WO2019090554A1 - 一种水源地水质监测方法 - Google Patents

一种水源地水质监测方法 Download PDF

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WO2019090554A1
WO2019090554A1 PCT/CN2017/110092 CN2017110092W WO2019090554A1 WO 2019090554 A1 WO2019090554 A1 WO 2019090554A1 CN 2017110092 W CN2017110092 W CN 2017110092W WO 2019090554 A1 WO2019090554 A1 WO 2019090554A1
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water
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周文浩
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苏州迪维勒普信息科技有限公司
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Priority to CN201780002676.6A priority patent/CN108064392A/zh
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    • Y02A20/00Water conservation; Efficient water supply; Efficient water use
    • Y02A20/152Water filtration

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  • the invention belongs to the technical field of water quality safety, and in particular relates to a water quality monitoring method for water source.
  • the existing regional ecological monitoring methods are mainly designed for cities, river basins, etc., lacking the index system and related index model for surface water source watershed ecological monitoring methods; for the basin monitoring method, due to the lack of multi-temporal quantitative spatial data Support, it is difficult to find out the complexity of the process of underlying surface in complex watersheds, so that most monitoring indicators are stuck in qualitative analysis due to lack of process-mechanism analysis and lack of reliability.
  • the technical problem mainly solved by the invention is to provide a water quality monitoring method for a water source, which ensures rapid and convenient realization of monitoring and evaluation of a wide range of surface water sources, and the obtained monitoring results also have the advantages of space and dynamics, and are convenient for water sources. Land management and pre-judgment of pollution.
  • a technical solution adopted by the present invention is to provide a water quality monitoring method for a water source, comprising the following steps:
  • Step 1 Confirm the target water source and use the remote sensing data of the observation satellite to construct a water flow model
  • Step 2 Evaluate the water quality elements of each water source according to the ecosystem stability, ecosystem loss and risk source risk of the water source;
  • Step 3 According to the water flow model, based on the fuzzy mathematical method, the overall safety level assessment of the water quality of the water source is performed;
  • Step 4 Predict the water quality migration distribution model of the water source according to the local meteorological environment and geological conditions
  • Step 5 Establish an early warning mechanism and an emergency mechanism by using the water source migration distribution model of the water source.
  • the ecosystem stability in the second step includes geological soil elements, geomorphic vegetation elements, ecological group structure, ecological restoration capacity elements and human factors.
  • the risk source risk in the second step includes soil desertification elements, soil erosion factors, pollution source emission factors, natural disaster elements, and drought and water shortage elements.
  • the degree of ecosystem loss in the second step includes a drinking water loss factor and a water conservancy factor.
  • the human factors include excessively cultivated land elements, overgrazing elements, and over-harvesting elements.
  • the remote sensing data of the observation satellite is used in the first step, the remote sensing data of the observation satellite is subjected to radiometric calibration, geometric correction and correction preprocessing, thereby obtaining a remote sensing image of the surface reflection.
  • the detection of the drinking water loss factor is calculated by using ground statistics, combined with the water supply capacity evaluation model, calculating the water supply amount and the proportion of the required water volume, confirming the current population demand of the water source, and calculating the current water source current.
  • the water supply capacity to assess the current level of safety of drinking water in the water source.
  • the present invention utilizes remote sensing data of observation satellites to further optimize the construction of the water flow model to ensure rapid and convenient implementation of monitoring and evaluation of a wide range of surface water sources;
  • the invention evaluates the water quality elements of various water sources according to the ecosystem stability, ecosystem loss and risk source risk of the water source. Considering the indicators, the overall safety level of the water source can be obtained, and the process mechanism is clear, combined with water quality migration.
  • the distribution model, the obtained monitoring results also have the advantages of spatial and dynamic;
  • the present invention predetermines the water source migration distribution model of the water source, improves the initiative of the water source safety warning, and facilitates the management of the water source and the pre-judgment of the pollution situation.
  • Embodiment A method for monitoring water quality in a water source, the present invention includes the following steps:
  • Step 1 Confirm the target water source and use the remote sensing data of the observation satellite to construct a water flow model
  • Step 2 Evaluate the water quality elements of each water source according to the ecosystem stability, ecosystem loss and risk source risk of the water source;
  • Step 3 According to the water flow model, based on the fuzzy mathematical method, the overall safety level assessment of the water quality of the water source is performed;
  • Step 4 Predict the water quality migration distribution model of the water source according to the local meteorological environment and geological conditions
  • Step 5 Establish an early warning mechanism and an emergency mechanism by using the water source migration distribution model of the water source.
  • the ecosystem stability in the second step includes geological soil elements, geomorphological vegetation elements, ecological group structure, ecological restoration capacity elements and human factors.
  • the risk source risk in the second step includes soil desertification elements, soil erosion factors, pollution source emission factors, natural disaster elements, and drought and water shortage elements.
  • the degree of ecosystem loss in the second step includes drinking water loss factors and water conservancy facilities.
  • the human factors include excessively cultivated land elements, overgrazing elements, and over-harvesting elements.
  • the remote sensing data of the observation satellite is subjected to radiometric calibration, geometric correction and correction preprocessing, thereby obtaining a remote sensing image of the surface reflection.
  • the detection of the drinking water loss factor is calculated by using ground statistical data, combined with the water supply capacity evaluation model, calculating the water supply amount and the proportion of the required water volume, confirming the current population demand of the water source, and calculating the current water supply capacity of the water source. Assess the current level of safety of drinking water in the water source.
  • the invention utilizes the remote sensing data of the observation satellite to further optimize the construction of the water flow model, and ensures that the monitoring and evaluation of a wide range of surface water sources can be realized quickly and conveniently;
  • the water source migration distribution model of the water source is preset, and the initiative of the water source safety warning is improved, which facilitates the management of the water source and the pre-judgment of the pollution situation.

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Abstract

一种水源地水质监测方法,包括以下步骤:步骤一:确认目标水源地,利用观测卫星的遥感数据,构建水流模型;步骤二:根据水源地的生态***稳定度、生态***损失度和风险源危险度对各项水源地水质要素进行评估;步骤三:根据水流模型基于模糊数学方法对水源地的水质进行整体的安全等级评估;步骤四:根据当地的气象环境和地质条件预设水源地水质迁移分布模型;步骤五:利用水源地水质迁移分布模型建立预警机制和应急机制。通过上述方式,能够保证快速、方便的实现大范围的地表水源地的监测评价,得到的监测结果也具有空间性和动态性的优点,便于水源地的管理和对污染情况的预判。

Description

一种水源地水质监测方法 技术领域
本发明属于水质安全技术领域,特别是涉及一种水源地水质监测方法。
背景技术
随着我国经济社会快速发展、人口持续增长和城镇化率逐步提高,水源地面临的环境压力显著增大,水质总体呈下降趋势,甚至部分水源因水质下降,不得不更换取水口位置,或是关闭水源地。目前,流域水环境的健康发展受到前所有为的挑战。
现有的区域生态监测方法中主要针对城市、流域等而设计的,缺乏面向地表水源集水区生态监测方法的指标体系和相关指数模型;对于流域监测方法中,由于缺乏多时相定量的空间数据支持,很难探明复杂流域下垫面作用过程的复杂性,以致大多数监测指标由于缺乏过程‐机理分析,停留在定性分析上,缺乏可靠性。
发明内容
本发明主要解决的技术问题是提供一种水源地水质监测方法,保证能够快速、方便的实现大范围的地表水源地的监测评价,得到的监测结果也具有空间性和动态性的优点,便于水源地的管理和对污染情况的预判。
为解决上述技术问题,本发明采用的一个技术方案是:提供一种水源地水质监测方法,包括以下步骤:
步骤一:确认目标水源地,利用观测卫星的遥感数据,构建水流模型;
步骤二:根据水源地的生态***稳定度、生态***损失度和风险源危险度对各项水源地水质要素进行评估;
步骤三:根据水流模型基于模糊数学方法对水源地的水质进行整体的安全等级评估;
步骤四:根据当地的气象环境和地质条件预设水源地水质迁移分布模型;
步骤五:利用水源地水质迁移分布模型建立预警机制和应急机制。
进一步地说,所述步骤二中的所述生态***稳定度包括地质土壤要素、地貌植被要素、生态群体结构、生态恢复能力要素和人为因素。
进一步地说,所述步骤二中的所述风险源危险度包括土壤沙化要素、水土流失要素、污染源排放要素、自然灾害要素和干旱缺水要素。
进一步地说,在所述步骤二中的所述生态***损失度包括饮用水损失度要素和水利设施要素。
进一步地说,所述人为因素包括过度垦殖土地要素、过度放牧要素和过度采药要素。
进一步地说,在所述步骤一的利用观测卫星的遥感数据之前,要对观测卫星的遥感数据进行辐射定标、几何纠正和纠正预处理,从而得到地表反射的遥感图像。
进一步地说,所述饮用水损失度要素的检测通过地面统计数据,结合供水能力评价模型,计算水体的可供水量以及需求水量的比例,确认水源地当前的人口的需求量,计算水源地当前的供水能力,评估水源地当前饮用水的安全等级。
本发明的有益效果至少具有以下几点:
一、本发明利用观测卫星的遥感数据,从而进一步优化构建水流模型,保证能够快速、方便的实现大范围的地表水源地的监测评价;
二、本发明根据水源地的生态***稳定度、生态***损失度和风险源危险度对各项水源地水质要素进行评估考虑各指标,可以得到水源的总体安全等级,过程机理明确,结合水质迁移分布模型,得到的监测结果也具有空间性和动态性的优点;
三、本发明根据气象环境和地质条件预设水源地水质迁移分布模型,提高水源地水质安全预警的主动性,便于水源地的管理和对污染情况的预判。
具体实施方式
下面对本发明的较佳实施例进行详细阐述,以使本发明的优点和特征能更易于被本领域技术人员理解,从而对本发明的保护范围做出更为清楚明确 的界定。
实施例:一种水源地水质监测方法,本发明包括以下步骤:
步骤一:确认目标水源地,利用观测卫星的遥感数据,构建水流模型;
步骤二:根据水源地的生态***稳定度、生态***损失度和风险源危险度对各项水源地水质要素进行评估;
步骤三:根据水流模型基于模糊数学方法对水源地的水质进行整体的安全等级评估;
步骤四:根据当地的气象环境和地质条件预设水源地水质迁移分布模型;
步骤五:利用水源地水质迁移分布模型建立预警机制和应急机制。
所述步骤二中的所述生态***稳定度包括地质土壤要素、地貌植被要素、生态群体结构、生态恢复能力要素和人为因素。
所述步骤二中的所述风险源危险度包括土壤沙化要素、水土流失要素、污染源排放要素、自然灾害要素和干旱缺水要素。
在所述步骤二中的所述生态***损失度包括饮用水损失度要素和水利设施要素。
所述人为因素包括过度垦殖土地要素、过度放牧要素和过度采药要素。
在所述步骤一的利用观测卫星的遥感数据之前,要对观测卫星的遥感数据进行辐射定标、几何纠正和纠正预处理,从而得到地表反射的遥感图像。
所述饮用水损失度要素的检测通过地面统计数据,结合供水能力评价模型,计算水体的可供水量以及需求水量的比例,确认水源地当前的人口的需求量,计算水源地当前的供水能力,评估水源地当前饮用水的安全等级。
本发明的工作原理如下:本发明利用观测卫星的遥感数据,从而进一步优化构建水流模型,保证能够快速、方便的实现大范围的地表水源地的监测评价;
根据水源地的生态***稳定度、生态***损失度和风险源危险度对各项水源地水质要素进行评估考虑各指标,可以得到水源的总体安全等级,过程机理明确,结合水质迁移分布模型,得到的监测结果也具有空间性和动态性的优点;
根据气象环境和地质条件预设水源地水质迁移分布模型,提高水源地水质安全预警的主动性,便于水源地的管理和对污染情况的预判。
以上所述仅为本发明的实施例,并非因此限制本发明的专利范围,凡是利用本发明说明书所作的等效结构变换,或直接或间接运用在其他相关的技术领域,均同理包括在本发明的专利保护范围内。

Claims (7)

  1. 一种水源地水质监测方法,其特征在于:包括以下步骤:
    步骤一:确认目标水源地,利用观测卫星的遥感数据,构建水流模型;
    步骤二:根据水源地的生态***稳定度、生态***损失度和风险源危险度对各项水源地水质要素进行评估;
    步骤三:根据水流模型基于模糊数学方法对水源地的水质进行整体的安全等级评估;
    步骤四:根据当地的气象环境和地质条件预设水源地水质迁移分布模型;
    步骤五:利用水源地水质迁移分布模型建立预警机制和应急机制。
  2. 根据权利要求1所述的一种水源地水质监测方法,其特征在于:所述步骤二中的所述生态***稳定度包括地质土壤要素、地貌植被要素、生态群体结构、生态恢复能力要素和人为因素。
  3. 根据权利要求1所述的一种水源地水质监测方法,其特征在于:所述步骤二中的所述风险源危险度包括土壤沙化要素、水土流失要素、污染源排放要素、自然灾害要素和干旱缺水要素。
  4. 根据权利要求1所述的一种水源地水质监测方法,其特征在于:在所述步骤二中的所述生态***损失度包括饮用水损失度要素和水利设施要素。
  5. 根据权利要求2所述的水源地水质监测方法,其特征在于:所述人为因素包括过度垦殖土地要素、过度放牧要素和过度采药要素。
  6. 根据权利要求1所述的一种水源地水质监测方法,其特征在于:在所述步骤一的利用观测卫星的遥感数据之前,要对观测卫星的遥感数据进行辐射定标、几何纠正和纠正预处理,从而得到地表反射的遥感图像。
  7. 根据权利要求4所述的一种水源地水质监测方法,其特征在于:所述饮用水损失度要素的检测通过地面统计数据,结合供水能力评价模型,计算水体的可供水量以及需求水量的比例,确认水源地当前的人口的需求量,计算水源地当前的供水能力,评估水源地当前饮用水的安全等级。
PCT/CN2017/110092 2017-11-09 2017-11-09 一种水源地水质监测方法 WO2019090554A1 (zh)

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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0938631A (ja) * 1995-07-26 1997-02-10 Hitachi Ltd リモートセンシング応用広域水圏監視システム
CN101944160A (zh) * 2010-08-31 2011-01-12 环境保护部华南环境科学研究所 基于层次分析法和综合评价法建立的近岸海域生态环境综合评价方法
CN102253423A (zh) * 2011-03-25 2011-11-23 南京师范大学 基于多源水文地质勘测信息的适宜供水位置智能识别技术
CN102565294A (zh) * 2011-02-01 2012-07-11 环境保护部卫星环境应用中心 水源地监测评价方法
CN104268657A (zh) * 2014-09-30 2015-01-07 北京师范大学 基于遥感的流域水生态风险预警和判别方法
CN104361418A (zh) * 2014-12-05 2015-02-18 北京师范大学 一种流域水生态安全监控预警平台及其预警方法
CN105868533A (zh) * 2016-03-23 2016-08-17 四川理工学院 基于物联网和3s技术江河流域水环境集成感知与应用方法

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012160535A2 (en) * 2011-05-26 2012-11-29 Consiliense Ltd. Recycled water process control

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0938631A (ja) * 1995-07-26 1997-02-10 Hitachi Ltd リモートセンシング応用広域水圏監視システム
CN101944160A (zh) * 2010-08-31 2011-01-12 环境保护部华南环境科学研究所 基于层次分析法和综合评价法建立的近岸海域生态环境综合评价方法
CN102565294A (zh) * 2011-02-01 2012-07-11 环境保护部卫星环境应用中心 水源地监测评价方法
CN102253423A (zh) * 2011-03-25 2011-11-23 南京师范大学 基于多源水文地质勘测信息的适宜供水位置智能识别技术
CN104268657A (zh) * 2014-09-30 2015-01-07 北京师范大学 基于遥感的流域水生态风险预警和判别方法
CN104361418A (zh) * 2014-12-05 2015-02-18 北京师范大学 一种流域水生态安全监控预警平台及其预警方法
CN105868533A (zh) * 2016-03-23 2016-08-17 四川理工学院 基于物联网和3s技术江河流域水环境集成感知与应用方法

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110930042A (zh) * 2019-11-29 2020-03-27 西京学院 基于ds证据理论的海洋水质数据在线分析评价方法
CN113610358A (zh) * 2021-07-16 2021-11-05 南昌工程学院 基于云平台的远程水质风险预警***

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