Spatial and Temporal Variability in Stream Thermal Regime Drivers for Three River Networks During the Summer Growing Season.

Many cold-water dependent aquatic organisms are experiencing habitat and population declines from increasing water temperatures. Identifying mechanisms which drive local and regional stream thermal regimes facilitates restoration at ecologically relevant scales. Stream temperatures vary spatially and temporally both within and among river basins. We developed a modeling process to identify statistical relationships between drivers of stream temperature and covariates representing landscape, climate, and management-related processes. The modeling process was tested in 3 study areas of the Pacific Northwest USA during the growing season (May [start], August [warmest], September [end]). Across all months and study systems, covariates with the highest relative importance represented the physical landscape (elevation [1st], catchment area [3rd], main channel slope [5th]) and climate covariates (mean monthly air temperature [2nd] and discharge [4th]). Two management covariates (ground water use [6th] and riparian shade [7th]) also had high relative importance. Across the growing season (for all basins) local reach slope had high relative importance in May, but transitioned to a regional main channel slope covariate in August and September. This modeling process identified regionally similar and locally unique relationships among drivers of stream temperature. High relative importance of management-related covariates suggested potential restoration actions for each system.

Riparian vegetation shade restoration and loss effects on recent and future stream temperatures.

River temperatures are expected to increase this century harming species requiring cold-water habitat unless restoration activities protect or improve habitat availability. Local shading by riparian vegetation can cool water temperatures, but uncertainty exists over the scaling of this local effect to larger spatial extents. We evaluate this issue using a regional spatial stream network temperature model with covariates representing shade effects to predict mean August stream temperatures across 78,195 km of tributaries flowing into the Columbia River in the northwestern US. We evaluate nine scenarios predicting stream temperatures for three riparian shade conditions (current, restored, and no riparian vegetation) within three different climate periods (2000s, 2040s, and 2080s). Results suggest riparian shade restoration (2000s climate) could decrease mean August stream temperatures by 0.62°C across the study network. Under the same restored shade conditions, temperature predictions for tributaries at their confluence with the Columbia River range from 0.02-2.08°C cooler than under current shade conditions. The climate warming effect predicted for the 2040s and 2080s, however, is greater than the cooling effect from restoring riparian shade. Streams less than 10m bankfull width cooled more frequently with riparian shade restoration. In Oregon, the proportion of fish habitat for salmon and trout rearing and migration that meet temperature numeric water quality criteria could be increased by 20% under restored shade conditions although net habitat declines may still occur in the future. We conclude riparian vegetation restoration could partially mitigate future warming and help maintain cold-water habitats that function as thermal refuges if implemented strategically.

Integrating thermal infrared stream temperature imagery and spatial stream network models to understand natural spatial thermal variability in streams.

Under a warmer future climate, thermal refuges could facilitate the persistence of species relying on cold-water habitat. Often these refuges are small and easily missed or smoothed out by averaging in models. Thermal infrared (TIR) imagery can provide empirical water surface temperatures that capture these features at a high spatial resolution (<1 m) and over tens of kilometers. Our study examined how TIR data could be used along with spatial stream network (SSN) models to characterize thermal regimes spatially in the Middle Fork John Day (MFJD) River mainstem (Oregon, USA). We characterized thermal variation in seven TIR longitudinal temperature profiles along the MFJD mainstem and compared them with SSN model predictions of stream temperature (for the same time periods as the TIR profiles). TIR profiles identified reaches of the MFJD mainstem with consistently cooler temperatures across years that were not consistently captured by the SSN prediction models. SSN predictions along the mainstem identified ~80% of the 1-km reach scale temperature warming or cooling trends observed in the TIR profiles. We assessed whether landscape features (e.g., tributary junctions, valley confinement, geomorphic reach classifications) could explain the fine-scale thermal heterogeneity in the TIR profiles (after accounting for the reach-scale temperature variability predicted by the SSN model) by fitting SSN models using the TIR profile observation points. Only the distance to the nearest upstream tributary was identified as a statistically significant landscape feature for explaining some of the thermal variability in the TIR profile data. When combined, TIR data and SSN models provide a data-rich evaluation of stream temperature captured in TIR imagery and a spatially extensive prediction of the network thermal diversity from the outlet to the headwaters.

Using Multiobjective Optimization to Inform Green Infrastructure Decisions as Part of Robust Integrated Water Resources Management Plans.

Uncertainty in the impacts of climate change and development on freshwater resources pose significant challenges for water resources management. Integrated and adaptive approaches to water resources management are a promising means of addressing uncertainty that afford flexibility in balancing multiple stakeholder objectives. However, guidance on designing such plans is lacking. In this study, we use multi-objective optimization to strategically incorporate green infrastructure (GI) into water resources management plans that maximize reductions in nutrient loads, minimize stormwater runoff, and minimize costs. Robust decision-making methods are applied to the resulting plan options to evaluate how optimized GI implementation varies under different possible future climates and to determine which solutions would be robust under a range of plausible future conditions. We demonstrate these coupled methods using a case study in southern Massachusetts, to address water quality issues related to point and nonpoint source nutrients in a rapidly developing watershed.

Recent Changes in Nitrogen Sources and Load Components to Estuaries of the Contiguous United States.

Regional Spatially Referenced Regressions on Watershed models were used to update 2002 delivered nitrogen (N) loads to estuaries of the contiguous US for 2011, supplemented by direct estuarine atmospheric deposition from the Community Multiscale Air Quality Model. Median 2011 watershed N yields were greatest for the Puget Trough, Virginian. and Oregon-Washington-Vancouver Coast marine ecoregions (MEs; 13. 7, 11.0, and 9.9 kg N/ha watershed/year, respectively); intermediate for the Floridian, Southern California Bight, and Northern California MEs (4.4-6.3 kg N/ha watershed/year); and lowest for the Northern Gulf of Mexico, Carolinian, and Gulf of Maine MEs (2.4-3.2 kg N/ha watershed/year). Dominant sources varied across marine ecoregions, with direct atmospheric deposition as the dominant source only in the far northern Gulf of Maine ME. Delivered N loads from atmospheric deposition have significantly decreased (p < 0.05) for most estuaries on the Atlantic and Gulf coasts for 2002-2012. Estimated point source delivered N loads for 2002-2012 increased for most estuaries with upstream treatment plants, with estimated loads to only seven estuaries decreasing by more than 50%. Urban runoff increased for most estuaries in the Puget Trough and Carolinian MEs and either increased or had no significant trend for the remaining marine ecoregions. The magnitude of change in total N delivered loads is uncertain due to incomplete monitoring for most minor dischargers. In areas with increased population growth and decreases in agricultural land, decreasing agricultural fertilizer inputs have been insufficient to offset increases in urban runoff.

Statistical Models to Predict and Assess Spatial and Temporal Low-Flow Variability in New England Rivers and Streams.

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 to 2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology and soils. These models performed better than most USGS 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 Index (NAO), 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, MA, a sensitive watershed undergoing rapid development, projected that low flow metrics will decrease over the next 50 years.

Can sediment total organic carbon and grain size be used to diagnose organic enrichment in estuaries?

Eutrophication (i.e., nutrient enrichment, organic enrichment, and oxygen depletion) is one of the most common sources of impairment in Clean Water Act 303(d)-listed waters in the United States. Although eutrophication can eventually cause adverse effects to the benthos, it may be difficult to diagnose. Sediment organic carbon (OC) content has been used as an indicator of enrichment in sediments, but the amount of surface area available for carbon adsorption must be considered. We investigated the utility of the relationship between OC and sediment grain size as an indicator of eutrophication. Data from the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program was used to test this relationship. However, anthropogenic contaminants are also capable of causing adverse effects to the benthos and often co-occur with elevated levels of OC. Contaminant analysis and toxicity tests were not consistently related to enrichment status as defined by relationship between total OC and grain size. Although variability in response occurred, reflecting the variance in the water column factors (dissolved oxygen, chlorophyll a, and nutrients) and limited sample sizes, the data supported the hypothesis that sites designated as enriched were eutrophied. Dissolved oxygen levels were reduced at enriched sites, whereas chlorophyll a and nutrients were higher at enriched sites. This suggests that the relationship of OC to grain size can be used as a screening tool to diagnose eutrophication.

How probability survey data can help integrate 305(b) and 303(d) monitoring and assessment of state waters.

Section 305(b) of the United States' Clean Water Act (CWA) requires states to assess the overall quality of waters in the states, while Section 303(d) requires states to develop a list of the specific waters in their state not attaining water quality standards (a.k.a impaired waters). An integrated, efficient and cost-effective process is needed to acquire and assess the data needed to meet both these mandates. A subset of presentations at the 2002 Environmental Monitoring and Assessment Program (EMAP) Symposium provided information on how probability data, tools and methods could be used by states and other entities to aid in development of their overall assessment of condition and list of impaired waters. Discussion identified some of the technical and institutional problems that hinder the use of EMAP methods and data in the analysis to identify impaired waters as well as development needs to overcome these problems.

Watershed-based survey designs.

Watershed-based sampling design and assessment tools help serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional conditions to meet Section 305(b), identification of impaired water bodies or watersheds to meet Section 303(d), and development of empirical relationships between causes or sources of impairment and biological responses. Creation of GIS databases for hydrography, hydrologically corrected digital elevation models, and hydrologic derivatives such as watershed boundaries and upstream-downstream topology of subcatchments would provide a consistent seamless nationwide framework for these designs. The elements of a watershed-based sample framework can be represented either as a continuous infinite set defined by points along a linear stream network, or as a discrete set of watershed polygons. Watershed-based designs can be developed with existing probabilistic survey methods, including the use of unequal probability weighting, stratification, and two-stage frames for sampling. Case studies for monitoring of Atlantic Coastal Plain streams, West Virginia wadeable streams, and coastal Oregon streams illustrate three different approaches for selecting sites for watershed-based survey designs.

Landscape character and fish assemblage structure and function in western Lake Superior streams: general relationships and identification of thresholds.

As part of a comparative watershed project investigating land-cover/land-use disturbance gradients for streams in the western Lake Superior Basin, we examined general relationships between landscape character and fish assemblage structure and function. We also examined the shape of those relationships to identify discontinuity thresholds where small changes in landscape character were associated with marked shifts in the fish assemblages. After completing a geographic analysis of second- and third-order watersheds in the western Lake Superior drainage, we randomly selected 48 streams along mature forest and watershed storage gradients in 2 hydrogeomorphic regions as our study sites. During the summers of 1997 and 1998, we used electrofishing to sample fish assemblages from each stream. Each of the landscape factors was significantly associated with fish assemblage structure and function based on analysis of covariance. Watershed storage was related to the greatest number of fish assemblage characteristics, but hydrogeopmorphic region and mature forest cover were strongly associated as well. The hydrogeomorphic region also mediated relationships between watershed character and fish assemblages. Discontinuity thresholds for our fish assemblages averaged 11% for watershed storage and 50% for watershed mature forest cover based on piecewise regression analysis. Although many of the landscape-fish relationships might have been manifest through effects on in-stream habitat, our results highlight the importance of management and land-use planning decisions at the watershed and landscape scales.