scholarly journals Spatiotemporal Assessment of Irrigation Performance of the Kou Valley Irrigation Scheme in Burkina Faso Using Satellite Remote Sensing-Derived Indicators

2020 ◽  
Vol 9 (8) ◽  
pp. 484
Author(s):  
Alidou Sawadogo ◽  
Louis Kouadio ◽  
Farid Traoré ◽  
Sander J. Zwart ◽  
Tim Hessels ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Burkina Faso ◽  
Sweet Potato ◽  
Water Consumption ◽  
Water Productivity ◽  
Cost Effective ◽  
Irrigation Performance ◽  
Irrigation Scheme ◽  
Landsat Images ◽  
Performance Patterns

Traditional methods based on field campaigns are generally used to assess the performance of irrigation schemes in Burkina Faso, resulting in labor-intensive, time-consuming, and costly processes. Despite their extensive application for such performance assessment, remote sensing (RS)-based approaches remain very much underutilized in Burkina Faso. Using multi-temporal Landsat images within the Python module for the Surface Energy Balance Algorithm for Land model, we investigated the spatiotemporal performance patterns of the Kou Valley irrigation scheme (KVIS) during two consecutive cropping seasons. Four performance indicators (depleted fraction, relative evapotranspiration, uniformity of water consumption, and crop water productivity) for rice, maize, and sweet potato were calculated and compared against standard values. Overall, the performance of the KVIS varied depending on year, crop, and the crop’s geographical position in the irrigation scheme. A gradient of spatially varied relative evapotranspiration was observed across the scheme, with the uniformity of water consumption being fair to good. Although rice was the most cultivated, a shift to more sweet potato farming could be adopted to benefit more from irrigation, given the relatively good performance achieved by this crop. Our findings ascertain the potential of such RS-based cost-effective methodologies to serve as basis for improved irrigation water management in decision support tools.

scholarly journals Global Satellite-Based ET Products for the Local Level Irrigation Management: An Application of Irrigation Performance Assessment in the Sugarbelt of Swaziland

2019 ◽  
Vol 11 (6) ◽  
pp. 705 ◽  
Author(s):  
Poolad Karimi ◽  
Bhembe Bongani ◽  
Megan Blatchford ◽  
Charlotte de Fraiture
Keyword(s):  
Remote Sensing ◽  
Performance Assessment ◽  
Management Practices ◽  
Local Level ◽  
Water Productivity ◽  
Irrigation Management ◽  
Irrigation Performance ◽  
Crop Water ◽  
Management Regime ◽  
Crop Water Productivity

Remote sensing techniques have been shown, in several studies, to be an extremely effective tool for assessing the performance of irrigated areas at various scales and diverse climatic regions across the world. Open access, ready-made, global ET products were utilized in this first-ever-countrywide irrigation performance assessment study. The study aimed at identifying ‘bright spots’, the highest performing sugarcane growers, and ‘hot spots’, or low performing sugarcane growers. Four remote sensing-derived irrigation performance indicators were applied to over 302 sugarcane growers; equity, adequacy, reliability and crop water productivity. The growers were segmented according to: (i) land holding size or grower scale (ii) management regime, (iii) location of the irrigation schemes and (iv) irrigation method. Five growing seasons, from June 2005 to October 2009, were investigated. The results show while the equity of water distribution is high across all management regimes and locations, adequacy and reliability of water needs improvement in several locations. Given the fact that, in general, water supply was not constrained during the study period, the observed issues with adequacy and reliability of irrigation in some of the schemes were mostly due to poor scheme and farm level water management practices. Sugarcane crop water productivity showed the highest variation among all the indicators, with Estate managed schemes having the highest CWP at 1.57 kg/m3 and the individual growers recording the lowest CWP at 1.14 kg/m3, nearly 30% less. Similarly center pivot systems showed to have the highest CWP at 1.63 kg/m3, which was 30% higher than the CWP in furrow systems. This study showcases the applicability of publicly available global remote sensing products for assessing performance of the irrigated crops at the local level in several aspects.

scholarly journals Influence of Spatial Resolution on Remote Sensing-Based Irrigation Performance Assessment Using WaPOR Data

2020 ◽  
Vol 12 (18) ◽  
pp. 2949
Author(s):  
Megan Blatchford ◽  
Chris M. Mannaerts ◽  
Yijian Zeng ◽  
Hamideh Nouri ◽  
Poolad Karimi
Keyword(s):  
Remote Sensing ◽  
Open Access ◽  
Performance Assessment ◽  
Spatial Resolution ◽  
Performance Indicators ◽  
Crop Production ◽  
Water Productivity ◽  
Temporal Trends ◽  
Irrigation Performance ◽  
Crop Water

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.

Retrieving water productivity parameters by using Landsat images in the Nilo Coelho irrigation scheme, Brazil

2013 ◽  
Author(s):  
Antônio H. de C. Teixeira ◽  
Hélio L. Lopes ◽  
Fernando B. T. Hernandez ◽  
Morris Scherer-Warren ◽  
Ricardo G. Andrade ◽  
...  
Keyword(s):  
Water Productivity ◽  
Irrigation Scheme ◽  
Landsat Images

Estimation of water consumption and crop water productivity of winter wheat in North China Plain using remote sensing technology

2008 ◽  
Vol 95 (11) ◽  
pp. 1271-1278 ◽  
Author(s):  
Hongjun Li ◽  
Li Zheng ◽  
Yuping Lei ◽  
Chunqiang Li ◽  
Zhijun Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Winter Wheat ◽  
Water Consumption ◽  
North China Plain ◽  
North China ◽  
Water Productivity ◽  
Crop Water ◽  
Remote Sensing Technology ◽  
Crop Water Productivity ◽  
Sensing Technology

scholarly journals A Framework for Irrigation Performance Assessment Using WaPOR data: The case of a Sugarcane Estate in Mozambique

2021 ◽  
Author(s):  
Abebe Demissie Chukalla ◽  
Marloes L. Mul ◽  
Pieter van der Zaag ◽  
Gerardo van Halsema ◽  
Evaristo Mubaya ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Performance Indicators ◽  
Water Productivity ◽  
Effective Means ◽  
Cost Effective ◽  
Absolute Error ◽  
Irrigation Performance ◽  
Irrigation Method ◽  
Spatially Distributed ◽  
Response To Water

Abstract. The growing competition for the finite land and water resources and the need to feed an ever-growing population requires new techniques to monitor the performance of irrigation schemes and improve land and water productivity. Datasets from FAO’s portal to monitor Water Productivity through Open access Remotely sensed derived data (WaPOR) is increasingly applied as a cost-effective means to support irrigation performance assessment and identifying possible pathways for improvement. This study presents a framework that applies WaPOR data to assess irrigation performance indicators including uniformity, equity, adequacy and land and water productivity differentiated by irrigation method (furrow, sprinkler and centre pivot) at the Xinavane sugarcane estate, Mozambique. The WaPOR data on water, land and climate is near-real-time and spatially distributed, with the finest spatial resolution in the area of 100 m. The WaPOR data were first validated agronomically by examining the biomass response to water, then the data was used to systematically analyse seasonal indicators for the period 2015 to 2018 on ~8,000 ha. The WaPOR based yield estimates were found to be comparable to the estate-measured yields with ±20 % difference, root mean square error of 19 ± 2.5 ton/ha and mean absolute error of 15 ± 1.6 ton/ha. A climate normalization factor that enables the spatial and temporal comparison of performance indicators are applied. The assessment highlights that in Xinavane no single irrigation method performs the best across all performance indicators. Centre pivot compared to sprinkler and furrow irrigation shows higher adequacy, equity, and land productivity, but lower water productivity. The three irrigation methods have excellent uniformity (~94 %) in the four seasons and acceptable adequacy for most periods of the season except in 2016, when a drought was observed. While this study is done for sugarcane in one irrigation scheme, the approach can be broadened to compare other crops across fields or irrigation schemes across Africa with diverse management units in the different agro-climatic zone within FaO WaPOR coverage. We conclude that the framework is useful for assessing irrigation performance using the WaPOR dataset.

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