Simulation of long‐term soil water dynamics at Reynolds Creek, Idaho: implications for rangeland productivity

Finzel, Julie A.; Seyfried, M. S.; Weltz, Mark A.; Launchbaugh, Karen L.

doi:10.1002/eco.1666

Cited by 8 publications

(6 citation statements)

References 52 publications

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“…Engda et al (2016) found early growing season soil water to be a reasonable predictor of growing‐season herbage production for Wyoming rangelands. A similar finding has been reported for an Idaho rangeland (Finzel et al, 2016). Soil water content therefore provides useful information to assess drought conditions.…”

supporting

confidence: 89%

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

Engda

Kelleners

Paige

2016

Vadose Zone Journal

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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.

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supporting

confidence: 89%

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

Engda

Kelleners

Paige

2016

Vadose Zone Journal

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“…Second, for many ecohydrological and biogeochemical processes, the measured θ at a given depth is not necessarily the value of interest and may, in fact, be misleading because differences in soil texture may obscure important soil water potential differences. In terms of soil water measurements, parameters of field capacity (θ FC ) and the plant extraction limit, θ PEL , are useful for hydrologic purposes (Finzel et al., 2016; Seyfried & Wilcox, 2006) and can be identified from field data (Chandler et al., 2017). Similarly, levels of microbial activity are also better described by θ values normalized to the same parameters of θ PEL , θ FC in addition to the saturated value of θ SAT (Moyano, 2013; Paul et al., 2003), and not the actual θ value.…”

Section: Resultsmentioning

confidence: 99%

Slope and aspect controls on soil climate: Field documentation and implications for large‐scale simulation of critical zone processes

Seyfried¹,

Flerchinger²,

Bryden

et al. 2021

Vadose Zone Journal

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Soil climate, as quantified by soil temperature (T S ) and water content (θ), exerts important controls on critical zone processes. It may be sensitive to variations in local slope and aspect (SA), but this attribute remains poorly quantified at the local scale and unresolved in large-scale models. Estimation of SA effects on soil climate across multiple scales may facilitated using topographically modified, incoming clear-sky solar radiation (S R,CS,T ). We established six paired automated soil climate monitoring stations on opposing north-facing (NF) and south-facing (SF) slopes (4 yr) and collected spatial T S and θ data within the hectare surrounding four stations (2 yr) to measure SA effects on soil climate. Results were compared with physically based simulations and evaluated in the context of S R,CS,T . Spatial θ data were more variable than Ts, and both were consistent with values from continuous monitoring stations. On average, the SF T S was much greater (4.7 ˚C) and the annual summer drought longer (36 d) than on the adjacent NF aspect. Seasonal variations of T S and θ were different from each other and also different from S R,CS,T . Local conditions, including snow cover, precipitation patterns, and soil properties, largely controlled seasonal variations of T S and θ, which cannot be predicted from S R,CS,T . This indicates that realistic simulation of many critical zone processes requires high-resolution inputs.Simulations captured first-order SA effects and could be useful for estimating SA effects in lieu of field monitoring.

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“…The distribution and function of vegetation within the RCEW are strongly controlled by terrain, precipitation, and soil moisture availability (Finzel et al. ). Across middle and upper elevations of the watershed, highly productive aspen stands are often distributed along leeward slopes and we hypothesize that they utilize water subsidies stemming from large snow drifts that persist late into the spring months (Seyfried et al.…”

Section: Methodsmentioning

confidence: 99%

Simulating the dependence of aspen (Populus tremuloides) on redistributed snow in a semi‐arid watershed

et al. 2018

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. 2018. Simulating the dependence of aspen (Populus tremuloides) on redistributed snow in a semi-arid watershed. Ecosphere 9(1):e02068.10. 1002/ecs2.2068 Abstract. In semi-arid mountainous regions across the western United States, the distribution of upland aspen (Populus tremuloides) is often related to heterogeneous soil moisture subsidies resulting from redistributed snow. As temperatures increase, interactions between decreasing snowpack and future trends in the net primary productivity (NPP) of aspen forests remain uncertain. This study characterizes the importance of heterogeneously distributed snow water to aspen communities in the Reynolds Creek Critical Zone Observatory located in southwestern Idaho, USA. Net primary productivity of three aspen stands was simulated at sites spanning elevational and precipitation gradients using the biogeochemical process model Biome-BGC and precipitation data adjusted to account for drifting snow. Compared to a spatially homogeneous precipitation distribution, Biome-BGC simulations accounting for redistributed precipitation were in better agreement with previous simulations of snow accumulation and soil moisture field measurements. During drought years, simulations below the largest drifts that included wind-redistributed snow resulted in NPP values nearly 77% higher than simulations assuming uniform precipitation. However, during wet years (and at sites with higher total precipitation), increased effective precipitation resulting from drifting snow did not have a significant role in aspen productivity. In these cases, soil moisture was found to be non-limiting even in the absence of redistributed snow. Increased water availability from snow drifts often exceeded the storage capacity of the soil and contributed little to plant available water used later in the growing season.

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Simulation of long‐term soil water dynamics at Reynolds Creek, Idaho: implications for rangeland productivity

Cited by 8 publications

References 52 publications

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

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

Slope and aspect controls on soil climate: Field documentation and implications for large‐scale simulation of critical zone processes

Simulating the dependence of aspen (Populus tremuloides) on redistributed snow in a semi‐arid watershed

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