Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data
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), an...
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doaj-7e127c58806545b9817cfc45e679688b2020-11-25T02:54:22ZengMDPI AGRemote Sensing2072-42922020-09-01122949294910.3390/rs12182949Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR DataMegan Blatchford0Chris M. Mannaerts1Yijian Zeng2Hamideh Nouri3Poolad Karimi4Department of Water Resources, Faculty of Geo-Information Sciences & Earth Observation, University of Twente, Hengelosestraat 99, 7500 AE Enschede, The NetherlandsDepartment of Water Resources, Faculty of Geo-Information Sciences & Earth Observation, University of Twente, Hengelosestraat 99, 7500 AE Enschede, The NetherlandsDepartment of Water Resources, Faculty of Geo-Information Sciences & Earth Observation, University of Twente, Hengelosestraat 99, 7500 AE Enschede, The NetherlandsDivision of Agronomy, University of Göttingen, 37075 Göttingen, GermanyIHE Institute for Water Education, Westvest 7, 2611 AX Delft, The NetherlandsThis 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.https://www.mdpi.com/2072-4292/12/18/2949irrigation performance indicatorsequityadequacycrop water productivityspatio-temporal scale |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Megan Blatchford Chris M. Mannaerts Yijian Zeng Hamideh Nouri Poolad Karimi |
spellingShingle |
Megan Blatchford Chris M. Mannaerts Yijian Zeng Hamideh Nouri Poolad Karimi Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data Remote Sensing irrigation performance indicators equity adequacy crop water productivity spatio-temporal scale |
author_facet |
Megan Blatchford Chris M. Mannaerts Yijian Zeng Hamideh Nouri Poolad Karimi |
author_sort |
Megan Blatchford |
title |
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data |
title_short |
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data |
title_full |
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data |
title_fullStr |
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data |
title_full_unstemmed |
Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data |
title_sort |
influence of spatial resolution on remote sensing-based irrigation performance assessment using wapor data |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-09-01 |
description |
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. |
topic |
irrigation performance indicators equity adequacy crop water productivity spatio-temporal scale |
url |
https://www.mdpi.com/2072-4292/12/18/2949 |
work_keys_str_mv |
AT meganblatchford influenceofspatialresolutiononremotesensingbasedirrigationperformanceassessmentusingwapordata AT chrismmannaerts influenceofspatialresolutiononremotesensingbasedirrigationperformanceassessmentusingwapordata AT yijianzeng influenceofspatialresolutiononremotesensingbasedirrigationperformanceassessmentusingwapordata AT hamidehnouri influenceofspatialresolutiononremotesensingbasedirrigationperformanceassessmentusingwapordata AT pooladkarimi influenceofspatialresolutiononremotesensingbasedirrigationperformanceassessmentusingwapordata |
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