Crop water use dynamics over arid and semi-arid croplands in the lower Colorado River Basin

IF 3.7 4区 地球科学 Q2 REMOTE SENSING European Journal of Remote Sensing Pub Date : 2023-09-25 DOI:10.1080/22797254.2023.2259244
Neda Abbasi, Hamideh Nouri, Pamela Nagler, Kamel Didan, Sattar Chavoshi Borujeni, Armando Barreto-Muñoz, Christian Opp, Stefan Siebert
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Abstract

Numerous studies have evaluated the application of Remote Sensing (RS) techniques for mapping actual evapotranspiration (ETa) using Vegetation-Index-based (VI-based) and surface energy balance methods (SEB). SEB models computationally require a large effort for application. VI-based methods are fast and easy to apply and could therefore potentially be applied at high resolution; however, the accuracy of VI-based methods in comparison to SEB-based models remains unclear. We tested the ETa computed with the modified 2-band Enhanced Vegetation Index (METEVI2) implemented in the Google Earth Engine – for mapping croplands’ water use dynamics in the Lower Colorado River Basin. We compared METEVI2 with the well-established RS-based products of OpenET (Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI and geeSEBAL). METEVI2 was then evaluated with measured ETa from four wheat fields (2017–2018). Results indicated that the monthly ETa variations for METEVI2 and OpenET models were comparable, though of varying magnitudes. On average, METEVI2 had the lowest difference rate from the average observed ETa with 17 mm underestimation, while SIMS had the highest difference rate (82 mm). Findings show that METEVI2 is a cost-effective ETa mapping tool in drylands to track crop water use. Future studies should test METEVI2’s applicability to croplands in more humid regions.
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科罗拉多河下游干旱和半干旱农田的作物水分利用动态
许多研究评估了遥感(RS)技术在利用基于植被指数(VI-based)和地表能量平衡方法(SEB)绘制实际蒸散发(ETa)的应用。SEB模型的应用需要大量的计算工作量。基于vi的方法快速且易于应用,因此可能应用于高分辨率;然而,与基于seb的模型相比,基于vi的方法的准确性尚不清楚。我们用谷歌地球引擎中改进的2波段增强植被指数(METEVI2)来测试ETa计算结果,该指数用于绘制科罗拉多河下游流域农田的水利用动态。我们将METEVI2与基于rs的OpenET产品(Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI和geeSEBAL)进行了比较。然后用四个麦田(2017-2018)的测量ETa对METEVI2进行评估。结果表明,METEVI2和OpenET模式的月ETa变化具有可比性,尽管幅度不同。平均而言,METEVI2与平均观测ETa的差值率最低,低估了17毫米,而SIMS的差值率最高(82毫米)。研究结果表明,METEVI2是一种具有成本效益的旱地ETa绘图工具,用于跟踪作物用水情况。未来的研究应该测试METEVI2在更潮湿地区的农田的适用性。
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来源期刊
CiteScore
7.00
自引率
2.50%
发文量
51
审稿时长
>12 weeks
期刊介绍: European Journal of Remote Sensing publishes research papers and review articles related to the use of remote sensing technologies. The Journal welcomes submissions on all applications related to the use of active or passive remote sensing to terrestrial, oceanic, and atmospheric environments. The most common thematic areas covered by the Journal include: -land use/land cover -geology, earth and geoscience -agriculture and forestry -geography and landscape -ecology and environmental science -support to land management -hydrology and water resources -atmosphere and meteorology -oceanography -new sensor systems, missions and software/algorithms -pre processing/calibration -classifications -time series/change analysis -data integration/merging/fusion -image processing and analysis -modelling European Journal of Remote Sensing is a fully open access journal. This means all submitted articles will, if accepted, be available for anyone to read anywhere, at any time, immediately on publication. There are no charges for submission to this journal.
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