Utilization of automatic weather station for evaluation of climate risks in agricultural production and farm forecasting: the case of DSSHT model application and climate field school
2014
Balderama, O.F. | Alejandro-Alejo, L. | Espino, A.N. | Mata, M.R.B.
Automatic weather stations (AWS) play a significant part in yield forecasting where models use daily weather data to investigate interaction of climatic changes in crop environment. Weather dictates mainly the key decisions for agricultural activities and thus predicts crop production results. A network of weather stations is an essential tool to study and examine weather data to create an overall weather picture as well as local and regional forecasts. AWS or Automated Weather Station is compact equipment powered by storage battery and solar cells, which are more accurate and dependable instruments for collecting climatic data. This instrument is equipped with data storage system, thus data downloading can be done on a daily, weekly or monthly basis. The frequency of data collection can also be programmed according to the needs and use of such information. Moreover, a telemetry system could be connected to the AWS so that data can be remotely accessed through mobile SMS or other form of messages in real time. One important utilization of AWS is on the implementation of simulation modeling studies for crop and soil management. A recent study on the application of Decision Support System and Agrotechnology Transfer (DSSAT) program for peanut in Cagayan Valley demonstrated the usefulness of AWS in simulating sensitivities to climate changes of agricultural crops. Result shows the effect of prolonged drought in the last quarter of 2009, which resulted to underestimated yield result, and the effect of warm weather in 2005 resulting to lowering of potential yield of 50%. Moreover, the benefits of AWS can be derived through the application and utilization of weather data to be generated, both in real time and historical on farm forecasting.
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