Water is an essential resource, playing a vital role in almost all human activities. Water is also a scarce resource. Population growth, industrialization, and climate change pose significant threats, necessitating on real-time monitoring of water resources. Recent developments in wireless sensor networks have made such monitoring possible, but the networks pose numerous challenges when deployed heterogenously at watershed scales. We present the detailed architecture of Savannah River Macroscope, an end-to-end ecological monitoring system designed to support large scale research and management of water resources. The system architecture spans four layers: (i) a custom wireless sensing platform; (ii) a multi-tier sensing fabric based on WiFi, cellular, and mesh-networking technologies; (iii) real-time streaming middleware for the processing, annotation, and archival of sensor data; and (iv) front-end applications for the management and visualization of sensor observations and system health information. Unique among existing implementations is the emphasis on data semantics and system configurability. In this paper, we describe how the system meets the challenges of large-scale hydrological sensing, detail the system architecture, and evaluate its performance with respect to current deployments.

Semantic technologies provide an expressive, interoperable means of deriving knowledge from the profusion of raw data gathered by sensor networks. The W3C's Semantic Sensor Network (SSN) ontology provides a complex but powerful metadata standard for describing large-scale sensing systems. However, managing this metadata across large, heterogeneous sensor networks is cumbersome, especially when non-technical parties independently deploy various types of instruments. To place the descriptive power of the Semantic Web at the fingertips of sensor network professionals, we must bridge the gap between abstract semantic frameworks and real-world sensor hardware. In this paper, we present a metadata management system for heterogeneous sensor networks based on the SSN ontology. Using Semantic Web concepts, we design and implement a system for maintaining hardware information and describing individual sensor deployments. Finally, we show the viability of our architecture by describing its integration with Intelligent River®, a large-scale sensor network initiative, and evaluating its effectiveness based on real sensor deployments.

Wireless mesh-based backhaul infrastructure is intended to provide reliable data transmission, with high throughput across large-scale networks. Load balancing is essential over a long period of operation to provide high throughput and uninterrupted service to end users. Load across mesh nodes is highly variable as the traffic depends on the number of clients connected to the nodes, as well as the services they use. Existing load balancing solutions are based on theoretical analysis and simulations. Most require distributed routing algorithms executed over compute-intensive routing nodes. It is also challenging to provide practical support for real-time traffic redirection using traditional mesh nodes. In this paper, we develop a prototype mesh infrastructure where flows from a source node can take multiple paths through the network. OpenFlow, an emerging technology that makes network switches programmable via a standard interface, allows flexible control of data flow paths. The Better Approach To Mobile Ad-hoc Networking (B.A.T.M.A.N) mesh protocol is used to provide mesh topology and link quality information. The OpenFlow controller decides the best data path based on this information to ensure high throughput data transfer. To demonstrate the usefulness of our approach, we have implemented three test cases to enable data path setup and redirection with low complexity and overhead. Our test case measurements confirm that OpenFlow is a promising complementary technology to traditional mesh routing protocols for wireless networks.

Real-time quality control (QC) of streaming natural resource data is needed to support the delivery of high quality data to system users. QC processes need to enable the identification of aberrations, as well as trends that may indicate degradation or component failures. These QC processes form a framework to support the goal of verified data delivered in a timely manner. In this paper, we investigate a method of computing Local Correlation Score (LCS) to detect anomalous patterns among sensor platforms in a concurrent manner. We use the R programming language and OpenMPI. Using empirical tests, we determine the benefits of computing the LCS in parallel, and on various sizes of clusters. We also analyze its use for real time mapping of Intelligent River data. Our results show that the LCS computed concurrently is an effective means for prompt quality assurance of natural resource data.

The world is witnessing tremendous innovation in wireless sensing technology, which creates opportunities to benefit environmental monitoring in significant ways. However, there are several challenges that are not thoroughly discussed by current studies in designing the wireless network infrastructure for these applications. In general, the monitoring units should provide reliable data communication across diverse environments. The wireless system should also meet requirements that most current platforms fail to satisfy, such as scalable coverage, reliability, robustness, and low operating cost. Finally, the network architecture should be kept simple to aid in the management of infrastructure deployments across disparate environments. With the aim of addressing these challenges, a two-tier network architecture for remote environmental monitoring is described in this study: (i) A sensor gateway is designed to transmit observation data from local sensors at the first tier. (ii) The second tier of the infrastructure reliably replays this data to a remote server for analysis via a wireless mesh network. A wide range of environments are supported, from open fields and dense forests, to Wi-Fi areas and cellular-only zones. In this study, a wireless backhaul network comprising wireless sensor gateways was deployed in Aiken, South Carolina. The network performance was systematically evaluated through experimental trials. Results demonstrate the infrastructures ability to support effective data collection and reliable data transmission.

This paper presents an ontology-based approach for data quality inference on streaming observation data originating from large-scale sensor networks. We evaluate this approach in the context of an existing river basin monitoring program called the Intelligent River®. Our current methods for data quality evaluation are compared with the ontology-based inference methods described in this paper. We present an architecture that incorporates semantic inference into a publish/subscribe messaging middleware, allowing data quality inference to occur on real-time data streams. Our preliminary benchmark results indicate delays of 100ms for basic data quality checks based on an existing semantic web software framework. We demonstrate how these results can be maintained under increasing sensor data traffic rates by allowing inference software agents to work in parallel. These results indicate that data quality inference using the semantic sensor network paradigm is viable solution for data intensive, large-scale sensor networks.

IThe LoCo score was calculated using turbidity data from second-order streams located in Dunn Hollow and Hembree Hollow in Eastern Tennessee from July 6, 2010 and July 13, 2010. These locations are ideal because of their physical proximity, but have differing levels of anthropogenic activity near each site. IObservations within the two data sets are typically similar, with occasional anomalies in correlation due to extraneous factors like human interference and environmental conditions.

Potential impacts from changing coastal landscapes, specifically the conversion of forested and agricultural lands to residential and commercial development, can be reduced by more informed decisionmaking related to green infrastructure if the appropriate tools are available. An assessment of existing natural resources and their benefits in terms of ecosystem services can allow for better guidance for their protection and preservation. In contrast, some highly impervious urban landscapes could benefit from restoration strategies based on green infrastructure principles as sustainable solutions that mimic natural hydrology and ecology. The effectiveness of sustainable land use strategies, whether in developed or developing areas, becomes an exercise in optimization at varying spatial and temporal scales: whether at the watershed level; within geopolitical boundaries; in developed neighborhoods, rural communities or preserved tracts of land, or within an individual practice or series of practices (i.e. treatment train). This work introduces tools for the assessment and feasibility of green infrastructure strategies between different scales as related to sustainable land use decisionmaking in coastal South Carolina from individual best management practices (BMPs) to the whole watershed. Specific hydrological and ecological parameters can be associated with each spatial and temporal scale. The question is: can these parameters be summed, compounded, and/or prioritized, and if so, what are the implications, if any, to coastal land use decision-making based on green infrastructure principles? INTRODUCTION Green infrastructure has been defined as “an interconnected network of natural areas and other open spaces that conserves natural ecosystem values and functions, sustains clean air and water, and provides a wide array of benefits to people and wildlife”. (Benedict and McMahon, 2006). Recent focus on green infrastructure by the U.S. EPA as a measure of “managing wet weather” includes a subset of technologies known as Low Impact Development (LID). EPA-recommended site-scale practices include rainwater harvesting, downspout disconnection, rain gardens, permeable pavements, vegetated swales, green roofs, and brownfield and infill redevelopment. Neighborhoodscale approaches include “green” parking, streets, and highways; pocket wetlands, and urban forestry strategies. Watershed scale strategies include riparian buffers (U.S. EPA, 2010a). Many of these strategies are further explored in a sustainable design and green building toolkit for local governments (U.S. EPA, 2010b). From a stormwater regulatory standpoint, anticipated changes to the NPDES permit requirements both nationwide and within South Carolina are moving toward volumeand infiltration-based strategies in contrast to the current requirements where post-development peak flows must at least equal those of pre-development. As these mandates move forward, local and regional decision-makers and land use practitioners need science-based tools to inform the design process. From a larger conceptual view of green infrastructure, we can summarize landscape design goals as follows:  Retain the natural landscape and hydrology  Promote open space, corridor, and habitat preservation  Encourage riparian and floodplain protection  Reduce and disconnect impervious surfaces  Provide on-site stormwater management and water re-use Potential shortand long-term impacts from coastal land use change can be reduced by informed decision-making at various scales, especially if targets for sustainable solutions are well-defined. Whether the effort is one of preservation or of restoration (or both within a given land area), the system components of hydrology, soils, and Figure 1. A conceptual model for a multi-scale system of landscape parameters, their interactive complex processes, and related ecosystem services. (Modified from Ge Sun, Southern Global Climate Program, USDA Forest Service) vegetation and their various elements must be incorporated into the strategy. A conceptual model of processes and their relationships within the coastal landscape fabric in terms of the system components and elements is given in Figure 1. Goals for sustainability, along with associated relevant criteria and metrics for achieving an optimal set of land use decisions, must be clearly defined at any scale. Ecosystem services defined in the figure may serve as goals for optimizing sustainable land use strategies. The conceptual model can be applied at various spatial and temporal scales, while some elements and processes may take priority depending on the given scale within which decisions are to be made, along with any initial and/or critical conditions, allowing for hierarchy and subsequent goal definition at that scale. Can what we learn from the local level be applied to the watershed scale, and vice versa? And if so, can we identify sustainable land use practices and natural resource preservation strategies given available landscape information? Further, can we develop science-based tools to inform the decisionmaking process related to green infrastructure? Toward this aim, we will consider both the landscape design goals listed above and the conceptual model for landscape parameters in our assessment tool development. METHODS Integrated research and extension programs designed to provide science-based information related to South Carolina’s natural resources, while representing various spatial scales, are being conducted and delivered, including: (a) evaluating individual LID practices for water budgets and pollutant removal; (b) monitoring hydrological and ecological parameters in forested watersheds prior to residential and commercial development; (c) evaluating green infrastructure design and practices in urbanizing and urbanized watersheds; (d) refining remote data acquisition tools in association with Clemson’s Intelligent River© project, and (e) developing web-based mapping tools for natural resource-based land use decision-making. As an example, we focus on the Waccamaw Neck in eastern Georgetown County, SC, where integrated programs include the online Community Resource Inventory (CRI), the Bannockburn Plantation site (originally part of the Figure 2. Map outputs from the Online Community Resource Inventory (CRI) for Georgetown County, SC, focusing on the Waccamaw Neck. Property ownership (parcels and protected lands) overlays a street map for natural resource planning and zoning (left) and soil drainage classes overlays a USGS topo map for stormwater management plan reviews and decision-making (right). Intelligent River© monitoring project), and a rain garden monitoring and demonstration project. Online Community Resource Inventory (CRI). An interactive web-based mapping tool has been developed for Georgetown County, SC. Available geographic data include parcels, protected lands, roads, soils, land use/land cover, habitat, flood zones, and water resources, and these can be displayed over topographic maps, satellite imagery, or a street map. Selected data overlays can depict specific resources relevant for a land use decision, such as those related to property ownership and the connection of open or green spaces, or to the recommendation and prioritization of stormwater management strategies based on soils and topography (Figure 2), among other information. A user can configure the map for specific views, while preconfigured maps are being developed to assist new users. Near real-time data as RSS feeds, including stream gage data from USGS, have been incorporated into the tool. This information can be incorporated in the conceptual model (Fig. 1) for hydrology (e.g. streamflow, flood zones), soils (e.g. drainage class), and vegetation (e.g. land cover, habitat type) with a goal of quantifying these relationships and linking them to specific ecosystem services (e.g. storm protection, habitat/corridors). Visit www.cri-sc.org for more information. Bannockburn Plantation. Headwater streams in undeveloped coastal forests with shallow water tables function as natural storage and conveyance mechanisms for surface flows and groundwater discharge. Groundwater position often controls stream flow and evapotranspiration plays the most significant role in surface and subsurface flows seasonally. Toward the determination of baseline ecohydrologic parameters for an undeveloped coastal tract of land, a monitoring project has been conducted at Bannockburn Plantation, where Figure 3. Monitoring stations for Upper Debidue Creek on the Bannockburn Plantation property and in DeBordieu Colony located upstream from North Inlet. The area in typified by low gradient topography and a shallow water table. Runoff: rainfall ratios and factors related to stream flow generation (rainfall, evapotranspiration, and water table position) are being investigated on Bannockburn Plantation as a benchmark for pre-development hydrology for coastal forested headwater streams. future development has been proposed (Hitchcock et al., 2008). One of the original sites for the larger statewide Intelligent River© project, the primary monitoring strategy for the land tract has included parameters for: (1) meteorological data; (2) surface hydrology and water quality; (3) groundwater hydrology; and (4) vegetative ecology. Two years of monitoring data from the Upper Debidue Creek watershed (approx. 400 acres) have been collected. This information can be incorporated in the conceptual model (Fig. 1) for hydrology (e.g. streamflow and water quality), soils (e.g. water table position), and vegetation (e.g. water/nutrient uptake, organic contribution) with a goal of quantifying these relationships and linking them to specific ecosystem services (e.g. flood control, water quality, habitat, nutrient cycling, carbon storage). Visit www.intelligentriver.org for more information. Rain Garden Monitoring. At the site design scale, bioretention (rai

In an effort to collect information on public perception, knowledge, behaviors and willingness to get involved in improved stormwater management, a telephone survey of South Carolina residents in targeted education areas was implemented in 2009. Results of the survey have identified target behaviors and awareness, adding focus to ongoing stormwater education efforts and establishing a baseline for measuring successes that may be attributed to these current and future efforts. This manuscript presents the results of this survey and offers some insight on stakeholders’ attitudes, knowledge and behaviors related to watershed and stormwater, critical factors in the initial development of effective stormwater education and public involvement programs. INTRODUCTION As stated by Costanzo et al. (1986), “behavior change is the only goal of consequence.” This is as true for watershed education as it is for other sustainability outreach efforts. Clemson University’s Carolina Clear program is implementing regional stormwater education and involvement programs in more than three dozen communities across South Carolina. These municipal/county and university partnerships have been spurred by the National Pollutant Discharge Elimination System (NPDES) Small Municipal Separate Storm Sewer Systems (MS4) General Permit, effective in South Carolina in March 2006. The US Environmental Protection Agency (US EPA) recommends language for permit writers of the next phase of the NPDES MS4 permit in the 2010 publication entitled, MS4 Permit Improvement Guide. Permit language recommended by the EPA asks the permittee to assess changes in public awareness and behavior resulting from the implementation of public education and involvement measures. A voluminous body of research has investigated relationships between environmental attitudes and behaviors, with researchers agreeing that knowledge can influence environmental concern (Kaltenborn, 1998; Thompson, 2004), and that both knowledge and concern are important antecedents for engaging in environmentally-friendly behaviors (Tarrant et al., 1997; Hines et al. 1986/1987; Bamberg and Moser, 2007). In the context of stormwater education, there is a need to improve understanding of how residents’ attitudes shape their behaviors, especially as a number of these behaviors can contribute to nonpoint source pollution. Nonpoint source pollution has been identified as one of the most significant threats to water quality (Sleavin and Civco, 2000). It is the hope of the authors that this manuscript presents data helpful in understanding society’s attitudes, knowledge and behaviors related to watersheds and stormwater, critical factors in the development and implementation of effective stormwater education and public involvement programs. PURPOSE In the summer and fall of 2009, a telephone survey of residents (n=1,599) from four regions of South Carolina was conducted through the Department of Sociology at Clemson University. The four regions include two coastal (urban areas surrounding Myrtle Beach and Charleston) and two inland (urban areas surrounding Columbia and Sumter and, separately, Florence). Responses from Columbia and Sumter were combined in this survey effort so that results could be summarized as representing the “Midlands” of South Carolina, a common reference to the geographic center of the state. The primary purpose of the survey was to obtain information about residents’ attitudes, knowledge, behaviors and intentions as they relate to watershed issues. Through multiple partner efforts, these four regions have been exposed to one to four years of targeted watershed and stormwater education including presence at community festivals, classroom education, rain garden installations at schools, rain barrel workshops, technical training including sediment erosion control, mass media (billboards, radio and television commercials), coordinated web pages and streamside clean-ups. In this paper, we report on findings that have particular relevance for refining these educational efforts in the coming years and the educational efforts of agencies and communities working with residents of South Carolina. METHODS The survey was conducted using Computer Assisted Telephone Interviewing (CATI) software. Random lists of phone numbers based on target zip codes were purchased from a reputable national vendor of telephone samples. The majority of calls were made during evening hours, weekdays between 5:00pm and 9:00pm. Limited daytime and weekend calling was also conducted in order to include other potential respondents. The respondent needed to be a resident of one of the 23 targeted zip codes to participate in the survey. The full survey and results are available online at www.clemson.edu/carolinaclear and upon request. Survey questions were organized into the following categories: 1) environmental concern; 2) environmental knowledge about concepts and practices and the causes of pollution; 3) participation in recreational activities; 4) participation in environmentally positive and negative behaviors; 5) willingness to get involved in efforts to improve water quality; and 6) familiarity with ongoing targeted stormwater and watershed education efforts. To better reflect the demographic characteristics of residents in the surveyed areas, the data for each region were adjusted for demographic differences per individual region between telephone sample and 2000 US Census data by using standard statistical weighting procedures; only weighted data is presented herein. DISCUSSION In this paper, we report on two main findings that are particularly relevant to stormwater education: environmental knowledge and engagement in potentially negative environmental behaviors. Stormwater Knowledge To gauge knowledge about stormwater, respondents were provided with a basic definition of stormwater as “runoff from yards and roads during storm events or from irrigation; it drains to ditches and storm sewers along roadways.” Following this, respondents were then asked to indicate “yes” or “no” in response to the question, “Do you believe that this stormwater is treated before reaching our lakes, streams and beaches?” Table 1 displays the responses. Of particular interest in the context of stormwater management, a significantly higher proportion of residents from the coastal counties near Myrtle Beach selected the correct response, as compared to the inland urbanized area of Florence. Residents of Florence were also more likely to indicate “do not know” for this particular survey item. The Myrtle Beach region is the area that has had the most exposure to regional stormwater education efforts in which Carolina Clear is a participant (greater than four years); whereas, Florence is the area that has most recently been targeted for Carolina Clear’s outreach efforts (greater than one year). Without baseline data, it is difficult to assess whether this difference between the two regions is due to programmatic stormwater-related efforts. However, these results do provide a good foundation for assessing future education impacts and comparing future survey results across regions. Watershed Knowledge To ascertain respondents’ familiarity with basic environmental concepts, respondents were asked to select the correct definition of a watershed, “all of the land area Table 1: Stormwater treated or untreated before discharge to waterways. Survey Region % Yes (Incorrect Response) % No (Correct Response) Do not know

Southeastern Natural Sciences Academy conducted a two-year intensive water quality study within the middle and lower Savannah River Basin between 2006 and 2008. We monitored nine mainstem river stations and three major tributaries to determine effects of the Central Savannah River Area (CSRA) on water quality. Multiparameter sondes were used to collect continuous temperature, dissolved oxygen, conductivity, pH, and turbidity data at 15-minute intervals. Monthly discrete aqueous chemistry samples and several storm/stochastic event samples were collected and analyzed for major inorganic and organic constituents. Several sediment samples were also collected and analyzed for metals, mercury, pesticides, herbicides, and polychlorinated biphenyls (PCBs). We also monitored aquatic macroinvertebrate populations bimonthly. Continuous monitoring indicated that river water quality was well above state standards for dissolved oxygen, with exceptions at stations downstream of J. Strom Thurmond Dam, Stevens Creek (SC), and Butler Creek (GA). Especially notable was supersaturated dissolved oxygen levels immediately downstream of the shoals reach of the river. Discrete aqueous chemistry sample results fell within expected ranges. Some samples did exceed chronic and/or acute toxicity limits for copper, cadmium, lead, and zinc. One or more samples from seven mainstem river stations exceeded chronic toxicity limits for mercury. However, mercury was detected in only a single sediment sample. Additionally, several herbicides, DDT, and a PCB were detected in some sediment samples. Macroinvertebrate data indicated EPT taxa increased with distance downstream of J. Strom Thurmond Dam.

Population growth, energy demand, and climate change are placing an unprecedented strain on water resources, requiring a fundamental shift in how these resources are managed. More precisely, resource management programs must embrace a new paradigm, one with realtime environmental monitoring at its core. The Intelligent River© is an environmental and hydrological observation system engineered to support research and management of water resources at watershed scales. The system architecture is comprised of three primary tiers: (i) a field-deployed sensor fabric and uplink infrastructure, (ii) real-time data streaming middleware, and (iii) repository, presentation, and web services. Sensor Web Enablement (SWE) adoption decisions revolve around balancing efficiency concerns and implementation time with capability and standards compliance. In this context, our team has examined, applied, and evaluated SWE technologies to enable data archival, access, and discovery. We have found varying levels of success with SWE adoption across the three tiers. At the fabric layer, platform configurability and ease-of-integration have been important engineering drivers. SensorML arose as a natural candidate solution; however, its resource requirements are largely incompatible with our target hardware platforms. At the middleware layer, recent efforts have focused on the use of SensorML and a metadata catalog to perform metadata annotation. This solution appends SensorML elements onto incoming observations, supporting data processing and semantic resolution. During early development of middleware technologies, we linked sensor platforms with web services using the transactional profile of the Sensor Observation Service (SOS) to perform data insertion and retrieval queries. At the application level, SOS is used to support data discovery and access, and Sensor Alert Service (SAS) is used to provide near-real time notifications of sensor status and QA/QC failures. In this paper, we report on our experiences, both positive and negative, and outline potential solutions to some of the most important obstacles we have encountered.

Access to timely and accurate hydrological and environmental observation data is a crucial aspect of an integrated approach to water resources management. This presentation describes an end-to-end system designed to support realtime monitoring and management of water resources. The main components of the hardware/software infrastructure of this system are broken into four categories and briefly described. This organization provides the basis for a synthesis of several prominent standards and software solutions relevant to the hydrologic and environmental observing communities. These standards are described in the context of their role in our end-to-end system. The presentation concludes with a case study describing a green infrastructure monitoring effort located in the City of Aiken, South Carolina.

ð ABSTRACT. The concepts of green infrastructure and low impact development provide a series of procedures and practices to modify the magnitude, frequency, and duration of stormwater runoff. Projects utilizing low-impact development design attempt to address the hydrologic and hydraulic challenges associated with urban stormwater by mimicing pre- development hydrology to enhance infiltration and treatment functions on site. The City of Aiken's Sand River Headwaters Green Infrastructure Project incorporates sustainable development practices in downtown watersheds with the goal of reducing ongoing impacts to the principal green infrastructure component of the city - Hitchcock Woods. Rain gardens, bioswales, underground cisterns, and pervious pavement provide smart green solutions. These Best Management Practices (BMPs) enhance nature's capacity to absorb stormwater, and provide both economic and environmentally sound approaches to reducing stormwater flows negatively impacting Sand River, Hitchcock Woods, and other downstream impaired waters. This project also enhances the city's environmental health while demonstrating community-based leadership towards sustainability.

Effective watershed and stormwater education and public involvement programs strive to increase awareness of watersheds and landscape connectivity and also encourage behavior changes that may be contributing to water quality and quantity problems within a targeted basin. According to new guidance from the US Environmental Protection Agency on stormwater permit improvement, regulators are looking for programs to utilize targeted issues relevant to a community to guide the development of a comprehensive outreach program. In an effort to collect information on public perception, knowledge, behaviors and willingness to get involved in improved stormwater management, a telephone survey was implemented. This manuscript presents the results of this survey and offers insight on stakeholders’ attitudes, knowledge, and behaviors related to watershed and stormwater, critical factors in the initial development of effective stormwater education and public involvement programs.