Agriculture’s efforts to better manage water have taken as step forward with the work of Daniel Hirmas, a professor at the University of Kansas. He and his team are using MLT scanners to predict water movement within the soil– a study which could lead to correct predictions of recharge rates of aquifers, predict how areas will react to climate change, and use water more efficiently for crops. The process may also help predict water runoff and soil erosion, deposition, and sedimentation of surface water reservoirs. It may even help us understand how plant nutrients are transported in the soil.
Hirmas is researching how easily water moves through soil, as process that must be done at night since daylight interferes with the detection of the macro pores that help move water through soil.
“The soil structure affects how easily water can be transported through the soil. This is called ‘hydraulic conductivity’,” says Hirmas. “Conductivity is a property of the soil. It affects how quickly water can be transported through the soil. Saturated hydraulic conductivity refers to the conductivity of the soil when the soil is fully saturated with water. In this case, all the soil pores are filled with water.”
The process can be complex. A soil pore two times as large as another can actually conduct sixteen times the volume of water of the smaller pore in the same amount of time. This preferential water flow means math can account for the differences in the soil and predict water movement.
You can read more about the study here.