使用GRU可以确定控制营养负荷的更好关注领域。

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