| Summary: | 碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 107 === Due to the impact of climate change and the rising frequency of extreme weather have caused the problem of food security and water resources. Precision agriculture in greenhouses is gradually becoming a trend because it is less affected by external environmental factors and easier to manage. In order to effectively improve the utilization of water resources and reduce wasting water, this study planted cherry tomatoes in the greenhouse and installed monitoring instruments to collect data. The soil temperature and volumetric water content during tomato growth can be predicted effectively by combining the weather forecast.
The Hydrus-1D, random forest method and ICON were used to simulate the change of soil temperature and volumetric water content in the greenhouse. The results of the simulation show good performances among the three models. Further combined with weather forecast data, three models were applied to predict soil temperatures and volumetric moisture contents.
Both of predicted soil temperature and volumetric water content by Hydrus-1D followed the trend of real measured data, but Hydrus-1D can’t predict the watering situation. The predicted performance of soil temperature by ICON was low. Nevertheless, both predictions by random forest method were better than others.
This study simulated and predicted the soil temperatures and volumetric water contents by applying Hydrus-1D, random forest method and ICON to improve greenhouse management and increase water-use efficiency.
|
|---|
