用于验证高分辨率卫星产品和监测农田灌溉的土壤水分实验

IF 5.9 1区农林科学 Q1 AGRONOMY

Agricultural Water Management Pub Date : 2024-09-25 DOI:10.1016/j.agwat.2024.109071

Weizhen Wang , Chunfeng Ma , Xufeng Wang , Jiaojiao Feng , Leilei Dong , Jian Kang , Rui Jin , Xingze Li

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引用次数: 0

摘要

卫星土壤水分产品的验证一直是一个活跃的研究课题，以促进产品的应用和检索算法的改进，吸引了广泛的关注。然而，现有的验证活动很少关注高分辨率土壤水分产品在精细尺度上的验证。为此，2021 年 8 月至 10 月，在中国西北部黑河流域中游开展了一项旨在验证高分辨率卫星遥感土壤水分产品的试验。本文介绍了试验的设计、合成和初步结果。通过两种传感器（CS616 和 Stevens Hydra Probe）建立了土壤水分观测网络，并与土壤岩心测量结果进行了验证。进行了几次同步活动，收集的数据用于验证 SMAP/Sentinel-1 L2 辐射计/雷达 30 秒场景 3 和 1 公里 EASE-Grid 土壤水分（SPL2SMAP_S）产品。此外，还应用光学梯形模型（OPTRAM）和收集的哨兵-2 数据估算土壤湿度和绘制灌溉面积图。初步分析表明1) Steven 探测器表现最佳，均方根误差为 0.040 m3m-3，超均方根误差为 0.034 m3m-3；2) SPL2SMAP_S 产品在 3 千米和 1 千米处均显示出较大的均方根误差（3 千米为 0.128 m3m-3，1 千米为 0.158 m3m-3）和超均方根误差（3 千米为 0.115 m3m-3，1 千米为 0.158 m3m-3）。3) OPTRAM 在裸露地表的探测结果呈现相对较小的均方根误差（0.06 m3m-3）和超均方根误差（0.057 m3m-3），而在植被覆盖的耕地上的探测结果呈现相对较大的均方根误差/超均方根误差（0.083/0.083 m3m-3），且这些探测结果可在实地尺度上识别灌溉面积。总之，该试验为高分辨率遥感产品的验证提供了富有成效的方法和数据集，有利于土壤水分检索算法和产品的开发和改进，为未来精准农业规模的灌溉调度和管理提供支持。

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A soil moisture experiment for validating high-resolution satellite products and monitoring irrigation at agricultural field scale

Validating the satellite soil moisture products is always an active research topic for the application of the products and improvement of the retrieval algorithms, attracting extensive attention. Nevertheless, seldom existing validation activities focus on the validation of high-resolution soil moisture products at the fine scale. To this end, an experiment was conducted in the middle stream of the Heihe River Basin in northwestern China in August to October of 2021, aiming to validate high-resolution satellite remote sensing products of soil moisture. The paper introduces the design, composite, and preliminary results of the experiment. A soil moisture observation network was established with two kinds of sensors (CS616 and Stevens Hydra Probe) validated against soil core measurements. Several synchronized campaigns were performed, and data were collected to validate the SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 and 1 km EASE-Grid Soil Moisture (SPL2SMAP_S) products. Besides, an optical trapezoid model (OPTRAM) and collected Sentinel-2 data were applied to estimate soil moisture and to map irrigated area. Preliminary analyses show that: 1) Steven probes perform best, with an RMSE = 0.040 m³m⁻³ and ubRMSE = 0.034 m³m⁻³; 2) Both the SPL2SMAP_S products at 3 km and 1 km show large RMSE (0.128 m³m⁻³ for 3 km and 0.158 m³m⁻³ for 1 km) and ubRMSE (0.115 m³m⁻³ for 3 km and 0.158 m³m⁻³ for 1 km); 3) The OPTRAM retrievals over bare surface present relatively smaller RMSE (0.06 m³m⁻³) and ubRMSE (0.057 m³m⁻³), while retrievals over vegetated croplands present a relatively large RMSE/ubRMSE (0.083/0.083 m³m⁻³), and the retrievals can identify the irrigated area at field scale. Overall, the experiment provides fruitful methodologies and datasets for the validation of high-resolution remote sensing products, benefiting the development and improvement of soil moisture retrieval algorithms and products to support irrigation scheduling and management at a precision agricultural scale in the future.

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来源期刊

Agricultural Water Management 农林科学-农艺学

CiteScore

12.10

自引率

14.90%

发文量

648

审稿时长

4.9 months

期刊介绍： Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.