Irrigation Scheduling Approaches and Applications: A Review

Gu, Zhe; Qi, Zhiming; Burghate, Rasika; Yuan, Shouqi; Jiao, Xiyun; Xu, Junzeng

doi:10.1061/(asce)ir.1943-4774.0001464

Cited by 131 publications

(67 citation statements)

References 117 publications

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“…The real-time calculation of the soil–water balance is essential for real-time irrigation scheduling. Real-time computations require the prediction of daily reference evapotranspiration (ET o ), which is the basis for estimating crop evapotranspiration (ET c ) and for computing crop irrigation requirements [ 17 ]. The FAO Penman–Monteith (FAO-PM) method is recommended as the standard ET o method [ 18 ] and it has long been accepted worldwide as a good ET o estimator when compared with other methods [ 19 , 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

An Experimental Comparison of IoT-Based and Traditional Irrigation Scheduling on a Flood-Irrigated Subtropical Lemon Farm

Zia

Rehman

Harris

et al. 2021

Sensors

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Over recent years, the demand for supplies of freshwater is escalating with the increasing food demand of a fast-growing population. The agriculture sector of Pakistan contributes to 26% of its GDP and employs 43% of the entire labor force. However, the currently used traditional farming methods such as flood irrigation and rotating water allocation system (Warabandi) results in excess and untimely water usage, as well as low crop yield. Internet of things (IoT) solutions based on real-time farm sensor data and intelligent decision support systems have led to many smart farming solutions, thus improving water utilization. The objective of this study was to compare and optimize water usage in a 2-acre lemon farm test site in Gadap, Karachi, for a 9-month duration, by deploying an indigenously developed IoT device and an agriculture-based decision support system (DSS). The sensor data are wirelessly collected over the cloud and a mobile application, as well as a web-based information visualization, and a DSS system makes irrigation recommendations. The DSS system is based on weather data (temperature and humidity), real time in situ sensor data from the IoT device deployed in the farm, and crop data (Kc and crop type). These data are supplied to the Penman–Monteith and crop coefficient model to make recommendations for irrigation schedules in the test site. The results show impressive water savings (~50%) combined with increased yield (35%) when compared with water usage and crop yields in a neighboring 2-acre lemon farm where traditional irrigation scheduling was employed and where harsh conditions sometimes resulted in temperatures in excess of 50 °C.

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Section: Introductionmentioning

confidence: 99%

An Experimental Comparison of IoT-Based and Traditional Irrigation Scheduling on a Flood-Irrigated Subtropical Lemon Farm

Zia

Rehman

Harris

et al. 2021

Sensors

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“…However, despite its benefits, irrigation should be used properly to avoid excessive or insufficient water application. In this sense, irrigation scheduling plays a key role, allowing one to provide water to different crops according to their requirements [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes

2021

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Alternative models for the estimation of reference evapotranspiration (ETo) are typically assessed using traditional error metrics, such as root mean square error (RMSE), which may not be sufficient to select the best model for irrigation scheduling purposes. Thus, this study analyzes the performance of the original and calibrated Hargreaves-Samani (HS), Romanenko (ROM) and Jensen-Haise (JH) equations, initially assessed using traditional error metrics, for use in irrigation scheduling, considering the simulation of different irrigation intervals/time scales. Irrigation scheduling was simulated using meteorological data collected in Viçosa-MG and Mocambinho-MG, Brazil. The Penman-Monteith FAO-56 equation was used as benchmark. In general, the original equations did not perform well to estimate ETo, except the ROM and HS equations used at Viçosa and Mocambinho, respectively. Calibration and the increase in the time scale provided performance gains. When applied in irrigation scheduling, the calibrated HS and JH equations showed the best performances. Even with greater errors in estimating ETo, the calibrated HS equation performed similarly or better than the calibrated JH equation, as it had errors with greater potential to be canceled during the soil water balance. Finally, in addition to using error metrics, the performance of the models throughout the year should be considered in their assessment. Furthermore, simulating the application of ETo models in irrigation scheduling can provide valuable information for choosing the most suitable model.

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“…Some programs appeared during past periods, which use to evaluate water consumption of crops as CROPWAT and SIM DUAL program. These programs deal with field, and there was necessary to find system deal with all water resource elements [5]. The water evaluation and planning WEAP model comes as a development of these programs, with different tools and methods.…”

Section: Introductionmentioning

confidence: 99%

Improving the Cultivated Area for the Ramadi Irrigation Project By Using Water Evaluation and Planning Model (WEAP)

Najm¹,

Al-bayati²,

Sulaiman³

2021

(AREJ)

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In this study, the water evaluation and planning WEAP model was used to improve the Ramadi irrigation project with 28342 hectares and annual budget 326 million 3 / year for the period (2018)(2019). The results showed the total water used was 111.5 million 3 /year and equalled 34.2% of Ramadi irrigation budget. The annual production was 39.3 million Kg/year for Ramadi irrigation, and total economic returns 16.04 million $/year. The study proposal two scenarios to improve the cultivated area. The first scenario increased water volume of the current year from 111.5 million 3 /year to 272.12 million 3 /year, which caused increased in annual productivity from 39.

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Irrigation Scheduling Approaches and Applications: A Review

Cited by 131 publications

References 117 publications

An Experimental Comparison of IoT-Based and Traditional Irrigation Scheduling on a Flood-Irrigated Subtropical Lemon Farm

An Experimental Comparison of IoT-Based and Traditional Irrigation Scheduling on a Flood-Irrigated Subtropical Lemon Farm

Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes

Improving the Cultivated Area for the Ramadi Irrigation Project By Using Water Evaluation and Planning Model (WEAP)

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