Accurate and timely information on soil moisture conditions is an important component to effectively prepare for the damaging aspects of hydrological extremes. The combination of sparsely dense in situ networks and shallow observation depths of remotely sensed soil moisture conditions often force local and regional decision-makers to rely on numerical methods when assessing the current soil state. In this study, soil moisture from a commonly used, high-resolution reanalysis dataset is compared to observations from the U.S. Climate Reference Network (USCRN). The purpose of this study is to evaluate how well the North American Regional Reanalysis (NARR) captured the evolution, intensity, and spatial extent of the 2012 drought using both raw volumetric values and standardized anomalies of soil moisture. Comparisons revealed that despite a dry precipitation bias of 22% nationally, NARR had predominantly wetter 5-cm volumetric soil conditions over the growing season (April–September) than observed at USCRN sites across the contiguous United States, with differences more pronounced in drier regions. These biases were partially attributed to differences between the dominant soil characteristics assigned to the modeled grid cells and localized soil characteristics at the USCRN stations. However, NARR was able to successfully capture many aspects of the 2012 drought, including the timing, intensity, and spatial extent when using standardized soil moisture anomalies. Standardizing soil moisture conditions reduced the magnitude of systematic biases between NARR and USCRN in many regions and provided a more robust basis for utilizing modeled soil conditions in assessments of hydrological extremes.

Wetlands are the most important natural source of methane (CH4) to the atmosphere, and there is still considerable uncertainty of CH4 flux and net carbon budgets of wetlands. This uncertainty is due in part to the complex role of wetland vegetation in controlling methane production, oxidation and transport, which challenge the modeling and forecast of CH4 fluxes. We combined CH4 and carbon dioxide (CO2) fluxes measured by the eddy covariance technique during two consecutive growing seasons with continuous measurements of water levels and water temperature in a Typha angustifolia L patch of a temperate wetland. We seek to evaluate the role of vegetation in CH4 flux processes. To this end, we determined the relationship between CH4 and CO2 fluxes, directly and indirectly linked to plant activity. Our results indicated significant but opposing relationships between CH4 and CO2 fluxes during the daytime and nighttime. Consequently, when analyzed on a diel timescale, this relationship was not significant. Both CH4 and CO2 fluxes were highly dependent on environmental drivers, and thus, the correlations observed at both the nighttime and daytime were likely the result of a shared response to environmental variables. Focusing on water temperature (the most commonly observed environmental variable in wetlands) and water level (the most commonly controlled one) as operational control variables for wetlands, we identified “hot” condition combinations when CH4 flux and net ecosystem CO2 uptake are maximized at half hourly and diel scales.

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