Special Issue "Remote Sensing for Water Productivity Assessments in Agriculture, Ecosystems and Water Resources"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 30 April 2021.

Special Issue Editors

Prof. Dr. Antônio Heriberto de Castro Teixeira
Website
Guest Editor
Federal University of Sergipe, Brazil
Interests: remote sensing; agrometeorology; environmental sciences
Dr. Fernando Braz Tangerino Hernandez
Website
Guest Editor
São Paulo University State (UNESP), Brazil
Interests: irrigation and drainage; water resources; remote sensing
Dr. Janice Freitas Leivas

Guest Editor
Brazilian Agricultural Research Company – Embrapa, Brazil
Interests: remote sensing; agrometeorology; environmental sciences
Dr. André Quintão de Almeida

Guest Editor
Agricultural Engineering Department from Federal University of Sergipe (UFS), Brazil
Interests: remote sensing; LiDAR; DAP; AGB; forest inventory
Dr. Edson Patto Pacheco
Website
Guest Editor
Brazilian Agricultural Research Company – Embrapa, Brazil
Interests: Precision Agriculture; Crop management; Remote Sensing

Special Issue Information

Dear Colleagues,

The difficulties of large-scale energy and water balance measurements by punctual measurements have prompted the use of geotechnologies to evaluate these components in mixed agroecosystems.

This Special Issue highlights the use of remote sensing at different spatial and temporal resolutions, together with agrometeorological data for water productivity assessments involving the use of water resources in natural vegetation and irrigated/rainfed agriculture inside hydrological basins with land-use changes.

Regarding irrigated agriculture, research should involve results for rational irrigation managements, while for rainfed agriculture, enphasis should be given to maximizing yield through the use of the rainfall water, both approaching the state-of-the-art as well as the operationalization of algorithms.

Reaserch may involve methods for acquirements of evapotranspiration, biomass production and water productivity, as well as other agrometeorological indicators, aiming to produce food, profits, rural development, and ecological benefits, with low social and environmental costs per unit of water applied and/or consumed.

The advances of large-scale modeling, uncertainties, calibrations, and algorithm validations may be included and discussed, aiming at improvements of energy and water balance computations under diferrent climate and land-use scenarios.

Prof. Antônio Heriberto de Castro Teixeira
Dr. Fernando Braz Tangerino Hernandez
Dr. Janice Freitas Leivas
Dr. André Quintão de Almeida
Dr. Edson Patto Pacheco
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Energy balance
  • Water balance
  • Evapotranspiration
  • Biomass production
  • Agrometeorological indicators
  • Water management

Published Papers (1 paper)

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Research

Open AccessArticle
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data
Remote Sens. 2020, 12(18), 2949; https://doi.org/10.3390/rs12182949 - 11 Sep 2020
Abstract
This paper analyses the effect of the spatial assessment scale on irrigation performance indicators in small and medium-scale agriculture. Three performance indicators—adequacy (i.e., sufficiency of water use to meet the crop water requirement), equity (i.e., fairness of irrigation distribution), and productivity (i.e., unit [...] Read more.
This paper analyses the effect of the spatial assessment scale on irrigation performance indicators in small and medium-scale agriculture. Three performance indicators—adequacy (i.e., sufficiency of water use to meet the crop water requirement), equity (i.e., fairness of irrigation distribution), and productivity (i.e., unit of physical crop production/yield per unit water consumption)—are evaluated in five irrigation schemes for three spatial resolutions—250 m, 100 m, and 30 m. Each scheme has varying plot sizes and distributions, with average plot sizes ranging from 0.2 ha to 13 ha. The datasets are derived from the United Nations Food and Agricultural Organization (FAO) water productivity through open access of remotely sensed–derived data (the Water Productivity Open Access Portal—WaPOR) database. Irrigation indicators performed differently in different aspects; for adequacy, all three resolutions show similar spatial trends for relative evapotranspiration (ET) across levels for all years. However, the estimation of relative ET is often higher at higher resolution. In terms of equity, all resolutions show similar inter-annual trends in the coefficient of variation (CV); higher resolutions usually have a higher CV of the annual evapotranspiration and interception (ETIa) while capturing more spatial variability. For productivity, higher resolutions show lower crop water productivity (CWP) due to higher aboveground biomass productivity (AGBP) estimations in lower resolutions; they always have a higher CV of CWP. We find all resolutions of 250 m, 100 m, and 30 m suitable for inter-annual and inter-scheme assessments regardless of plot size. While each resolution shows consistent temporal trends, the magnitude of the trend in both space and time is smoothed by the 100 m and 250 m resolution datasets. This frequently results in substantial differences in the irrigation performance assessment criteria for inter-plot comparisons; therefore, 250 m and 100 m are not recommended for inter-plot comparison for all plot sizes, particularly small plots (<2 ha). Our findings highlight the importance of selecting the spatial resolution appropriate to scheme characteristics when undertaking irrigation performance assessment using remote sensing. Full article
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