WO2002041092A2

WO2002041092A2 - Irrigation controller using modified regression model

Info

Publication number: WO2002041092A2
Application number: PCT/US2000/042175
Authority: WO
Inventors: Kirk Buhler; Sylvan Addink
Original assignee: Aqua Conservation Systems, Inc.
Priority date: 2000-11-14
Filing date: 2000-11-14
Publication date: 2002-05-23
Also published as: WO2002041092A3

Abstract

The present invention provides systems and methods in which an irrigation controller (200) uses a regression model (140) that has applied to it a current temperature value to arrive at a first estimated evapotranspiration rate (estimated ETo 1)(320), uses a current cloud cover value to modify the estimated ETo 1 to arrive at a second estimated evapotranspiration rate (estimated ETo 2)(340), and uses the estimated ETo 1 or estimated ETo 2 along with other factors, such as crop coefficient and irrigation efficiency to affect an irrigation schedule executed by the controller (200). The temperature can represent air temperature or soil temperature. The current temperature values and cloud cover values may enter the controller (200) from a local sensor (294, 295), a distal signal source, or both.

Description

IRRIGATION CONTROLLER USING MODIFIED REGRESSION MODEL

Field of the Invention

The field of the invention is irrigation controllers.

Background of the Invention Many 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.

With respect to the simpler types of irrigation controllers, 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 landscapes 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. These changes to the watering schedule are typically insufficient to achieve efficient watering.

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 sensors detect 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 (ETo) can be calculated from meteorological data collected on- site, or from a similar site. Generally, the best estimate of ETo is derived from a calculation that includes the following four factors, temperature, solar radiation, wind speed and relative humidity (hereinafter termed "ETo"). A system that uses meteorological factors collected on-site to determine ETo 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 US Patent No. 5,097,861 issued March 1992 to Hopkins, et al., US Patent No. 5,023,787 issued June 1991and US Patent No. 5,229,937 issued July 1993 both to Evelyn-Veere, US Patent No. 5,208,855, issued May 1993, to Marian, US Patent No. 5,696,671, issued December 1997, and US Patent No.

5,870,302, issued February 1999, both to Oliver and US Patent No. 6,102,061, issued August, 2000 to Addink.

Due to cost and/or complicated operating requirements very few of these efficient irrigation controllers, discussed in the previous paragraph, are being installed on residential and small commercial landscape sites. Therefore, controllers that provide inadequate schedule modification primarily irrigate most residential and small commercial landscape sites. This results in either too much or too little water being applied to the landscapes, which in turn results in both inefficient use of water and unnecessary stress on the plants. Therefore, a need existed for a cost-effective irrigation system for residential and small commercial landscape sites that is capable of frequently varying the irrigation schedule based upon estimates of the plant's water requirements.

This need was met in part by a recent patent application, PCT application serial number PCT/USOO/l 8705. 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. The environmental factors from which the value was obtained included temperature, solar radiation, wind speed speed, relative humidity, barometric pressure, and soil moisture. Of the six environmental factors listed above, temperature and solar radiation are generally more closely correlated with ETo than the other four and solar radiation generally more closely correlated with ETo than temperature. Therefore, solar radiation should be the preferred environmental factor to use when applying an environmental factor to a regression model to estimate ETo as discussed in the patent application, United States application serial number PCT/USOO/l 8705. However, due to solar radiation sensor maintenance problems, temperature may be a more reliable environmental factor than solar radiation to use in the estimating of ETo.

On clear days, temperature and ETo have similar correlation values to solar radiation and ETo. However, on cloudy days solar radiation is much more closely correlated with

ETo than temperature. If the estimated ETo, which is arrived at by using temperature values applied to a regression model, could be modified to take into account the effect cloud cover has this should result in a modified estimated ETo value that is very similar to an ETo value. The present invention achieves this goal.

Summary of the Invention

The present invention provides systems and methods in which an irrigation controller uses a regression model that has applied to it a current temperature value to arrive at a first estimated evapotranspiration rate (estimated ETo 1), uses a current cloud cover value to modify the estimated ETo 1 to arrive at a second estimated evapotranspiration rate (estimated ETo 2), and uses either the estimated ETo 1 or estimated ETo 2 to at least partly affect an irrigation schedule executed by the controller.

It is contemplated that in addition to estimated ETol or estimated ETo 2, other factors, such as a crop coefficient value and an irrigation efficiency value, will be used to affect an irrigation schedule executed by the controller.

The regression model is based upon a comparison of historical ETo values against corresponding historical temperature values, with the data advantageously spanning a time period of at least two days, and more preferably at least one month.

The temperature values may be from air temperature and/or soil temperature. The current temperature and cloud cover values may enter the controller from a local sensor, a distal signal source, or both.

Various objects, features, aspects, and advantages of the present invention will become more apparent from the following detailed description of preferred embodiments of the invention, along with the accompanying drawings in which like numerals represent like components.

Brief Description of the Drawings

Figure 1 is a figure showing an exemplary relationship of ETo versus air temperature.

Figure 2 is a flow chart of the steps in the determination of a regression model, which would be programmed in irrigation controllers.

Figure 3 is a map depicting how California might be divided into zones with similar evapotranspiration characteristics, and the location of representative weather stations within the zones.

Figure 4 is a schematic of an irrigation controller.

Figure 5 is a flow chart of an irrigation system according to the present invention.

Detailed Description

Figure 1 shows an exemplary relationship of air temperature versus ETo over a month. An increase in air temperature generally results in an increase in the ETo value, with the opposite occurring upon a decrease in air temperature.

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 historical temperature and ETo values used in the determination of the regression model 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), CόAgMet 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 speed, and relative humidity.

In Figure 2 the initial step in a preferred determination of a regression model that will be programmed in the microprocessor of an irrigation controller is to select zones with similar evapotranspiration characteristics, step 110. A representative weather station, which provides ETo values, is selected in the zone, step 120. Preferably, monthly linear regression is performed of historical temperature values against the historical ETo values, step 130. Alternatively, it is contemplated that bi-monthly, quarterly, or other time periods may be used in performing the linear regression of historical temperature values against the historical ETo values. Additionally, it is contemplated that multiple regression or other regression analysis maybe used in the determination of the regression relationships between historical temperature values and historical ETo values.

Monthly regression models are determined from these monthly regression relationships, step 140. All irrigation controllers located in a specific zone are then programmed with the regression models determined for that zone, step 150.

The regression model is preferably programmed into the central processing unit or memory of the irrigation controller using a suitable assembler language or microcode (See Figure 4, 210 and 220). The current temperature value applied against the regression model and the cloud cover value used in arriving at a value for the estimated ETo 2 are preferably obtained from local sensors (see Figure 5, steps 310 and 330). The microprocessor-based central processing unit may have conventional interface hardware for receiving and interpreting of data or signals from such sensors.

Figure 3 is a map depicting how California might be diyided into zones with similar evapotranspiration characteristics, and the location of one or more representative weather station within each zone. Figure 4 is a schematic of an irrigation controller 200 according to the present invention that generally includes a microprocessor 220, an on-board memory 210, some manual input devices 230 through 232 (buttons and/or knobs), an input/output (I/O) circuitry 221 connected in a conventional manner, a display screen 250, electrical connectors 260 which are connected to a plurality of irrigation stations 270 and a power supply 280, a rain detection device 291, a flow sensor 292, a pressure sensor 293, a temperature sensor 294 and a cloud cover sensor 295. Each of these components by itself is well known in the electronic industry, with the exception of the programming of the microprocessor in accordance with the functionality set forth herein. There are hundreds of suitable chips that can be used for this purpose. At the present, experimental versions have been made using a generic Intel 80C54 chip, and it is contemplated that such a chip would be satisfactory for production models.

hi a preferred embodiment of the present invention the controller has one or more common communication internal bus(es). The bus can use a common or custom protocol to communicate between devices. There are several suitable communication protocols, which can be used for this purpose. At present, experimental versions have been made using an I²C serial data communication, and it is contemplated that this communication method would be satisfactory for production models. This bus is used for internal data transfer to and from the EEPROM memory, and is used for communication with peripheral devices and measurement equipment including but not limited to water flow sensors, water pressure sensors, and temperature sensors.

When the irrigation controller is initially installed an irrigation program is programmed into the controller, and is stored in the memory. In a preferred embodiment of the present invention the initial irrigation program is modified during the year to execute an irrigation of the landscape that meets the water requirements of the landscape plants with a minimum waste of water.

Figure 5 is a flow chart of an irrigation system according to the present invention, hi step 300, an irrigation controller is provided that has disposed in it a microprocessor programmed with a regression model. Step 310 is the receiving of measurements from a temperature sensor that are used to generate current temperature values. The temperature values are applied to the regression model and an estimated ETo 1 is determined 320. Measurements are received from a cloud cover sensor to generate current cloud cover values 330. The current cloud cover values are used to modify the estimated ETo 1 values to arrive at a value for an estimated ETo 2 340. In Step 350 irrigation run times are determined based on the estimated ETo 2, crop coefficient and irrigation efficiency. It is contemplated that the microprocessor will be preprogrammed to prevent the controller from activating the valves to irrigate the landscape until an adequate irrigation run time has accumulated to permit for the deep watering of the soil 360. When an adequate irrigation run time has been accumulated the controller will activate the valves to each station and the landscape will be irrigated, except when a manual or automatic override of irrigation occurs, steps 370 through 390.

Preferably in step 310 and 330 the data or signals are received from local sensors through a direct hardwire connection between the irrigation controller and the sensors but it may be received by any suitable wireless link, such as optical, radio, hydraulic or ultrasonic. Additionally, it is contemplated that both the current temperature data and current cloud cover data or either one of them may be received via distal signals. Distal signals are most likely received by radio wave, perhaps as sub signals on commercial broadcasts, or as main signals from a weather transmitting station. The distal signals may be received by other than radio waves, such as, the Internet, telephone line, pager, two-way pager, cable, and any other suitable communication mechanism.

Preferably the data and signals relate to current temperature and cloud cover conditions at the irrigation site. The term "current is used herein to mean within the last two weeks. It is preferred, however, that the current weather information is from the most recent few days, and even more preferably from the current day.

In a preferred embodiment of the present invention, the historical and current temperature values are air temperature values but it is contemplated they could be soil temperature values.

Crop species vary in their moisture requirements therefore a crop coefficient is preferably assigned to the crop to be irrigated. This crop coefficient is at least partly used in the determination of the irrigation run times 350. Additionally, irrigation systems are not 100% efficient in the application of water to a landscape. Therefore, an efficiency value is determined for the irrigation system and preferably the efficiency value is also a part of the determination of the irrigation run times 350.

Although, in a preferred embodiment of the present invention, the irrigation schedule is determined as a function of the estimated ETo 2 it maybe determined as a function of the estimated ETo 1. For example, if the data or signals are not received from a cloud cover sensor and/or based on parameters set in the microprocessor it is determined that the cloud cover data or signals may be in error, then the irrigation controller may use the estimated ETo 1 in the determination of the irrigation schedule instead of the estimated ETo 2.

Thus, specific methods and apparatus of the present invention have been disclosed. It should be apparent, however, to those skilled in the art that many more modifications besides those described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims.

Claims

CLAIMSWhat is claimed is:

1. An irrigation controller comprising: a memory that stores a regression model; a microprocessor that applies a current temperature value to the regression model to arrive at a first estimated evapotranspiration rate (estimated ETo 1) and uses a current cloud cover value to modify the estimated ETo 1 to arrive at a second estimated evapotranspiration rate (estimated ETo 2); and a mechanism that uses at least one of the estimated ETo 1 and estimated ETo 2 to at least partly affect an irrigation schedule executed by the irrigation controller.

2. The controller of claim 1 wherein the regression model is based upon a set of historical ETo values and a set of corresponding historical temperature values.

3. The controller of claim 1 wherein the set of historical ETo values and historical temperature values span a time period of at least two days.

4. The controller of claim 2 wherein the regression model comprises a linear regression.

5. The controller of claim 2 wherein the regression model comprises a multiple regression.

6. The controller of claim 1 wherein the temperature is at least one of air temperature and soil temperature.

7. The controller of claim 1, further comprising the mechanism using at least partly a crop coefficient value to affect the irrigation schedule executed by the controller.

8. The controller of claim 1, further comprising the mechanism using at least partly an irrigation efficiency value to affect the irrigation schedule executed by the controller.

9. An irrigation system comprising an irrigation controller according to claim 1, and a local sensor that provides a signal corresponding to the current temperature value.

10. An irrigation system comprising an irrigation controller according to claim 1, and a receiver that receives from a distal source a signal corresponding to the current temperature value.

11. An irrigation system comprising an irrigation controller according to claim 1, and a local sensor that provides a signal corresponding to the current cloud cover value.

12. An irrigation system comprising an irrigation controller according to claim 1, and a receiver that receives from a distal source a signal corresponding to the current cloud cover value.