Validation of rapid assessment methods to determine streamflow duration classes in the Pacific Northwest, USA.

Environmental Management DOI 10.1007/s00267-015-0466-4

Validation of Rapid Assessment Methods to Determine Streamflow Duration Classes in the Pacific Northwest, USA Tracie-Lynn Nadeau1 • Scott G. Leibowitz2 • Parker J. Wigington Jr.2 • Joseph L. Ebersole2 • Ken M. Fritz3 • Robert A. Coulombe4 • Randy L. Comeleo2 Karen A. Blocksom2

•

Received: 23 November 2013 / Accepted: 21 March 2015 Ó Springer Science+Business Media New York (outside the USA) 2015

Abstract United States Supreme Court rulings have created uncertainty regarding U.S. Clean Water Act (CWA) authority over certain waters, and established new data and analytical requirements for determining CWA jurisdiction. Thus, rapid assessment methods are needed that can differentiate between ephemeral, intermittent, and perennial streams. We report on the validation of several methods. The first (Interim Method) was developed through best professional judgment (BPJ); an alternative (Revised Method) resulted from statistical analysis. We tested the Interim Method on 178 study reaches in Oregon, and constructed the Revised Method based on statistical analysis of the Oregon data. Next, we evaluated the regional applicability of the methods on 86 study reaches across a variety of hydrologic landscapes in Washington and Idaho. During the second phase, we also compared the

Revised Method with a similar approach (Combined Method) based on combined field data from Oregon, Washington, and Idaho. We further compared field-based methods with a GIS-based approach (GIS Method) that used the National Hydrography Dataset and a synthetic stream network. Evaluations of all methods compared results with actual streamflow duration classes. The Revised Method correctly determined known streamflow duration 83.9 % of the time, versus 62.3 % accuracy of the Interim Method and 43.6 % accuracy for the GIS-based approach. The Combined Method did not significantly outperform the Revised Method. Analysis showed biological indicators most accurately discriminate streamflow duration classes. While BPJ established a testable hypothesis, this study illustrates the importance of quantitative field testing of rapid assessment methods. Results support a consistent method applicable across the Pacific Northwest.

Parker J. Wigington Jr. is now retired.

Keywords Streamflow duration Ephemeral Intermittent Rapid assessment Clean Water Act jurisdiction Macroinvertebrate indicators

Electronic supplementary material The online version of this article (doi:10.1007/s00267-015-0466-4) contains supplementary material, which is available to authorized users. & Tracie-Lynn Nadeau [email protected] 1

U.S. EPA, Region 10, 805 SW Broadway, Suite 500, Portland, OR 97205, USA

2

Western Ecology Division, National Health and Environmental Effects Research Laboratory, U.S. EPA, 200 SW 35th Street, Corvallis, OR 97333, USA

3

Ecological Exposure Research Division, National Exposure Research Laboratory, U.S. EPA, 26 West Martin Luther King Dr., Cincinnati, OH 45268, USA

4

Western Ecology Division, National Health and Environmental Effects Research Laboratory, CSS-Dynamac, 200 SW 35th Street, Corvallis, OR 97333, USA

Introduction Duration, frequency, and timing of streamflow or drying, as well as flow magnitude, are fundamental properties of streams (Poff and Ward 1989; Winter et al. 1998), which can influence the structure and function of stream ecosystems (e.g., Chadwick and Huryn 2007; Fritz et al. 2008; Austin and Strauss 2011; Datry 2012). Watershed geology, climate, topography, soils, vegetation, and human activities can all influence streamflow (Winter et al. 1998; Winter 2007). Water to support streams can originate from numerous sources within a watershed including overland flow

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from rainfall or snowmelt, shallow subsurface flow through the unsaturated zone, and groundwater discharge (Winter 2007). Streams may be perennial, intermittent, or ephemeral. Perennial streams flow year-round during a typical year, receiving appreciable quantities of water from numerous sources but with consistent groundwater inputs required throughout the year (Winter et al. 1998; Winter 2007). In cases where groundwater aquifers are unable to supply sufficient quantities of water, intermittent streams cease to flow during dry periods (Mosley and McKerchar 1993; Rains and Mount 2002; Rains et al. 2006). Ephemeral streams flow only in direct response to precipitation including rainstorms, rain on snow events, or snowmelt. They do not receive appreciable quantities of water from any other source, and their channels are, at all times, above local water tables (Gordon et al. 2004; McDonough et al. 2011). The United States Clean Water Act (CWA), enacted in 1972, has the broad mandate to ‘‘restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.’’ Prior to 2001, any tributary to a navigable-in-fact water was regarded as jurisdictional under the CWA (Wood 2004). However, U.S. Supreme Court rulings in 2001 (Solid Waste Agency of Northern Cook County v U.S. Army Corps of Engineers, 531 US 159; SWANCC) and 2006 (Rapanos v United States, 547 US 715; Rapanos) created uncertainty regarding federal CWA authority over certain waters, including some ephemeral and intermittent streams (Downing et al. 2003; Nadeau and Leibowitz 2003; Nadeau and Rains 2007; Leibowitz et al. 2008). While CWA Section 404, which requires a permit for the discharge of dredged or fill material into waters of the U.S., triggered these U.S. Supreme Court cases, critically important is that the definition of ‘‘waters of the U.S.’’ affects all CWA programs, not just Section 404 (Downing et al. 2003). The Rapanos decision, in particular, established new data and analytical requirements for determining whether a particular water is covered under the CWA. In 2008, the U.S. Environmental Protection Agency (EPA) and U.S. Army Corps of Engineers (Corps), the coadministering agencies of CWA Section 404, issued guidance to EPA and Corps field staff implementing the Rapanos decision (USEPA/USACE 2008). Under the 2008 Rapanos guidance, the federal agencies assert jurisdiction over nonnavigable tributaries of traditional navigable waters that are ‘relatively permanent’ (in general practice, streams considered perennial and intermittent) according to the so-called Justice Antonin Scalia standard. For the agencies to assert jurisdiction over non-navigable tributaries that are not ‘relatively permanent’ (in general practice, streams considered ephemeral), they require a ‘significant nexus’ determination which results from an assessment of whether or not the stream significantly influences the chemical, physical, and biological integrity of downstream navigable waters. The

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federal Rapanos guidance (USEPA/USACE 2008) has posed a challenge to EPA and Corps field staff and to the regulated community in determining whether a particular water is jurisdictional under the CWA (USEPA 2009; Caruso 2011). This is partly due to the lack of widely accepted rapid assessment methods to determine streamflow duration classes of non-navigable tributary streams. Given the many drivers for development of methods to assess streamflow duration—such as informing implementation of state and local mandates and ordinances (e.g., riparian buffer requirements), improving predictability for ecological assessment of streams to set appropriate water quality expectations, and prioritization of restoration and protection efforts—several state and local governmental agencies have implemented regionally specific, rapid fieldbased assessment procedures for characterizing flow duration in streams. One such method is the North Carolina Division of Water Quality’s protocol (NCDWQ 2010), which is periodically updated and has been in use for more than a decade. An Oregon-specific method was developed by the Corps and the EPA to distinguish between ephemeral, intermittent, and perennial streams based, in part, on the experiences and progress of the North Carolina method (NCDWQ 2005) in combination with expert consultation. Following peer-review and an initial pilot study of the method in the major physiographic and climatic regions of Oregon, the Streamflow Duration Assessment Method for Oregon was made available as an interim version (Interim Method; Topping et al. 2009). Rapid assessment methods, including those for determining streamflow duration, often rely to some extent on best professional judgment (BPJ) for their development (e.g., indicator selection, attribute weighting, and categorical thresholds) due to constraints in staff, funding, and time which generally make intensive hydrological monitoring on a site-by-site basis infeasible. Therefore, field validation of rapid assessment methods is necessary to assure that results are accurate and that methodologies are robust. At a minimum, results of a method should be tested against expert opinion. However, to assess accuracy, a streamflow duration assessment method should be compared against true streamflow duration classes, where ‘truth’ is determined using independently and objectively defined field criteria (Stauffer and Goldstein 1997). Fritz et al. (2008) assessed the utility of existing rapid field-based tools to classify streamflow duration outside the regions for which they were developed. They applied three methods developed in the east and midwest to headwater streams across humid regions in the midwestern, northwestern, and northeastern U.S. These authors found the methods could differentiate ephemeral from perennial and intermittent sites, but not between intermittent and perennial sites. They concluded that the complexity of factors


influencing hydrologic permanence precludes a comprehensive hydrologic map or simple nationwide indicator of streamflow duration, and recommend regional testing to confirm and adapt indices for regional relevancy. A more recent study (Fritz et al. 2013b) evaluated the North Carolina method’s ability to classify the streamflow permanence of forested streams from Piedmont and Southeastern Plains ecoregions in South Carolina. Again, scores did not differ between the intermittent and perennial reaches compared in the study, but did clearly distinguish them from ephemeral reaches. Scores were seasonally stable between consecutive wet and dry seasons in their study, and results were used to calibrate and fine-tune method thresholds discriminating between streamflow duration classes. The objectives of this study were to (1) measure the accuracy of the Interim Method, developed through BPJ, in different hydrologic landscapes and seasons; (2) determine if accuracy results could be improved by developing an alternative method based on statistical analysis of field data; and (3) compare the accuracy of field-based methods with a GIS-based approach that used the National Hydrography Dataset (NHD) and a synthetic stream network.

Methods The Interim Method includes 21 indicators, or attributes, of streamflow duration: seven geomorphic, five hydrologic, and nine biologic (Table 1; see Topping et al. 2009 for a detailed description of indicators). Ordinal scoring of attributes is based on the premise that flow duration or persistence of water is related to the degree (i.e., strong, moderate, weak, or absent) to which an attribute is observable. The attribute scores are numerically weighed to reflect the perceived relative utility of the attributes. The numerical values for these 21 attributes are summed, and this total score is then compared to threshold values that separate perennial, intermittent, and ephemeral classes. In addition, the Interim Method classifies streams as at least intermittent (i.e., intermittent or perennial) based on the presence of Single Indicator measures: fish, or water-dependent life stages of specific herpetological and macroinvertebrate species (see Topping et al. 2009). The described study consisted of two phases. In the first phase, we undertook a 2-year field validation study of the Interim Method in Oregon. We then constructed a new method (Revised) based on statistical analysis of the Oregon data identifying the best indicators to discriminate flow duration classes. In the second phase, we conducted a 1-year field study of the Interim and Revised methods in Washington and Idaho to evaluate the applicability of the methods developed in Oregon to other areas of the Pacific Northwest. During this second phase, we also compared the

Revised Method, which was developed from Oregon data alone, with a similar approach (Combined Method) that was based on combined field data from Oregon, Washington, and Idaho. Finally, we compared results from these three field-based methods with a fourth approach (GIS Method) that used the NHD and a synthetic stream network. Using the combined data from both phases, our evaluations compare results of the four methods with actual streamflow duration classes, as determined by independently and objectively defined field criteria. Study Area Located in the northwestern United States, Oregon, Washington, and Idaho are states with very diverse hydrologic conditions (Fig. 1). The Cascade Mountain Range runs north–south through Oregon and Washington, creating a strong demarcation between the wet western and the dry eastern sides of the ranges (Loy et al. 2001; Jackson and Kimerling 2003; Elsner et al. 2010). Elevation ranges from sea level along the Pacific coast to over 4000 m in the Cascade Mountain Range. Moisture conditions west of the Cascades range from the moderately wet Willamette Valley (760–1520 mm average annual precipitation) to the wetter coastal areas (1780–2290 mm) and the very wet rain forests of the Oregon Coast Range (2540–5080 mm) and Washington’s Olympic Peninsula (*3470 mm). In contrast, areas east of the Cascades are generally dry (200–380 mm) except at high mountain elevations. Idaho climate and hydrology are also extremely varied. Northern and north-central Idaho are dominated by the Bitterroot Mountains, part of the Rocky Mountain Range, and much of southern and south-central Idaho belong to the arid Snake River Plain and Basin and Range Province. The elevation range is also extreme, from about 220 m at the confluence of the Clearwater and Snake Rivers to 3859 m at the highest peak (Jackson and Kimerling 2003). Winter precipitation maximums and midsummer minimums range from annual averages of 1016–1270 mm at higher elevations to less than 254 mm in the southern plains and valleys. In the Pacific Northwest, the delivery of precipitation is generally greatest during the winter months, resulting in fairly distinct wet winter/spring and dry summer seasons. The dominance of seasonal winter precipitation, as rain or snow, overlays a variety of regional climates (Jackson and Kimerling 2003). Sampling Design In both phases of the study, we had three study design and site selection goals: (1) to have a relatively balanced sample of perennial, intermittent, and ephemeral streams; (2) to test the different streamflow duration assessment

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Environmental Management Table 1 Description of Interim Method indicators (grouped by type), summary and single indicator metrics, and supplemental indicators Indicator

Brief assessment description

Weight

Geomorphica B&B—continuous bed and bank

Clearly defined; having a discernible bed and bank

Primary

Deposition—depositional features

Depositional features such as bars or fresh deposits of alluvial materials in channel or on floodplain; evidence of active floodplain at bankfull elevation

Primary

Erosion—erosional features

Evidence of fluvial erosion, including undercut banks, scour marks, channel downcutting, and other features of channel incision

Secondary

Headcuts—headcuts and grade controls

Presence of headcuts and/or grade controls

Secondary

Sinuosity—sinuosity

Total stream length as measured along thalweg divided by straight line valley length

Primary

Structure—in-channel structure/ organized sequences

Regular sequence of coherent, organized fluvial erosion/deposition structural features

Primary

Texture—soil texture/substrate sorting

Stream substrate texture differs from adjacent floodplain soil or evidence of sorting of stream substrate materials

Primary

Hydrologica Debris—debris piles and wrack lines

Accumulation of debris piles or lines in channel or active floodplain

Secondary

GW—groundwater (wet)/Hyporheic (dry)

Groundwater discharge to stream, or saturated hyporheic zone

Primary

Leaflitter—leaf litter/loose debris distribution

Leaves or other aerially deposited debris accumulating in thalweg

Secondary

Redox—redoximorphic features in toe of bank

Soil redoximorphic features in toe of bank, base of headcuts, or in hyporheic zone

Secondary

Springs—springs and seeps

Presence of springs and/or seeps in, or upstream, of reach

Primary

a

Biologic

Amph_M09—amphibians

Presence of water-dependent life cycle stages of herpetological species

Secondary

Bacteria—iron-oxidizing activity

Presence of orange-red flocculent material or oily sheen associated with microbial ironoxidation

Primary

Fish—fish

Presence of fish

Primary

Lichen—lichen lineb

Distinct line on streambed rocks, or banks, below which no lichen grows

Secondary

Macro_M09—macroinvertebrates Mosses—streamer mosses and algal mats

Presence of aquatic macroinvertebrates with perennial or intermittent indicator status Presence of streamer mosses or algal mats in streambed

Primary Secondary

Riparian—riparian corridorb

Distinct change in vegetation between the surrounding uplands and riparian zone/corridor

Primary

Roots—fibrous roots/rooted plants in thalweg

Presence of fibrous roots of woody upland plants, or rooted herbaceous upland plants, growing in the thalweg

Primary

Wetl_pl_M09—wetland plants in/ near streambed

Indicator status of most hydrophytic plant found in streambed or within one half channel width of streambank

Primary

Summary and single indicator metrics Amph_M08—amphibians M08c

Amphibian indicator based on an earlier draft version of the Interim Method

–

Macro_M08—macroinvertebrates M08c

Macroinvertebrates indicator based on an earlier draft version of the Interim Method

–

Macro_M09b—macroinvertebrates M09b

Sum of Macro_M09 and Per_macro_present

–

Per_macro_present—perennial macroinvertebrates present

Perennial macroinvertebrate presence (1) or absence (0)

–

SI_amph—amphibian single

Amphibian single indicator presence (1) or absence (0) as defined by the Interim Method

–

SI_fish—fish single indicator

Fish single indicator presence (1) or absence (0) as defined by the Interim Method

–

SI_macro—macroinvertebrate single indicator

Macroinvertebrate single indicator presence (1) or absence (0) as defined by the Interim Method

–

Tot_all_M09—total all

Sum of all 21 Interim Method indicators

–

Tot_bio_M09—total biology

Sum of the biology indicators (Wetl_pl_09, roots, mosses, bacteria, Macro_M09, Amph_M09, fish, lichen, riparian)

–

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Environmental Management Table 1 continued Indicator

Brief assessment description

Weight

Tot_geo_M09—total geomorphology

Sum of the geomorphology indicators (B&B, structure, texture, erosion, deposition, headcuts) excluding sinuosity

–

Tot_hyd—total hydrology

Sum of the hydrology indicators (GW, springs, leaflitter, debris, redox)

–

Visual estimation of percentage of reach length where the streambed is dominated by bedrock

–

Supplemental indicators %Bedrock—streambed bedrock Basom—basommatophora

Basommatophora abundance category (0, 1–5, 6–20, 21–100, [ 100)

–

Coleop—coleoptera

Coleoptera abundance category (0, 1–5, 6–20, 21–100, [ 100)

–

Decap—decapoda

Decapoda abundance category (0, 1–5, 6–20, 21–100, [ 100)

–

Ephem—ephemeroptera

Ephemeroptera abundance category (0, 1–5, 6–20, 21–100, [ 100)

–

Hemip—hemiptera

Hemiptera abundance category (0, 1–5, 6–20, 21–100, [ 100)

–

Odon—odonata Other_macro—other macroinvertebrates

Odonata abundance category (0, 1–5, 6–20, 21–100, [100) Other macroinvertebrates abundance category (0, 1–5, 6–20, 21–100, [ 100)

– –

Plecop—plecoptera

Plecoptera abundance category (0, 1–5, 6–20, 21–100, [100)

–

Slope_v—reach slope

Percent straight line slope, measured with a clinometer, between lower and upper extent of assessment reach

–

Trichop—trichoptera

Trichoptera abundance category (0, 1–5, 6–20, 21–100, [100)

–

Secondary indicators received half the weight of primary indicators. Note that summary and single indicator metrics and supplemental indicators do not require weighting. For a more detailed description of how each Interim Method indicator and single indicator is assessed, see Topping et al. (2009) a

Interim method indicators

b

Arid regions only

c

Collected in Oregon only

methods across a wide range of hydrologic conditions; and (3) to maximize the number of study reaches that could be sampled by limiting travel time and site access issues. To accomplish our first goal, we applied a GIS Method to assign an initial streamflow duration class to stream reaches, using ArcGIS geographic information system (GIS) software (ESRI 2009). This GIS Method first defines a stream network, using the high-resolution form (1:24,000 scale) of the NHD (http://nhd.usgs.gov/index.html) and a synthetic stream network that we produced. The NHD categorizes streams as perennial or intermittent, which we used in our GIS Method. However, ephemeral streams are generally not included in the NHD within Oregon. For these, we used ArcGIS to derive a synthetic stream network using the National Elevation Dataset, a 30-m resolution digital elevation model (http://ned.usgs.gov/). This entailed performing a flow accumulation analysis using a 10-hectare minimum drainage area to initiate the network, since this produced a synthetic stream network with terminal streams that matched places in Oregon where we knew ephemeral streams were present. We then assigned Strahler (1952) stream order to this synthetic stream network. The GIS Method defined ephemeral streams as first-order

streams from the synthetic network that were upstream from NHD intermittent and/or perennial streams. If a stream reach defined in this fashion was selected for sampling and, subsequently, found to not have a channel, then the reach was dropped from the sample. Although we initially developed this method as a site selection tool to assist with achieving a balance between the three streamflow duration classes, we also included this as an independent assessment method due to interest in evaluating the utility of mapped databases for determining streamflow classes (Fritz et al. 2013a). Our second goal was to test the different methods across a range of hydrologic settings. This was achieved in part by including sites from five different regions within the Pacific Northwest that we defined from physiographic features (Fig. 1): the Blue Mountains and the Basin and Range region in eastern Oregon (OR_e); the Willamette River Basin in western Oregon (OR_w), consisting of the valley floor and foothills and the mountains (Coast Range and Cascades); Washington’s southern Puget Sound, lowlands, and adjoining mountains (WA_w); the mountains of the Idaho panhandle and eastern Washington’s Palouse (ID_n); and the Snake River Plain and nearby Sawtooth Mountains and

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Fig. 1 Three-state study area. Black dots indicate study stream sites in the five study regions: OR_e eastern Oregon; OR_w western Oregon, WA_w western Washington, ID_n northern Idaho, including

eastern Washington sites, and ID_c Central Idaho. Climate and aquifer permeability classes from Wigington et al. (2013) for Oregon and from draft versions of maps for Washington and Idaho

associated valleys of Idaho (ID_c). In addition, we developed GIS-based lists of prospective study reaches that were distributed over different hydrologic settings (Table 2). Due to differences in availability of GIS information, timing of field work, and other field work constraints, the criteria that were used to develop these lists varied by region. While these differences in criteria would be of concern if we were trying to develop a statistical characterization of Pacific Northwest stream reaches, our main purpose here was for our sample to include all the major hydroclimatic regions within the study area, and not to produce a representative sample. For various reasons (e.g., erroneous mapping, access issues, and local impacts), field crews were unable to identify sufficient numbers of study reaches using the GIS-based lists. To increase total sample size and ensure coverage of certain stream types, field crews identified additional study reaches based on field reconnaissance. This resulted in a total of 264 study reaches: 88 in OR_e, 90 in OR_w, 28 in WA_w, 28 in ID_n, and 30 in ID_c. Of these 264 study reaches, 77 %

were identified through GIS, with the remaining 23 % selected in the field. A list of final study reaches (not shown) that includes hydrologic landscape information indicated that we succeeded in distributing our study reaches over a wide range of hydrologic conditions. Because our study encompassed such a broad geographic area, our final goal was to limit travel time and site access issues. We accomplished this by restricting our sampling to the five described study regions that covered a wide range of hydrologic conditions found in the Pacific Northwest. In addition, we limited the pool of potential study reaches to those that intersected with primary or secondary roads located on public land, minimizing issues with site access on private land. For the valley floor of the Willamette Basin and locations in Washington and Idaho, we also included intersection with local roads, in order to get sufficient numbers of study reaches. Roads were identified using TIGER/Line Census 2000 data (http://www.census.gov/geo/www/tiger/), and public lands were determined from state public ownership GIS layers (http://spatialdata.oregonexplorer.info,

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Environmental Management Table 2 Criteria used to develop lists of prospective study reaches Region

Criteria

Notes

OR_e

Reaches distributed within four water surplus/Strahler (1952) stream order categories:

Water surplus categories were defined to test the methods under a range of climatic conditions. Low-order streams were emphasized in wetter areas since they are more difficult to characterize, but higher order streams had to be included in drier regions to obtain sufficient sample numbers. Annual water surplus (in mm) calculated according to Wigington et al. (2013) as the difference between 30-year (1971–2000) mean annual precipitation and potential evapotranspiration, using commercially available PRISM (Parameter-elevation Regressions on Independent Slopes Model; Daly et al. 2008) data. Surplus values less than zero represent annual deficits

(1) C900 mm (very humid) and B2nd order; (2) C250 and \900 mm (humid) and B3rd order; (3) C0 and \250 mm (subhumid) and B4th order; (4) C-250 and \0 mm (semiarid) and B6th order; (5) \-250 (arid) and B 6th order

OR_w

Selection of valley floor reaches unconstrained; mountain (Coast Range and Cascades) reaches limited to stream order of one and areas with water surplus C900 mm and mountain terrain

No constraints necessary for valley floor due to fairly homogeneous water surplus classes (defined as above). Mountain terrain defined as in Wigington et al. (2013)

ID_c

None

Timing of field work did not allow for development and execution of selection criteria. Field crews selected study reaches distributed over a range of hydrologic conditions by using draft climate and aquifer permeability maps based on Wigington et al. (2013), which defines arid, semiarid, dry, moist, wet, and very wet climate classes using Feddema (2005). The arid class was dropped due to the paucity of streams in such areas

ID_n WA_w

Criteria were intended to spread study reaches across the range of the region’s climate types and to exclude larger perennial rivers from consideration, since classification would be more problematic with smaller perennial streams. Criteria varied across regions because of differences in availability of GIS information, timing of field work, and other field work constraints. Implementation of criteria was done using ArcGIS Regions: OR_E eastern Oregon, OR_W western Oregon, WA_w western Washington, ID_n northern Idaho, ID_c central Idaho

http://www.dnr.wa.gov/businesspermits/topics/data/pages/ gis_data_center.aspx, and http://inside.uidaho.edu). Reach Establishment For each study location, data were collected within a stream reach that was established during the initial visit. All subsequent assessments evaluated the same established reach. The downstream reach boundary was assigned at a location 10 m upstream from any culvert or bridge feature, except in instances where a road crossing or culvert clearly impacted the stream physical characteristics; in such cases, the study reach was established further upstream to avoid those impacts. Study reaches were equivalent to 40 times the channel width of a stream (Peck et al. 2006), as measured along the thalweg, or a minimum of 30 m for streams with a channel width less than 0.75 m. Channel width resulted from averaging three width measurements along each reach, measured at the downstream reach boundary, and 15 and 30 m upstream of the first measurement. For measurement purposes, ‘channel’ was defined as the outer limits of the ordinary high water mark. Once established each study reach was described using Global Positioning System (GPS) coordinates and flagged to facilitate subsequent assessments.

Data Collection Data collection included potential predictor variables that were used to develop the Revised and Combined methods and to assign streamflow duration classes using the three field-based methods. Actual streamflow duration class was also determined in order to assess the accuracy of the four different methods. Predictor Variables Field crews assigned scores for the 21 Interim Method indicators (Table 1) at all study reaches in both phases of the study. We also collected data on 11 summary (Total Biology, Total Geology, and Total Hydrology) and Single Indicator metrics (the Total summary metrics are each the sum of the scores of all indicators of the respective types), because these were included in early drafts of the Interim Method and related approaches. In addition, supplemental data were collected, including slope of reach, percentage streambed bedrock, and macroinvertebrate abundance (Table 1). Collection of the 21 indicators and Single Indicator measures followed protocols in Topping et al. (2009); supplemental data were collected using published methods (Mazzacano and Black 2008; Nadeau 2011) or

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standard operating procedures that we developed (available from the lead author). Field assessments were made by two crews, each consisting of two people, who participated in several days of field training prior to conducting assessments; crew leaders made any final judgments where there were disagreements on scoring of indicators. To characterize crew variability, five percent of study reaches were independently assessed by both crews in order to serve as duplicate assessments. Upon completion of each study phase, all data were entered into a spreadsheet, independently validated against the field forms, and corrected as necessary. These validated spreadsheet files were combined, manipulated, and reduced as part of the data processing. Finally, 5 % of the data records in the final worksheet were randomly selected and compared to the original field forms (no errors found). Timing of field data collection targeted ‘typical’ hydrological conditions for the wet or dry season. Based on the Palmer Z Index (http://www.ncdc.noaa.gov/temp-andprecip/drought/historical-palmers.php), which measures short-term drought on a monthly scale, spring 2009 ranged from moderate drought to moderately moist for Oregon, with some very moist areas in the Cascades. Conditions in fall 2009 were moderate drought to midrange in western Oregon, and severe drought to very moist in eastern Oregon. For fall 2010 in Washington and Idaho, conditions were moderate drought to very moist, while spring 2011 was midrange to extremely moist. This indicates that sampling covered a range of climatic conditions. Sampling occurred over two field seasons at the 178 Oregon study reaches; a wet season data collection in March–June 2009 and a dry season sampling in August– October 2009. For the 86 Idaho and Washington study reaches, dry and wet season data collection occurred during August–September 2010 and April–July 2011, respectively. Field sampling was generally not conducted within 48 h of significant precipitation. Actual Streamflow Duration Class In order to determine the accuracy of the four methods, it was necessary to assign each study reach an independently determined, objectively defined streamflow duration class as a basis for comparison (Table 3). Establishment of the actual streamflow duration class—perennial, intermittent, or ephemeral—for study reaches was initially based on a series of direct hydrological observations at each site according to the following three criteria (note that this designation was distinct from, and not always consistent with, our assignment of classes for study reach selection using the GIS Method): (1) Study reaches were considered perennial if they were observed to have surface or hyporheic flow through the entire reach during both wet

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(winter/spring) and dry seasons (i.e., during every site visit), since ephemeral and intermittent streams have no flow during the dry season; dry season sampling was timed so as to occur before the beginning of fall rains. Hyporheic flow consists of water from the stream channel that enters the subsurface materials of the streambed and then returns to the stream (Bencala 2005). (2) We classified a study reach as ephemeral if there was no observed flow during all field visits, since ephemeral streams only flow in direct response to precipitation, and because we generally did not conduct field work within 48 h of significant precipitation. Precipitation was determined through onsite observation and use of the National Weather Service’s precipitation mapping tool (http://water.weather.gov/precip/). (3) All remaining study reaches not classified as perennial or ephemeral were classified as intermittent. Note that use of these three criteria to establish actual streamflow duration class was possible because of the distinct seasonality of PNW precipitation and discharge (Supplementary Materials 1). For perennial reaches, the presence of standing (stagnant) pools was not considered to be indicative of flowing conditions, although hyporheic flow was. Since hyporheic flow occurs below the surface of the streambed, it is not easily observed. However, we assessed several attributes indicating the presence of hyporheic flow: flowing surface water disappearing into alluvium deposits and reappearing downstream; water flowing out of the streambed (alluvium) and into isolated pools; and flowing water below the streambed surface, observed by moving streambed rocks or digging small holes in the streambed. Initial streamflow duration classes for each assessment reach were independently assigned by two researchers using the previous three criteria. We recognized the most likely misclassification would be assigning ephemeral study reaches to the intermittent streamflow duration class following recent precipitation. For the first phase of the study in Oregon, we deployed electrical resistance (ER) data loggers (Intermountain Environmental, Inc.) in approximately 40 % of study reaches from February to November, 2009. The ER data loggers continuously record the timing and duration of dry and wet conditions (Fritz et al. 2006, 2008). Given our observations of the ER data, we reclassified as ephemeral any wet reach (i.e., one with surface flow or standing pools) that had recent rainfall and for which there were ER data that indicated three occurrences of the stream drying within 3 days of wetting. In addition, any differences in the independent assignments of the field crew were reconciled according to the above criteria and a review of the available ER and precipitation data. The ER data were also used to verify many of the Oregon streamflow duration class assignments.

Environmental Management Table 3 Distribution of actual streamflow duration class for all study reaches (Oregon, Washington, and Idaho) and by region and climate class

Number of assessment reaches

Streamflow duration class Ephemeral

Intermittent

Perennial

96

97

71

ID_c

10

13

7

ID_n

7

13

8

OR_e

41

35

12

OR_w

29

28

33

WA_w

9

8

11

Semiarid

29

10

3

Dry

14

16

8

Moist Wet

3 35

22 35

4 34

Very wet

15

14

22

All Region

Climate class

OR_E eastern Oregon, OR_W western Oregon, WA_w western Washington, ID_n northern Idaho, ID_c central Idaho

Although the ER data corroborated our direct hydrological observations at Oregon study reaches, logistics and maintenance requirements precluded the deployment of ER sensors in the second phase of the validation study in Idaho and Washington. Instead, we added three additional onsite visits (November, 2010, March through April, 2011, and August through September, 2011) to the streams to make streamflow observations. These were conducted at different times than hydrologic assessments made in association with the 2010 dry and 2011 wet season field visits. Statistical Method Development The Revised Method was developed with classification tree (CT) techniques that were conducted using the R statistical package (R Core Team 2013). Classification trees use binary recursive partitioning (i.e., data are split into two groups which can then be subsequently split) of nonlinear data to model response variables (Breiman et al. 1984). In this analysis, our response variable was streamflow duration class (ephemeral, intermittent, or perennial). Our predictor variables included 41 of the field variables as well as region and season. Note that the lichen line and riparian corridor Interim Method indicators were omitted since they were only collected for arid regions, and the statistical techniques we used required no missing data. However, the presence of a riparian corridor would be captured by the hydrophytic plant indicator so we expect the results would be similar. Because of the large number of independent variables, our first step was to use random forests (RF) (Breiman 2001; Cutler et al. 2007) to identify which of the 41 predictors were the most consistently important indicators for

classifying streamflow duration. RF uses many CTs from bootstrap samples that are built using randomly selected indicators. We used the randomForest package in R to build 500 trees, with eight predictors randomly selected for splitting at each node. The average importance of the predictors across the ‘‘forest’’ of CTs was then used to identify a candidate subset of predictor variables. The next step involved building a CT using the multivariate regression tree package mvpart (De’Ath 2002) to assign study reaches into streamflow duration classes. Multivariate regression trees are an effective tool for classifying study reaches based on both continuous and categorical predictor variables, are not constrained to linear relationships, are robust to colinearity, and can incorporate high-order interactions (De’Ath 2002). Additionally, mvpart allows a cross-validation procedure that randomly holds out a portion (10 %) of the data when constructing trees, providing an estimate of the error (cross-validation, or CV error) that might be expected if the model were applied to new data. We used the subset of predictor variables identified by the RF analysis. In addition, CT construction also included Total Biology, Total Geology, Total Hydrology, and the macroinvertebrate, amphibian, and fish Single Indicator variables. These indicators were included even if they were not identified as important by the RF analysis. They were used because Single Indicator and Total summary metrics have been employed in early drafts of the Interim Method and related approaches. Also, if such indicators prove to be reliable indicators of streamflow duration, they can be more rapid alternatives to the collection of more comprehensive sets of metrics in field

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surveys. The best CT, which then became our Revised Method, was selected by comparing predicted and actual streamflow duration classes. Following the collection of Washington and Idaho data, we repeated the RF and CT analyses using the three-state combined data to determine whether we could construct an improved CT for the Pacific Northwest. The resulting best CT, which was based on Oregon, Washington, and Idaho data, is our Combined Method.

Method Performance Overall accuracy of the four methods was determined by using confusion (or error) matrices (Congalton 2001; Carle 2011) to compare predicted and actual streamflow duration classes (P = perennial, I = intermittent, and E = ephemeral). Overall accuracy was calculated as the sum of the diagonal of the confusion matrix (see Table 4) divided by the matrix total. Accuracies were calculated for combined results and by region, climate class, and season (wet or dry). Climate classes—semiarid, dry, moist, wet,

Table 4 Confusion matrix comparing actual streamflow duration class for all Oregon study reaches with class based on the Interim and Revised Methods

ACTUAL

NUMBER OF OBSERVATIONS

Ephemeral

Intermittent

Perennial

Ephemeral

84

56

0

Intermittent

11

57

58

Perennial

0

10

80

NUMBER OF OBSERVATIONS

ACTUAL

INTERIM METHOD

REVISED METHOD Ephemeral

Intermittent

Perennial

Ephemeral

128

12

0

Intermittent

6

113

7

Perennial

0

24

66

Entries represent number of observations in each actual/Method combination (number of observations equals number of sites multiplied by two seasons). For the Interim Method, overall accuracy and I/P accuracy (the accuracy when the intermittent and perennial classes are combined) are 62.1 and 81.2 %, respectively. These accuracies are 86.2 and 94.9 %, respectively, for the Revised Method. Overall accuracy is calculated as the sum of the diagonal divided by the matrix total; I/P accuracy is calculated as the sum of the upper-left entry and the four bottom-right entries (demarcated by heavier lines) divided by the matrix total

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and very wet—were determined from Wigington et al. (2013) for Oregon and through draft versions of climate maps for Washington and Idaho. We also calculated accuracy rates for distinguishing between ephemeral and an ‘at least intermittent’ class (i.e., intermittent and perennial combined); this corresponds to the Justice Scalia standard of ‘relatively permanent.’ This variable, which we refer to as I/P accuracy, is calculated as the sum of the upper-left entry and the four bottom-right entries of the confusion matrix (see Table 4) divided by the matrix total. In addition, we calculated accuracies for the three Single Indicator measures. User’s accuracy was also calculated for the four methods. User’s accuracy accounts for errors of commission (Congalton 2001; Carle 2011), and represents how accurate the classification is when applied by a user in the field. It is calculated from the confusion matrix as the diagonal entry for the class divided by the column total of the class. Including this measure was important because of the need to inform the method’s users of the error rate associated with an assessment. The complementary metric, producer’s accuracy (errors of omission), was not included since we focused instead on overall accuracy, and because producer’s accuracy can be easily calculated from the confusion matrix (the diagonal entry for the class divided by the row total of the class). In all cases, confusion matrices for combined, regional, and climate class results included each of the two seasons as independent observations, e.g., n = 528 for the combined results (264 study reaches times two seasons). Finally, we assessed variability between field crews by comparing duplicate assessments that were conducted at five percent of our study reaches. Two full sets of statistical analyses were run to assess significance of results. One was performed on all three streamflow duration classes. The second was run on just two classes—E and the combined I/P class. The process for each set of analyses is shown in Fig. 2; details are provided in Supplementary Material 2.

Results The actual streamflow duration class designations of the 264 study stream reaches are summarized in Table 3. The Interim Method agreed with the known streamflow duration class for 62.1 % of Oregon observations (Table 4). The accuracy rate for distinguishing between ephemeral and ‘at least intermittent’ (i.e., intermittent or perennial) streams was 81.2 %. Note that for the purposes of this study, stream classifications based on the Interim Method did not rely on Single Indicator measures or supplemental data, but were solely determined using scores from the 21 Interim Method indicators (Table 1).


Select Method for Further Analysis Compare Interim vs. Revised Models

Compare Revised vs. Combined Models

Adequate counts for each combination of responses

Combine factor levels

Run full log-linear model

Interaction Significant?

Rerun model without interaction

No

Yes Estimate specific contrasts based on parameter estimates of log-linear model

Yes

Main Factor Significant?

Fig. 2 Flow chart illustrating procedure for statistical analyses. The procedure was run twice, once for all three flow duration classes (ephemeral, intermittent, and perennial), and the second with the intermittent and perennial classes combined (ephemeral and I/P). Parallel analyses were conducted using either climate class or region as the main factor. All procedures performed using PROC CATMOD in SAS v. 9.2 (SAS Institute Inc. 2009). See Supplementary Material 2 for additional details

Analyses of the Oregon data found that a subset of the Interim Method and supplemental indicators appeared to have the strongest explanatory power in separating the perennial, intermittent, and ephemeral stream classes. Based on the RF analysis, the best indicators of streamflow duration for the Oregon study reaches were, in decreasing order of importance: Macro_M09b, Macro_M08, Macro_M09, Ephem, Wetl_pl_M09, Slope_v, SI_macro, Mosses, and Leaflitter (see Table 1 for description of indicators). From these indicators, plus inclusion of Single Indicator and Total Score variables, the Revised Method was developed based on CT results (Fig. 3a). The Revised Method comprises five indicators: macroinvertebrates (Macro_M09b), wetland plants in/near streambed (Wetl_ pl_M09), Ephemeroptera (Ephem), the presence of perennial macroinvertebrates (Per_macro_present), and reach slope (Slope_v). Note that this classification tree contains

only one of the macroinvertebrate indicators, Macro_M09b, as the other two (Macro_M08 and Macro_M09) were highly correlated with Macro_M09b. The Revised Method correctly classified 307 of the 356 Oregon observations (Table 4), which is 86.2 % correct compared with 62.1 % accuracy of the Interim Method. Additionally, accuracy rates for distinguishing between ephemeral and ‘at least intermittent’ classes (I/P accuracy) rose from 81.2 % to 94.9 % with the Revised Method. The Revised Method was significantly more accurate (P \ 0.0001) than the Interim Method for predicting all three classes and for I/P accuracy. The expected classification success of the Revised Method on new data, estimated from cross-validation error, was 75 %. This classification tree subsequently became the basis for the Streamflow Duration Assessment Method for Oregon (Nadeau 2011; Fig. 3b). The Revised Method, when applied to the Washington and Idaho study reaches, correctly classified 79.1 % (136/ 172) of observations, and ‘at least intermittent’ with 91.3 % accuracy. To determine whether the method could be further improved using data for all three states, we combined data from all study reaches and repeated the RF analysis. The most important indicators from the combined dataset included a new candidate predictor; Plecoptera (see Table 1 for indicator description). We included this predictor in construction of a CT for the combined three-state dataset (the Combined Method), which successfully classified the streamflow duration class for 445 of 528 observations (84.3 %; Table 5). This was an equivalent performance to that of the Revised Method, which correctly classified 83.9 % of observations from the three-state study area (Table 5). Differences between the Combined and Revised Methods were not significantly different at the 95 % confidence interval (P = 0.056). The Revised Method consistently outperforms the Interim and GIS Methods in all categories (Table 5). Performance accuracy of the Revised Method for the regional categories is highest in eastern Oregon (91.5 % overall accuracy) and lowest in northern Idaho (73.2 %). For climate class, performance accuracy is highest in semiarid climates (91.7 %) and lowest in wet climates (77.4 %). Performance accuracy is similar by season, i.e., 84.1 % in the wet winter/spring and 83.7 % in the dry summer. We found that there were significant differences (P = 0.025) across regions with the Revised Method; results for OR_e were significantly more accurate than those for OR_w or ID_n. Season did not have a significant effect on results (P = 0.904) when considered alone. However, there were significant interactions between season and climate: the Revised Method performed significantly better during the spring for semiarid (P = 0.017) and very wet (P = 0.025) climate classes, while classification was more accurate (P = 0.012) during the fall for wet climate. Thus,

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Environmental Management Fig. 3 a Classification tree from Oregon only data. Calculated cutoff values from the mvpart multivariate regression tree package appear above each split. Note that the length of a branch is proportional to the variance explained by the split (De’Ath 2002). Distribution of actual reach classification is shown by bar plots (white = ephemeral, gray = intermittent, black = perennial) and numeric summaries below each branch. Key: E ephemeral, I intermittent, P perennial, macro_M09b macroinvertebrates, wetl_pl_M09 wetland plants in/ near streambed, Ephem Ephemeroptera, CV crossvalidation. b Resulting decisiontree used in Revised Method (Nadeau 2011). Key: SAV submerged aquatic vegetation, FACW facultative wetland plants, OBL obligate wetland plants

(a)

(b)

performance of the Revised Method varies in different settings and at different times. However, its overall accuracy for determining ‘at least intermittent’ is nearly 90 % or greater in all categories. The Combined Method had slightly higher accuracy than the Revised Method in 6 of the 12 categories examined, but improvement is generally less than 2 % and in only one category (northern Idaho regional cluster) does this exceed 5 % (78.6 vs. 73.2 % for Revised Method).

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However, overall results from the Combined Method were not significantly different (P = 0.056) than those from the Revised Method. In addition, use of the Combined Method would require assessment of two additional indicators. We therefore ruled it out as providing an improved on-theground streamflow duration assessment method for the Pacific Northwest. The GIS Method classified 74 of the 264 sites as ephemeral. Of those 74 sites, 46 % were determined to be

Environmental Management Table 5 Accuracies of four different classification methods as determined from confusion matrices (not shown)

Accuracy (%)

Method GIS

Interim

Revised

Combined

43.6 (65.9)

62.3 (81.6)

83.9 (93.8)

84.3 (94.3)

ID_c

50.0 (50.0)

63.3 (78.3)

80.0 (88.3)

80.0 (88.3)

ID_n

42.9 (64.3)

62.5 (87.5)

73.2 (89.3)

78.6 (94.6)

OR_e

47.7 (70.5)

59.7 (81.3)

91.5 (97.2)

92.6 (98.3)

OR_w

41.1 (71.1)

64.4 (81.1)

81.1 (92.8)

79.4 (91.7)

WA_w

32.1 (53.6)

62.5 (82.1)

83.9 (96.4)

83.9 (96.4)

Semiarid

40.5 (42.9)

66.7 (73.8)

91.7 (94.0)

94.0 (96.4)

Dry

57.9 (73.7)

53.9 (78.9)

86.8 (96.1)

85.5 (94.7)

Moist Wet

44.8 (96.6) 41.3 (66.3)

67.2 (98.3) 60.1 (79.8)

91.4 (100.0) 77.4 (89.9)

89.7 (98.3) 77.9 (90.9)

Very wet

39.2 (60.8)

66.7 (84.3)

84.3 (96.1)

85.3 (97.1)

Dry summer

–

65.9 (80.7)

83.7 (92.8)

82.6 (92.0)

Wet winter/spring

–

58.7 (82.6)

84.1 (94.7)

86.0 (96.6)

All Region

Climate class

Season

Data presented for all observations (Oregon, Washington, and Idaho) and by region, climate class, and season. Initial number is overall accuracy and parenthetical number is I/P accuracy, both in percent. GIS classifications were assigned a single time and not assessed by season OR_E eastern Oregon, OR_W western Oregon, WA_w western Washington, ID_n northern Idaho, ID_c central Idaho

intermittent or perennial in the field. The GIS Method generally did not perform well when compared to the fieldbased methods, correctly classifying only 43.6 % of study reaches (Table 5). It more accurately determined ‘at least intermittent’ study reaches (65.9 %), but still performed well below the other methods. Overall, the GIS method tended to overestimate the flow duration class relative to the field determinations, i.e., it classified a site as having a longer streamflow duration class than was observed (37.5 % out of the total 56.4 % disagreement). Separating the data into climate classes, the GIS method had a stronger tendency to overestimate flow duration class in the semiarid (54.8 out of 59.5 %), dry (34.2 out of 42.1 %), and moist climate classes (48.3 out of 55.2 %) compared to the wet (30.8 out of 58.6 %) and very wet climate classes (33.3 out of 60.8 %). Interestingly, the GIS Method was extremely accurate in determining ‘at least intermittent’ in the moist climate class (96.6 %); however, sites were the least evenly distributed across flow permanence classes within this climate class having *76 % of the sites being intermittent. To evaluate method accuracy when applied by a user in the field, we calculated user accuracies using data from all study reaches. User accuracies account for errors of commission and represent how accurate the classification is when applied in the field (i.e., the probability that the estimated streamflow duration class is really that class). For

all stream types—ephemeral, intermittent, and perennial— user accuracies were higher for the Revised Method than for the Interim Method (Table 6). However, agreement between duplicate assessments (n = 35) was somewhat higher for the Interim Method, 94.3 versus 88.6 % for the Revised Method (Table 7). Both the Interim and Revised Methods include the presence of Single Indicator measures as an approach for determining whether a stream is ‘at least intermittent.’ There are three such Single Indicator measures in the Interim Method: fish; identified herpetofauna life history Table 6 User’s accuracies of four different classification methods by streamflow duration class for all observations (Oregon, Washington, and Idaho) Accuracy (%)

Method GIS

Interim

Revised

Combined

Streamflow duration class Ephemeral

54.1

89.3

92.5

91.3

Intermittent

36.7

48.7

76.1

77.6

Perennial

42.0

59.1

84.1

84.0

Average

44.2

65.7

84.2

84.3

User’s accuracy accounts for errors of commission, and represents how accurate the classification is when applied by a user in the field. It is calculated from the confusion matrix (not shown) as the diagonal entry for the class divided by the column total of the class

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Environmental Management Table 7 Agreement between duplicate assessments (n = 35) for three different classification methods Agreement (%)

Method Interim

All

Revised

Combined

94.3 (100.0)

88.6 (94.3)

91.4 (97.1)

88.2 (100.0) 100.0 (100.0)

88.2 (94.1) 88.9 (94.4)

94.1 (100.0) 88.9 (94.4)

Season Dry Summer Wet Winter/Spring

Data presented for all observations (Oregon, Washington, and Idaho) and by season. Initial number is overall agreement and parenthetical number is I/P agreement, both in percent. GIS classifications are not included since they were assigned a single time and so were not duplicated

stages requiring the sustained presence of water; and identified aquatic macroinvertebrates classified as perennial or intermittent indicators (Topping et al. 2009). The Streamflow Duration Assessment Method for Oregon (Nadeau 2011) includes only the first two as Single Indicators, as aquatic macroinvertebrate indicators comprise three of the five indicators used in that method. Examining the accuracy of the Single Indicators (Table 8) showed that while the absence of Single Indicator measures is not indicative of streamflow duration, their presence is strongly predictive. In other words, the organisms that make up the Single Indicator measures frequently do not occur in perennial or intermittent stream reaches, but when they do occur, they are very accurate indicators of perennial or intermittent streamflow.

Discussion The high error rate of the BPJ-based Interim Method in Oregon highlighted the need for an alternative method to more accurately determine streamflow duration. The Revised Method, a model developed through statistical analyses of field data, provides a more simplified approach with significantly higher classification accuracy than the additive, weighted scale Interim Method. Although initially developed in Oregon, the Revised Method also performs well in the hydrologic landscapes of Idaho and Washington. To be accurate and objective, a method should consist of actual measurements rather than ocular estimates or subjective classification, and be precisely describable (Poole et al. 1997). Precise written description of methods based on objective measurement is easier than describing categories of complex phenomena; subjective measurements include subjective interpretation by the reader when applying the methods (Poole et al. 1997). Based on our extensive observations and feedback from users, the Interim

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Method contains several indicators that are difficult to objectively assess. Historic disturbances (e.g., debris flows) and/or land use practices (e.g., logging) may complicate how geomorphology attributes discriminate among flow duration classes. Anecdotally, we also observed that relatively unimpaired streams tend to score higher than impaired streams; this may result, in part, because Interim Method scoring is additive. The Revised Method is mainly based on stream attributes that are biological; i.e., a hydrophytic plant (Wetl_pl_M09) and three aquatic macroinvertebrate (Macro_M09b, Ephem, Per_macro_ present) indicators. All are measureable, rather than subjective, as is the fifth indicator, the abiotic channel slope (Slope_v). We posit a twofold explanation as to why the simpler, more biologically based Revised Method is more accurate than the Interim Method. First, the Revised Method is a model that used a formal data-driven, statistical process to select stream attributes having the greatest potential explanatory power. We were then able to validate the model using a spatially extensive, independent dataset generated in a second phase of the study in Idaho and Washington. In contrast, the Interim Method, while reflecting current literature, practice, and understanding, was primarily the result of collective BPJ. In the absence of quantitative data, several assumptions were made both in the inclusion and subsequent scoring and weighting of specific indicators in the Interim Method (Topping et al. 2009). In an attempt to develop a method that would be applicable across the geologically and hydrologically diverse landscapes of Oregon, a range of indicators were included in the Interim Method that assumed their usefulness in some landscapes or stream types, versus others; for instance, indicators that were only applicable in arid regions (riparian corridor and lichen line). Effective indicators allow for changes in the response value to be distinguished from background variability (Dale and Beyeler 2001), and should be independent and not redundant (Stauffer and Goldstein 1997). Our results indicate that many of the Interim Method indicators are not providing independent value as indicators of streamflow duration. Secondly, the Revised Method primarily relies on biological metrics rather than physical measures which may be influenced by factors other than streamflow duration. Hydrology (especially duration, frequency, rate of change, and timing of flow) is a critical element of the abiotic template that governs the biological attributes of headwater and temporary streams (Williams 1996; Rolls et al. 2012; Gallart et al. 2012). Seven of the top nine RF indicators in discriminating among flow duration classes for the Oregon sites were biological (macroinvertebrates, macrophytes, and mosses), whereas only one was hydrological (Leaflitter) and one geomorphological (Slope_v). Biological

Environmental Management Table 8 Accuracies of three different single indicator groups as determined from confusion matrices (not shown)

Accuracy (%)

Single indicator Macroinvertebrates

Amphibians

Fish

86.7 (97.8)

48.5 (97.1)

42.8 (100.0)

ID_c

80.0 (88.9)

38.3 (100.0)

33.3 (*)

ID_n

83.9 (100.0)

35.7 (100.0)

26.8 (100.0)

OR_e

93.8 (100.0)

52.8 (100.0)

50.6 (100.0)

OR_w

83.9 (97.9)

50.6 (94.6)

41.1 (100.0)

WA_w

83.9 (100.0)

51.8 (100.0)

50.0 (100.0)

Semiarid

92.9 (100.0)

71.4 (100.0)

71.4 (100.0)

Dry

88.2 (100.0)

44.7 (100.0)

40.8 (100.0)

Moist Wet

87.9 (100.0) 84.6 (94.9)

20.7 (100.0) 50.5 (94.9)

13.8 (100.0) 42.8 (100.0)

Very Wet

84.3 (100.0)

44.1 (100.0)

37.3 (100.0)

Dry Summer

83.7 (97.7)

43.2 (100.0)

43.6 (100.0)

Wet Winter/Spring

89.8 (98.0)

53.8 (96.0)

42.0 (100.0)

All Region

Climate class

Season

Data presented for all observations (Oregon, Washington, and Idaho) and by region, climate class, and season. Initial number is I/P accuracy and parenthetical number is presence accuracy, both in percent. Presence accuracy is the number of observations where the indicator group was present and the actual streamflow duration class was at least intermittent divided by the total number where the indicator was present OR_E eastern Oregon, OR_W western Oregon, WA_w western Washington, ID_n northern Idaho, ID_c central Idaho * No fish were observed at any ID_c sites

indicators (macroinvertebrates and macrophytes) continued to be more represented in the RF analysis (eight of the top ten) than the hydrological (Total Hydrology) and geomorphological (Slope_v) indicators when combining data from Oregon, Idaho, and Washington. Recent studies verify that non-perennial streams maintain distinct macroinvertebrate communities with adapted species (e.g., Dieterich and Anderson 2000; Santos and Stevenson 2011; see papers cited in Blackburn and Mazzacano 2012). Reviewing the literature and current understanding of aquatic macroinvertebrates as indicators of streamflow duration in Idaho and Washington, Blackburn and Mazzacano (2012) concluded that such indicators largely reflected those reported previously for Oregon (Mazzacano and Black 2008). The most commonly noted aquatic macroinvertebrate indicators of perennial flow across our study reaches were the presence of five or more EPT (Ephemeroptera, Plecoptera, and Trichoptera) taxa and the prosobranch snail, Juga. The presence of limnephilid caddisfly cases was the most commonly noted aquatic macroinvertebrate indicator of at least intermittent flow. Like aquatic macroinvertebrates, hydrophytic plants have long been used as one of the three defining features of wetted areas (U.S. Army Corps of Engineers 1987). Recognizing the

importance of regional differences in hydrophytic plant distribution, climate, and geology, the Corps Wetlands Delineation Manual has been updated with Regional Supplements (e.g., Western Mountains, Valleys, and Coast) to better reflect the state-of-the-science (U.S. Army Corps of Engineers 2010). This is also reflected in a parallel effort resulting in an updated, regionalized National Wetland Plant List (U.S. Army Corps of Engineers 2013). In our study, the presence of some lotic organisms (fish and certain herpetofauna) provides a useful indicator of a stream reach being ‘at least intermittent.’ We hypothesize that the poor performance of the geomorphic variables is because they are, at times, more reflective of past flow magnitude rather than flow duration. While user accuracies were higher for the Revised Method than for the Interim Method, agreement between duplicate assessments was somewhat higher for the Interim Method. This high level of repeatability between teams may be due, in part, to crew training and the large number of assessments that were conducted. Repeatability might not be expected to be as high for users who lack training (Poole et al. 1997; Stauffer and Goldstein 1997). The higher repeatability for the Interim Method was due to higher winter/spring repeatability—agreement between

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users was similar in the summer for the Interim and Revised Methods. This higher winter/spring repeatability may have been due to redundant indicators that are easier to distinguish during wetter conditions. However, we caution that while it had somewhat higher agreement between users, the Interim Method was less accurate. Given the complexity of factors affecting hydrology at both the local and regional scales, it is unlikely that there is a simple indicator of streamflow duration class applicable nationwide (Fritz et al. 2008; Johnson et al. 2009; Fritz et al. 2013b). Biological indicators, including aquatic macroinvertebrates, were among the most important attributes in discriminating among streamflow duration classes in a study evaluating the North Carolina Method’s applicability to the Piedmont and Southeastern Plains ecoregions of South Carolina (Fritz et al. 2013b). That study, as with the current one, also found that geomorphology indicators were not important in determining streamflow duration classes, and concludes that while the indicator-based approach is a strong foundation for building a streamflow duration assessment method, modifications may be warranted for application in different ecoregions. Larval salamanders and physical habitat variables are valuable in discriminating streamflow classes in Midwestern forested headwater streams, but are likewise limited to the regional scale (Johnson et al. 2009). Streambed slope was the best single predictor (r2 = 0.70) of flow duration across 23 headwater streams in eastern Kentucky, where it had a negative relationship with flow duration (Svec et al. 2005). Taken together, these studies point to the importance of testing the regional relevance of identified indicators and existing methods prior to application outside the region of development. An additional result that emerged for both the Interim and Revised Methods is that they more accurately and consistently discriminate ephemeral streams from those that are ‘at least intermittent’ than distinguishing the three separate streamflow classes. This corroborates previous findings of recent studies evaluating indicators and assessment methods of streamflow class in forested headwater streams (Fritz et al. 2008, 2013b). Fritz et al. (2008, 2013b) noted the inherent variability in flow over time and recorded longitudinal shifts in hydrologic permanence categories at study streams, and attribute some of the interannual shift in streamflow duration class to interannual variation in precipitation. Such hydrologic variability may present an obstacle to classifying streamflow duration. Generally, the GIS Method did not perform well when compared to the field-based methods, correctly classifying 43.6 % of study reaches and 65.9 % of ‘at least intermittent’ study reaches. These findings corroborate those reported in Fritz et al. (2013a) where high-resolution NHD and topographic map classifications of streamflow duration

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agreed with *50 % of field determinations across *300 headwater sites and agreement increased to 73.8 % when considering ‘at least intermittent’ study reaches. The lack of high-resolution identification of ephemeral stream channels in the existing NHD has been noted by others (e.g., O’Connor et al. 2014), including a recent study in a Colorado mountain watershed in which the high-resolution NHD underestimated the number of intermittent and ephemeral streams by 22 % (Caruso 2014). Because the original delineation of most streams in NHD was based upon interpretations from stereo orthophotographs, the ability to discern headwater streams on the landscape likely varied not only among cartographers but also with surrounding vegetation and season. Headwater streams were also likely to be more under-represented in densely dissected landscapes than in those with low channel densities simply due to the space limitation of the original paper maps (Chorley and Dale 1972). Overall, the GIS method tended to overestimate the flow duration class relative to the field determinations in the present study. This includes misclassifying ephemeral streams as intermittent or perennial streams. A previous study in the western U.S. also found the NHD to be four times more likely to overestimate flow permanence than underestimate it (Stoddard et al. 2005). In addition to lower drainage densities, there is greater distinction of riparian corridors from surrounding uplands in most western U.S. regions compared to more mesic U.S. regions, which may help to explain the NHD’s tendency to overestimate flow permanence in more arid areas. The relative tendency for over- or underestimating flow permanence across the five climate classes in this study supports this explanation. The disagreement in flow classification by the NHD tended to be largely overestimations in the dry (34.2 % overestimation vs. 7.9 % underestimation), semiarid (54.8 vs. 4.8 %), and moist (48.3 vs. 6.9 %) climate classes, whereas it tended to be more evenly split in the wet (30.8 vs. 27.9 %) and very wet (33.3 vs. 27.4 %) classes. While hydrogeographic databases are important tools for watershed and water resource management, our findings emphasize and corroborate (e.g., Fritz et al. 2013a; Caruso 2014; O’Connor et al. 2014) that limitations in portraying the extent and flow status associated with existing databases must be considered in their application, and in conclusions drawn from their use. Although our study focused on the development and evaluation of methods to classify streamflow duration in stream reaches in the U.S. Pacific Northwest, our findings have broader implications. Headwater streams with temporary flow are distributed in all biomes and their flow regimes can be attributed to natural and anthropogenic controls. Like many of the streams we studied, numerous headwater streams throughout the world are undocumented on maps and in hydrographic databases (Bishop et al. 2008; Benstead


and Leigh 2012). Historically, headwater streams were too extensive for cartographers to comprehensively document on most paper maps, yet the extensive distribution of headwater streams contributes to their likely importance to global biodiversity and water and biogeochemical cycling. More broadly speaking, intermittent and ephemeral streams have received less protection than their perennial counterparts, despite the fact that many of these streams drain into perennial water bodies and may represent vital sources of freshwater in semiarid and arid regions (Taylor et al. 2011; Steward et al. 2012; Acunã et al. 2014; O’Connor et al. 2014). Accurate classification of flow permanence is fundamental to water monitoring programs and watershed models. For example, headwater streams not delineated in hydrographic datasets could bias monitoring designs and affect model estimates by treating streams as uplands. Accurate classification of flow permanence is also critical for setting appropriate expectations for the ecological status of intermittent and ephemeral streams (Fritz et al. 2006; Watson and Dallas 2013; Prat et al. 2014) and for the early detection and evaluation of anthropogenic drivers of water quantity and quality changes, such as irrigation withdrawals, effluent discharge, and climate change (e.g., Brooks 2009; Falke et al. 2011; David et al. 2013). The importance of various stream attributes in classifying streamflow duration in our study contributes to a growing collective understanding of the drivers and ecological responses to flow permanence.

Conclusions Using a statistically based modeling approach and physical predicator variables gathered in stream reaches across Oregon, we were able to develop a rapid assessment method (Revised Method) that more accurately estimated streamflow duration classes than a method based on BPJ. Although BPJ establishes a testable hypothesis, this study illustrates the importance of quantitative field testing of rapid assessment methods and associated indicators prior to routine implementation. The Revised Method, developed using data only from Oregon, had a comparable level of predictive capability as a similar method using combined data from Oregon, Washington, and Idaho. A GIS method based on high-resolution NHD did not perform as well as the fieldbased methods evaluated in this study. The validation study described herein supports a consistent, robust, and repeatable (i.e., less than 12 % variation between duplicate assessments) method that is applicable across the diverse hydrological landscapes of the U.S. Pacific Northwest. The EPA and the Corps recently released a jointly proposed rule to clarify protection under the U.S. Clean Water Act (USACE/USEPA 2014). The proposed rule, informed by

an extensive review of scientific literature examining the connectivity of streams and wetlands to downstream waters (USEPA 2015), includes a definition of ‘‘tributary’’ as channels contributing flow to downstream waters regardless of whether that contributing flow is perennial, intermittent, or ephemeral, which recognizes that intermittent and ephemeral streams are key parts of the broader aquatic ecosystem and contribute to downstream functions. The Revised Method is useful where knowledge of streamflow duration improves ecological assessment, management, and decision-making, including continuing to inform CWA jurisdictional determinations, while the proposed rule is open to debate. From the humid west side of the Cascade Mountains to the dry and semiarid areas of the Snake River Plain and Basin and Range Province, the Revised Method can be used to distinguish between ephemeral, intermittent, and perennial streams. Given the range of hydrologic landscapes covered in the current validation study, it may be relatively straightforward to further validate the method for use in other Western ecoregions and hydrologic landscapes. Acknowledgments Many thanks are due to Blake Hatteberg, Lindsey Webb, Shawn Majors, Rachel LovellFord, and Howard Bruner for field data collection assistance over the course of the study. Jess Jordan, Mike Turaski, Pete Ryan, and Brian Topping provided helpful insight to implementation and results from the Oregon phase of the study. We are grateful to colleagues across the Pacific Northwest who provided local knowledge for study site reconnaissance and/ or additional hydrological observations at study reaches: John Olson, Jess Jordan, Yvonne Vallette, Linda Storm, Jim Zokan, and Tina Tong. We acknowledge the U.S. Forest Service, Turnbull National Wildlife Refuge, Coeur d’Alene Tribe, U.S. Bureau of Land Management, and McDonald Forest for allowing site access, and thank Brian Stabb, Michael Rule, Angelo Vitale, and Rosemary Mazaika for facilitating access. We thank the U.S. EPA Region 10, EPA’s Office of Wetlands, Oceans and Watersheds, and the Regional Applied Research and Regional Research Partners Award programs for funding to support the study. The information in this document has been funded entirely by the U.S. Environmental Protection Agency, in part through contract #EP-D-11-027 to Dynamac Corporation. It has been subjected to EPA’s peer and administrative review and approved for publication as an EPA document. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. The authors thank three anonymous reviewers for constructive comments that greatly improved the manuscript. Conflict of interest of interest.

The authors declare that they have no conflict

Ethical standards The experiments comply with the current laws of the United States of America, where they were performed.

References Acunã V, Datry T, Marshall J, Barcelo´ D, Dahm CN, Ginebreda A, McGregor G, Sabater S, Tockner K, Palmer MA (2014) Why should we care about temporary waterways? Science 343(6175):1080–1081. doi:10.1126/science.1246666

123

Environmental Management Austin BJ, Strauss EA (2011) Nitrification and denitrification response to varying periods of desiccation and inundation in a western Kansas stream. Hydrobiologia 658(1):183–195 Bencala KE (2005) Hyporheic exchange flows. In: Anderson M, McDonnell JJ (eds) Encyclopedia of hydrological sciences, vol 3. Wiley, New York Benstead JP, Leigh DS (2012) An expanded role for river networks. Nat Geosci 5:678–679 Bishop K, Buffam I, Erlandsson M, Fo¨lster J, Laudon H, Seibert J, Temnerud J (2008) Aqua Incognita: the unknown headwaters. Hydrol Process 22(8):1239–1242. doi:10.1002/hyp. 7049 Blackburn M, Mazzacano C (2012) Using Aquatic Macroinvertebrates as Indicators of Streamflow Duration: Washington and Idaho Indicators. Report prepared by the Xerces Society for Invertebrate Conservation, 18 pp, http://www.xerces.org/wpcontent/uploads/2009/03/Streamflow_duration_indicators_IDWA_ 2012_Final_06072012.pdf. Accessed 29 Jan 2015 Breiman L (2001) Random forests. Mach Learn 45(1):5–32 Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Wadsworth International Group, Belmont Brooks RT (2009) Potential impacts of global climate change on the hydrology and ecology of ephemeral freshwater systems of the forests of the northeastern United States. Clim Change 95(3–4):469–483. doi:10.1007/s10584-008-9531-9 Carle MV (2011) Estimating wetland losses and gains in coastal North Carolina: 1994-2001. Wetlands 31(6):1275–1285. doi:10. 1007/s13157-011-0242-z Caruso BS (2011) Science and policy integration issues for stream and wetland jurisdictional determinations in a semi-arid region of the western US. Wetlands Ecol Manage 19(4):351–371 Caruso BS (2014) GIS-based stream classification in a mountain watershed for jurisdictional evaluation. J Am Water Resour Assoc 50(5):1034–1324 Chadwick MA, Huryn AD (2007) Role of habitat in determining macroinvertebrate production in an intermittent-stream system. Freshw Biol 52(2):240–251 Chorley RJ, Dale PF (1972) Cartographic problems in stream channel delineation. Cartography 7(4):150–162. doi:10.1080/00690805. 1972.10437698 Congalton RG (2001) Accuracy assessment and validation of remotely sensed and other spatial information. Intern. J Wildland Fire 10(3–4):321–328. doi:10.1071/wf01031 Cutler DR, Edwards TC Jr, Beard KH, Cutler A, Hess KT, Gibson J, Lawler JJ (2007) Random forests for classification in ecology. Ecology 88(11):2783–2792 Dale VH, Beyeler SC (2001) Challenges in the development and use of ecological indicators. Ecological Indicators 1(1):3–10. doi:10. 1016/S1470-160X(01)00003-6 Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, Pasteris PP (2008) Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int J Climatol 28(15):2031–2064. doi:10.1002/joc.1688 Datry T (2012) Benthic and hyporheic invertebrate assemblages along a flow intermittence gradient: effects of duration of dry events. Freshw Biol 57(3):563–574 David A, Tournoud M-G, Perrin J-L, Rosain D, Rodier C, Salles C, Bancon-Montigny C, Picot B (2013) Spatial and temporal trends in water quality in a Mediterranean temporary river impacted by sewage effluents. Environ Monit Assess 185(3):2517–2534. doi:10.1007/s10661-012-2728-4 De’Ath G (2002) Multivariate regression trees: a new technique for modeling species-environment relationships. Ecology 83(4):1105–1117

123

Dieterich M, Anderson NH (2000) The invertebrate fauna of summerdry streams in western Oregon. Archiv fu¨r Hydrobiologie 147(3):273–295 Downing DM, Winer C, Wood LD (2003) Navigating through Clean Water Act jurisdiction: a legal review. Wetlands 23(3):475–493 Elsner MM, Cuo L, Voisin N, Deems JS, Hamlet AF, Vano JA, Mickelson KEB, Lee S-Y, Lettenmaier DP (2010) Implications of 21st century climate change for the hydrology of Washington State. Clim Change 102(1–2):225–260. doi:10.1007/s10584010-9855-0 ESRI (2009) ArcGIS 9.3. Environmental Research Systems Institute, Redlands Falke JA, Fausch KD, Magelky R, Aldred A, Durnford DS, Riley LK, Oad R (2011) The role of groundwater pumping and drought in shaping ecological futures for stream fishes in a dryland river basin of the western Great Plains, USA. Ecohydrology 4(5):682–697. doi:10.1002/eco.158 Feddema JJ (2005) A revised Thornthwaite-type global climate classification. Phys Geogr 26(6):442–466. doi:10.2747/02723646.26.6.442 Fritz KM, Johnson BR, Walters DM (2006) Field operations manual for assessing the hydrologic permanence and ecological condition of headwater streams. U.S. Environmental Protection Agency, Office of Research and Development, Washington EPA/600/R-06/126 Fritz KM, Johnson BR, Walters DM (2008) Physical indicators of hydrologic permanence in forested headwater streams. J N Am Benthol Soc 27(3):690–704. doi:10.1899/07-117.1 Fritz KM, Hagenbuch E, D’Amico E, Reif M, Wigington PJ Jr, Leibowitz SG, Comeleo RL, Ebersole JL, Nadeau T-L (2013a) Comparing the extent and permanence of headwater streams from two field surveys to values from hydrographic databases and maps. J Am Water Resour Assoc 49:867–882 Fritz KM, Wenerick WR, Kostich MS (2013b) A validation study of a rapid field-based rating system for discriminating among flow permanence classes of headwater streams in South Carolina. Environ Manage 52:1286–1298. doi:10.1007/s00267-013-0158-x Gallart F, Prat N, Garcıá-Roger EM, Lataron J, Rieradevall M, Llorens P, Barbera GG, Brito D, De Girolamo AM, Lo Porto A, Buffagni A, Erba S, Neves R, Nikolaidis NP, Perrin JL, Querner EP, Quinõnero JM, Tournoud MG, Tzoraki O, Skoulikidis N, Go´mez R, Sańchez-Montoya MM, Froebrich J (2012) A novel approach to analyzing the regimes of temporary streams in relation to their controls on the composition and structure of aquatic biota. Hydrol Earth Sys Sci 16:3165–3182 Gordon ND, McMahon TA, Finlayson BL, Gippel CJ, Nathan RJ (2004) Stream hydrology: an introduction for ecologists. Wiley, Chicheste Jackson PL, Kimerling AJ (2003) Atlas of the Pacific Northwest, 9th edn. Oregon State University Press, Corvallis Johnson BR, Fritz KM, Blocksom KA, Walters DM (2009) Larval salamanders and channel geomorphology are indicators of hydrologic permanence in forested headwater streams. Ecol Ind 9(1):150–159 Leibowitz SG, Wigington PJ Jr, Rains MC, Downing DM (2008) Non-navigable streams and adjacent wetlands: addressing science needs following the Supreme Court’s Rapanos decision. Front Ecol Environ 6(7):364–371. doi:10.1890/070068 Loy WG, Allan S, Buckley AR, Meacham JE (2001) Atlas of Oregon, 2nd edn. University of Oregon Press, Eugene Mazzacano C, Black SH (2008) Using Aquatic Macroinvertebrates as Indicators of Streamflow Duration. Report prepared by the Xerces Society for Invertebrate Conservation, 33 pp, http:// www.xerces.org/wp-content/uploads/2009/03/xerces_macroin vertebrates_indicators_stream_duration.pdf. Accessed 29 Jan 2015

Environmental Management McDonough OT, Hosen JD (2011) Temporary streams: the hydrology, geography, and ecology of non-perennially flowing waters. In: Elliot HS, Martin LE (eds) River ecosystems: dynamics, management and conservation. Nova Science Publishers, Hauppauge, pp 259–289 Mosley MP, McKerchar AI (1993) Streamflow. In: Maidment D (ed) Handbook of Hydrology. McGraw-Hill, USA, pp 8.1–8.39 Nadeau T-L (2011) Streamflow Duration Assessment Method for Oregon (Revised). EPA/910/R-11/002, U.S. Environmental Protection Agency, Region 10, Seattle, WA, http://www.epa. gov/region10/pdf/water/sdam/final_sdam_oregon_nov2011.pdf. Accessed 29 Jan 2015 Nadeau T-L, Leibowitz SG (2003) Isolated wetlands: an introduction to the special issue. Wetlands 23(3):471–474 Nadeau T-L, Rains MC (2007) Hydrological connectivity between headwater streams and downstream waters: how science can inform policy. J Am Water Resour Assoc 43(1):118–133 NCDWQ (2005) Identification Methods for the Origins of Intermittent and Perennial Streams, Version 3.1. North Carolina Division of Water Quality, Raleigh, NC, http://portal.ncdenr.org/c/docu ment_library/get_file?uuid=6b6a0403-d445-43de-8e29-83bc549 fdf88&groupId=38364. Accessed 29 Jan 2015 NCDWQ (2010) Methodology for Identification of Intermittent and Perennial Streams and Their Origins, Version 4.11. North Carolina Division of Water Quality, Raleigh, NC, http://portal. ncdenr.org/c/document_library/get_file?uuid=0ddc6ea1-d7364b55-8e50-169a4476de96&groupId=38364. Accessed 29 Jan 2015 O’Connor BL, Hamada Y, Bowen EE, Grippo MA, Hartmann HM, Patton TL, Van Lonkhuyzen RA, Carr AE (2014) Quantifying the sensitivity of ephemeral streams to land disturbance activities in arid ecosystems at the watershed scale. Environ Monit Assess 186:7075–7095 Peck DV, Herlihy AT, Hill BH, Hughes RM, Kaufmann PR, Klemm DJ, Lazorchak JM, McCormick FH, Peterson SA, Ringold PL, Magee T, Cappaert (2006) Environmental Monitoring and Assessment Program: Surface Waters Western Pilot Study – Field Operations Manual for Wadeable Streams. U.S. Environmental Protection Agency, Washington EPA/620/R-06/003 Poff NL, Ward JV (1989) Implications of streamflow variability and predictability for lotic community structure: a regional analysis of streamflow patterns. Can J Fish Aquat Sci 46(10):1805–1818 Poole GC, Frissell CA, Ralph SC (1997) In-stream habitat unit classification: inadequacies for monitoring and some consequences for management. J Am Water Resour Assoc 33(4):879–896 Prat N, Gallart F, Von Schiller D, Polesello S, Garcıá-Roger EM, Latron J, Rieradevall M, Llorens P, Barbera´ GG, Brito D, De Girolamo AM, Dieter D, Lo Porto A, Buffagni A, Erba S, Nikolaidis NP, Querner EP, Tournoud MG, Tzoraki O, Skoulikidis N, Go´mez R, Sańchez-Montoya MM, Tockner K, Froebrich J (2014) The Mirage toolbox: an integrated assessment tool for temporary streams. River Res Appl. doi:10.1002/rra.2757 Rains MC, Mount JF (2002) Origin of shallow ground water in an alluvial aquifer as determined by isotopic and chemical procedures. Ground Water 40(5):552–563 Rains MC, Fogg GE, Harter T, Dahlgren RA, Williamson RJ (2006) The role of perched aquifers in hydrological connectivity and biogeochemical processes in vernal pool landscapes, Central Valley, California. Hydrol Process 20(5):1157–1175 Rolls RJ, Leigh C, Sheldon F (2012) Mechanistic effects of low-flow hydrology on riverine ecosystems: ecological principles and consequences of alteration. Freshw Sci 31(4):1163–1186 Santos AN, Stevenson RD (2011) Comparison of macroinvertebrate diversity and community structure among perennial and nonperennial headwater streams. Northeast Nat 18(1):7–26

SAS Institute Inc (2009) SAS/STAT 9.2 User’s guide, Second Edition. SAS Institute Inc, Cary, pp 1092–1228 Stauffer JC, Goldstein RM (1997) Comparison of three qualitative habitat indices and their applicability to prairie streams. North Am J Fish Manag 17:348–361 Steward AL, von Schiller D, Tockner K, Marshall JC, Bunn SE (2012) When the river runs dry: human and ecological values of dry riverbeds. Front Ecol Environ 10(4):202–209. doi:10.1890/ 110136 Stoddard JL, Peck DV, Olsen AR, Larsen DP, Van Sickle J, Hawkins CP, Hughes RM, Whittier TR, Lomnicky G, Herlihy AT et al (2005) Environmental Monitoring and Assessment Program (EMAP): western streams and rivers statistical summary, vol vol 600. Office of Research and Development, U.S. Environmental Protection Agency, Washington, D.C EPA 620/R-05/006 Strahler AN (1952) Hypsometric (area-altitude) analysis of erosional topography. Geol Soc Am Bull 63(11):1117–1142 Svec JR, Kolka RK, Stringer JW (2005) Defining perennial, intermittent, and ephemeral channels in eastern Kentucky: application to forestry best management practices. For Ecol Manage 214(1):170–182 Taylor MP, Ives CD, Davies PJ, Stokes R (2011) Troubled waters–an examination of the disconnect between river science and law. Environ Sci Technol 45(19):8178–8179 R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org/. Accessed 29 Jan 2015 Topping BJD, Nadeau T-L, Turaski MR (2009) Interim Version, Oregon Streamflow Duration Assessment Method. U.S. Environmental Protection Agency and U.S. Army Corps of Engineers, http://www.epa.gov/region10/pdf/water/sdam/interim_ sdam_oregon_march2009.pdf. Accessed 29 Jan 2015 U.S. Army Corps of Engineers (1987) Wetlands Delineation Manual. Technical Report Y-87-l. U.S. Army Engineer Waterways Experiment Station, Vicksburg U.S. Army Corps of Engineers (2010) Regional Supplement to the Corps of Engineers Wetland Delineation Manual: Western Mountains, Valleys, and Coast Region (Version 2.0). ERCD/ EL TR-10-3. U.S. Army Engineer Research and Development Center, Vicksburg U.S. Army Corps of Engineers (2013) National Wetland Plant List. http://rsgisias.crrel.usace.army.mil/NWPL/. Accessed 29 Jan 2015 U.S. Army Corps of Engineers/U.S. Environmental Protection Agency (2014) Definition of ‘‘Waters of the United States’’ Under the Clean Water Act; Proposed Rule. U.S. Army Corps of Engineers and Environmental Protection Agency. Federal Register 79 (76):22188–22274 http://www.gpo.gov/fdsys/pkg/FR2014-04-21/pdf/2014-07142.pdf. Accessed 29 January 2015 U.S. Environmental Protection Agency (2009) Congressionally Requested Reports on Comments Related to Effects of Jurisdictional Uncertainty on Clean Water Act Implementation. Report No. 09-N-0149, U.S. Environmental Protection Agency, Office of Inspector General, http://www.epa.gov/oig/reports/2009/ 20090430-09-N-0149.pdf. Accessed 29 Jan 2015 U.S. Environmental Protection Agency (2015) Connectivity of Streams & Wetlands to Downstream Waters: A Review & Synthesis of the Scientific Evidence. EPA/600/R-14/475F, U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC. http://cfpub.epa.gov/ncea/cfm/ recordisplay.cfm?deid=296414. Accessed 29 Jan 2015 U.S. Environmental Protection Agency/U.S. Army Corps of Engineers (2008) Clean Water Act Jurisdiction Following the U.S. Supreme Court’s Decision in Rapanos v. United States and Carabell v. United States. U.S. Environmental Protection Agency and U.S. Army Corps of Engineers, http://www.usace.

123

Environmental Management army.mil/Portals/2/docs/civilworks/regulatory/cwa_guide/cwa_ juris_2dec08.pdf. Accessed 29 Jan 2015 Watson M, Dallas HF (2013) Bioassessment in ephemeral rivers: constraints and challenges in applying macroinvertebrate sampling protocols. Afr J Aquat Sci 38(1):35–51. doi:10.2989/ 16085914.2012.742419 Wigington PJ Jr, Leibowitz SG, Comeleo RL, Ebersole JL (2013) Oregon hydrologic landscapes: a classification framework. J Am Water Resour Assoc 49:163–182. doi:10.1111/jawr.12009 Williams DD (1996) Environmental constraints in temporary fresh waters and their consequences for the insect fauna. J N Am Benthol Soc 15:634–650

123

Winter TC (2007) The role of ground water in generating streamflow in headwater areas and in maintaining base flow. J Am Water Resour Assoc 43(1):15–25 Winter TC, Harvey JW, Franke OL, Alley WM (1998) Ground water and surface water: a single resource. Circular 1139. U.S. Geological Survey, Denver Wood LD (2004) Don’t Be Misled: CWA Jurisdiction Extends to All Non-Navigable Tributaries of the Traditional Navigable Waters and to Their Adjacent Wetlands. Environmental Law Review 34:10187–10193

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