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Updated: Mar 2, 2026

08:20
In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
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为印度开发格式根区土壤水分产品,1981-2024年
Dipesh Singh Chuphal1, Abhishek1, Anuj Prakash Kushwaha2
1Department of Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar, Gandhinagar, India.
Scientific data
|March 1, 2026
概括
通过使用混合模型,为印度 (1981-2024) 创建了一个新的长期土壤湿度数据集. 这些关键数据有助于监测该地区的干旱和农业规划.
科学领域:
- 地球和环境科学 地球和环境科学
- 水文学的水文学
- 遥感 遥感 遥感 遥感
背景情况:
- 准确的土壤湿度数据对于印度的农业和干旱管理至关重要.
- 现有的卫星数据 (SMAP,SMOS) 在记录长度,深度和准确性方面存在局限性.
研究的目的:
- 为印度 (1981-2024) 开发一个高分辨率的长期根区土壤湿度 (RZSM) 数据集.
- 为干旱分析,水文建模和农业风险评估提供强大的资源.
主要方法:
- 一种混合方法,将H08土地表面模型与使用随机森林回归的SMAP RZSM数据相结合.
- 模型校准和预测器培训使用SMAP观测从2016-2024.
- 验证使用交叉验证,现场测量和太阳诱导的叶绿素光.
主要成果:
- 重建的RZSM数据集 (每天0.05°) 与SMAP (R2 > 0.90) 和现场数据 (R2 = 0.94) 强烈一致.
- 与SMAP相比,RMSE<0.03 m3/m3实现了高精度,而在现场数据中,RMSE=0.04 m3/m3.
- 在干旱年内对植被活动进行验证的数据集.
结论:
- 开发的数据集为印度提供了可靠的,长期的RZSM记录.
- 它是了解干旱动态和支持农业决策的宝贵工具.
- 提高印度水文研究和风险管理的能力.
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