Soil Water Monitoring and Numerical Flow Modeling to Quantify Drought Conditions in a Rangeland Ecosystem. Issue 10 (14th October 2016)

• Record Type: Journal Article
• Authors: Engda, T.A.; Kelleners, T.J.; Paige, G.B.
• Is Part Of: Vadose zone journal. Volume 15:Issue 10(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-10-14
• Subjects: Soil science -- Periodicals; Zone of aeration -- Periodicals; Groundwater flow -- Periodicals; Groundwater flow; Zone of aeration; Periodicals; Electronic journals; 631.4
• DOI: 10.2136/vzj2016.04.0036
• Languages: English
• ISSNs: 1539-1663

Abstract

Abstract : Core Ideas: Soil water content data can be used for drought monitoring. Expected soil water conditions can be modeled using reanalysis climate data. Drought conditions can be inferred by comparing measured and expected soil water contents. A one‐dimensional vertical numerical model for coupled water flow and heat transport was calibrated for a mixed‐grass rangeland at the Sustainable Agricultural Research and Extension Center, Lingle, WY. The model predicted soil water content reasonably well, with a modeling efficiency (ME) of 0.71 (at 10‐cm depth), 0.79 (30 cm), and 0.78 (60 cm) during calibration. After further validation, the model was used to calculate historical soil water content for the rangeland site using North American Regional Climate Change Assessment Program (NARCCAP) reanalysis climate data (available years 1971–1999). The 29‐yr calculated median soil water content, representing the expected (normal) soil water content during the year, was used to assess drought conditions for the 2011 to 2015 water years with measured soil water contents. The soil water anomaly Z ( θ ¯ ), calculated as the deviation of measured root zone soil water content from the expected root zone soil water content, confirmed that 2012 was a drought year. The Climate Prediction Center (CPC) crop moisture index (CMI), which was used for comparison, indicated that 2011 to 2015 were all drought years, which did not agree with observations.