Evapotranspiration Estimation Using Soil Water Balance, Weather and Crop Data

Zeleke, Ketema; Wade, Leonard

doi:10.5772/17489

Cited by 8 publications

(5 citation statements)

References 13 publications

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“…The required amount of water in irrigation process is also estimated by Raspberry pi using crop's evapotranspiration equation [13] [14] [15] and [16]: 𝑬𝑻𝒄 = 𝑬𝑻𝒐 × 𝑲𝒄 (𝟕) where, ETc is the crop water requirements [mm day−1], ET0 is the reference evapotranspiration [mm day−1], and Kc is the crop coefficient. The net irrigation amount 𝒅 𝒏 is estimated by [17] [18]:…”

Section: Proposed Smart Irrigation System Structurementioning

confidence: 99%

Optimized power and water allocation in smart irrigation systems

Abdulaziz¹,

Croock²

2022

PEN

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Agriculture has a significant role in countries' economy, but irrigation process consumes both power and water resources. Since in agriculture the goal is to maximize crop's yields with minimize costs, it is important to design a national smart irrigation system with optimal allocation of power and water resources especially in a plantation area with little rains. In this work, an optimized on-demand smart irrigation system is proposed to manage the allocation of the consumed power and water in agriculture field. The system controls irrigation process by utilizing Wireless Sensor Network (WSN) to collect real-time data from the field using sensors. Raspberry pi takes appropriate decision about irrigation process according to received data from sensor nodes, and commands are sent from it to actuator nodes. Secured Message Queuing Telemetry Transport (MQTT) protocol with Transport Layer Security (TLS) authentication protocol is used in managing the data exchange in the network over Wi-Fi technology. In addition, an optimal power and water consumptions formula is derived using Lagrange Multiplier method to allocate resources in an optimal way depending on watering demands. Both theoretical and practical results approve the efficiency of the proposed system in managing irrigation process optimally.

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Section: Proposed Smart Irrigation System Structurementioning

confidence: 99%

Optimized power and water allocation in smart irrigation systems

Abdulaziz¹,

Croock²

2022

PEN

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“…The climatic data needed for (1) is obtained using CLIMWAT software provided by Food and Agriculture Organization (FAO). The crop water requirements (ETc) could be estimated according to (2) [12][21] [22], and [23]:…”

Section: The Proposed Irrigation Systemmentioning

confidence: 99%

“…(2) Where, ETc is the crop water requirements [mm day−1], ET0 is the reference evapotranspiration [mm day−1], and Kc is the crop coefficient. Total Available Water (TAW) which is the total available water in the root zone is calculated according to (3) [22][17]:…”

Section: The Proposed Irrigation Systemmentioning

confidence: 99%

Design of Smart Irrigation System for Vegetable Farms Based on Efficient Wireless Sensor Network

2022

IJCCCE

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Designing an efficient irrigation system is a crucial issue in agriculture, due to water scarcity problem around the world with the need of increasing agricultural production to satisfy the demands of the enlargement of population. Therefore, to design a smart irrigation system, a real monitoring of field’s information that affects the watering status is required which can be achieved with Wireless Sensor Networks (WSN). In this paper, an irrigation system based WSN is proposed to save water, power, labor, and as a result, saving cost with production and profit increase. Sensor nodes collect field data to be sent to the Raspberry pi, as a main controller, to make optimal decisions about irrigation process. The field data includes the sensor readings of temperature and soil moisture. Crop evapotranspiration is also considered; thus, the required amount of water is estimated with a particular irrigation time to avoid over irrigation that hurts the plants growth and yields quality. The obtained results show the efficiency of the proposed system operation and controlling on the irrigation process. These results are taken for tomato plant as a case study. The monitoring tools are used to verify the suggested algorithm effectiveness in irrigation scheduling. Index Terms— Evapotranspiration, Irrigation systems, Raspberry pi, WSN.

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“…Soil water balance and weighing lysimeters follow a hydrological approach (Holmes, 1984). Tilahun and John (2012) estimated evapotranspiration as an independent output of the soil water balance equation over a field crop grown in Australia's semi-arid environment. The energy balance/Bowen ratio, the aerodynamic method, and the Eddy-Covariance (EC) adopt a micrometeorological line (Rose and Sharma, 1984).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Crop Evapotranspiration and Deep Percolation in a Commercial Irrigated Citrus Orchard Under Semi-Arid Climate: Combined Eddy-Covariance Measurement and Soil Water Balance-Based Approach

ALI¹

2022

SSRN Journal

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Evapotranspiration Estimation Using Soil Water Balance, Weather and Crop Data

Cited by 8 publications

References 13 publications

Optimized power and water allocation in smart irrigation systems

Optimized power and water allocation in smart irrigation systems

Design of Smart Irrigation System for Vegetable Farms Based on Efficient Wireless Sensor Network

Assessment of Crop Evapotranspiration and Deep Percolation in a Commercial Irrigated Citrus Orchard Under Semi-Arid Climate: Combined Eddy-Covariance Measurement and Soil Water Balance-Based Approach

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