Integrating forecast meteorological data into the ArcDualKc model for estimating spatially distributed evapotranspiration rates of a citrus orchard

Longo-Minnolo, Giuseppe; Vanella, Daniela; Consoli, Simona; Intrigliolo, Diego S.; Ramírez-Cuesta, Juan Miguel

doi:10.1016/j.agwat.2019.105967

Cited by 20 publications

(11 citation statements)

References 40 publications

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“…Since direct accounting of irrigation water use is often not feasible, procedures based on crop-water-balance modeling have been proposed for a quantitative assessment of irrigation water use at regional scale [8][9][10][11][12][13][14]. In Mediterranean regions, where rainfall and groundwater capillary rise are negligible in the irrigation season (generally from April to September), evapotranspiration is the key variable of the crop water budget.…”

Section: Introductionmentioning

confidence: 99%

Comparison of ERA5-Land and UERRA MESCAN-SURFEX Reanalysis Data with Spatially Interpolated Weather Observations for the Regional Assessment of Reference Evapotranspiration

Pelosi

Terribile

D’Urso

et al. 2020

Water

121

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Reanalysis data are being increasingly used as gridded weather data sources for assessing crop-reference evapotranspiration (ET0) in irrigation water-budget analyses at regional scales. This study assesses the performances of ET0 estimates based on weather data, respectively produced by two high-resolution reanalysis datasets: UERRA MESCAN-SURFEX (UMS) and ERA5-Land (E5L). The study is conducted in Campania Region (Southern Italy), with reference to the irrigation seasons (April–September) of years 2008–2018. Temperature, wind speed, vapor pressure deficit, solar radiation and ET0 derived from reanalysis datasets, were compared with the corresponding estimates obtained by spatially interpolating data observed by a network of 18 automatic weather stations (AWSs). Statistical performances of the spatial interpolations were evaluated with a cross-validation procedure, by recursively applying universal kriging or ordinary kriging to the observed weather data. ERA5-Land outperformed UMS both in weather data and ET0 estimates. Averaging over all 18 AWSs sites in the region, the normalized BIAS (nBIAS) was found less than 5% for all the databases. The normalized RMSE (nRMSE) for ET0 computed with E5L data was 17%, while it was 22% with UMS data. Both performances were not far from those obtained by kriging interpolation, which presented an average nRMSE of 14%. Overall, this study confirms that reanalysis can successfully surrogate the unavailability of observed weather data for the regional assessment of ET0.

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Section: Introductionmentioning

confidence: 99%

Comparison of ERA5-Land and UERRA MESCAN-SURFEX Reanalysis Data with Spatially Interpolated Weather Observations for the Regional Assessment of Reference Evapotranspiration

Pelosi

Terribile

D’Urso

et al. 2020

Water

121

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“…The time-series of NDVI at the different CSs (Figures 5 and 6) have shown a typical annual pattern deriving from the sum of two contributions: (i) the fairly stable vegetation dynamic of citrus trees and (ii) the presence of typical conditions of grassed soil [64][65][66][67]. It can be assumed, given that the ground cover plays a role of constant "background" every year, that the dynamics of the seasonal NDVI parameters are mainly linked to the presence of citrus groves.…”

Section: Discussionmentioning

confidence: 99%

Suitability of the MODIS-NDVI Time-Series for a Posteriori Evaluation of the Citrus Tristeza Virus Epidemic

et al. 2020

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The technological advances of remote sensing (RS) have allowed its use in a number of fields of application including plant disease depiction. In this study, an RS approach based on an 18-year (i.e., 2001–2018) time-series analysis of Normalized Difference Vegetation Index (NDVI) data, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and processed with TIMESAT free software, was applied in Sicily (insular Italy). The RS approach was carried out in four orchards infected by Citrus tristeza virus (CTV) at different temporal stages and characterized by heterogeneous conditions (e.g., elevation, location, plant age). The temporal analysis allowed the identification of specific metrics of the NDVI time-series at the selected sites during the study period. The most reliable parameter which was able to identify the temporal evolution of CTV syndrome and the impact of operational management practices was the “Base value” (i.e., average NDVI during the growing seasons, which reached R2 values up to 0.88), showing good relationships with “Peak value”, “Small integrated value” and “Amplitude”, with R2 values of 0.63, 0.70 and 0.75, respectively. The approach herein developed is valid to be transferred to regional agencies involved in and/or in charge of the management of plant diseases, especially if it is integrated with ground-based early detection methods or high-resolution RS approaches, in the case of quarantine plant pathogens requiring control measures at large-scale level.

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“…ArcDualK c is an FAO-56K c based approach implemented in the Geographical Information System (GIS) which facilitates Sentinel-2 in the spatial mapping of ET [128]. Considering the precision and needlessness of ground measurands, the forecasted data began to replace measured meteorological data [129] and was incorporated with Sentinel-2 VI for computing the ET [130]. Irrespective of its quality and predictability, the forecasted data are subjected to model errors.…”

Section: Remote Sensing Of Evapotranspiration In Droughtmentioning

confidence: 99%

Reviewing the Potential of Sentinel-2 in Assessing the Drought

et al. 2021

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This paper systematically reviews the potential of the Sentinel-2 (A and B) in assessing drought. Research findings, including the IPCC reports, highlighted the increasing trend in drought over the decades and the need for a better understanding and assessment of this phenomenon. Continuous monitoring of the Earth’s surface is an efficient method for predicting and identifying the early warnings of drought, which enables us to prepare and plan the mitigation procedures. Considering the spatial, temporal, and spectral characteristics, the freely available Sentinel-2 data products are a promising option in this area of research, compared to Landsat and MODIS. This paper evaluates the recent developments in this field induced by the launch of Sentinel-2, as well as the comparison with other existing data products. The objective of this paper is to evaluate the potential of Sentinel-2 in assessing drought through vegetation characteristics, soil moisture, evapotranspiration, surface water including wetland, and land use and land cover analysis. Furthermore, this review also addresses and compares various data fusion methods and downscaling methods applied to Sentinel-2 for retrieving the major bio-geophysical variables used in the analysis of drought. Additionally, the limitations of Sentinel-2 in its direct applicability to drought studies are also evaluated.

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Integrating forecast meteorological data into the ArcDualKc model for estimating spatially distributed evapotranspiration rates of a citrus orchard

Cited by 20 publications

References 40 publications

Comparison of ERA5-Land and UERRA MESCAN-SURFEX Reanalysis Data with Spatially Interpolated Weather Observations for the Regional Assessment of Reference Evapotranspiration

Comparison of ERA5-Land and UERRA MESCAN-SURFEX Reanalysis Data with Spatially Interpolated Weather Observations for the Regional Assessment of Reference Evapotranspiration

Suitability of the MODIS-NDVI Time-Series for a Posteriori Evaluation of the Citrus Tristeza Virus Epidemic

Reviewing the Potential of Sentinel-2 in Assessing the Drought

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