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Report From the Course
Weather Stations

Dan Dinelli, superintendent at North Shore Country Club in Glenview, Ill., has been utilizing weather stations at his facility since 1994, when the club purchased a Metos weather station. When the club needed to replace the Metos unit, a Watchdog unit from Spectrum Technologies was installed. After six years, they switched to their current system from Campbell Scientific.

Dinelli says, “Basically, most weather stations’ hardware is the same, [there are] some options in sensors, but it is the software and support that makes the biggest difference from one brand versus another, i.e. disease models built into the software for turf is important. The data for irrigation scheduling is also important, so weather station software that interacts with irrigation software is important.”

Dinelli shares what he wrote about his experiences after first using a weather station on the course:

The Metos station is a complete weather station offering many features, including 10 sensors; two thermometers, one for air temperature 5 inches above the turf, and one for soil temperature 2 inches below the turf in our fourth green; a rain gauge to measure rainfall and irrigation water; two leaf wetness sensors; a solarimeter to record solar radiation and day length; and a soil moisture probe, located 2 inches deep, in the fourth green.

Relative humidity is measured 6 inches above the turf. Wind speed and direction are sensed and recorded. It offers raw weather data, degree-day calculations, evapotranspiration (ET) value and three disease models. Spray data can be entered into the program to track the impact of spray decisions on disease activity. The Metos micrologger automatically scans all sensors every 12 minutes and stores this data for up to a week. Information is downloaded from the micrologger to a personal computer in the office. The data is stored on the hard drive and used in the Metos software. One more attribute on the Metos is the solar-powered charging system.

Singularly or collectively, data from these sensors offers us much information, improving, and at times justifying, many of our management practices. For example: The soil moisture sensor is a watermark gypsum block with a range of .2 to 15 bar. The computer graphs the soil wetness with readings from 0 (= completely saturated) to 254 (= completely dry). We were able to design a rating scale that helped us determine daily watering needs. This information was more helpful to us than calculated evapotranspiration (ET) values. However, the data from the two combined gave an even clearer picture of moisture loss and needs. If one had greens constructed to USGA specifications, it would be interesting to have two soil moisture sensors, one close to the top to sense moisture available for shorter roots and ground conditions affecting playability, another located at the bottom of the sand layer, just above the perched water table. This deeper sensor may prove helpful in assessing available water from the reservoir provided by the perched water table.

Information gathered from soil temperature has helped us to better judge the timing of our first fungicide application to control summer patch and take-all patch. Soil temperature data will also indicate the proper timing of preemergent herbicide treatments for crabgrass control.

Microbial activity is governed largely by soil temperature and moisture. Nutrient release by some fertilizer carriers is also governed by soil moisture and temperature. With a better understanding of these factors, we can better understand and predict fertilizer activity.

Insect development relies on many factors. One of the largest factors is heat. Scientists have come up with a way to better predict insect emergence and activity by tracking accumulated heat, expressed as degree-days. The Metos calculates degree-days by summing 120 air temperature measurements for the day and dividing that sum by 120 to get an average temperature for the day.

Once the average is obtained, the degree total for the day is this average minus the base temperature. We use a degree base of 50. Therefore, for a day with an average temperature of 59, at base 50, the degree-days for that day would be 9. Each day, this calculation is repeated and the result added to the previous days’ figures to get the running total of accumulated degree-day values. If the average temperature for the day is less than the base, the degree-days for that day are zero, not a negative number. Researchers have developed degree-day thresholds for many insects. Knowing the degree-day value and referencing it to a particular insects’ development, in effect, creates a calendar of insect activity. Following such a calendar helps the turf manager to focus on intense scouting for a particular insect and better target insecticide applications if needed.

Other biological activity can be predicted using degree-day figures. Plants respond to accumulated heat as well. Some plants’ determination to flower or set fruit can be predicted with degree-days. Poa annua has a degree-day model for its flowering period. Understanding the plants physiological state can better determine the timing of plant growth regulator applications. Because plants and insects share this heated phenomena, field observations of plant activity can also help in determining insect and weed activity. For example, it is noted that preemergent crabgrass controls should be applied when the bridal wreath spirea blooms. In this case, the bridal wreath spirea is an indicator plant for the conditions of crabgrass germination. Next season, we will make comparisons of degree-day values versus indicator plant responses. We have a garden of indicator plants growing on the golf course for this purpose.

The Metos has three prediction models for turf diseases, Pythium blight, brown patch and dollar spot. The predictive models are based on complex mathematical calculations to estimate severity and timing of disease events. The calculations include information collected from sensors of air temperature, soil temperature, rain or irrigation, relative humidity and length of leaf wetness. These predictive disease models are used as indicators of favorable environmental conditions for disease. It does not account for inoculum pressure, species or cultivar resistance to disease, fertility or future weather (environmental) conditions that may or may not favor further disease development. Ultimately, it is the turf manager who makes the decision on disease pressure versus needed controls.

It has proved to be an important tool in our integrated pest management program. Information from the Metos weather station helped in fine-tuning our irrigation needs. It also helped our timing to scout for disease and insect activity. It is a powerful tool, offering an objective guide to pest management. People who may question our management activities can relate to a computer printout over a “judgment” based on experience. If ET value calls for irrigation, it is based on scientific calculations and not a person’s “opinion.” This “scientific” support of what we do is becoming increasingly important.

There is a lot of room for “homegrown” research based on collected data coupled with field observations. We are looking at soil temperature readings to help fine-tune the timing of green cover applications, day length and how it may affect plant responses, solar thermal units to further refine degree units, and soil temperature versus root growth. The uses and applications are limited to your imagination, that’s what makes this tool so exciting.