A regional evaporation coefficient partitioning calculation method

By establishing a multiple linear regression model and weight calculation, combined with reclassification and spatial weighted superposition operations, the accuracy problem of calculating the groundwater evaporation coefficient in large-scale regions was solved, realizing the accurate conversion from relative spatial partitioning to absolute physical values, thus improving the calculation accuracy and reliability of engineering applications.

CN122196329APending Publication Date: 2026-06-12HEFEI UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HEFEI UNIV OF TECH
Filing Date
2026-05-14
Publication Date
2026-06-12

AI Technical Summary

⚠Technical Problem

Existing technologies are insufficient for accurately calculating the evaporation coefficient of groundwater over large-scale areas. They neglect the spatial heterogeneity of factors such as groundwater depth, meteorological conditions, vadose zone lithology, and land use types, resulting in significant discrepancies between the calculated results and the actual situation.

⚗Method used

By collecting measured and spatial data, a multiple linear regression model is established, the weights of each factor are determined, and reclassification and spatial weighted superposition operations are performed. Combined with a family of quadratic curves, a precise transformation from relative spatial partitioning to absolute physical values ​​is achieved.

🎯Benefits of technology

It significantly improves the accuracy and objectivity of calculating the groundwater evaporation coefficient in large-scale regions, overcomes the problem of weighting distortion caused by inconsistent dimensions, and achieves high-precision spatial zoning and reliability in engineering applications.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a regional phreatic evaporation coefficient partition calculation method, which comprises the following steps: collecting measured data and spatial data of a target region to obtain a point-scale phreatic evaporation coefficient; obtaining an interpolation surface, an air gap lithology map and a land use type map according to the spatial data; establishing a multiple linear regression model according to the phreatic evaporation coefficient and the spatial data to determine the weight of each factor; obtaining grid data or a grid map according to the interpolation surface, the air gap lithology map and the land use type map and reclassifying to obtain a dimensionless grade value; performing four-factor grid file spatial weighted superposition operation according to the weight to obtain a phreatic evaporation coefficient partition map; obtaining a quadratic curve family according to the measured data; obtaining a unique phreatic evaporation coefficient value according to the spatial distribution value or the range in the phreatic evaporation coefficient partition map and outputting a regional phreatic evaporation coefficient result map. Through the application, the accuracy and objectivity of large-scale regional phreatic evaporation coefficient calculation can be significantly improved.
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