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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #302501

Title: A ground based L-band radiometer for the monitoring of soil moisture in the region of Millbrook, New York, USA

item TEMIMI, M. - City University Of New York
item LAKHANKAR, T. - City University Of New York
item ZHAN, X - National Oceanic & Atmospheric Administration (NOAA)
item Cosh, Michael
item KRAKAUER, N. - City University Of New York
item KELLY, V. - Cary Institute Of Ecosystem Studies
item KUMISSI, L. - City University Of New York

Submitted to: Vadose Zone Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/13/2014
Publication Date: 3/14/2014
Publication URL:
Citation: Temimi, M., Lakhankar, T., Zhan, X., Cosh, M.H., Krakauer, N., Kelly, V., Kumissi, L. 2014. A ground based L-band radiometer for the monitoring of soil moisture in the region of Millbrook, New York, USA. Vadose Zone Journal. 13:3. doi: 10.2136/vzj2013.06.0101.

Interpretive Summary: Microwave radiometers are a useful tool for estimating a variety of land surface parameters, including surface soil moisture. Several ground-, aircraft-, and satellite- based experiments have been conducted to develop relationships between soil moisture and the microwave signal. The majority of these experiments however, are seeking to validate models at singular moments on a day, to develop daily estimates. This experiment was developed to analysis the diurnal pattern of the microwave signal, which is important to not only tower and truck based radiometer development, but to scientists who need to integrate microwave products which are collected at different times of day. This diurnal variation is a challenge for integration of current satellite missions with different overpass times. The principle conclusion of this study was the importance of soil temperature on the soil moisture retrieval. The results of these findings will influence how future experiments collect and estimate this significant land surface parameter.

Technical Abstract: A field experiment was performed in grassland near Millbrook, New York, using a NOAA Microwave Observation Facility, which comprises a network for in situ observation of soil moisture and a mobile dual polarized L band radiometer. During the field campaign, intensive measurements of L band brightness temperatures, surface temperature, and soil moisture and temperature at 3, 7 and 12 cm depth were collected. Observations were collected first early in the morning, starting at 8 AM, then a second pass started at 11 AM and finally a third pass started at 2 PM. During the second and the third pass half of the pixels were irrigated. Soil roughness and vegetation water content of the short grass remaining after mowing were measured. The Tau-Omega model was then used to assess the potential of using L band microwave observations for the retrieval of soil moisture. A particular focus was placed on investigating the performance of the retrieval when temperature at different depths is used. Also, the collected observations at three different times in the day were used to assess the impact of the diurnal cycle of temperature on the performance of soil moisture retrieval.Obtained results showed that the root mean square error has declined throughout the day to reach 0.03 m3/m3 in the afternoon pass when skin temperature values are used in the Tau-Omega model. In addition, amongst the three different passes, the lowest root mean square error was consistently obtained when the 12 cm temperature is used. A root mean square error of 0.02 m3/m3 was obtained in the afternoon pass when the 12 cm temperatures were used. The reported research contributes to understanding of the performance of microwave soil moisture retrieval algorithms in rocky soils typical of the northeastern US. It is found the tau-omega model may perform acceptably under these conditions but that attention should be paid to the diurnal cycle of the depth-varying soil temperature profile to reduce retrieval errors.