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Statistical Models to Predict and Assess Spatial and Temporal Low-Flow Variability in New England Rivers and Streams
Citation:
Detenbeck, N. Statistical Models to Predict and Assess Spatial and Temporal Low-Flow Variability in New England Rivers and Streams. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, 54(5):1087-1108, (2018). https://doi.org/10.1111/1752-1688.12673
Impact/Purpose:
Summer low flows are a key characteristic of aquatic habitat which often limit the distribution of fish species, either directly by determining the amount of available habitat, or indirectly, by influencing other water quality parameters such as temperature and dissolved oxygen. Thus, low flows are regulated through a variety of mechanisms, including water quality criteria for flows, as well as water withdrawal permits and dam relicensing. Low flows also help to establish limits for other permits and criteria by defining worst-case conditions with low dilution. Urban development can impact flow regimes by increasing runoff and decreasing groundwater recharge. Impacts on flow regimes can be moderated through use of green infrastructure stormwater best management practices such as rain gardens, permeable pavement, and green roofs. In order to determine the reference and impacted flow conditions of streams and rivers across New England, statistical models predicting summer flows and base flows were generated. Separate models were developed to predict average conditions as well as interannual changes in flows, allowing us to predict time series for base flow and to evaluate trends in baseflows and related flow metrics. These models will allow managers to describe reference condition and to set restoration targets for implementation of natural and constructed green infrastructure.
Description:
In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985–2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology, and soils. These models performed better than most United States Geological Survey models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation (NAO) index, and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile [Q10] and minimum 3‐in‐5 year average flows). The first metric is commonly used in assessing risk to low‐flow conditions over time, while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985–2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, Massachusetts, a sensitive watershed undergoing rapid development, projected that low‐flow metrics will decrease over the next 50 years.
URLs/Downloads:
DOI: Statistical Models to Predict and Assess Spatial and Temporal Low-Flow Variability in New England Rivers and Streams