Monthly Detection Of Irrigation In California Central Valley Using Smap

Author : Chelsy Rae Salas
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.6/5 (625 download)

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Download or read book Monthly Detection of Irrigation in California, Central Valley Using SMAP written by Chelsy Rae Salas and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil moisture plays an important role in land-atmospheric coupling and can affect precipitation occurrence and rates by influencing low level moisture availability, heating and cooling of the near-surface boundary layer, and ultimately convective processes that lead to the development of precipitation (i.e. wind, cloud cover, atmospheric boundary layer thickness, and incoming solar radiation). Spatial and temporal patterns of soil moisture depend on the variability of precipitation and recent studies have shown that regional precipitation patterns may be influenced and modified by pre-existing soil moisture conditions. Research also suggests that anthropogenic influences such as irrigation may play a role in modifying soil moisture which can alter the hydrologic cycle regionally. Here we aim to evaluate the existence of anthropogenic influences of agricultural irrigation on monthly timescales, which has been shown to be influential to regional hydrological cycles. The Jet Propulsion Laboratory's (JPL) Earth observation satellite, Soil Moisture Active Passive (SMAP) is used to evaluate SMAP's ability to capture irrigation signals from California Central Valley (CCV) on monthly timescales. Soil moisture from SMAP is examined over the period of 45 months (April 2015 to December 2018) and compared to soil moisture estimates from the North American Land Data Assimilation System (NLDAS) land-surface model (LSM) which does not include an irrigation scheme. Precipitation estimates from NLDAS and in situ station data from California Irrigation Management Information System (CIMIS) are used to highlight SMAP's high soil moisture observations during the May through October growing season; a time when little to no rain occurs in the CCV. These results suggest satellite derived soil moisture is capable of capturing monthly irrigation signals in the CCV and compliments prior research which has shown satellite derived estimates of soil moisture are able to detect signs of irrigation on sub-monthly timescales. Results found in this study suggest SMAP holds promising potential to assists in improving weather and forecasting models due to its ability in capturing anthropogenic irrigation signals over the CCV on a monthly timescale.