Soil Water Monitoring and Numerical Flow Modeling to Quantify Drought Conditions in a Rangeland Ecosystem

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(θtrue¯), 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.

Quantification of water balance using a lysimeter in Mexico

“…The variations of were associated with rainfall events > 4 mm and evaporation. The non-linear decrease of , as it has been reported in the literature (Engda et al, 2016), was also observed in this lysimeter. During rainy seasons, average ranged 0.146-0.137 cm 3 /cm 3 and its coefficient of variation ranged between 38.4 and 40.0%.…”

Hydrogeophysical Inversion of Time‐Lapse ERT Data to Determine Hillslope Subsurface Hydraulic Properties

“…The reader is directed to Engda et al. (2016) and Fullhart et al. (2018, 2019) for more detail on the development and implementation of this method, but we include an abbreviated description of the process.…”

“…This method implicitly accounts for the presence of coarse fragments in the subsurface to allow for the development of effective hydraulic properties that include the effects of coarse fragments that may be missed when calibrating water retention parameters directly. In Engda et al (2016) and Fullhart et al (2018Fullhart et al ( , 2019, this method was initially referred to as dry soil bulk density optimization. However, we refer to the same methodology as fine-earth fraction optimization to avoid confusing soil bulk density as defined by Engda et al (2016) and Fullhart et al (2018Fullhart et al ( , 2019 with the usual definition of soil bulk density where the volume of coarse fragments is subtracted from the total subsurface region volume (e.g., Vincent & Chadwick, 1994; see also ;Fullhart et al, 2018).…”

“…Recently, Engda et al. (2016) employed a fine‐earth fraction optimization method that was successful in determining hydraulic properties in mountainous environments and has shown promise for reducing the overall number of parameters needed for calibration (Fullhart et al., 2018, 2019). The fine‐earth fraction optimization method relates measured fine‐earth characteristics (texture and gravimetric water retention) to a volumetric water retention function through a fine‐earth fraction bulk density whose value is calibrated to implicitly account for varying fractions of fine‐earth and coarse fragments in the subsurface.…”

Isotopic fractionation induced by a surface effect influences the estimation of the hydrological process of topsoil

“…Stable isotope compositions of oxygen and hydrogen (δ 18 O and δ 2 H) in soil water are eco‐friendly indicators for water‐use strategies in plants, water transport, and evaporation (Engda et al, 2016; Fiipovic et al, 2014; Gebremeskel & Pieterse, 2007; He et al, 2017; Sprenger et al, 2016). However, a large spatial heterogeneity of the isotopic signal (Thomas et al, 2013; Yang et al, 2016) influenced by soil properties was detected, which hinders additional applications of isotopes in water.…”