Soil Moisture Data: From Using Citizen Science to Satellite Technology

Soil moisture is one of the most important components of ecological and hydrological models at different scales. This variable plays a key role in the exchange of water, energy, and carbon between land and atmosphere, and can be evaluated in order to examine the long-term impacts of climate change. Also, soil moisture is one of the factors affecting the formation of floods and is used to predict and monitor droughts. Soil moisture conservation is vital for increasing irrigation efficiency and protecting the vegetation. In spite of the great importance and high value of soil moisture data, it is not widely available because its field sampling is relatively expensive and it does not have a custodian in many developing countries that water and soil management are handled by different agencies. Field measurements have been subjected to many constraints. These limitations result in inaccessibility of data with acceptable accuracy and appropriate spatial distribution. The necessity of paying more attention to utilizing available technologies and tools to offset the traditional methods of collecting soil moisture data, is more pressing with increasing concerns about climate change. The objective of this study is to use a range of available tools from citizen science to satellite technology to generate soil moisture data with acceptable accuracy. Data provided by the first method has high spatial distribution and temporal variability, but it is suffering from subjectivity. Satellite data has high accessibility at no cost to the users, but its spatial resolution is not high and has to be downscaled. In this study, initial steps are taken to show how to deal with subjectivity errors, use of ground-based, and satellite data to provide soil moisture information for engineering applications.