67. Remote sensing estimates of crop water use for improved irrigation water management

This study on a large irrigation scheme in Morocco addressed a two-fold question: (a) does the local water management authority adapt water releases to atmospheric water demand ET0-P? and (b) does crop actual evapotranspiration respond to inter- and intra-annual variability in water releases? We have evaluated the inter-annual variability of ET0-P during the period 1992–2017 and compared its anomalies (i.e., deviations from average) with anomalies in annual water release. Overall, it appeared that anomalies in water release were consistent with anomalies in ET0-P. The actual evapotranspiration (ETa) was estimated using a time series of multi-spectral satellite image data by applying the Surface Energy Balance (SEBAL) algorithm in a dry, wet, and reference year. We have determined the quartiles of the distribution of the ET0-P time series to identify these three years. The dry year was 2015–2016, the wet year was 2014–2015, and the reference (median of ET0-P) was 2013–2014. Finally, we compared seasonal and annual anomalies in ET0-P, ETa and release, Wd of irrigation water. In the period 1992–2017, the relative anomalies in ET0-P and Wd were similar only in 2000–2001 and 2015–2016. The analysis of anomalies in water inflow and stocks confirmed the response in increased Wd following wet years with higher inflow and replenishment of the reservoir. The response of crop water use to the irrigation water supply was evaluated by comparing anomalies in the ratio of actual to maximum ET, i.e., ETa/ETc with anomalies in Wd. As regards the Sidi Bennour, Faregh, and Gharbia districts, the relative anomalies in ETa/ETc and Wd were consistent, i.e., they had the same sign and comparable magnitude. Overall, the study shows that water delivery Wd responds to inter-annual variability in the pre-irrigation season water inflows into the reservoirs, rather than in ET0-P. On the other hand, actual crop water use, i.e., ETa/ETc, does respond to inter- and intra-annual variability in Wd. This evidence suggests that there is scope for adaptive water management based on a flexible adaptation of water release to inter- and intra-annual variability in water demand.

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Remote sensing for irrigation water management in the semi-arid Northeast of Brazil

Agricultural Water Management ◽

10.1016/j.agwat.2009.04.021 ◽

2009 ◽

Vol 96 (10) ◽

pp. 1398-1408 ◽

Cited By ~ 43

Author(s):

M.T. Folhes ◽

C.D. Rennó ◽

J.V. Soares

Keyword(s):

Water Management ◽

Remote Sensing ◽

Irrigation Water ◽

Irrigation Water Management ◽

Semi Arid

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Application of remote sensing and geographic information systems in irrigation water management under water scarcity conditions in Fayoum, Egypt

Journal of Environmental Management ◽

10.1016/j.jenvman.2021.113683 ◽

2021 ◽

Vol 299 ◽

pp. 113683

Author(s):

Fahmy Salah Abdelhaleem ◽

Mohamed Basiouny ◽

Eid Ashour ◽

Ali Mahmoud

Keyword(s):

Water Management ◽

Remote Sensing ◽

Information Systems ◽

Geographic Information Systems ◽

Irrigation Water ◽

Water Scarcity ◽

Geographic Information ◽

Irrigation Water Management

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CubeSats Enable High Spatiotemporal Retrievals of Crop-Water Use for Precision Agriculture

Remote Sensing ◽

10.3390/rs10121867 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1867 ◽

Cited By ~ 20

Author(s):

Bruno Aragon ◽

Rasmus Houborg ◽

Kevin Tu ◽

Joshua B. Fisher ◽

Matthew McCabe

Keyword(s):

Remote Sensing ◽

Eddy Covariance ◽

Water Use ◽

Spatial Resolution ◽

Precision Agriculture ◽

High Spatial Resolution ◽

Assessment Tools ◽

Optical Data ◽

Crop Water ◽

Crop Water Use

Remote sensing based estimation of evapotranspiration (ET) provides a direct accounting of the crop water use. However, the use of satellite data has generally required that a compromise between spatial and temporal resolution is made, i.e., one could obtain low spatial resolution data regularly, or high spatial resolution occasionally. As a consequence, this spatiotemporal trade-off has tended to limit the impact of remote sensing for precision agricultural applications. With the recent emergence of constellations of small CubeSat-based satellite systems, these constraints are rapidly being removed, such that daily 3 m resolution optical data are now a reality for earth observation. Such advances provide an opportunity to develop new earth system monitoring and assessment tools. In this manuscript we evaluate the capacity of CubeSats to advance the estimation of ET via application of the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) retrieval model. To take advantage of the high-spatiotemporal resolution afforded by these systems, we have integrated a CubeSat derived leaf area index as a forcing variable into PT-JPL, as well as modified key biophysical model parameters. We evaluate model performance over an irrigated farmland in Saudi Arabia using observations from an eddy covariance tower. Crop water use retrievals were also compared against measured irrigation from an in-line flow meter installed within a center-pivot system. To leverage the high spatial resolution of the CubeSat imagery, PT-JPL retrievals were integrated over the source area of the eddy covariance footprint, to allow an equivalent intercomparison. Apart from offering new precision agricultural insights into farm operations and management, the 3 m resolution ET retrievals were shown to explain 86% of the observed variability and provide a relative RMSE of 32.9% for irrigated maize, comparable to previously reported satellite-based retrievals. An observed underestimation was diagnosed as a possible misrepresentation of the local surface moisture status, highlighting the challenge of high-resolution modeling applications for precision agriculture and informing future research directions. .

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Evaluating Remote Sensing-based Crop Water Use Monitoring Methods Using Soil Moisture Sensors

10.13031/2013.41797 ◽

2012 ◽

Author(s):

José Luis Chávez ◽

Saleh Taghvaeian ◽

Thomas J Trout

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Water Use ◽

Crop Water ◽

Monitoring Methods ◽

Crop Water Use ◽

Soil Moisture Sensors

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Variation in the estimations of ET<sub>o</sub> and crop water use due to the sensor accuracy of the meteorological variables

Natural Hazards and Earth System Science ◽

10.5194/nhess-13-1401-2013 ◽

2013 ◽

Vol 13 (6) ◽

pp. 1401-1410 ◽

Cited By ~ 2

Author(s):

R. Moratiel ◽

A. Martínez-Cob ◽

B. Latorre

Keyword(s):

Water Management ◽

Wind Speed ◽

Relative Humidity ◽

Irrigation Water ◽

Meteorological Variables ◽

Crop Water ◽

Water Requirements ◽

Crop Water Use ◽

Irrigation Districts ◽

Annual Scale

Abstract. In agricultural ecosystems the use of evapotranspiration (ET) to improve irrigation water management is generally widespread. Commonly, the crop ET (ETc) is estimated by multiplying the reference crop evapotranspiration (ETo) by a crop coefficient (Kc). Accurate estimation of ETo is critical because it is the main factor affecting the calculation of crop water use and water management. The ETo is generally estimated from recorded meteorological variables at reference weather stations. The main objective of this paper was assessing the effect of the uncertainty due to random noise in the sensors used for measurement of meteorological variables on the estimation of ETo, crop ET and net irrigation requirements of grain corn and alfalfa in three irrigation districts of the middle Ebro River basin. Five scenarios were simulated, four of them individually considering each recorded meteorological variable (temperature, relative humidity, solar radiation and wind speed) and a fifth scenario combining together the uncertainty of all sensors. The uncertainty in relative humidity for irrigation districts Riegos del Alto Aragón (RAA) and Bardenas (BAR), and temperature for irrigation district Canal de Aragón y Cataluña (CAC), were the two most important factors affecting the estimation of ETo, corn ET (ETc_corn), alfalfa ET (ETc_alf), net corn irrigation water requirements (IRncorn) and net alfalfa irrigation water requirements (IRnalf). Nevertheless, this effect was never greater than ±0.5% over annual scale time. The wind speed variable (Scenario 3) was the third variable more influential in the fluctuations (±) of evapotranspiration, followed by solar radiation. Considering the accuracy for all sensors over annual scale time, the variation was about ±1% of ETo, ETc_corn, ETc_alf, IRncorn, and IRnalf. The fluctuations of evapotranspiration were higher at shorter time scale. ETo daily fluctuation remained lower than 5 % during the growing season of corn and alfalfa. This estimation fluctuation in ETo, ETc_corn, ETc_alf , IRncorn, and IRnalf at daily time scale was within an acceptable range, and it can be considered that the sensor accuracy of the meteorological variables is not significant in the estimation of ETo.

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