JP1.13
A Soil Moisture Monitoring Network: The Oklahoma Mesonet Perspective

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Tuesday, 31 January 2006
A Soil Moisture Monitoring Network: The Oklahoma Mesonet Perspective
Exhibit Hall A2 (Georgia World Congress Center)
Bradley G. Illston, Univ. of Oklahoma, Norman, OK OK; and J. B. Basara, C. A. Fiebrich, R. L. Elliott, D. K. Fisher, E. D. Hunt, and J. R. Kilby

Soil moisture is an integral part of the hydrologic cycle. The need for soil moisture observations has been addressed in recent articles, which emphasized that improved observations of soil moisture conditions may lead to dramatic forecasting improvements related to the location and timing of the onset of deep convection over land, quantitative precipitation forecasting, and seasonal climate prediction. Furthermore, it has been noted that existing surface networks could be instrumented with sensors to measure soil water as well as atmospheric processes. The information gathered by these co-located sensors could be used to evaluate new hydrological theories, modeling and remote sensing techniques. Recognizing the need for improved in situ measurements, the Oklahoma Mesonet installed sensing devices to measure soil moisture conditions.

The Oklahoma Mesonet is a statewide meteorological observing network that provides real-time data from 116 stations with at least one station in every county. Data are recorded every 5 minutes and include meteorological variables such as air temperature, wind speed and direction, and rainfall. In 1996, Campbell Scientific 229-L (CSI 229-L) heat dissipation soil moisture sensors were installed at 60 Mesonet sites at depths of 5, 25, 60, and 75 cm to provide continuous observations of soil moisture. In 1999, an additional 43 sites had soil moisture sensors install as part of a network upgrade. The soil moisture sites collect observations every 30 minutes and are quality assured through multi-pass procedures. The 229-L sensors measure a temperature difference, which is a change in the sensor temperature after a heat pulse is introduced. From the measured temperature difference, hydrological variables such as soil water content, soil matric potential, and Fractional Water Index (FWI) can be calculated for public display, research datasets, and modeling applications.