Water use and soil water balance of Mediterranean tree crops assessed with the SIMDualKc model in orchards of southern Portugal

Ramos, Tiago B.; Darouich, Hanaa; Oliveira, Ana R.; Farzamian, Mohammad; Monteiro, Tomás; Castanheira, Nádia; Paz, Ana Marta; Gonçalves, M. C.; Pereira, L. S.

doi:10.1016/j.agwat.2023.108209

Cited by 18 publications

(12 citation statements)

References 91 publications

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“…This observation underscores the method's limitations in simulating soil resistance and vine stomatal conductance under more stressful conditions, as investigated in this study. The observed limitations of the FAO-56 Kc-ET0 method in accurately estimating ETc act in vineyards are consistent with previous literature, including studies by [15,16,19,22,36,37].…”

Section: Evaluation Of Fao-56 Kc-et 0 Methods To Estimate Actual Crop...supporting

confidence: 90%

Predicting Crop Evapotranspiration under Non-Standard Conditions Using Machine Learning Algorithms, a Case Study for Vitis vinifera L. cv Tempranillo

Egipto,

Aquino,

Costa

et al. 2023

Agronomy

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This study focuses on assessing the accuracy of supervised machine learning regression algorithms (MLAs) in predicting actual crop evapotranspiration (ETc act) for a deficit irrigated vineyard of Vitis vinifera cv. Tempranillo, influenced by a typical Mediterranean climate. The standard approach of using the Food and Agriculture Organization (FAO) crop evapotranspiration under standard conditions (FAO-56 Kc-ET0) to estimate ETc act for irrigation purposes faces limitations in row-based, sparse, and drip irrigated crops with large, exposed soil areas, due to data requirements and potential shortcomings. One significant challenge is the accurate estimation of the basal crop coefficient (Kcb), which can be influenced by incorrect estimations of the effective transpiring leaf area and surface resistance. The research results demonstrate that the tested MLAs can accurately estimate ETc act for the vineyard with minimal errors. The Root-Mean-Square Error (RMSE) values were found to be in the range of 0.019 to 0.030 mm·h⁻¹. Additionally, the obtained MLAs reduced data requirements, which suggests their feasibility to be used to optimize sustainable irrigation management in vineyards and other row crops. The positive outcomes of the study highlight the potential advantages of employing MLAs for precise and efficient estimation of crop evapotranspiration, leading to improved water management practices in vineyards. This could promote the adoption of more sustainable and resource-efficient irrigation strategies, particularly in regions with Mediterranean climates.

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Section: Evaluation Of Fao-56 Kc-et 0 Methods To Estimate Actual Crop...supporting

confidence: 90%

Predicting Crop Evapotranspiration under Non-Standard Conditions Using Machine Learning Algorithms, a Case Study for Vitis vinifera L. cv Tempranillo

Egipto,

Aquino,

Costa

et al. 2023

Agronomy

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“…Therefore, the values shown in Figure 4 represent a minimum threshold of possible savings because substantially higher values would be obtained if the target of the full irrigation schedule was to maintain soil moisture closer to the soil field capacity. Estimated gross (and net) crop irrigation requirements (CIRs) found a general correspondence with values in the literature, particularly when deficit-irrigation strategies were considered [58,68,69]. In all groups, the CIR increased with plant density and atmospheric demand.…”

Section: Gross Irrigation Water Savingssupporting

confidence: 57%

“…The K cb estimates for low-density orchards agreed with those for orange in Vilallobos et al [56], for which an f c of 0.42 corresponded to K cb mid = 0.58; and with El-Raki et al [57], for which an f c of 0.30 corresponded to K cb mid = 0.50. They were higher than those for orange, clementine, and mandarin in Ramos et al [58] because of the lower tree height in these orchards with 5-6-year-old trees. Inversely, they were lower than those for clementine in Ballester et al [59], for which an f c of 0.38 resulted in a K cb mid = 0.65.…”

Section: Crop Coefficients For Citrus Orchardsmentioning

confidence: 52%

Setting Irrigation Thresholds for Building a Platform Aimed at the Improved Management of Citrus Orchards in Coastal Syria

et al. 2023

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Citrus is one of the most valuable crops in Syria, with the largest production areas being in the coastal provinces of Tartus and Latakia, where this study was performed. A companion paper reported on the basal crop coefficients derived from the field water balance and on the performance assessment of various irrigation methods used in a citrus orchard located in the same region. That study evidenced the need for the improved management of irrigation water, mainly reducing water applications and increasing productivity, thus leading to the current research. The main objectives consisted of (i) providing a set of reliable basal (Kcb) and average (Kc) crop coefficients to be used in practice in the citrus orchards of the Syrian coastal area, while accounting for the diversity of characteristics observed; (ii) to estimate the seasonal consumptive use of typical orchards under different climate-demand and deficit-irrigation scenarios; and (iii) to assess possible water savings and related yield reductions. The previously calibrated water balance model SIMDualKc was used for these purposes. The computed Kcb values for the mid-season and average demand for water ranged from 0.52, when the plant density was low, to 0.84, when plant density was very high. The corresponding Kc values, which further reflected the impact of drip irrigation on controlling soil evaporation, were 0.72 and 0.97, respectively. Overall, the consumptive use of water was estimated to range from 867 to 1573 mm. The assessed water-saving scenarios consisted of adopting increased management-allowed depletion (MAD) thresholds relative to the p depletion fraction for no stress: MAD = 1.05, 1.10, 1.20, and 1.30 p. For trees under a very high climatic demand, water savings ranged from 12 to 34%, but the yield losses induced by the water deficits ranged from 8 to 48%. Although the selection of optimal strategies should be based upon economic terms, these may only be used when the Syrian economy recovers from civil war and the current crisis. The present results show the feasibility of adopting such MAD thresholds for building an irrigation management platform. The data provided by the current study are valuable because they can be efficiently used to support of the irrigation management of Syrian citrus production systems.

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“…Orchards represent one of the emblematic crops of the Mediterranean region. They have high water requirements increasing significantly due to climatic changes (Ramos et al, 2023). The water consumption of orchards depends on various factors, among them, soil and climate, and temporal variations of leaf development and farming practices (Ahumada-Orellana et al, 2019;Dian et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

“…A lot of bibliography has explored RS acquired at very high resolutions from drones (UAV) to detect pruning for example (Johansen et al, 2018) or count trees (Dong et al, 2020), or information on orchard structure from Quickbird satellites (Panda et al, 2010) and LIDAR (Dian et al, 2023). Various models have been developed to assess evapotranspiration of orchards (Elfarkh et al, 2023;Nieto et al, 2019;Ramos et al, 2023). Some of them such as Qualitree model (Miras-Avalos et al, 2013) can take into account a lot of processes and can simulate the fruit quality.…”

Section: Introductionmentioning

confidence: 99%

Grass Cover, Tree Density, and Leaf Development of Mediterranean Orchards From High Resolution Data

Rouault,

Courault,

Pouget

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The study focused on Mediterranean orchards and aimed to explore different remote sensing data (Sentinel 2 data (2016–2023), 1 Pleiades image (2022) and the extraction of Google-satellite-hybrid images (GSH,2017)) to compute key variables affecting water requirements such as tree age and density per plot, leaf development, the inter-row management. Surveys were conducted on 22 farms where accurate information on agricultural practices was collected. The results have shown that a thresholding on the NDVI Sentinel 2 in the summer period allowed the identification of young orchards with an accuracy of 98%. The analysis of temporal profiles of FAPAR allowed the identification of key phenological stages such as flowering and fruit set. Supervised classification was employed to separate grassed and non-grassed plots using three spectral bands of Sentinel 2. Classifications performed from GSH images gave more accurate results (81% well classified) compared with Sentinel 2 (79%) and Pleiades (57%) when identifying grassed plots. The methods presented in this study propose methods easily accessible based on free-to-download data, making them applicable in diverse orchard contexts.

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Water use and soil water balance of Mediterranean tree crops assessed with the SIMDualKc model in orchards of southern Portugal

Cited by 18 publications

References 91 publications

Predicting Crop Evapotranspiration under Non-Standard Conditions Using Machine Learning Algorithms, a Case Study for Vitis vinifera L. cv Tempranillo

Predicting Crop Evapotranspiration under Non-Standard Conditions Using Machine Learning Algorithms, a Case Study for Vitis vinifera L. cv Tempranillo

Setting Irrigation Thresholds for Building a Platform Aimed at the Improved Management of Citrus Orchards in Coastal Syria

Grass Cover, Tree Density, and Leaf Development of Mediterranean Orchards From High Resolution Data

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