农业机械学报2025，Vol.56Issue(8)：62-73,12.DOI:10.6041/j.issn.1000-1298.2025.08.006
基于数据融合的高时空分辨率作物蒸散发反演与高效精细化灌溉决策
Data Fusion-based High Spatiotemporal Resolution Retrieval of Crop Evapotranspiration and Efficient Refined Irrigation Decision-making for Irrigation Areas
摘要
Abstract
Efficient water resources utilization and precision irrigation management are critical for improving agricultural productivity.Evapotranspiration(ET)estimation,a pivotal parameter in irrigation water management,has traditionally been limited by low spatiotemporal resolution,thereby constraining the implementation of precise irrigation practices.A framework combining remote sensing,data fusion,and multi-objective optimization for high-resolution evapotranspiration(ET)estimation and irrigation management was presented.The framework used a spatiotemporal fusion model to generate accurate surface variables(NDVI,Albedo,land surface temperature),enabling daily field-scale(30 m × 30 m)ET estimation.It also integrated the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)to optimize irrigation strategies for different districts.Results showed that the framework effectively addressed spatiotemporal variability,providing precise irrigation to meet crop water needs.Optimized irrigation reduced water use by 57 mm during non-critical growth stages,increased crop yield by 423.23 kg/hm2,achieving both water savings and yield enhancement.Analysis with the temperature vegetation drought index(TVDI)revealed spatial differences:in humid zones(0＜TVDI＜0.1),optimized strategies reduced irrigation by 83.17 mm,maintaining high yields(greater than 9 500 kg/hm2)while minimizing water waste.In arid zones(TVDI＞0.4),where insufficient irrigation reduced yields(7 500～8 500 kg/hm2),increased irrigation by 37.15 mm,boosted yields by 2 171.88 kg/hm2,alleviating drought risks.Overall,the framework improved agricultural water management,increased regional yield by 4.6％,enhanced irrigation efficiency by 14％,and reduced irrigation volume by 11％.This decision-making framework at a 30 m grid scale offered valuable insights for sustainable precision agriculture.关键词
蒸散发/遥感/数据融合/干旱监测/灌溉制度优化Key words
evapotranspiration/remote sensing/data fusion/drought monitoring/irrigation scheduling optimization分类
农业科技引用本文复制引用
李茉,徐敏,王璐晨,王一甲,董文浩..基于数据融合的高时空分辨率作物蒸散发反演与高效精细化灌溉决策[J].农业机械学报,2025,56(8):62-73,12.基金项目
国家重点研发计划项目(2024YFD1502000)、国家自然科学基金项目(52479035)、中国地质调查局黑河流域水循环野外站联合开放基金项目(WCSHR-2024-04)和黑龙江省重点研发计划项目(GA23B012) （2024YFD1502000）
