Rural Training Center, Thailand (RTC-Thailand)

RTC-TH Programs: G.R.O.W.

Mar 06, 2010

G.R.O.W. (Getting Real On-farm Weather) evolved from a set of weather observation lessons we did for Na Fa Elementary School.

The lesson series of covered the major weather variables: Temperature, Relative Humidity, Wind speed, Wind direction, and Precipitation. Originally, the weather observations were to supplement the NASA CERES S?’COOL project. In many cases, the lessons also include simple DIY (Do It Yourself) instructions for making the instruments needed to make the measurements. The idea behind making your own weather instruments is based on a number of considerations: 1) cost savings over purchasing equipment; 2) the benefits of the insight gained as to the science of measurement and the limitations of measuring devices (homemade or manufactured); 3) the sense of accomplishment having made something with your own hands; 4) opportunities to light the spark of creativity to ?“make it better?” or ?“finding an easier way?” or adapting other materials to make the device; 5) the activity naturally integrates knowledge from a number of different disciplines giving students practical experience at integrating their knowledge from both inside and outside the classroom; 6) this type of lesson can stimulate the student to learn using their natural curiosity. [Note: In summer 2005, weather observation lessons were requested by Na Fa Elementary School. Reports about this activity are in the PDF section.] The adaptation of those lessons for GROW provides continuity from the classroom to the family farm to reinforce the school lessons.

The school lessons were adapted support water resource management on small farms. We saw this as a way to move the classroom lessons to the ?“real world.?” Continuity in the lessons would facilitate this adaptation making it easy for students to become ?“little teachers?” in their families. This provided an alternative to the RTC-TH conducting formal training sessions. All too often, farmers have difficulty taking time off from busy work schedules to attend a class or training session. And for some, there are added expenses for fees, transportation and food to attend training sessions. [Note: It is the policy of the RTC-TH not to charge fees for its training. Any fees charged are based on the need to recover cost of materials given to the participants. This situation is avoided as much as possible by having participants bring necessary tools and materials to a session if not held at our farm.]

Weather (especially rainfall) is highly variable from one place to another. Rainfall is the primary source of water for most farms. Accurate rainfall data for a farm are critical for estimating rainwater harvesting, soil erosion potential, soil moisture, and other farm operations. Climate change is a major concern, and having records to supplement regional weather/climate data helps local climate change impacts that can affect management plans for small rural family farms. [Note: For those not familiar with Nan Province, the terrain is mountainous. It is similar to the Great Basin?’s Basin and Range topography with a series of parallel North-South trending ridges and valleys. This makes for varying weather and climate conditions in the Province. The SW monsoon brings a rainy season (warm, wet) to Nan from May to Oct. Typhoons tracking in from the Gulf of Tonkin to the east bring torrential rains as they degrade to tropical depressions. This will be the time of greatest soil erosion and possible flooding. The NE monsoon in the winter (cool, dry season) is from Nov to Feb. For most farmers, this will be the season to grow ?“dry land?” crops. The hot, dry season (Mar to Apr) is when some will turn to hunting. Others will be busy preparing fields for planting when the rains come. There is much burning and land clearing in this season.

Our demonstration farm is located about 9.1 km / 5.7 mi from the official Thai government weather station in Thawangpha. Initially, we made our rainwater harvesting calculations based on the only available data (the Thawangpha station). In the past, there have been numerous occasions when heavy rain fell on one place and not the other. This pointed out the need to gather relevant weather data on the farm.

To make the farm weather data as useful as possible, the measurements follow the criteria of the W.M.O. (World Meteorological Organization). This means that the students learn the proper location of the weather instruments and standards for making the weather observations. The lessons include knowing the affects of different kinds of surfaces on temperature measurement. For example, bare soil, short grasses, shrubs and trees, and pavement. These surfaces also have different soil moisture characteristics. These insights give deeper meaning to the lessons in SOS, SOW, COMPOST, and BUGS.

Not all farm weather stations may fully conform to these rigorous international standards. In fact, not all weather stations are able to conform to the standards. But keeping good records allows users of the GROW weather data to process the data accordingly. For example, in Nan Province, there are only 3 official government weather stations for the 11472.1 km2 / 4429.4 mi2. This is a distribution density of 1 station per 3,824 km2 / 1476 mi2. If just 50 students (about half of the students in Na Fa Elementary School) were to set up basic GROW stations on their family farms, the density of weather stations would be 1 station per 216 km2 / 83 mi2. In essence, we operate on the basis that some data of known or limited quality is better than no data at all. The idea here is that even if the GROW weather data is not reliable enough for WMO standards, professional meteorologists could use the GROW weather data to identify areas of interest where they might want to locate an official weather station in the future.

Temperature and relative humidity are widely reported weather variables. But the measurements must be reported using instruments located in the shade. Temperature and relative humidity affect the health of people, plants, and animals (e.g. heat stress index, seed germination, etc.). It determines the rate evaporation affecting water levels in ponds, soil moisture, etc. After a harvest, many farmers are drying their crops in the sun. These weather variables affect how fast and how complete the drying will occur. At present, most farmers monitor this by subjective experience. The use of weather data may help some farmers to better manage their time and energy in the drying process. In the future, we hope to experiment with enclosed passive solar food drying units. An enclosed drying unit has an advantage over open air drying especially during times of inclement weather. Temperature is also affected by solar angles (e.g. vertical angle above the horizon, and horizontal angle or compass direction). This then leads into data that can be used to plan passive solar projects in the I.F.S. program.

Wind speed and direction affects a variety of farm operations: location of livestock pens, orientation of fish ponds (for natural aeration), fire safety and fire fighting planning, free pollination, soil erosion management. Natural cross ventilation is a free way of cooling buildings. Knowing the wind speed and directions helps orient buildings to take advantage of the wind. Obviously the use of wind energy systems requires this data. Unfortunately our farm is not suitable for wind energy systems.

Precipitation (especially in the form of rainfall) is the most significant natural water resource for small farms. GROW focuses on measuring the amount of rainfall. Typically measurements are made once a day. We suggest the same time each morning, so the data recorded would be the rainfall for the previous 24-hours. Over time, farmers can see the rainfall pattern for their farm. Of course, this can vary from year to year. And as any measurement or statistic, the longer the records, the better you can ?“average?” the data and get a more ?“reliable?” result. Our key concern is more accurate and relevant data for rainwater harvesting calculations for the farm. If a farmer knows the total area of the rainwater catchment on the farm, they can better estimate the storage capacity needed. The storage can be in ponds, tanks / cisterns, or in the soil. Water is a very precious resource. And knowing the amount of water available will affect what can be grown, when it can be planted, and help give insights to soil erosion potential. This is the basis for creating a water budget. The rainfall is the ?“income?”. Evaporation and crop growing are the main ?“expenditures?”. Water storage can help to make water available during drier times of the year.

Recordkeeping is a critical part of weather observations. The careful review of past records helps to detect patterns and trends in weather. Over time, the past records are collectively considered to be climate. Seeing changes over time in the measurements is important to managing the farm. Having written records is a big difference to relying on the subjective (and sometimes selective) memories of local farmers. It will be next to impossible to expect GROW stations to have complete records. Even professional weather stations with automated recording equipment do not have 100% complete data sets. But again, given the lack of weather stations in rural areas, we feel that having some data is better than having no data at all.

Most farmers tend to operate on the basis of subjective memory and experience. This tends to be reactive and often doesn?’t enable them to effectively respond to droughts. GROW can provide real data to ?“predict?” based on trends. Actions in terms of rainwater harvesting and other strategies in SOW empower farmers to be more ?“pro-active?” to prepare for times of drought. In light of long term climate change, BUGS points the way by encouraging farmers to consider integrating drought tolerant crops and crops capable of germinating in higher soil temperatures to prepare in advance of these changes.

Soil erosion potential is affect by various weather conditions: rainfall, wind speed and direction. The total amount of rainfall is a convenient measure. But the intensity and duration of the rainfall affects soil erosion rates. For example, 254 mm / 1 inch of rain falling in 1 hour has a very different effect if spread over 24 hours. And falling in as an intense thundershower is quite different than falling as a drizzle. A strong wind driving the rain has a different impact on soil erosion. If the wind is from the South, slopes facing the South will get more rainfall than those facing North, East, or West. Farmers can plan their soil management strategies using this weather information to set priorities when trying to deal with soil erosion on their farms.

A scenario we envision is school children participating in managing their family?’s farm. As they carry the weather observation lessons home and put them to use on the farm, they reinforce their learning. At the same time, they perform an important and useful task for their family farm. So even as children, they become an integral part of managing the family farm. This fits well with our ideas of learning being a lifelong experience, and of sharing knowledge. In this way, parents can also learn about GROW through their children. This provides adults with an alternative to taking time off from working on the farm to attend training classes. Additionally, it is well known that one of the best ways to learn something is to try to teach it to others. An added benefit to this is providing people with an opportunity to expand their horizons. The weather observation lessons in Na Fa Elementary School and GROW gives them a preview of a real world job in the Royal Thai Meteorology Department.

GROW is primarily an education program for awareness. If farmers chose NOT to undertake GROW for their farms, they are more aware of how to use existing weather data to become more pro-active in managing their farms. As with most endeavors, GROW takes time and effort. Each farm family makes their own determination as to the cost / benefits of undertaking GROW. The RTC-TH provides the opportunity to learn. The demonstration farm shows others the results of our efforts. The proof of the pudding is in the eating. The fact that our farm has been recognized more than once as the best farm in the Jompra subdistrict and Thawangpha district based on the King?’s Theory of Self-sufficient agriculture is reassurance we are on the right path.

For the RTC-TH, the weather observation and GROW lessons created another community service opportunity. In times of emergency, organizations providing relief and aid often lack local weather data critical to relief operations planning. The RTC-TH adapted its school and GROW lessons to create MEWS (Mobile Emergency Weather Station). This will be reported in a separate article in this series.

[Note: This was a brief description of GROW. For the lessons to be meaningful, they are all adapted to local site conditions prior to training. A typical scenario for off-farm training involves time to pre-view the area for the training (about ?½ to 1 day prior to the training). This lets us tailor the lessons to be as site specific as possible. Relevance is critical to making the lessons useful. Thus, there isn?’t a ?“standard?” lesson booklet as such. Included with the training is the ?“teach back?” model. This encourages the participants to share the knowledge with others, just as we are freely sharing our knowledge with them. Payment for the training consists of covering our costs to get to and from the training site, and room/board for the duration of the training. Although we are not a formal / legal non-profit organization, we conduct ourselves in that manner. We are not doing this to make a profit. This is primarily a ?“give back to the community?” activity.

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