Remote sensing-based evapotranspiration and soil water balance estimation for a tropical pasture in Brazil using the SETMI model

IF 3 3区 地球科学 Q2 BIOPHYSICS
Vitor de J. M. Bianchini, Ivo Z. Gonçalves, Christopher M. U. Neale, Alex da S. Sechi, Thieres G. F. da Silva, Fábio R. Marin
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Abstract

Developing strategies to improve pasture yield and mitigate environmental impacts is crucial in Southeastern Brazil, where livestock farming faces competition for areas with profitable crops. Accurate evapotranspiration (ET) estimation is an essential component of managing soil water balance and evaluating pasture response to drought and water productivity. The objectives of this study were to: (1) develop a relationship between the basal crop coefficient (Kcb) derived from observed ET, and the soil-adjusted vegetation index (SAVI) from PlanetScope images; (2) integrate the Kcb-SAVI relationship into remote sensing-based soil water balance (RSWB) to generate daily Kcb and then simulate the actual evapotranspiration (ETa) of an intensively grazed tropical pasture in the state of São Paulo, Brazil; and (3) use the spatialized estimate of ETa to assess the crop water productivity (\({\text{W}\text{P}}_{{\text{E}\text{T}}_{\text{a} \text{m}\text{o}\text{d}}}\)). The Kcb-SAVI relationship developed in this study showed a strong positive correlation between SAVI and Kcb, with Pearson correlation coefficient (\(\rho\)) and \({\text{R}}^{2}\) values of 0.89 and 0.79, respectively. Comparisons between observed and simulated ETa indicated good agreement for daily values (\(\text{R}\text{M}\text{S}\text{E}\) of 0.59 mm d−1, Willmott index of agreement (\(\text{D}\)) of 0.86) and for average weekly values (\(\text{R}\text{M}\text{S}\text{E}\) of 0.38 mm d−1, \(\text{D}\) of 0.93). Biases of -5% and 3% were obtained for modelled cumulative ETa in the years 2021–2022 and 2022–2023, respectively. The average \({\text{W}\text{P}}_{{\text{E}\text{T}}_{\text{a} \text{m}\text{o}\text{d}}}\) values were similar for both years, 2.2 kg m−3 in 2021–2022 and 1.8 kg m−3 in 2022–2023. These findings demonstrate the potential of RSWB, ETa, and WP assessments to enhance decision-making, monitoring, and management of water resources in pasture-based livestock farming.

基于SETMI模型的巴西热带牧场蒸散发和土壤水分平衡遥感估算
在巴西东南部,制定提高牧草产量和减轻环境影响的战略至关重要,因为那里的畜牧业面临着对有利可图作物地区的竞争。准确的蒸散发估算是管理土壤水分平衡和评估牧草对干旱和水分生产力的响应的重要组成部分。本研究的目的是:(1)建立基于ET观测的基础作物系数(Kcb)与基于PlanetScope影像的土壤调整植被指数(SAVI)之间的关系;(2)将Kcb- savi关系整合到基于遥感的土壤水分平衡(RSWB)中,生成日均Kcb,并模拟巴西圣保罗州集约放牧热带牧场的实际蒸散量(ETa);(3)利用ETa的空间化估算来评价作物水分生产力([公式:见文])。本研究建立的Kcb-SAVI关系显示,SAVI与Kcb呈正相关,Pearson相关系数(ρ)和[公式:见文]分别为0.89和0.79。观测值和模拟值之间的比较表明,日值([公式:见文]为0.59 mm d-1, Willmott一致指数([公式:见文])为0.86)和周平均值([公式:见文]为0.38 mm d-1,[公式:见文]为0.93)吻合良好。2021-2022年和2022-2023年的累积ETa模型偏差分别为-5%和3%。这两年的平均值[公式:见文本]相似,2021-2022年为2.2 kg m-3, 2022-2023年为1.8 kg m-3。这些发现证明了RSWB、ETa和WP评估在加强放牧畜牧业水资源决策、监测和管理方面的潜力。
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来源期刊
CiteScore
6.40
自引率
9.40%
发文量
183
审稿时长
1 months
期刊介绍: The Journal publishes original research papers, review articles and short communications on studies examining the interactions between living organisms and factors of the natural and artificial atmospheric environment. Living organisms extend from single cell organisms, to plants and animals, including humans. The atmospheric environment includes climate and weather, electromagnetic radiation, and chemical and biological pollutants. The journal embraces basic and applied research and practical aspects such as living conditions, agriculture, forestry, and health. The journal is published for the International Society of Biometeorology, and most membership categories include a subscription to the Journal.
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