...
首页> 外文期刊>Environmental Modelling & Software >Model Output Uncertainty Of A Coupled Pathogen Indicator-hydrologic Catchment Model Due To Input Data Uncertainty
【24h】

Model Output Uncertainty Of A Coupled Pathogen Indicator-hydrologic Catchment Model Due To Input Data Uncertainty

机译:输入数据不确定性的耦合病原体-水文集水模型的模型输出不确定性

获取原文
获取原文并翻译 | 示例

摘要

A conceptual model of Escherichia coli behaviour in catchments, the EG model, coupled with a standard hydrological model has been previously developed and tested. This paper presents an analysis of the uncertainty of the modelled pathogen concentrations and loads due to uncertainties in the models data inputs. The data collected at three different large Australian catchments were used. Firstly, uncertainties in the models input data, i.e. hourly rainfall, monthly potential evapotranspiration, catchment size and daily surface pathogen deposition rates, were assessed. Random and systematic sources of errors were taken into account. It was found that systematic errors in rainfall and random errors in pathogen deposition rates have the biggest impact on uncertainty in the models output.
机译:先前已经开发并测试了在流域中大肠杆菌行为的概念模型,EG模型以及标准水文模型。本文对由于模型数据输入中的不确定性而引起的病原体浓度和负荷建模的不确定性进行了分析。使用了在三个不同的澳大利亚大型流域收集的数据。首先,评估了模型输入数据的不确定性,即每小时降雨量,每月潜在蒸散量,集水面积和每日表面病原体沉积率。考虑了随机和系统错误的来源。发现降雨的系统误差和病原体沉积速率的随机误差对模型输出的不确定性影响最大。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号