Integrating local and scientific knowledge for environmental management

This paper evaluates the processes and mechanisms available for integrating different types of knowledge for environmental management. Following a review of the challenges associated with knowledge integration, we present a series of questions for identifying, engaging, evaluating and applying different knowledges during project design and delivery. These questions are used as a basis to compare three environmental management projects that aimed to integrate knowledge from different sources in the United Kingdom, Solomon Islands and Australia. Comparative results indicate that integrating different types of knowledge is inherently complex – classification of knowledge is arbitrary and knowledge integration perspectives are qualitatively very different. We argue that there is no single optimum approach for integrating local and scientific knowledge and encourage a shift in science from the development of knowledge integration products to the development of problem-focussed, knowledge integration processes. These processes need to be systematic, reflexive and cyclic so that multiple views and multiple methods are considered in relation to an environmental management problem. The results have implications for the way in which researchers and environmental managers undertake and evaluate knowledge integration projects.     

Big society,little justice? Community renewable energy and the politics of localism

This paper challenges “Big Society (BS) Localism”, seeing it as an example of impoverished localist thinking which neglects social justice considerations. We do this through a critical examination of recent turns in the localist discourse in the UK which emphasise self-reliant communities and envisage a diminished role for the state. We establish a heuristic distinction between positive and negative approaches to localism. We argue that the Coalition Government's BS programme fits with a negative localist frame as it starts from an ideological assumption that the state acts as a barrier to community-level associational activity and that it should play a minimal role. “BS localism” (as we call it) has been influential over the making of social policy, but it also has implications for the achievement of environmental goals. We argue that this latest incarnation of localism is largely ineffective in solving problems requiring collective action because it neglects the important role that inequalities play in inhibiting the development of associational society. Drawing upon preliminary research being undertaken at the community scale, we argue that staking environmental policy success on the ability of local civil society to fill the gap left after state retrenchment runs the risk of no activity at all.     

Applied tracer tests in fractured rock: Can we predict natural gradient solute transport more accurately than fracture and matrix parameters?

Applied tracer tests provide a means to estimate aquifer parameters in fractured rock. The traditional approach to analysing these tests has been using a single fracture model to find the parameter values that generate the best fit to the measured breakthrough curve. In many cases, the ultimate aim is to predict solute transport under the natural gradient. Usually, no confidence limits are placed on parameter values and the impact of parameter errors on predictions of solute transport is not discussed. The assumption inherent in this approach is that the parameters determined under forced conditions will enable prediction of solute transport under the natural gradient. This paper considers the parameter and prediction uncertainty that might arise from analysis of breakthrough curves obtained from forced gradient applied tracer tests. By adding noise to an exact solution for transport in a single fracture in a porous matrix we create multiple realisations of an initial breakthrough curve. A least squares fitting routine is used to obtain a fit to each realisation, yielding a range of parameter values rather than a single set of absolute values. The suite of parameters is then used to make predictions of solute transport under lower hydraulic gradients and the uncertainty of estimated parameters and subsequent predictions of solute transport is compared. The results of this study show that predictions of breakthrough curve characteristics (first inflection point time, peak arrival time and peak concentration) for groundwater flow speeds with orders of magnitude smaller than that at which a test is conducted can sometimes be determined even more accurately than the fracture and matrix parameters.     

GEOGRAPHIC INFORMATION SYSTEM BASED NONPOINT POLLUTION MODELING1

ABSTRACT: The reauthorization of the Clean Water Act reemphasizes the need for regional scale monitoring and management of nonpoint pollution loads. The magnitude of the task will require that local governments and their consultants integrate information systems and modeling if they are to manage the massive data sets and conduct the array of simulations that will be needed to support the decision making processes. Interfacing geographic information systems (GIS) and nonpoint pollution modeling is a logical approach. The objective of the present study was to use the 37,000-acre area defined by the Kensington Quadrangle sheet in Montgomery County, Maryland, to show that GIS-supported nonpoint pollution modeling is practical and economically attractive. The purpose of the GIS is to estimate the spatial distribution of nonpoint nitrogen, phosphorous, zinc, lead, BOD, and sediment using a model developed by the Northern Virginia Planning District Commission. The system allows the user to change land uses in subareas to simulate the consequences of additional development or alternate management strategies. The tests show that in-house development of this type of special purpose GIS is a practical alternative to vendor supplied systems and that the required databases can be developed quite reasonably.     

A GIS analysis of suitability for construction aggregate recycling sites using regional transportation network and population density features

Aggregate is used in road and building construction to provide bulk, strength, support, and wear resistance. Reclaimed asphalt pavement (RAP) and reclaimed Portland cement concrete (RPCC) are abundant and available sources of recycled aggregate. In this paper, current aggregate production operations in Virginia, Maryland, and the District of Columbia are used to develop spatial association models for the recycled aggregate industry with regional transportation network and population density features.The cost of construction aggregate to the end user is strongly influenced by the cost of transporting processed aggregate from the production site to the construction site. More than 60% of operations recycling aggregate in the mid-Atlantic study area are located within 4.8 km (3 miles) of an interstate highway. Transportation corridors provide both sites of likely road construction where aggregate is used and an efficient means to move both materials and on-site processing equipment back and forth from various work sites to the recycling operations.Urban and developing areas provide a high market demand for aggregate and a ready source of construction debris that may be processed into recycled aggregate. Most aggregate recycling operators in the study area are sited in counties with population densities exceeding 77 people/km² (200 people/mile²). No aggregate recycling operations are sited in counties with less than 19 people/km² (50 people/mile²), reflecting the lack of sufficient long-term sources of construction debris to be used as an aggregate source, as well as the lack of a sufficient market demand for aggregate in most rural areas to locate a recycling operation there or justify the required investment in the equipment to process and produce recycled aggregate.Weights of evidence analyses (WofE), measuring correlation on an area-normalized basis, and weighted logistic regression (WLR), are used to model the distribution of RAP and RPCC operations relative to transportation network and population distribution data. The models can be used on a regional scale to quickly map the relative site suitability for a RAP or RPCC aggregate recycling operation in a particular area based on transportation network and population parameters. The results can be used to identify general areas to be further evaluated on a site-specific basis using more detailed marketplace information. As transportation or population features change due to planning or actual development, the models can be easily revised to reflect these changes.     

DETERMINING CRITICAL WATER QUALITY CONDITIONS FOR INORGANIC NITROGEN IN DRY,SEMI‐URBANIZED WATERSHEDS1

ABSTRACT: Traditional approaches to establishing critical water quality conditions, based on statistical analysis of low flow conditions and expressed as a recurrence interval for low flow conditions (e.g., 7Q10), may be inappropriate for drier watersheds. The use of 7Q10 as a standard design flow assumes year‐round flow, but in these watersheds, 7Q10 is zero or very small. In addition, the increasing use of multiple year dynamic water quality models at daily time steps can supercede the use of steady state approaches. Many of these watersheds are also under increasing urbanization pressure, which accentuates the flashiness of runoff and the episodic nature of critical water quality conditions. To illustrate, the conditions in the Santa Clara River, California, are considered. A statistical analysis indicates that higher inorganic nitrogen concentrations correlate strongly with low flow. However, peaks in concentrations can occur during the first storms, particularly where nonpoint source contribution is significant. Critical conditions can thus occur at different flow regimes depending on the relative magnitude of flow and pollutant contributions from various sources. The use of steady state models for these dry semi‐urbanized watersheds based on 7Q10 flows is thus unlikely to accurately simulate the potential for exceeding water quality objectives. Dynamic simulation of water quality is necessary, and as the recent intense storm event sampling data indicate, the models should be formulated to consider even smaller time steps. This places increasing demand on computational resources and datasets to accurately calibrate the models at this temporal resolution.