Application of the stream load reduction tool (SLRT) to quantify the project and reach scale water
quality benefits of Upper Truckee River restoration efforts
Tahoe Science Program Round 12 Request for Proposals
Subtheme 2b: Quantifying the benefits of urban storm water management
November 14, 2011
Principal Investigator: Nicole Beck, PhD, 2NDNATURE LLC, nbeck@2ndnaturellc.com
Team Members: Catherine Riihimaki (Drew University)
Agency Collaborators: Scott Carroll (CTC), Cyndi Walck (CA State Parks)
Grant Contact: Krista McDonald, 2NDNATURE LLC, krista@2ndnaturellc.com
2NDNATURE LLC, 500 Seabright Ave. #205, Santa Cruz, CA 95062, 831.426.9119, fax 831.426.7092
Total Funding Requested: $ 100,058.00
Total Cost Share: $29,500-$32,000
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 1 II. Proposal Narrative A. ABSTRACT Many stream and meadow restoration projects have been implemented throughout the Tahoe Basin over the past two decades and a majority of these projects have included improved water quality as a restoration goal. However, an approach to report restoration effectiveness with respect to water quality improvements has not been defined nor have standardized methods been established to monitor and evaluate pre‐ and post‐restoration conditions to demonstrate these improvements over time. This lack of a reliable effectiveness evaluation impedes the ability for designers, funders and reviewers to communicate reliable water quality benefits of stream restoration efforts to regulators and policy makers. 2NDNATURE (2N) is currently completing the stream load reduction tool (SLRT), a standardized method to consistently estimate the average annual sediment load reductions as a result of SEZ restoration efforts (2N 2010a). These Round 12 SNPLMA research funds will be used to apply the SLRT methods to completed and planned restoration efforts on the Upper Truckee River (UTR) and Angora Creek by leveraging existing pre‐ and post‐restoration data, available from Lake Tahoe Interagency Monitoring Program (LTIMP) and other Tahoe Basin hydrologic and water quality research. Implementation of this research would provide a tangible broad scale application of the new SLRT to a number of completed SEZ restoration efforts with varying levels of available water quality and morphologic data, in addition to providing UTR restoration project proponents with quantitative estimates of the water quality benefits of their actions for use to obtain additional funding sources for monitoring, adaptive management, or future restoration projects. B. JUSTIFICATION STATEMENT Intended benefits of stream and meadow restoration efforts conducted in the Tahoe Basin over the last two decades has generally been to meet a number of multifaceted ecological and recreational objectives. However, water quality improvement is also typically included as an objective of many Tahoe Basin stream and SEZ restoration projects (2N et al. 2010). The recent adoption of the Lake Tahoe Total Maximum Daily Load (TMDL; LRWQCB and NDEP 2010) makes the need for SEZ restoration practitioners to be able to quantity and justify the water quality benefit (i.e., reduction of pollutant loads delivered to the Lake) of these actions even more critical. A number of recent Tahoe Basin efforts have been carried out in response to the known limitations and inconsistencies with determining the effectiveness of SEZ restoration efforts. 2NDNATURE (2N), Environmental Incentives (EI), and River Run Consulting developed a standardized process to focus and improve the quality of stream restoration effectiveness evaluations by providing a framework to increase the consistency of setting project goals and objectives and collecting appropriate data to inform long‐term adaptive management decisions (2N et al. 2010). The Upper Truckee River Watershed Advisory Group (UTRWAG) has made considerable strides to define guidelines for general monitoring plans to evaluate the effectiveness of stream restoration projects on the Upper Truckee River (UTRWAG 2007). However, measuring the water quality benefit of an SEZ restoration would require years of pre‐ and post‐restoration water quality monitoring that is extremely costly and technically complex to manage, analyze and reporting in a meaningful way. In response to the need for a reliable and cost‐effective method to estimate the water quality benefit of SEZ restoration, the 2N team is currently funded by SNPLMA to complete the stream load reduction tool (SLRT). The SLRT methodology provides a standardized and comparable approach to estimate the water quality benefit of an SEZ restoration effort. SLRT can be completed using typically available morphologic and existing hydrologic and water quality data, and the results are reported in a format consistent with other TMDL tools and reporting requirements (e.g., Pollutant Load Reduction Model [PLRM] (NHC et al. 2009); Lake Clarity Crediting Program (LRWQCB and NDEP 2011)). This proposed Round 12 SNPLMA research will directly address the research need of Theme 2b; “…improve and validate existing tools, models and methods methodology to estimate urban stormwater load reductions associated with the effects of restoration actions to reduce sediments and nutrient loads using SEZs.” This research also addresses key components of Theme 2d, particularly focusing upon the enhancement and conservation of SEZ critical functions including flood attenuation, surface and groundwater quality protection and the quantification of the fine sediment load reductions as a result of SEZ restoration efforts. Applying the SLRT methodology developed 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 2 by 2N (expected completion summer 2012, 2N 2010a) to a compilation of UTR and Angora Creek restoration projects that have varying levels of existing data will provide critical user guidance so that the SLRT can be implemented by resource managers in a consistent manner in the future. The ability to provide UTR restoration proponents with reliable FSP load reduction estimates and a detailed documented application of the SLRT methodology on a range of restoration projects would be invaluable. Defensible and standardized estimates of the average annual pollutant load reductions as a result of restoration actions, as intended by the SLRT, is critical for SEZ restoration proponents in the Tahoe Basin. C. BACKGROUND/PROBLEM STATEMENT The recent adoption of the Lake Tahoe TMDL will focus and prioritize public resources to reduce pollutant loads into Lake Tahoe with the intention of restoring the renowned clarity of Lake Tahoe (LRWQCB and NDEP 2010). The TMDL Pollutant Load Reduction Opportunity Report (LRWQCB and NDEP 2008) lists a number of priority restoration actions to be completed on Tahoe streams, but only considers the water quality improvement opportunity through source control by quantifying the sediment load reduction achieved as a result of reduced stream channel erosion. Yet, SEZ modifications are expected to have an even greater fine sediment particle (FSP; < 16 µm) load reduction benefit from treatment via sediment retention as a result of increased frequency and duration of floodplain inundation (2N 2010a). UTR project proponents (UTRWAG, California Tahoe Conservancy (CTC), CA State Parks, Lake Tahoe Basin Management Unit (LTBMU) and others) continue to struggle with securing grant funds because resource managers have not been able to reliably quantify the water quality benefits of the stream restoration projects. However, on‐going floodplain pollutant retention research on select Tahoe streams suggests overbank flow events do provide FSP pollutant treatment and concentration reduction via settling, adherence to vegetation, flocculation and stranding (Andrews and Schladow 2010a, 2010b; 2N 2006, 2010b, 2011). The water quality improvement opportunity of SEZ restoration efforts should include the sum of the source control and treatment load reductions, and the SLRT has been developed to meet this need. Water quality improvement is a typical goal of stream restoration and a priority for TMDL objectives, yet to date there are no reasonable estimates of these water quality benefits. SEZ restoration projects continue to be implemented within the Tahoe Basin without standardized protocols to quantify effectiveness. The density of restoration projects completed on the UTR and its critical tributaries between Meyers and the UTR Marsh provide an opportunity to apply the newly developed SLRT methodology to a series of restoration projects that vary in scale, approach, status and objectives. Total restoration project costs (planning, design, implementation and monitoring) will be obtained from the proponents to conduct simple water quality cost benefit analyses. In addition, an estimate of the cumulative benefits from SLRT will provide initial comparisons to pollutant load reduction opportunity estimates for other source category groups (LRWQCB and NDEP 2008). D. GOALS, OBJECTIVES, AND HYPOTHESES GOAL Apply the SLRT methodology to estimate the pollutant load reductions achieved as a result of numerous individual stream restoration efforts on the Upper Truckee River and Angora Creek and the cumulative benefit of these actions. OBJECTIVES 1.
2.
3.
Quantify project average annual FSP and TSS load reductions achieved by each designed or completed restoration project on the UTR and Angora Creek. Quantify total average annual FSP and TSS load reductions achieved as a result of restoration actions completed on UTR and Angora Creek. Evaluate the cost effectiveness ($/lb) of FSP reductions by each completed restoration project and compare to other pollutant load reduction strategies considered to meet the Lake Tahoe TMDL. 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 3 HYPOTHESES TO BE TESTED 1.
2.
SEZ restoration is a cost‐effective means to achieve significant FSP load reductions in the Tahoe Basin, particularly on large stream systems such as the Upper Truckee River. The current Tahoe Basin TMDL management recommendations underestimate the pollutant load reductions achievable with stream restoration by ignoring the reductions achievable through increased particle retention on the restored floodplain. E. APPROACH, METHODOLOGY AND LOCATION LOCATION OF RESEARCH The proposed research will apply the SLRT methodology to restoration projects on the Upper Truckee River between Highway 50 in Meyers and Lake Tahoe Boulevard in South Lake Tahoe, CA and will include Angora Creek, a critical tributary to the UTR where significant restoration efforts have been conducted (Figure 1). Even though restoration efforts have been conducted on the UTR Marsh below Lake Tahoe Blvd, it is assumed that SLRT methods will not be directly applicable to these projects given the hydrologic and sediment deposition variability within the Marsh. APPROACH The research approach will include 2 distinct steps: 1.
2.
Obtain, manage and analyze the necessary datasets of the identified restoration project sites with coordination from UTRWAG. Conduct pollutant load reduction estimates for each project reach using the SLRT methodology and conclude with a system‐wide estimate. Compare load reduction estimates to other water quality improvement strategies, and provide insight on the potential water quality improvement opportunity associated with SEZ restoration. Application of SLRT methods to each project will be documented in a step‐wise, transparent process so that other researchers can replicate the methodology at additional restoration sites with varying levels of available data. All data obtained and managed for the research will be compiled into a custom MS Access database and will be provided to the client and UTRWAG members at research completion. Recommendations and guidance to future users will detail the lessons learned from analyzing data generated by others and applying the data to restoration projects using the SLRT. These comparative analyses will include all assumptions and information sources, such that managers will have a clear understanding of how data were generated and how conclusions were made. METHODOLOGY The SLRT methodology developed by 2N (2010a) integrates available hydrologic, topographic and water quality data to estimate the water quality improvement from an SEZ restoration project. Geomorphic modifications of incised channels in the Tahoe Basin aim to increase the likelihood of inundating adjacent floodplain areas, which in turn increases sediment deposition on the floodplain and decreases in‐channel shear stress that drives sediment generation via channel erosion. Modeling the potential reduction in sediment loading at the downstream end of the restored SEZ on an average annual basis therefore requires several types of information about the pre‐ and post‐project conditions of the subject reach. While the final details of the SLRT methodology (expected late summer 2012) will be refined prior to the award of this funding, below is a technical outline of the expected SLRT methodology that will be applied to the completed UTR and Angora Creek restoration projects. The SLRT approach applies reasonable methods to available datasets to determine the probability distribution of specific discharge ranges expected at the subject reach. Empirically derived algorithms are used to predict the sediment loading introduced to the restored reach as a function of discharge, and morphologic site characteristics are used to constrain the expected load reduction benefits of restoration effort. The SLRT approach produces an average annual load reduction estimate without the years of costly water quality sampling that can be very difficult to obtain. Greater availability and higher resolution of the available data will improve confidence in SLRT 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 4 estimates, but there is an intentional flexibility and guidance within the methodology to allow users to estimate variables using the data that is available, comparable sites and best professional judgment. FLOODPLAIN DEPOSITION MODEL – POLLUTANT TREATMENT The restoration project benefit associated with increased floodplain retention of sediment (TSS and FSP) can be quantified by modeling the sediment loads between the discharge range of pre‐ and post‐restoration channel capacity, where the primary water quality benefit is expected to occur. Discharge events below the range are irrelevant because they do not inundate the floodplain under either channel geometry, high discharge events (above the range) are irrelevant because they happen less frequently and there is a degree of uncertainty with respect to floodplain deposition pre‐project. Under the SLRT methodology, net benefits to water quality from floodplain deposition (ΔD) can be calculated as: Q pre
ΔD =
∑R S t i
i i
(E1) i= Q post
where Si is the incoming TSS and FSP load for a given discharge (MT/day), ti is the expected amount of time that a given discharge occurs over the pre‐defined study period (days), and Ri is the retention coefficient that expresses the percent of sediment retained on the floodplain at different discharge conditions (%). The discharge range is between the channel capacity post‐project (Qpost) and channel capacity pre‐project (Qpre) where the primary water quality benefit is expected to occur. Figure 2 illustrates the relationship between input variables pre‐ and post‐
project and how these factors are integrated to produce an annual fine sediment load estimate for floodplain deposition. The greatest data gap present in the proposed SLRT approach shown in Figure 2 is the data to determine the retention efficiency of a floodplain with respect to discharge. With SNPLMA funding and continued collaboration with CA State Parks, over 80 floodplain sediment samples have been collected from the restored reach of Trout Creek (2N 2010b) and a functional floodplain on the Upper Truckee River (2N 2011) during the WY10 and WY11 snowmelt events at a range of discharge conditions. These floodplain sediment samples were analyzed longitudinally and laterally to determine percent difference and averaged by event discharge to produce measured retention coefficients. These averaged values for both sites were normalized as a function of the event discharge to channel capacity ratio for both of the sites sampled and presented in Figure 3. A sampled discharge to channel capacity ratio of 1 represents when the discharge of the event sampled equals the channel capacity, which allows integration of data from across sites. The floodplain topography and characteristics of each sampled site have surveyed pre and post inundation events. High resolution turbidity monitoring at the upstream and downstream extents of the Trout Creek restored floodplain are being used to verify the measured FSP retention coefficients. The current dataset supports the assumption that the retention coefficient varies exponentially as a function of discharge, with diminishing sediment retention as discharge increases. The retention coefficient is expected to be a function of the following measureable floodplain characteristics: •
•
•
Floodplain inundation area, generally obtained from HEC‐GeoRAS model outputs or GIS mapping (Figure 3.1); Average floodplain water depth, generally obtained from HEC‐GeoRAS model outputs or mapping (Figure 3.2); Average water column vegetation density (%), generally obtained from floodplain surveys at discrete floodplain water depths for critical discharge intervals (Figure 3.3). Floodplain sampling requires overbank events that are infrequent and unpredictable, requiring years of sampling to generate site‐specific retention coefficient curves like the one shown in Figure 3. Rather than instrumenting each floodplain to measure the retention coefficient for a specific discharge, SLRT recommends an approach to estimate the retention coefficient for specific discharge ranges based on measurable floodplain characteristics in a consistent and relatively accurate manner. The rapid, cost‐effective protocols provided in the SLRT to measure the 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 5 key floodplain characteristics will be implemented at each of the research sites on the UTR and Angora Creek to estimate the site‐specific retention coefficients. STREAM EROSION MODEL – POLLUTANT SOURCE CONTROL SEZ restoration efforts can result in net water quality benefit downstream as a result of reduced streambank erosion. In order to estimate this reduction, we must estimate the amount of channel erosion for different water discharge value ranges (Figure 4). We assume that the mass of sediment generated from the channel via erosion is a direct function of shear stress (τ) (Simon et al. 2000), which is defined as: τ = ρwgds ; where ρw is the density of water (kg/m3), g is the acceleration due to gravity (m/s2), d is the depth of water (m), and s is the slope of the channel. The following data are needed to determine the reduction in sediment inputs to the system from channel erosion as a result of restoration actions: •
•
•
Change in channel depth and width by lowering banks and/or raising the bed during restoration for a given discharge, generally assessed in the restoration planning and checked through channel cross‐
section measurements (Figure 4.1); Change in channel slope by increasing the channel length during restoration, generally assessed in the restoration planning and checked through channel longitudinal profile measurements (Figure 4.2); Frequency of occurrence for the range of discharge conditions, generally obtained from analyzing long‐term hydrological monitoring data (Figure 4.3). Using the site data described above and including separate coefficients that relate shear stress to vertical incision (k1) and lateral bank erosion (k2) (Figure 4.4), the net benefits to water quality from reduced channel erosion (ΔE) as a result of restoration actions can be calculated as: Qpre
ΔE = ρb
∑[k (τ
1
post ,i l post w post
) (
)]
- τ pre ,i l pre w pre + k2 τ post ,i l post hpost - τ pre ,i l pre hpre t i (E2) i =Qpost
where post‐ and pre‐restoration parameters are denoted with “pre” and “post” subscripts, ρb is the bulk density of channel material (kg/m3), τi is shear stress at a given discharge i (N/m2), l is channel length (m), w is channel width (m), h is bank height (m), and ti is the expected amount of time that a given discharge i occurs over the relevant study period (sec). Load reduction estimates from E2 can be calculated in a spreadsheet, with inputs from readily available pre‐ and post‐project channel geometry data. The integration of discharge yields a more realistic expression of channel conditions while remaining relatively simple to calculate. Scaling of coefficients (k) can be found in previous studies (e.g., Simon 2008, Simon et al. 2000). While scaling of the coefficients is most efficient these calculations are limited in resolution because the shear stress calculations for a given discharge (τι) are an average approximation of uniform flow. A more accurate calculation of shear stress distribution includes the variation associated with meander patterns (Figure 4.5). In the current development of SLRT, the research team is using a comparison of HEC‐GeoRAS outputs, which can incorporate variations of shear stress as a result of meander patterns (Figure 4.5), to verify the relative consistency of using equation E2 to estimate the reduced sediment input from channel erosion. Under the proposed research, HEC‐GeoRAS will be used to model select UTR and Angora Creek restoration project sites with sufficient pre‐ and post‐project topography data. Comparison of the net load reduction estimate derived from both average approximation and modeled shear stress inputs will inform SLRT users on the data necessary and level of effort required to produce sufficient load reduction estimates. CUMULATIVE LOAD REDUCTIONS The goal of the proposed research is to estimate the pollutant load reductions achieved as a result of numerous stream restoration efforts on the UTR and Angora Creek. Results from the floodplain deposition and stream erosion modeling estimates described above will be integrated to determine the total TSS and FSP load reduction for a range of discharge conditions on a project‐by‐project basis. This annual load reduction combines the increase in floodplain retention (kg/yr) with the reduction in channel erosion (kg/yr), which can then be integrated to produce a reach‐wide annual load reduction estimate for UTR and Angora Creek. 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 6 EXISTING DATA NEEDS Project evaluation using SLRT methodology requires channel cross‐sections, hydrology and water quality monitoring data be obtained for the restored reach. Sources of the necessary data include UTRWAG, CTC, CA State Parks, USGS, City of South Lake Tahoe, and others. The cost of each project will be obtained from proponents for each project in comparable formats that will include the planning, design and implementation. UTRWAG has continued to compile and integrate existing datasets on the UTR and Angora Creek, thus research collaboration with this group will be critical. Pre‐ and post‐project channel capacity will be determined from channel geometry data. Available hydrologic and water quality data from LTIMP will be used to determine sediment loading per discharge intervals. High resolution LiDAR topography (Watershed Sciences 2011) will be used as a HEC‐GeoRAS base surface for modeling and to determine floodplain characteristics at each site. Field evaluations will need to be completed to characterize vegetation density for discrete overbank discharge conditions. 2N currently has a large amount of hydrology, water quality and project effectiveness evaluation data for completed restoration projects on UTR and Angora Creek as a result of 2N’s Round 8 SNPLMA research that synthesized the quality and approach to riparian restoration effectiveness evaluations in the Tahoe Basin (2N et al. 2010). At the time of that research the SLRT methodology did not exist and, thus, our ability to provide a reasonable estimate of water quality benefits for completed projects was not possible nor within the project scope. Data relevant to this proposed effort will need to be processed, managed and analyzed in a standard format specific to the SLRT. F. RELATIONSHIP OF RESEARCH TO PREVIOUS AND CURRENT EFFORTS The proposed research will significantly leverage and utilize a wide array of existing datasets, particularly the integrated geomorphic and water quality datasets compiled by UTRWAG, CTC, CA State Parks and LTBMU. Pre‐ and post‐restoration observations and monitoring data collected on the completed UTR projects will be synthesized and integrated to determine the state of our existing knowledge on stream restoration effectiveness of water quality improvement. Applying SLRT methodology to planned projects such as the Upper Truckee River Restoration and Golf Course Relocation Project by the CA State Parks will be of immediate value. Scott Carroll of CTC and Cyndi Walck of CA State Parks will be partners in this research to assist with necessary coordination of information sharing and feedback. The results will assist with obtaining critical public support by providing a comparable and defensible estimate of water quality benefit. In addition, the proposed research will inform and/or build upon the following Tahoe Basin efforts: •
•
•
•
•
•
•
Methodology to Predict Fine Sediment Load Reductions as a Result of Floodplain Inundation in Lake Tahoe Streams (2N 2011); Stream Load Reduction Tool development (2N 2010a); Riparian Ecosystem Restoration Effectiveness Framework (2N et. al. 2010) Pollutant Load Reduction Model (NHC et. al. 2009) Pollutant Load Reduction Opportunity Report (LRWQCB and NDEP 2008) Lake Tahoe Total Daily Maximum Load (LRWQCB and NDEP 2010) Lake Clarity Crediting Program (LRWQCB and NDEP 2011) SNPLMA funded research efforts led by 2N have been used to develop and refine rapid evaluation methods and low cost event‐based sampling protocols to better understand and quantify fine sediment particle retention on SEZ floodplains (2N 2006, 2011). SNPLMA Round 11 research included the application of the SLRT (2N 2010a) to the Trout Creek restoration project in order to refine and solidify the methodology used to characterize condition, evaluate effectiveness, and estimate preliminary FSP load reductions achieved as a result of SEZ floodplain inundation. Trout Creek restoration, considered one of Tahoe Basin’s most successful stream restorations, is being used as a reference point for subsequent evaluations throughout the Tahoe Basin using the SLRT methodology. Through the development process, 2N has identified the needs, challenges and lessons learned in order to advise future SLRT users on how to best improve the consistency of estimates and constrain the relative uncertainty given the quality and breadth of available data. 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 7 G. STRATEGY FOR ENGAGING MANAGERS The research team will collaborate with and obtain necessary data from local agencies, resource managers and working groups. The team will provide two presentations to UTRWAG, given their knowledge and continued involvement in UTR and Angora Creek restoration, monitoring and management issues. The first presentation will be following the compilation and attainment of existing data, but prior to SLRT application to restoration projects. This meeting will allow for solicitation of additional data for consideration and feedback on the scale and technical approaches of the research, as well as information sharing to ensure all members are aware that load reduction estimates will be available shortly. The team will also present the draft report to UTRWAG and provide the group with an opportunity to comment prior to the final report. H. DESCRIPTION OF DELIVERABLES TASK 1 – DATA COLLECTION AND MANAGEMENT FOR SLRT APPLICATION The project team will coordinate and collaborate with agency personnel to obtain available data that will directly inform inputs to, or verification of, SLRT estimates. Field data collection will also be necessary to extend the current datasets at each project location. A presentation will be held at a routine UTRWAG meeting to ensure stakeholder awareness, participation and identification of all potentially applicable data. All data collected will be managed and compiled into a custom MS Access database, which will be made available to the client and interested stakeholders after completion of this research. Deliverable: MS Access database of data used for calculations TASK 2 – POLLUTANT LOAD REDUCTION ESTIMATES The 2N team will provide an average annual FSP load reduction estimate for each of the planned or completed projects identified (see Figure 1). The expected average annual cumulative FSP load reduction as a result of these projects will be determined and compared to the TMDL load reduction predictions from other strategies outlined in the Pollutant Load Reduction Opportunity Report (LRWQCB and NDEP 2008) and other available estimates. Deliverable: Summary table of SLRT derived pollutant load reduction estimates and other comparable estimates TASK 3 – TECHNICAL REPORTING The methods, SLRT inputs, results and conclusions will be provided in the technical report and presented to UTRWAG at a routine meeting. Any recommendations to assist future SLRT users and/or improve the methodology estimates will be provided. Beyond providing the specific FSP load reduction estimates for each restoration project identified, the objectives of the final report are to: •
Provide a detailed application of the SLRT methodology to guide users to complete future estimates on other SEZs. • Provide a broader basin‐wide perspective of the potential opportunity to reduce FSP loading to Lake Tahoe as a result of both reduced streambank erosion and increased floodplain retention. Deliverables: Draft and Final Technical Report TASK 4 – PROJECT MEETINGS AND ADMINISTRATION 2N will conduct two presentations at UTRWG routine meetings. One will be held during Task 1 to ensure stakeholder awareness, participation and identification of all potentially applicable data. The second presentation will review the pollutant load reduction estimates and draft technical report. Project administration, invoicing and quarterly progress reports will be ongoing. Deliverables: Two presentations to UTRWG TAC team; Quarterly progress reports 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 8 III. Schedule of Major Milestones/Deliverables Project schedule provided below is based on contract award by August 2012. Task 1 2 3 4 Deliverable
Compile and manage existing data. Select and conduct field analysis of example restoration sites as necessary. Pollutant load reduction estimates; field surveys
Draft Technical Report
Final Technical Report
UTRWAG TAC Meeting #1
UTRWAG TAC Meeting #2
Quarterly progress reports Invoicing Start Date
End Date Aug 12 Jan 13 Jan 13
June 13
Sept 13
June 13 Sep 13 Nov13 Nov 12 Sept 13 1st of Jan, April, July and Oct throughout project duration Ongoing monthly 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Proposal: Tahoe Research Supported by SNPLMA Round 12 Theme 2b: Quantifying the benefits of urban storm water management p. 9 IV. Literature Cited 2NDNATURE. 2006. CSLT Upper Truckee River Sediment Monitoring, Middle Reach (2002‐2005). Prepared for the City of South Lake Tahoe. Final Report. Funded by the Bureau of Reclamation in cooperation with Tahoe Resource Conservation District (TRCD). Monitoring designed and implemented by the CSLT. March 27, 2006. 2NDNATURE, Environmental Incentives and River Run Consulting. 2010. Riparian Ecosystem Restoration Effectiveness Framework. Final Technical Report. Prepared for USDA Forest Service Pacific Southwest Research Station. January 2010. 2NDNATURE. 2010a. Quantification and Characterization of Trout Creek Restoration Effectiveness: Focused Development of a Stream Load Reduction Methodology (SLRT). Final Characterization Plan. Prepared for USDA Forest Service Pacific Southwest Research Station. April 2010. 2NDNATURE. 2010b. Quantification and Characterization of Trout Creek Restoration Effectiveness: Focused Development of a Stream Load Reduction Methodology (SLRT). WY2010 Data Collection Summary. Prepared for USDA Forest Service Pacific Southwest Research Station. November 2010. 2NDNATURE. 2011. Methodology to Predict Fine Sediment Load Reductions as a Result of Floodplain Inundation in Lake Tahoe Streams. Final Technical Report. Prepared for USDA Forest Service Pacific Southwest Research Station. February 2011. Andrews, S.W. and S.G. Schladow. 2010a. Floodplain deposition modeling: quantifying the sequestration of fine sediment on Trout Creek. Lake Tahoe Stream Environment Zone Symposium. Incline Village, NV. Andrews, S.W. and S.G. Schladow. 2010b. Numerical modeling of the influences of floodplain morphology and vegetation on sediment retention in Trout Creek. 5th Biennial Lake Tahoe Basin Science Conference. Incline Village, NV. Lahontan Regional Water Quality Control Board (LRWQCB) and Nevada Division of Environmental Protection (NDEP). 2008. Lake Tahoe TMDL Pollutant Reduction Opportunity Report. California and Nevada. March 2008. LRWQCB and NDEP. 2010. Tahoe Basin Total Maximum Daily Load, Technical Report. California and Nevada. June 2010. LRWQCB and NDEP. 2011. Lake Clarity Crediting Program Handbook for Tahoe Basin TMDL Implementation v1.0. Prepared by Environmental Incentives, LLC. South Tahoe Basin, CA. September 2011. Northwest Hydraulic Consultants (NHC), Geosyntec Consultants, and 2NDNATURE. 2009. Pollutant Load Reduction Model (PLRM) Model Development Document. Prepared for Lake Tahoe Basin Storm Water Quality Improvement Committee. South Lake Tahoe, CA. Simon, A., Curini, A., Darby, S.E., and Langedoen, E.J. 2000. Bank and near‐bank processes in an incised channel: Geomorphology, v. 35, p. 193‐217. Simon, A. 2008. Fine‐sediment loadings to Lake Tahoe: Journal of American Water Resources Association, v. 44, p. 618‐639, doi:10.1111 ⁄ j.1752‐1688.2008.00188.x. Upper Truckee River Watershed Advisory Group (UTRWAG). 2007. Guidelines for Upper Truckee River Restoration Project Monitoring. Prepared January 2007. Watershed Sciences. 2011. LiDAR Remote Sensing: Lake Tahoe Watershed, California and Nevada. Prepared January, 2011. 2NDNATURE, LLC
500 Seabright Avenue Suite 205 Santa Cruz CA 95062 p 831.426.9119 w 2ndnaturellc.com
Lake Tahoe
LEGEND
Upper Truckee Marsh (not included)
Research Area
Upper Truckee Riv
er
Highw
ay 89
e
ho
ke
vd
Bl
Ta
ek
re
tC
High
way
50
Tro
u
Fallen Leaf Lakte
La
Ango
ra
Cr
k
ee
Lake
Tahoe
Meyers
FIGURE 1: Proposed research will be conducted on the completed
Figure 1: Upper Truckee River restoration project locations.
and/or planned SEZ restoration projects on the Upper Truckee River
between Meyers and the UTR Marsh and projects on the critical
tributary Angora Creek.
Miles
0
0.25
0.5
0.5
miles
11
Frequency of occurrence (days)
TSS and FSP load (tonnes/day)
1 (Si)
TSS
FSP
2 (ti)
Discharge (cfs)
Discharge (cfs)
Retention coefficient (Ri)
3 (Ri)
?
Floodplain research to determine Ri
inundation
pre- and postrestoration
inundation
post-restoration
only
no floodplain
inundation
Average annual sediment (TSS
and FSP) retained on
floodplain (tonnes/year)
Discharge (cfs)
post-
pre-
Water discharge (cfs)
Floodplain deposition model: Deposition on the floodplain for total and fine sediment can be determined using available
water quality (1) and water discharge data (2) to determine the amount of sediment transported during specific discharge
conditions. A retention coefficient is applied (3) that estimates the fraction of TSS and FSP load retained on the floodplain for
different discharge conditions pre- and post-project . 2NDNATURE floodplain sampling efforts during WY09 - WY11 have
provided data to inform the Ri to discharge relationship (see Figure 3). The retention coefficient is based on floodplain factors
such as vegetation height and density, floodplain inundation area, and average floodplain water depth. The primary floodplain
water quality benefit as a result of restoration actions occurs at discharge values between inundation post-project and inundation pre- and post-project (bottom graph between red lines).
Figure 3. Floodplain Deposition Model Components for SLRT
Floodplain deposition model and inputs
FIGURE 2
100%
Trout
90%
100%
TroutUTR
70%
80%
UTR
y = 1.0e -0.4x
R² = 0.6
60%
70%
Retention Coefficient (Ri)
60%
50%
50%
40%
40%
30%
30%
20%
20%
10%
10%
0%
0%0.0
0.0
1.0
1.0
2.0
3.0
Discharge /2.0
Channel Capacity3.0
Ratio (cfs/cfs)
4.0
4.0
5.0
5.0
Sampled Discharge to Channel Capacity Ratio
pre-restoration
Qpost Qpre
Discharge (cfs)
post-restoration
pre-restoration
Qpost Qpre
Discharge (cfs)
Avg Water Column Vegetation Density (%)
post-restoration
Avg Floodplain Water Depth (ft)
(NQQFRNCKP4GVGPVKQP%QGHHKEKGPV The plot above contains preliminary data estimated from 2010 and 2011
spring snowmelt floodplain water quality sampling events on Upper Truckee River and Trout Creek. The retention
coefficient (Rfsp) can be calculated using passive floodplain samples given a range of discharges of floodplain
inundation.1Since the Rfsp plot contains two stream
reaches with various site
2
3 characteristics, a ratio of the
discharge at the time of sampling occured is normalized to the channel capacity discharge.
Floodplain Inundation Area (sq ft)
Retention Coefficient (Rfsp)
80%
90%
post-resto
ration
pre-restor
ation
Qpost Qpre
Discharge (cfs)
3a
Q2
Q
1
Retention Coefficient: The preliminary floodplain sample data presented
60%
in the upper curve was collected during WY10 and WY11 snowmelt on
80%
Trout Creek and UTR. The x-axis represents the sampled discharge to
channel capacity ratio, where a ratio of 1 represents when the discharge
Average water column
of the event sampled equals the post-project channel capacity. The
vegetation density
provided curve illustrates an exponential decay of floodplain sediment
retention with increasing discharge. The retention coefficient is expected
to be largely a function of (1) inundation area, (2) average floodplain water depth, and (3) average water column
vegetation density for a given discharge. Average water column vegetation density refers to the cross sectional area of
vegetation within the total water column as a function of floodplain water depth (3a). The hypothetical curves shown
in graphs 1-3 are estimated based on the floodplain of the Trout Creek restoration site. The actual shape and slope of
the pre- and post-restoration curves may depend on site-specific floodplain characteristics. Post overbank floodplain
surveys confirm significant adherence of particles to vegetation, which is supported by other Tahoe Basin researchers
(Andrews and Schladow 2010ab).
(.11&2.#+0%*#4#%6'4+56+%5#0&/'#574'&4'6'06+10
(+)74':
retention coefficient and measurable proxies
FIGURE 3
Elevation (ft)
Water depth (ft)
pre-restoration
Frequency of occurrence (days)
2
1
post
-rest
oratio
n
post-restoration
pre-rest
oration
Discharge (cfs)
Discharge (cfs)
Distance (ft)
4
3
5
E2~k2t
Sediment produced (TSS and FSP)
by channel erosion
(amount per time)
E1~k1t
pre-
post-
Water discharge (cfs)
Channel erosion model: Generating a total and fine sediment load by erosion of the channel can be determined
using changes in average channel water depth for a given discharge (1) from lowering bank heighs and/or raising bed
elevation, and in channel gradient (shown as changes in the longitudinal profile in 2) from increasing sinuosity.
Adding parameters of frequency of a particular discharge occurrence (3) and separately model vertical incision and
stream bank erosion (4) using channel geometry measurements and coefficients that relate shear stress to vertical
incision (k1) and lateral bank erosion (k2) allow for annual sediment load calcualtions to be modeled. Where sufficient
project data are available, a 2D model HEC-geoRAS can be used to more precisely calculate vertical and horizontal
erosion for multiple cross-sections, thereby producing 2D erosion results (5). The cumulative water quality benefit is
greatest at intermediate water discharge conditions (bottom graph).
Figure 4. Channel Erosion Model Components for SLRT
Channel erosion model and inputs
FIGURE 4