Item talk:Q60929

{"@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "USGS Numbered Series", "name": "Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams", "identifier": [{"@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "sir20135089", "url": "https://pubs.usgs.gov/publication/sir20135089"}, {"@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70047766}, {"@type": "PropertyValue", "propertyID": "DOI", "value": "10.3133/sir20135089", "url": "https://doi.org/10.3133/sir20135089"}], "inLanguage": "en", "isPartOf": [{"@type": "CreativeWorkSeries", "name": "Scientific Investigations Report"}], "datePublished": "2013", "dateModified": "2018-11-01", "abstract": "More than 300 ambient monitoring sites in New Jersey have been identified by the New Jersey Department of Environmental Protection (NJDEP) in its integrated water-quality monitoring and assessment report (that is, the 305(b) Report on general water quality and 303(d) List of waters that do not support their designated uses) as being impaired with respect to aquatic life; however, no unambiguous stressors (for example, nutrients or bacteria) have been identified. Because of the indeterminate nature of the broad range of possible impairments, surrogate measures that more holistically encapsulate the full suite of potential environmental stressors need to be developed. Streamflow alteration resulting from anthropogenic changes in the landscape is one such surrogate. For example, increases in impervious surface cover (ISC) commonly cause increases in surface runoff, which can result in \u201cflashy\u201d hydrology and other changes in the stream corridor that are associated with streamflow alteration. The NJDEP has indicated that methodologies to support a hydrologically based Total Maximum Daily Load (hydro-TMDL) need to be developed in order to identify hydrologic targets that represent a minimal percent deviation from a baseline condition (\u201cminimally altered\u201d) as a surrogate measure to meet criteria in support of designated\u00a0uses.The primary objective of this study was to develop an applicable hydro-TMDL approach to address aquatic-life impairments associated with hydrologic alteration for New Jersey streams. The U.S. Geological Survey, in cooperation with the NJDEP, identified 51 non- to moderately impaired gaged streamflow sites in the Raritan River Basin for evaluation. Quantile regression (QR) analysis was used to compare flow and precipitation records and identify baseline hydrographs at 37 of these sites. At sites without an appropriately long period of record (POR) or where a baseline hydrograph could not be identified with QR, a rainfall-runoff model was used to develop simulated baseline hydrographs. The hydro-TMDL approach provided an opportunity to evaluate proportional differences in flow attributes between observed and baseline hydrographs and to develop complementary flow-ecology response relations at a subset of Raritan River Basin sites where available flow and ecological information\u00a0overlapped.The New Jersey Stream Classification Tool (NJSCT) was used to determine the stream class of all 51 study sites by using either an observed or a simulated baseline hydrograph. Two New Jersey stream classes (A and C) were evaluated to help characterize the unique hydrology of the Raritan River Basin. In general, class C streams (1.99\u201340.7\u00a0square miles) had smaller drainage areas than class A streams (0.7\u2013785\u00a0square miles). Many of the non-impaired and moderately impaired class A and C streams in the Raritan River Basin were found to have significant hydrologic alteration as indicated by numerous flow values that fell outside the established 25th-to-75th- and the more conservative 40th-to-60th-percentile boundaries. However, percent deviations for the class C streams (defined as moderately stable streams with moderately high base-flow contributions) were, in general, much larger than those for the class A streams (defined as semiflashy streams characterized by moderately low base flow). The greater deviations for class C streams in the hydro-TMDL assessments likely resulted from comparisons that were based solely on simulated baseline hydrographs, which were developed without considering any anthropogenic influences in the basin. In contrast, comparisons for many of the class A streams were made by using an observed baseline, which already includes an implicit level of ISC and other human influences on the\u00a0landscape.By using the hydro-TMDL approach, numerous flow deviations were identified that were indicative of streams that are highly regulated by reservoirs or dams, streams that are affected by increasing amounts of surface runoff resulting from ISC, and streams that are affected by water abstraction (that is, groundwater or surface-water withdrawals used for agricultural and human supply). Eight of the reservoir- and (or) dam-affected sites showed flow deviations that are indicative of flow-managed systems. For example, indices that account for the timing and magnitude of high and low flows were often found to fall outside the 25th-to-75th-percentile range. In general, at regulated class C streams, annual summer low flows are arriving later and tend to be lower, and high flows are arriving earlier with higher magnitudes of longer duration. At class A streams, high and low flows are arriving later with an overall increase in discharge with respect to the prereservoir baseline\u00a0conditions.The drainage basins of eight of the study sites had large values of ISC (>10 percent), most likely as a result of expanding urban development. In general, the magnitude and frequency of high flows at class A and C sites with high ISC are increasing and were commonly found to fall outside the 25th-to-75th-percentile range. Additionally, magnitudes of low flows are becoming lower and, although the timing of high flows was highly variable, low-flow events appeared to be arriving earlier than would be expected under normal low-flow conditions. Three of the study sites appeared to be affected by hydrologic changes associated with water abstraction. At these sites, the timing of flows appeared to be altered. For example, low flows tended to arrive earlier and high flows arrived later at two of the three sites. Additionally, the magnitude and duration of low flows were commonly less than the 25th-percentile value and the duration of high flows appeared to\u00a0increase.A reduced set of hydrologic and ecological variables was used to develop univariate and multivariate flow-ecology response models for the aquatic-invertebrate assemblage. Many hydrologic variables accounting for the duration, magnitude, frequency, and timing of flows were significantly correlated with ecological response. Multiple linear regression (MLR) models were developed to provide a more holistic evaluation of the combined effects of hydrologic alteration and to identify models with two or three hydrologic variables that account for a significant proportion of the variability in invertebrate-assemblage condition as represented by assemblage metric scores. MLR models, derived on the basis of hydrologic attributes, accounted for 35 to 75 percent of the variability in assemblage\u00a0condition.The hydro-TMDL method developed herein for non- to moderately impaired Raritan River Basin streams utilizes a \u201csurrogate\u201d approach in place of the traditional \u201cpollutant of concern\u201d approach commonly used for TMDL development. Managers can use the results obtained by using the hydro-TMDL method to offset the effects of impervious-surface runoff and altered streamflow and to implement measures designed to achieve the necessary load reductions for the \u201cpollutant of concern\u201d (that is, percentage deviations of stream-class-specific flow-index values outside the established 25th-to-75th-percentile range). In this case, such deviations could represent all or a subset of the altered flow indices that prevent the stream from meeting designated aquatic-life criteria. This hydro-TMDL uses a reference, or attainment stream approach for developing the TMDL endpoint. That is, either observed or simulated baseline hydrographs were selected as appropriate reference conditions on the basis of results of QR analysis and watershed modeling procedures, respectively. For any stream in the Raritan River Basin evaluated as part of this study, the hydro-TMDL can be expressed as the greatest amount of deviation in flow a stream can exhibit without violating the stream\u2019s designated aquatic-life criteria. Use of this surrogate approach is appropriate because flows that fall outside the established percentile ranges are ultimately a function of many anthropogenic modifications of the landscape, including the amount of stormwater runoff generated from impervious surfaces within a given basin, the presence of manmade structures designed to retain or divert water, the magnitude of ground- and surface-water abstraction, and the presence of water-supply processes implemented to support human needs. In addition, the stream-type-specific flow indices used as the basis for the hydro-TMDL approach are useful for representing the hydrologic conditions of class A and C streams/basins because they incorporate the full spectrum of flow conditions (very low to very high) that occur in the stream system over a long period of time, as well as those flow properties that change as a result of seasonal\u00a0variation.Ultimately, an estimate of the maximum percentage flow reduction that could be allowed will be needed to address the aquatic-life impairments in many of the study streams in the Raritan River Basin and will be necessary for identifying appropriate target flow conditions for hydro-TMDL implementation. As described in this report, a target flow value equal to the 25th- or 75th-percentile flow rate could be selected as the point useful for setting specific hydrologic targets. This selection, however, is a management decision that could vary depending on the designated use of the stream or other regulatory factors (for example, water-supply protection, trout production, antidegradation policies, or special protection designations). In New Jersey streams where no unambiguous stressors can be identified, State monitoring agencies, such as the NJDEP, could choose to require the implementation of a flow-based TMDL that not only supports designated uses, but meets the regulatory requirements under the Clean Water Act, and represents a balance between water supply intended to meet human needs and the conservation of ecosystem\u00a0integrity.", "description": "viii, 86 p.", "publisher": {"@type": "Organization", "name": "U.S. Geological Survey"}, "author": [{"@type": "Person", "name": "Kennen, Jonathan jgkennen@usgs.gov", "givenName": "Jonathan", "familyName": "Kennen", "email": "jgkennen@usgs.gov", "identifier": {"@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-5426-4445", "url": "https://orcid.org/0000-0002-5426-4445"}, "affiliation": [{"@type": "Organization", "name": "New Jersey Water Science Center", "url": "https://www.usgs.gov/centers/new-jersey-water-science-center"}]}, {"@type": "Person", "name": "Colarullo, Susan J. colarull@usgs.gov", "givenName": "Susan J.", "familyName": "Colarullo", "email": "colarull@usgs.gov", "identifier": {"@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-4504-0068", "url": "https://orcid.org/0000-0003-4504-0068"}, "affiliation": [{"@type": "Organization", "name": "New Jersey Water Science Center", "url": "https://www.usgs.gov/centers/new-jersey-water-science-center"}]}, {"@type": "Person", "name": "Reilly, Pamela A. jankowsk@usgs.gov", "givenName": "Pamela A.", "familyName": "Reilly", "email": "jankowsk@usgs.gov", "identifier": {"@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-2937-4490", "url": "https://orcid.org/0000-0002-2937-4490"}, "affiliation": [{"@type": "Organization", "name": "New Jersey Water Science Center", "url": "https://www.usgs.gov/centers/new-jersey-water-science-center"}]}, {"@type": "Person", "name": "Riskin, Melissa L. mriskin@usgs.gov", "givenName": "Melissa L.", "familyName": "Riskin", "email": "mriskin@usgs.gov", "identifier": {"@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0001-6499-3775", "url": "https://orcid.org/0000-0001-6499-3775"}, "affiliation": [{"@type": "Organization", "name": "New Jersey Water Science Center", "url": "https://www.usgs.gov/centers/new-jersey-water-science-center"}, {"@type": "Organization", "name": "WMA - Earth System Processes Division", "url": "https://www.usgs.gov/mission-areas/water-resources"}, {"@type": "Organization", "name": "WMA - Observing Systems Division", "url": "https://www.usgs.gov/mission-areas/water-resources"}]}], "funder": [{"@type": "Organization", "name": "New Jersey Water Science Center", "url": "https://www.usgs.gov/centers/new-jersey-water-science-center"}], "spatialCoverage": [{"@type": "Place", "additionalType": "country", "name": "United States", "url": "https://geonames.org/6252001"}, {"@type": "Place", "additionalType": "state", "name": "New Jersey", "url": "https://geonames.org/5101760"}, {"@type": "Place", "geo": [{"@type": "GeoShape", "additionalProperty": {"@type": "PropertyValue", "name": "GeoJSON", "value": {"type": "FeatureCollection", "features": [{"type": "Feature", "properties": {}, "geometry": {"type": "Polygon", "coordinates": [[[-75.25, 40], [-74.25, 40], [-74.25, 41], [-75.25, 41], [-75.25, 40]]]}}]}}}, {"@type": "GeoCoordinates", "latitude": 40.5, "longitude": -74.75}]}]}