Development and Demonstration of a GIS-Based Cumulative Effectiveness Approach to Buffer Design and Evaluation

Riparian buffers are important features that help to mitigate suspended sediment loads within rivers running through agricultural landscapes. Evaluating their effectiveness for sediment control by different modelling approaches can help direct beneficial management practices. The Soil and Water Assessment Tool (SWAT) model and the Adapted Neuro-Fuzzy Inference System (ANFIS) based model were used for prediction of suspended sediment concentrations (SSC) and sediment loads in the Mill River watershed (PEI, Canada). Those models were then used to assess the impact of riparian buffer widths in reducing sediment loads. The ANFIS model predicted measured SSC more accurately than the SWAT model. The relationship between buffer width and sediment reduction was asymptotic, and the relationship begins to plateau when the width reaches 50 m. Increasing the buffer width from 15 to 100 m led to an increase in sediment loads retention of 30.5% and 36.2% of the total stream sediment load for the SWAT and ANFIS models, respectively. This study highlighted that a data-driven ANFIS based model can be used to simulate the impact of land use changes on the sediment delivery in a river.

This paper presents the design of an output buffer with DAC functionality, which meets the requirements of small size, low power consumption, and high precision for OLED source driver chips. The two-stage DAC has a smaller area compared to traditional resistor string DACs, providing higher precision grayscale voltages that better meet the requirements of display drivers. The buffer utilizes a rail-to-rail input stage and Class AB output stage to achieve a wide input-output voltage range. Cascode Miller compensation is employed to improve stability, and a programmable tail current source with current steering DAC is used to realize 3-bit interpolation, saving overall chip area and power consumption. In the HLMC 55 nm CMOS process, the buffer has a rise time of 0.52 us and a fall time of 0.6 us for input voltages ranging from 0-1.2 V. The buffer occupies an area of 35×30 um2.

The U.S. Environmental Protection Agency (EPA) Total Maximum Daily Load (TMDL) program has accounted for the listing of over 40,000 impaired waters nationwide and the development of over 37,000 TMDLs since the program’s creation. Case-specific accounts of implementation are widespread, but the actual rate of implementing TMDLs nationally or regionally has remained virtually unknown because full census and tracking of every implemented practice would be an overwhelming if not impossible task. To gain insights on implementation, EPA’s TMDL Program Results Analysis Project conducted a sample-based analysis of TMDL implementation rates and characteristics in the six EPA Region 5 states (IL, IN, MI, MN, OH and WI). A probabilistic sample was drawn from all TMDLs established through FY2007. Sampled TMDLs were allocated proportionally to states based on each state’s total TMDL production. Regional but not specific state-level statistics were the goal of the study. Subpopulations of interest contrasted older (through FY2003) versus newer (FY2004 – FY2007) TMDLs, and nonpoint-source (NPS)-only TMDLs versus point source (PS)-only and mixed (PS/NPS) TMDLs. The project team extracted information on each of the 138 sample TMDLs and their proposed NPS and PS controls from EPA data systems in advance of working with each state to verify implementation rates and patterns across the Region. Findings demonstrated that, within a +/- 10% margin of error at 90% C.I., an estimated 80.3% of Region 5 TMDLs were at least partially implemented. Full implementation was uncommon. No implementation was observed in approximately 20% of the sample, but the diffuse nature of control practices typical of many TMDLs made complete verification of every practice difficult. Among subpopulations, implementation rates did not differ significantly between older or newer TMDLs, but the mixed TMDLs implementation rate exceeded the NPS-only rate by 16.1%. Implementation plans existed for 79.6% of TMDLs, and NPS-only TMDLs showed more plans than the mixed TMDL subpopulation. TMDLs generated as part of large watershed, multiTMDL efforts comprised 13.2% more of the newer TMDLs subpopulation than the older TMDLs subpopulation. Post-analysis steps included exploring GIS data on the watershed traits of each sampled TMDL for other possible associations with patterns of implementation. Analysis of predominant land cover in the samples’ watersheds did not reveal significant differences among implementation rates associated with urbanized, heavily agricultural, lightly agricultural, and rural non-agricultural watersheds.

Intermountain West planners, designers, and resource managers are looking for science-based procedures for determining buffer widths and management techniques that will optimize the benefits riparian ecosystems provide. This study reviewed the riparian buffer literature, including protocols used to determine optimum buffer widths for water quality and wildlife habitat functions. We selected an existing protocol for determining buffer widths for water quality functions that could be readily adapted for use in this region. The protocol is based on the best available science, uses existing or easily obtained data, and is practical for in-field applications. The protocol was modified to accommodate Intermountain West landscape attributes. In addition, a companion protocol was developed to determine buffer widths for wildlife habitat tiered to landowner willingness to participate in wildlife conservation. The research findings of this study have been compiled in handbook format. This handbook provides the user with a step-by-step protocol for determining optimal (variable) buffer widths for water quality and wildlife that maximize riparian ecosystem benefits and minimize the loss of productive farm and ranch land. It also includes a companion CD including a case study, data forms, worksheets, reference appendices, and other informational material to assist the user.

Kim, Y.H.; Sugarman, D.E.; Kim, H.C.; Son, S.; Ha, H.K.; Chang, W.K.; Han, K.W., and Ryu, J., 2018. Implementation of a Numerical Model of Metals for Total Maximum Daily Loads (TMDLs) in Onsan Harbor, Korea. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1506–1510. Coconut Creek (Florida), ISSN 0749-0208.Accumulation of heavy metals has been one of fundamental environmental concerns for many coastal and estuarine systems, which can be directly influenced by contaminants loading from land. Onsan Harbor, Korea, surrounded by Onsan National Industrial Complex, shows high concentration of heavy metals in the seabed sediments. In order to establish proper environmental management plan for Onsan Harbor, the implementation of a Total Maximum Daily Loads (TMDL) was proposed. As a part of TMDL for metals, numerical model has been developed to evaluate metal fluxes into the Onsan harbor.A bathtub model for four different metals, including Copper, Zinc, Lead, and Mercury, was implemented in Onsan harbor. To supply data for boundary conditions and model calibration, extensive monitoring programs were conducted in the study area for past three years, between 2014 and 2016. The data from the monitoring programs includes freshwater discharge rate, load of metals from streams and tributaries, concentration of dissolved and particulate metals in water and sediments, sedimentation rates, and current velocities. The model was calibrated and validated with these monitoring data and other public data sets, and the results confirm high performance of the metal TMDL model in Onsan Harbor system. To evaluate numeric targets of the TMDL for metals, more than 100 scenarios were simulated with the well-calibrated model. The results show that (1) after the reduction of 10% loading from the present level, the copper concentration in sediments will be lower than Probable Effects Level (PEL) within 12 years, and (2) after the reduction of 10% zinc loading, the zinc concentration in sediments will be lower than PEL in 17 years.

The Tigris River in Baghdad is a large sand-bed river, supply-limited because of the implementation of a water flow regulation scheme comprising a series of reservoirs and barrages. The significant reduction in the water discharge has affected the hydraulic performance of the river and turned it into an under-fit river of complicated morphology where many islands and bank deposits have been showed up across an 18 km reach in addition to the essential sinuosity. Measuring sediment load at individual cross-sections in the river gives misleading estimates and the corresponding sediment rating curve has a locally limited using. A spatially sediment rating by investigating sediment loads over the complicated reach is required to overcome the local limitations. Sediment transport rates have been investigated at 16 cross-sections along the study reach by collecting suspended load, bed load and bed material samples. Velocity profiles were measured at the sampling stations using an Acoustic Doppler Current Profiler (ADCP). The measurement results indicated that the suspended load is the dominant mode of transport (93.5%). However, bedloads were considered in determining the total loads. A spatial total load rating curve in the form of a power function was established and examined against the sediment measurements. Twenty-two previously published total load formulae where applied at the same sections and of these the Colby1964 formula gave the closest fit to the measured loads. Based on the results from this study a recommended procedure is established for using a spatial total load rating curve to estimate sediment transport rates for similar morphologically complicated rivers. Average annual transport rates during the period 2009–13 was estimated at 3.21 million tons.

This effort develops a surrogate modeling approach for predicting the effects of manufacturing variations on blade unsteadiness and performance of a transonic turbine. CFD results from a set of 105 as-manufactured turbine blade geometries are used to train and validate the surrogate models. Blade geometry variation is characterized with point clouds created from a structured light optical measurement system and as-measured CFD grids are generated through mesh morphing of the nominal design grid data. Results from a Reynolds-averaged Navier-Stokes flow solver with the two-equation Wilcox turbulence model are used as training and validation data. Principal Component Analysis (PCA) of the measured airfoil geometry variations is used to create reduced basis of independent surrogate model parameters. Results of the surrogate are compared to the CFD results. It is shown that the surrogate model typically captures between 60% and 80% of the full CFD predicted variance. Three new approaches are introduced to improve the accuracy of the surrogate. A zonal PCA approach is defined which improves surrogate accuracy by focusing on key regions of the airfoil. A training point reduction strategy is proposed that is based on the kd-tree nearest neighbor search algorithm and reduces the required training points by 25%. A second reduction approach uses k-means clustering to effectively select training points from the 105 blade population and is used to reduce the required training points by up to 66%.

This effort develops a surrogate modeling approach for predicting the effects of manufacturing variations on performance and unsteady loading of a transonic turbine. Computational fluid dynamics (CFD) results from a set of 105 as-manufactured turbine blade geometries are used to train and validate the surrogate models. Blade geometry variation is characterized with point clouds gathered from a structured light, optical measurement system and as-measured CFD grids are generated through mesh morphing of the nominal design grid data. Principal component analysis (PCA) of the measured airfoil geometry variations is used to create a reduced basis of independent surrogate model parameters. It is shown that the surrogate model typically captures between 60% and 80% of the CFD predicted variance. Three new approaches are introduced to improve surrogate effectiveness. First, a zonal PCA approach is defined which investigates surrogate accuracy when limiting analysis to key regions of the airfoil. Second, a training point reduction strategy is proposed that is based on the k–d tree nearest neighbor search algorithm and reduces the required training points up to 38% while only having a small impact on accuracy. Finally, an alternate reduction approach uses k-means clustering to effectively select training points and reduces the required training points up to 66% with a small impact on accuracy.

Although the U.S. Congress established the Total Maximum Daily Load (TMDL) program in the original Clean Water Act of 1972, Section 303(d), it did not receive attention until the 1990s. Currently, two methods are available for tracking pollution in the environment and assessing the effectiveness of the TMDL process on improving the quality of impaired water bodies: field monitoring and mathematical/computer modeling. Field monitoring may be the most appropriate method, but its use is limited due to high costs and extreme spatial and temporal ecosystem variability. Mathematical models provide an alternative to field monitoring that can potentially save time, reduce cost, and minimize the need for testing management alternatives. However, the uncertainty of the model results is a major concern. Uncertainty is defined as the estimated amount by which an observed or calculated value may depart from the true value, and it has important policy, regulatory, and management implications. The source and magnitude of uncertainty and its impact on TMDL assessment has not been studied in depth. This article describes the collective experience of scientists and engineers in the assessment of uncertainty associated with TMDL models. It reviews sources of uncertainty (e.g., input variability, model algorithms, model calibration data, and scale), methods of uncertainty evaluation (e.g., first-order approximation, mean value first-order reliability method, Monte Carlo, Latin hypercube sampling with constrained Monte Carlo, and generalized likelihood uncertainty estimation), and strategies for communicating uncertainty in TMDL models to users. Four case studies are presented to highlight uncertainty quantification in TMDL models. Results indicate that uncertainty in TMDL models is a real issue and should be taken into consideration not only during the TMDL assessment phase, but also in the design of BMPs during the TMDL implementation phase. First-order error (FOE) analysis and Monte Carlo simulation (MCS) or any modified versions of these two basic methods may be used to assess uncertainty. This collective study concludes that a more scientific method to account for uncertainty would be to develop uncertainty probability distribution functions and transfer such uncertainties to TMDL load allocation through the margin of safety component, which is selected arbitrarily at the present time. It is proposed that explicit quantification of uncertainty be made an integral part of the TMDL process. This will benefit private industry, the scientific community, regulatory agencies, and action agencies involved with TMDL development and implementation.

Traditional approaches aiming at protecting surface waters from the negative impacts of forestry often focus on retaining fixed width buffer zones around waterways. While this method is relatively simple to design and implement, it has been criticized for ignoring the spatial heterogeneity of biogeochemical processes and biodiversity in the riparian zone. Alternatively, a variable width buffer zone adapted to site‐specific hydrological conditions has been suggested to improve the protection of biogeochemical and ecological functions of the riparian zone. However, little is known about the monetary value of maintaining hydrologically adapted buffer zones compared to the traditionally used fixed width ones. In this study, we created a hydrologically adapted buffer zone by identifying wet areas and groundwater discharge hotspots in the riparian zone. The opportunity cost of the hydrologically adapted riparian buffer zones was then compared to that of the fixed width zones in a meso‐scale boreal catchment to determine the most economical option of designing riparian buffers. The results show that hydrologically adapted buffer zones were cheaper per hectare than the fixed width ones when comparing the total cost. This was because the hydrologically adapted buffers included more wetlands and low productive forest areas than the fixed widths. As such, the hydrologically adapted buffer zones allows more effective protection of the parts of the riparian zones that are ecologically and biogeochemically important and more sensitive to disturbances without forest landowners incurring any additional cost than fixed width buffers.

Water quality modeling is a major source of scientific uncertainty in the Total Maximum Daily Load (TMDL) process. The effects of these uncertainties extend to water quality trading programs designed to implement TMDLs. This study identified how water quality model uncertainty affects outcomes related to the Non-Tidal Passaic River Basin TMDL for total phosphorus (TP) and potential trades of TP between point sources. Although the TMDL scenario showed greater than 10% probability of exceeding TMDL targets for chlorophyll-a (chl-a) at Dundee Lake and TP load diverted to the Wanaque Reservoir, the efficacy of TMDL measures was clearly demonstrated when compared directly to actual conditions in Water Year (WY) 2002. Trading scenario simulations suggest that trading ratios have been well designed. Each scenario demonstrated parity with or improvement from the baseline at the TMDL critical locations of Dundee Lake and the Wanaque South intake, and low risk of hot spots elsewhere.

<p>River is one of important water sources for many activities including industrial and domestic usage such as daily usage, transportation, power supply and recreational activities. However, increasing activities in a river has grown the sources of pollutant enters the water bodies, and degraded the water quality of the river. It becomes a challenge to develop an effective river management to ensure the water sources of the river are well managed and regulated. In Malaysia, several approaches for river management have been implemented such as Integrated River Basin Management (IRBM) program for coordinating the management of resources in a natural environment based on river basin to ensure their sustainability lead by Department of Drainage and Irrigation (DID), Malaysia. Nowadays, Total Maximum Daily Load (TMDL) is one of the best approaches for river management in Malaysia. TMDL implementation is regulated and implemented in the United States. A study on the development of TMDL in Malacca River has been carried out by doing water quality monitoring, the development of water quality model by using Environmental Fluid Dynamic Codes (EFDC), and TMDL implementation plan. The implementation of TMDL will help the stakeholders and regulators to control and improve the water quality of the river. It is one of the good approaches for river management in Malaysia.</p>

Climate change will have numerous and diverse impacts on the environment, including those on ambient water quality. In areas projected to experience decreased runoff (e.g., in many semiarid areas), water quality deterioration will be even more pronounced. The number of waterbodies recognized as impaired is likely to increase, even if pollution levels remain stable. However, projected climate change impacts on ambient water quality and Total Maximum Daily Load (TMDL) have been studied relatively little. The objectives of this paper are to review available water quality studies in the context of climate change and recommend ways in which a few key issues in water quality programs (e.g. critical condition, uncertainty analysis) should be adapted to reinforce effective water quality management in a changing climate. This paper reviewed water quality issues in a climate change context from several available studies that extend to different waterbody types (stream, lake, and estuary) and conducted a preliminary comparison between threshold approach and scenario approach. It also provided a summary of threshold approach and scenario approach, including major advantage and disadvantage of both approaches, for evaluating climate change impact on ambient water quality and related TMDL program. Case studies reviewed in this paper included climate change evaluation on long-term water quality by U.S. Environmental Protection Agency (USEPA) Chesapeake Bay Program and consideration for incorporating climate uncertainty in the upcoming Bay TMDL, a river in Mid-Atlantic region using USEPA BASINS Climate Assessment Tool, and a nutrient-impaired lake in the Northeast. In response to the statement that stationarity should no longer serve as a central, default assumption in water-resource risk assessment and planning , trade-offs need to be made between ambient water quality simulations using either long-term historical data series or stochastic predictions of such data based on properties of the historical time series. It is important to assess the pollutant loading estimate and future effectiveness of a water quality program or TMDL implementation plan under projected climate change scenarios as well as under different management actions in response to climate. The water quality management and permitting programs will need to adapt by considering the long-range implications for waterbody impairment associated with climate change and make needed revisions to TMDL guidance and water quality-based effluent limitations (e.g. under future lower low-flow condition). Ongoing studies will equip policymakers with the information and decision tools required to cost-effectively adapt to climate change impacts on water quality management.

In 2006, the Connecticut Department of Environmental Protection issued an impervious cover (IC) Total Maximum Daily Load (TMDL) for the Eagleville Brook watershed, located on the University of Connecticut campus and the adjacent Town of Mansfield, CT. While traditional TMDLs typically target a specific pollutant, this one addresses the impacts of urban development directly by using IC as the TMDLs metric. This approach was chosen because the Eagleville Brook Watersheds biological impairment could not be attributed to any one pollutant, but rather, was ascribed to an array of pollutants transported by stormwater and linked to urbanization or, more specifically, impervious cover (IC). The existing IC in the Eagleville Brook Watershed was measured at 18.0%, but the TMDL target was set at 11% based on characteristics of similarly sized watersheds in Connecticut that had healthy macroinvertebrate populations.

Most states in the U.S. have a general water quality standard intended to protect water from all potential pollutants not specifically named or identified in other standards. Biological indicators are used, in part, to assess the level of water quality with respect to this general standard. Under EPA’s Total Maximum Daily Load (TMDL) program, impaired waters based on a biological assessment require an additional step compared with non-biological TMDLs. In non-biological TMDLs, the “pollutant” is typically the parameter being monitored, with a direct link to the impairment. In biological TMDLs, cause and effect must first be established between one or more pollutants and the impacted biological community. This article presents examples of approaches taken in different states to monitor and assess the biological health of our streams based on varying combinations of algal, macroinvertebrate, and fish communities. While fish are the ultimate integrator of lower ecological organisms, their occurrence and abundance has been greatly manipulated by humankind. Periphytic algae are perhaps the fastest responding biological population and can be used for some pollutant-specific diagnoses, but most states lack the expertise required for detailed taxonomic classification. Macroinvertebrates, the most commonly monitored biological community, are abundant in most streams, but most metrics are not diagnostic of specific stressors. Within the TMDL framework, issues are discussed related to setting TMDL targets, linking biological impairments with pollutants, and defining biological target endpoints. Although surrogate measures are often used for setting TMDL target loads, biological recovery is measured against biological endpoints. The use of biological indicators for assessment and development of biological TMDLs can be improved through modeling procedures that better define cause-and-effect relationships, through a better understanding of the limits of restoration, and through a more unified national policy that focuses on restoration.