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Creators/Authors contains: "Bell, Colin D."

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  1. Abstract

    The spatial variation of soil moisture over very small areas (<100 m2) can have nonlinear impacts on cycling and flux rates resulting in bias if it is not considered, but measuring this variation is difficult over extensive temporal and spatial scales. Most studies examining spatial variation of soil moisture were conducted at hillslope (0.01 km2) to multi‐catchment spatial scales (1000 km2). They found the greatest variation at mid wetness levels and the smallest variation at wet and dry wetness levels forming a concave down relationship. There is growing evidence that concave down relationships formed between spatial variation of soil moisture and average soil moisture are consistent across spatial scales spanning several orders of magnitude, but more research is needed at very small, plot scales (<100 m2). The goal of this study was to characterise spatial variation in shallow soil moisture at the plot scale by relating the mean of measurements collected in a plot to the standard deviation (SD). We combined data from a previous study with thousands of new soil moisture measurements from 212 plots in eight catchments distributed across the US Mid‐Atlantic Region to (1) test for a generalisable mean–SD relationship at plot scales, (2) characterise how landcover, land use, season, and hillslope position contribute to differences in mean–SD relationships, and (3) use these generalised mean–SD relationships to quantify their impacts on catchment scale nitrification and denitrification potential. Our study found that 98% of all measurements formed a generalised mean–SD relationship like those observed at hillslope and catchment spatial scales. The remaining 2% of data comprised a mean–SD relationship with greater spatial variation that originated from two riparian plots reported in a previous study. Incorporating the generalised mean–SD relationship into estimates of nitrification and denitrification potential revealed strong bias that was even greater when incorporating mean–SD observations from the two riparian plots with significantly greater spatial variation.

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  2. Abstract

    Outdoor water use represents over 50% of total water demand in semiarid and arid cities and presents both challenges to and opportunities for improved efficiency and water resilience. The current work adapts a remote sensing‐based methodology to estimate growing season irrigation rates at the census block group scale in Denver, Colorado. Results show that city‐wide outdoor water use does not change significantly from 1995 to 2018, while per capita water use and total water use significantly decrease from 2000 to 2018. Because total water use, but not outdoor use, is decreasing, the percent of water used outdoors significantly increases across the city from 2000 to 2018. Climate variables account for one‐quarter of interannual variation in mean irrigation rates due primarily to changes in temperature, not precipitation. Percent impervious land cover exhibits a significant inverse nonlinear relationship with irrigation rates at the census block group scale. Finally, 38% of Denver census block groups show significantly increasing irrigation rates between 1995 and 2018 driven primarily by increasing temperatures. The increasing proportion of water used for irrigation highlights the importance of outdoor demand management for urban water systems as indoor efficiencies improve. We advocate that resilient water systems necessitate integrated land use, infrastructure, and water planning in the face of urban growth and climate change. While minimizing irrigated urban areas may reduce demand, remaining green spaces should be designed to maximize multiple benefits including reductions in water demand and urban heat islands, stormwater management, and recreation to improve the sustainability of growing cities.

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  3. Abstract

    Urban development of watersheds increases runoff and nitrogen loads by adding urban impervious surfaces and increasing the hydrologic connectivity of these surfaces to streams. Storm water control measures (SCMs) are designed to disrupt this connectivity by retaining water in biologically active depressions where nitrogen retention, transformation, and removal occur. This work applies a mechanistic, spatially distributed, hydroecological model (RHESSys) to a suburban watershed in Charlotte, NC, with 15% total imperviousness (TI) and 33% watershed area mitigated by SCMs. We developed emergent relationships between watershed‐scale predictors (TI and connectivity to SCMs) and water and nitrogen response variables (storm water runoff ratios and nitrogen load by species). Results showed that annual runoff ratios were insensitive to increases in connectivity to SCMs (varying by ~1% of rainfall) because SCMs did not substantially increase evaporation but that runoff ratios increased by an average 0.2% per 1% increase in TI due to decreases in transpiration in the watershed. Generally, nitrate loads increased with TI but decreased as more surfaces were mitigated by SCMs. However, these nitrate reductions corresponded to increased export of dissolved organic nitrogen and ammonium. Together, these results indicate that SCMs act as both removers and transformers of nitrogen at the watershed scale. SCMs showed a net assimilation of nitrogen in warm months and net release in cool months, which offset the timing of nitrogen export relative to inputs. This work highlights that using a hydroecological, process‐based model reveals both the emergent relationships between watershed condition and response and the processes controlling those relationships.

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  4. Abstract

    Decades of research has concluded that the percent of impervious surface cover in a watershed is strongly linked to negative impacts on urban stream health. Recently, there has been a push by municipalities to offset these effects by installing structural stormwater control measures (SCMs), which are landscape features designed to retain and reduce runoff to mitigate the effects of urbanisation on event hydrology. The goal of this study is to build generalisable relationships between the level of SCM implementation in urban watersheds and resulting changes to hydrology. A literature review of 185 peer‐reviewed studies of watershed‐scale SCM implementation across the globe was used to identify 52 modelling studies suitable for a meta‐analysis to build statistical relationships between SCM implementation and hydrologic change. Hydrologic change is quantified as the percent reduction in storm event runoff volume and peak flow between a watershed with SCMs relative to a (near) identical control watershed without SCMs. Results show that for each additional 1% of SCM‐mitigated impervious area in a watershed, there is an additional 0.43% reduction in runoff and a 0.60% reduction in peak flow. Values of SCM implementation required to produce a change in water quantity metrics were identified at varying levels of probability. For example, there is a 90% probability (high confidence) of at least a 1% reduction in peak flow with mitigation of 33% of impervious surfaces. However, as the reduction target increases or mitigated impervious surface decreases, the probability of reaching the reduction target also decreases. These relationships can be used by managers to plan SCM implementation at the watershed scale.

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