Optimal Selection of Priority Development Areas Considering Tradeoffs Between Hydrology and Development Configuration

Mixed-integer linear programs are proposed for siting development and conservation areas in watersheds, addressing economic objectives (development perimeter and proximity) and ecological objectives. Links between watershed hydrology and ecology need not be well defined. Parameters for the linear programs are obtained from linearization of the SWAT hydrologic model.     

DPX快速萃取程序升温大体积进样GC/MS法测定水中19种多溴联苯化合物

建立DPX快速吸附萃取、程序升温(PTV)大体积进样与气相色谱/质谱(GC/MS)联用,SIM模式同时测定水中19种多溴联苯(PBBs)单体的方法。该方法在PBBs质量浓度1~50μg/L范围内线性良好,19种PBBs单体检出限为0.147~0.230μg/L,相对标准偏差为6.61%~10.5%,加标回收率为61.5%~82.6%。     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

Multi-stand Forest Management under a Climatic Risk: Do Time and Risk Preferences Matter?

We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial private forest-owner located in North-East of France. We show that the optimal decisions both depend upon risk and time preferences. The authors would like to thank participants at the international conference on Economics of Sustainable Forest Management in Toronto, at the PARIS 1 seminar on Environmental and Natural Resource Economics, at the 2004 Applied Microeconomics Conference in Lille and at the 13th annual conference of the European Association of Environmental and Resource Economists at Budapest.     

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.     

COMPARISON OF RESERVOIR LINEAR OPERATION RULES USING LINEAR AND DYNAMIC PROGRAMMING1

ABSTRACT: Mathematical optimization techniques are used to study the operation and design of a single, multi-purpose reservoir system. Optimal monthly release policies are derived for Hoover Reservoir, located in Central Ohio, using chance-constrained linear programming and dynamic programming-regression methodologies. Important characteristics of the former approach are derived, discussed, and graphically illustrated using Hoover Reservoir as a case example. Simulation procedures are used to examine and compare the overall performance of the optimal monthly reservoir release policies derived under the two approaches. Results indicate that, for the mean detention time and the corresponding safe yield target water supply release under existing design of Hoover Reservoir, the dynamic programming policies produce lower average annual losses (as defined by a two-sided quadratic loss function) while achieving at least as high reliability levels when compared to policies derived under the chance-constrained linear programming method. In making this comparison, the reservoir release policies, although not identical, are assumed to be linear. This restricted form of the release policy is necessary to make the chance-constrained programming method mathematically tractable.     

MULTICRITERION ANALYSIS OF FOREST WATERSHED MANAGEMENT ALTERNATIVES1

ABSTRACT: The impacts of alternative forest watershed management practices are examined from a multicriterion viewpoint in order to select the most satisfactory management scheme. The selection process is carried out using two types of multicriterion decision making techniques: the outranking types of ELECTRE I and II, and the distance-based type of compromise programming (CP). The process is illustrated using the U.S. Forest Service Beaver Creek Experimental Watershed in the Salt-Verde River Basin of Arizona as an example. The desired objectives of the experimental study and the alternative forest watershed resources management schemes are transformed into an evaluation matrix of alternatives versus criteria array. Analyses of the matrix using the aforementioned techniques result in a complete preference ordering of the feasible alternatives in the cases of ELECTRE LI and CP and a partial ordering when ELECTRE I is used. In addition, some sensitivity analyses have been performed and showed ELECTRE II and CP to be fairly robust with respect to parameter changes, while ELECTRE I being highly sensitive to changes in threshold levels. Overall the three techniques pointed out that 65 percent vegetation cut is the best management scheme, while the next best is shown to be 50 percent vegetation cut.     

WATER POLICIES FOR ENERGY DEVELOPMENT1

ABSTRACF: Examination of a series of studies of the economically efficient water allocations in the Upper Colorado River, Yellowstone River, and Great Basins indicate that water is not a serious general physical constraint on the development of energy resources, so long as public institutions do not hinder the exchange of water rights in markets. Energy development will cause limited impacts on other water-using sectors, principally agriculture. There appears to be little reason to develop large-scale water storage facilities, even during periods of reduced water production. Water storage developments appear to be necessary only when institutional constraints severely restrict water rights markets and transfers.     

DERIVING THE NONLINEAR RISK-BENEFIT ALGORITHM FOR RESERVOIRS1

ABSTRACT: The Nonlinear Risk-Benefit (NRB) Algorithm includes risk as one of the objectives in a multiple-objective optimization problem. The NRB Algorithm is derived by extending the Surrogate Worth Trade-Off method to quadratic programming. This category of problem is common in water resources planning and design, especially multipurpose reservoir systems. Consequently, an example is given using the algorithm for optimally operating a multipurpose reservoir.     

A dynamic model for intertemporal allocation of old-growth forests in the Pacific Northwest

Across the globe, continued policy debates regarding the management of old-growth forests center around the difficult task of balancing economic and ecological considerations. Though the forests of the Pacific Northwest United States are among the most studied old-growth ecosystems, ecological and economic analyses have yielded public land management directives that remain controversial. Specifically, the recently adopted Northwest Forest Plan lacks explicit goals for maintaining intergenerational equity for the use of forest resources and the diversity of old-growth ecosystems. Unlike previous studies which rely on monetary quantification of costs and benefits, this study develops and applies a conceptual framework for evaluating socially optimal Pacific Northwest old-growth forest utilization strategies. Conditions for the optimal management of old-growth forests are derived using dynamic programming. The objective function synthesizes relevant biological and economic attributes of the old-growth allocation problem. Results in the form of extraction paths are compared given social pressure for consumptive and non-consumptive benefits, as well as different planning horizons, rates of social time preference, and environmental variance. Lengthening the planning horizon results in a vast divergence of optimal policies in the absence of discounting. Extraction rates appear to approach zero as the planning horizon approaches infinity. While higher rates of social time preference increase the rate of extraction, forest stocks remaining at the terminal time period equal levels remaining with a lower discount rate. Increasing environmental variance results in a higher level of stock remaining at the terminal time period. This analysis, while specific to the old-growth controversy of the Pacific Northwest, does provide general guidelines for addressing similar problems of multiple uses of natural areas, particularly where such uses are mutually incompatible, or where one use may be irreversibly destructive to another.