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Modeling hydrologic and water quality response of a mixed land use watershed in Piedmont physiographic region (Maryland).

机译:对皮埃蒙特自然地理区(马里兰州)的混合土地利用流域的水文和水质响应进行建模。

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Nonpoint source pollution of surface and groundwater has become recognized as an important environmental problem associated with agricultural production for any region. Mathematical watershed scale models are among the best tools available for analyzing water resources (quantity and quality) issues in spatially diverse watersheds. Existing models without proper validation have resulted in some misconceptions about such models.; A conceptual, continuous time, and watershed scale, distributed hydrologic/water quality model, SWAT, was applied to a 340 ha watershed with mixed land use in the Piedmont physiographic region of Maryland to test its performance in predicting hydrologic/water quality response. Six years (1994–1999) of hydrologic and nutrient loading data were used to calibrate and validate the capability of SWAT. Additionally, an artificial neural network approach based on a back propagation scheme (ASCE, 2000a and 2000b) was used to generate the incomplete flow data in 1998.; Results indicated that the SWAT model like many other similar models only handle subsurface flow bounded by the surface topography, thus neglecting the possible subsurface flow contribution from outside the watershed. A water budget analysis therefore was performed to quantify various components of the hydrologic cycle within the watershed. The imbalance in water budget analysis showed the ground water contribution from outside the watershed to be in the range of 20%–61% of the measured base flow. Therefore, accounting for such contribution is deemed to be necessary for fair evaluation of the model results. Adjustments of measured base flow and stream flow made to exclude the extra groundwater recharge showed a moderate improvement in model's predictions.; Finally, model's simulations of monthly sediment and nutrient loadings were poor. Despite the poor monthly predictions and some extreme events, the model showed a strong agreement between annual measured and simulated data for sediment, nitrate and soluble phosphorus loadings. It was concluded that SWAT is a reasonable watershed scale model on long-term simulations of the impact of different management practices on hydrologic and water quality response of mixed land use watersheds. However, its use on short-term or storm by storm basis may not be appropriate.; The uncertainty analysis of input parameters and its effect on model simulation was also investigated in this study. The large standard deviation (102.4 mm) and large range of stream flow (215.0 to 530.0 mm) imply significant uncertainty in stream flow prediction. This portion of the study concluded that assessing the uncertainty in model outputs resulting from uncertainty in input data may be very vital in evaluating the environmental risks associated from such uncertainties.
机译:地表和地下水的非点源污染已被公认为与任何地区的农业生产相关的重要环境问题。数学分水岭规模模型是可用于分析空间多样化流域中的水资源(数量和质量)问题的最佳工具。没有适当验证的现有模型已导致对此类模型的误解。在马里兰州皮埃蒙特地理区域,将一个概念性,连续时间和分水岭规模的分布式水文/水质模型SWAT应用于340公顷具有混合土地利用的分水岭,以测试其在预测水文/水质响应中的性能。六年(1994-1999年)的水文和养分含量数据用于校准和验证SWAT的能力。另外,在1998年使用了基于反向传播方案(ASCE,2000a和2000b)的人工神经网络方法来生成不完整的流量数据。结果表明,SWAT模型与许多其他类似模型一样,仅处理受表面地形限制的地下流,因此忽略了分水岭外部可能产生的地下流。因此,进行了水预算分析以量化流域内水文循环的各个组成部分。水量预算分析的不平衡表明,流域外部的地下水贡献量为实测基础流量的20%–61%。因此,为公平评估模型结果,有必要考虑此类贡献。调整测得的基础流量和水流量以排除额外的地下水补给,表明模型的预测有中等程度的改善。最后,月沉积物和养分含量的模型模拟很差。尽管每月的预测很差并且发生了一些极端事件,但该模型仍显示出沉积物,硝酸盐和可溶性磷含量的年度实测数据与模拟数据之间的一致性。得出结论,SWAT是长期模拟不同管理实践对混合土地利用流域水文和水质响应的影响的合理分水岭规模模型。但是,短期使用或逐个风暴使用它可能不合适。本文还研究了输入参数的不确定性分析及其对模型仿真的影响。大的标准偏差(102.4毫米)和大的流量范围(215.0至530.0毫米)暗示着流量预测中的显着不确定性。研究的这一部分得出结论,评估由输入数据的不确定性导致的模型输出的不确定性对于评估此类不确定性带来的环境风险可能至关重要。

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