WO2002038284A1 - Centrale de régulation de l'irrigation utilisant une évaluation du rayonnement solaire - Google Patents

Centrale de régulation de l'irrigation utilisant une évaluation du rayonnement solaire Download PDF

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Publication number
WO2002038284A1
WO2002038284A1 PCT/US2000/041944 US0041944W WO0238284A1 WO 2002038284 A1 WO2002038284 A1 WO 2002038284A1 US 0041944 W US0041944 W US 0041944W WO 0238284 A1 WO0238284 A1 WO 0238284A1
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WO
WIPO (PCT)
Prior art keywords
controller
solar radiation
irrigation
temperature
environmental factor
Prior art date
Application number
PCT/US2000/041944
Other languages
English (en)
Inventor
Sylvan Addink
Kirk Buhler
Original Assignee
Aqua Conservation Systems, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Aqua Conservation Systems, Inc. filed Critical Aqua Conservation Systems, Inc.
Priority to PCT/US2000/041944 priority Critical patent/WO2002038284A1/fr
Priority to US10/416,056 priority patent/US7048204B1/en
Publication of WO2002038284A1 publication Critical patent/WO2002038284A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G25/00—Watering gardens, fields, sports grounds or the like
    • A01G25/16—Control of watering
    • A01G25/167—Control by humidity of the soil itself or of devices simulating soil or of the atmosphere; Soil humidity sensors

Definitions

  • the field of the invention is irrigation controllers.
  • irrigation controllers have been developed for automatically controlling application of water to landscapes.
  • Known irrigation controllers range from simple devices that control watering times based upon fixed schedules, to sophisticated devices that vary the watering schedules according to local geographic and climatic conditions.
  • a homeowner typically sets a watering schedule that involves specific run times and days for each of a plurality of stations, and the controller executes the same schedule regardless of the season or weather conditions. From time to time the homeowner may manually adjust the watering schedule, but such adjustments are usually only made a few times during the year, and are based upon the homeowner's perceptions rather than the actual watering needs.
  • One change is often made in the late Spring when a portion of the yard becomes brown due to a lack of water.
  • Another change is often made in the late Fall when the homeowner assumes that the vegetation does not require as much watering.
  • More sophisticated irrigation controllers usually include some mechanism for automatically making adjustments to the irrigation run times to account for daily environmental variations.
  • One common adjustment is based on soil moisture. It is common, for example, to place sensors locally in the soil, and suspend irrigation as long as the sensor detects moisture above a given threshold. Controllers of this type help to reduce over irrigating, but placement of the sensors is critical to successful operation.
  • More sophisticated irrigation controllers use evapotranspiration rates for determining the amount of water to be applied to a landscape.
  • Evapotranspiration is the water lost by direct evaporation from the soil and plant and by transpiration from the plant surface.
  • Potential evapotranspiration can be calculated from meteorological data collected on- site, or from a similar site.
  • One such system is discussed in U.S. Patent No. 5,479,339 issued December, 1995, to Miller. Due to cost, most of the data for ETo calculations is gathered from off-site locations that are frequently operated by government agencies. Irrigation systems that use ETo data gathered from off-site locations are discussed in U.S. Patent No. 5,023,787 issued June, 1991, and U.S. Patent No.
  • the patent discusses operation of an irrigation controller comprising: a memory that stores a regression model; a microprocessor that applies a value for an environmental factor to the regression model to estimate an evapotranspiration rate (estimated ETo); and a mechanism that uses the estimated ETo to affect an irrigation schedule executed by the controller.
  • Some of the environmental factors from which the value is obtained are temperature, solar radiation, wind speed, and humidity.
  • all four meteorological factors; temperature, solar radiation, wind speed, and humidity are typically used in a formula for calculating the actual ETo, temperature and solar radiation have a greater effect on the ETo value than either wind speed or humidity.
  • Temperature data for any given installation is typically obtained using only one type of sensor.
  • solar radiation data can be obtained by various solar radiation measuring devices, all of which have the commonality of an optical port through which the solar radiation passes prior to being measured by some means.
  • a diffuser or some other cover over the optical port, which can be of any suitable material that does not unduly interfere with the solar radiation reaching the measuring means.
  • this can be problematic since the cover must be kept clean to prevent foreign material from interfering with the solar radiation reaching the measuring means.
  • the solar radiation data obtained and used in the determination of ETo is generally obtained from government weather stations. Maintenance is done according to a regular schedule at most or all weather stations, and the solar radiation sensor diffuser or cover is cleaned during each of the scheduled maintenance visits. However, if solar radiation were to be used at a homeowners' residence to estimate ETo for irrigation purposes, the homeowner would probably not do the necessary maintenance to keep the optical port cover clean and the solar radiation data would not be very reliable. What is required is another method for estimating solar radiation that does not require regular maintenance, and would still provide a relatively close approximation of the actual solar radiation at the irrigation site.
  • the present invention provides systems and methods in which an irrigation controller uses an estimated solar radiation value to affect an irrigation schedule executed by the controller.
  • the estimated solar radiation value is partly derived from the difference between the temperature data collected from a non-shaded temperature sensor and the temperature data collected from a shaded temperature sensor.
  • a data point from the estimated solar radiation is applied to a regression model stored in the memory of the irrigation controller to determine the estimated ETo which is used to affect an irrigation schedule executed by the controller.
  • the regression model can comprise a linear regression, a multiple regression, or any other type of regression.
  • the regression model is preferably based upon a comparison of historical ETo values against corresponding historical environmental values, with the data advantageously spanning a time period of at least two days, and more preferably at least one month. Data from multiple environmental factors may also be used.
  • the environmental factor(s) utilized may advantageously comprise one or more of estimated solar radiation, temperature, wind speed, humidity, and soil moisture, and so forth. Values relating the environmental factor(s) may enter the controller from a local sensor, a distal signal source, or both.
  • Figure 1 is a flow chart of a preferred embodiment of the method of the present invention.
  • Figure 2 is a figure showing an exemplary relationship of ETo versus solar radiation.
  • Figure 3 is a flow chart of the steps in the determination of a regression model which would be programmed in irrigation controllers.
  • Figure 4 is a map depicting how California might be divided into zones with similar evapotranspiration characteristics, and the location of a representative weather station within each zone.
  • Figure 5 is a schematic of an irrigation controller.
  • Figure 6 is a flow chart of an irrigation system according to the present invention.
  • the estimated solar radiation by itself, could be used to affect an irrigation schedule executed by the irrigation controller.
  • a data point from the estimated solar radiation is preferably stored in the memory of the irrigation controller, and applied to a regression model.
  • the result provides and estimated ETo, which is used to affect an irrigation schedule executed by the irrigation controller.
  • a preferred method of controlling irrigation run time generally comprises: providing historical ETo values 10; providing corresponding environmental values 20; performing a linear regression for the historical ETo values and the historical environmental values 30; determining a regression model 40; obtaining an estimated solar radiation value 50 and possibly a current local value for another environmental factor 55; applying the values to the regression model 60 to estimate current ETo 60; using the current ETo to determine the watering schedule 70; and then executing the watering schedule 80.
  • the actual solar radiation at the irrigation site could be used.
  • the estimated solar radiation is partly determined by measuring the temperature in a non-shaded area and a shaded area and, then determining the difference between these two measurements. The difference may be slightly modified by one or more factors, so it will more closely represent what the actual measurement would have been had a solar radiation sensor been used.
  • the historical ETo values may be obtained from a number of sources, including government managed weather stations such as CIMIS (California Irrigation Management Information System, maintained by the California Department of Water Resources), CoAgMet maintained by Colorado State University-Atmospheric Sciences, AZMET maintained by University of Arizona-Soils, Water and Environmental Science Department, New Mexico State University-Agronomy and Horticulture, and Texas A&M University- Agricultural Engineering Department. Although slight variations in the methods used to determine the ETo values do exist, most ETo calculations utilize the following environmental factors: temperature, solar radiation, wind speed and humidity.
  • Figure 2 shows an exemplary relationship of solar radiation versus ETo over a month.
  • An increase in solar radiation generally results in an increase in the ETo value, with the opposite occurring upon a decrease in solar radiation.
  • the other factors have greater or lesser effects than solar radiation on ETo, but all have some effect on ETo, and in addition to estimated solar radiation each of the other environmental factors can be used in the determination of a regression model.
  • Regression analysis can be performed on any suitable time period. Several years of data is preferred, but shorter time spans such as several months, or even a single month, can also be used. Different regression models can also be generated for different seasons during the year, for different geographic zones, and so forth.
  • the regression model is preferably based upon a comparison of historical ETo values against corresponding historical environmental values, with the data advantageously spanning a time period of at least two days, and more preferably at least one month. Data from multiple environmental factors may also be used.
  • the environmental factor(s) utilized may advantageously comprise one or more of estimated solar radiation, temperature, wind speed, humidity, and soil moisture, and so forth. Values relating the environmental factor(s) may enter the controller from a local sensor, a distal signal source, or both.
  • the regression model is preferably programmed into the central processing unit 210 or memory 220 of the irrigation controller using a suitable assembler language or microcode (See Figure 5).
  • the value or values applied against the regression model are preferably obtained from one or more local sensors, steps 311 through 315 (see Figure 6).
  • the microprocessor based central processing unit may have conventional interface hardware for receiving and interpreting of data or signals from such sensors.
  • the initial step in a preferred determination of a regression model is to select zones with similar evapotranspiration characteristics, step 100.
  • a representative weather station which provides ETo values, is selected in the zone, step 110.
  • monthly linear regression is performed of one or more historical factor(s) against the historical ETo values, step 120.
  • bi-monthly, quarterly, or other time periods may be used in performing the linear regression of historical temperature values against the historical ETo values.
  • multiple regression or other regression analysis may be used in the determination of the regression relationships between historical temperature values and historical ETo values.
  • Figure 4 is a map depicting how California might be divided into zones with similar evapotranspiration characteristics, and the location of a representative weather station within each zone.
  • FIG. 5 is a schematic of an irrigation controller programmed with a regression model that, along with other inputs and/or adjustments, would determine the run times for the various stations controlled by the irrigation controller.
  • a preferred embodiment of an irrigation controller 200 generally includes a microprocessor based central processing unit 210, an on-board memory 220, some manual input devices 230-through 234 (buttons and or knobs), a signal receiving device 240, a display screen 250, a plurality of electrical connectors 260 for connecting with solenoids 270, and a power supply 280.
  • a microprocessor based central processing unit 210 generally includes a microprocessor based central processing unit 210, an on-board memory 220, some manual input devices 230-through 234 (buttons and or knobs), a signal receiving device 240, a display screen 250, a plurality of electrical connectors 260 for connecting with solenoids 270, and a power supply 280.
  • FIG. 6 is a flow chart of an irrigation system according to the present invention. It starts with the controller 300 such as that described in the immediately preceding paragraph. Step 310 is the receiving of measurements of one or more current environmental factor(s) 311-315. These measurements are applied to the regression model and estimated ETo is determined 320. The estimated ETo is used to determine irrigation run times 330. Then the solenoids are activated, valves are opened and the landscape is irrigated 340.
  • Step 310 is the receiving of measurements of one or more current environmental factor(s) 311-315. These measurements are applied to the regression model and estimated ETo is determined 320. The estimated ETo is used to determine irrigation run times 330. Then the solenoids are activated, valves are opened and the landscape is irrigated 340.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Soil Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Water Supply & Treatment (AREA)
  • Environmental Sciences (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

La présente invention concerne une centrale de régulation de l'irrigation (200) utilisant des relevés de température pour calculer une valeur estimée de rayonnement solaire. Un modèle de régression conservé dans une mémoire (220) de la centrale de régulation de l'irrigation (200) travaille sur un point de données tiré de l'évaluation du rayonnement solaire pour évaluer une vitesse d'évapotranspiration servant à préciser un programme d'irrigation mis en oeuvre par la centrale (200). Le modèle de régression s'appuie de préférence sur une comparaison entre l'historique des valeurs d'évapotranspiration (ETo) et l'historique des valeurs de conditions d'ambiances correspondantes, les données portant avantageusement sur une période de deux jours, et de préférence d'au moins un mois. On peut également prendre en compte des données correspondant à au moins un autre facteur d'environnement et tout spécialement le rayonnement solaire estimé, la température, l'anémométrie, l'humidité relative, et l'humidité du sol. Les valeurs se rapportant aux facteurs d'environnement peuvent être fournies à la centrale par une sonde locale (240), une source de signal à distance, ou les deux.
PCT/US2000/041944 2000-11-06 2000-11-06 Centrale de régulation de l'irrigation utilisant une évaluation du rayonnement solaire WO2002038284A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/US2000/041944 WO2002038284A1 (fr) 2000-11-06 2000-11-06 Centrale de régulation de l'irrigation utilisant une évaluation du rayonnement solaire
US10/416,056 US7048204B1 (en) 2000-11-06 2000-11-06 Irrigation controller using estimated solar radiation

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2000/041944 WO2002038284A1 (fr) 2000-11-06 2000-11-06 Centrale de régulation de l'irrigation utilisant une évaluation du rayonnement solaire

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3460534A1 (fr) * 2017-09-22 2019-03-27 Electricité de France Procédé et dispositif de détermination indirecte d'un flux solaire incident
CN109862779A (zh) * 2016-09-07 2019-06-07 莱南科技私人有限公司 灌溉系统和方法

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5208855A (en) * 1991-09-20 1993-05-04 Marian Michael B Method and apparatus for irrigation control using evapotranspiration
US5870302A (en) * 1994-02-17 1999-02-09 Waterlink Systems, Inc. Evapotranspiration remote irrigation control system
US6076740A (en) * 1996-02-02 2000-06-20 Irrigation Control Networks Pty. Ltd. Irrigation control system
US6102061A (en) * 1998-05-20 2000-08-15 Addink; John W. Irrigation controller

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5208855A (en) * 1991-09-20 1993-05-04 Marian Michael B Method and apparatus for irrigation control using evapotranspiration
US5870302A (en) * 1994-02-17 1999-02-09 Waterlink Systems, Inc. Evapotranspiration remote irrigation control system
US6076740A (en) * 1996-02-02 2000-06-20 Irrigation Control Networks Pty. Ltd. Irrigation control system
US6102061A (en) * 1998-05-20 2000-08-15 Addink; John W. Irrigation controller

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109862779A (zh) * 2016-09-07 2019-06-07 莱南科技私人有限公司 灌溉系统和方法
CN109862779B (zh) * 2016-09-07 2022-05-24 莱南科技私人有限公司 灌溉系统和方法
EP3460534A1 (fr) * 2017-09-22 2019-03-27 Electricité de France Procédé et dispositif de détermination indirecte d'un flux solaire incident
FR3071623A1 (fr) * 2017-09-22 2019-03-29 Electricite De France Procede et dispositif de determination indirecte d'un flux solaire incident

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