Freeze-thaw basin nutrient loss comprehensive monitoring method

By combining remote sensing inversion and SWAT modeling, the layout of sampling points and field sample analysis were optimized, solving the resource limitation problem of monitoring nutrient loss in freeze-thaw watersheds and achieving efficient and low-cost scientific monitoring results.

CN120992502APending Publication Date: 2025-11-21BEIJING NORMAL UNIVERSITY +1
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Patent Information

Application Number
CN202510951314.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-10
Publication Date
2025-11-21

AI Technical Summary

Technical Problem

Existing technologies are insufficient for efficiently monitoring nutrient loss in mid-to-high latitude freeze-thaw basins under conditions of limited resources. Traditional methods are difficult to implement routinely in remote areas, and simulation results lack effective observational data support, leading to monitoring results that deviate from reality.

Method used

A comprehensive monitoring method combining remote sensing inversion, model simulation, and field sampling was adopted. Key periods were identified through remote sensing data, sub-basins were divided by combining the SWAT model, sampling point layout was optimized, field samples were collected and laboratory analysis was conducted, and peak pollution periods and key areas were systematically identified.

Benefits of technology

It enables efficient, low-cost, and scientifically reliable monitoring of nutrient loss in freeze-thaw watersheds in resource-limited areas, improving the understanding and management of loss patterns, and is applicable to high-altitude and high-latitude regions.

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Abstract

The invention provides a comprehensive monitoring method for nutrient loss of a freeze-thaw basin, which comprises the following four steps of: 1, analyzing hydrometeorological characteristics of the basin based on remote sensing data, and determining a key period of nutrient loss; 2, dividing a sub-basin and a river network structure by using an SWAT model, and scientifically arranging representative sampling points; thirdly, surface water collection is carried out in combination with the determined sampling scheme, and laboratory analysis is carried out on key indexes such as total nitrogen and total phosphorus; and 4, identifying a key period and a source region of pollutant loss based on the river network convergence relationship and the monitoring data. The method integrates three technologies of remote sensing identification, model simulation and field observation, has the advantages of low cost, high efficiency, high representativeness and strong adaptability, and is especially suitable for data scarce areas such as medium and high latitude freeze thawing areas. The method has a good application prospect in the fields of water environment monitoring and pollution identification.
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