Aggregating high-priority landscape areas to the parcel level: an easement implementation tool

Landscape characteristics and parcel ownership information are often collected on different spatial scales leading to difficulties in implementing land use plans at the parcel level. This study provides a method for aggregating highly resolute landscape planning information to the parcel level. Our parcel prioritization model directly incorporates a Land Trust's conservation goals in the form of a compromise programming model. We then demonstrate the use of our approach for implementation decisions, including parcel selection under a budget constraint and the estimation of a total conservation budget necessary to meet specific conservation goals. We found that these cost constraints significantly alter the composition of the 'best' parcels for conservation and can also provide guidance for implementation. The model's results were integral to a local Land Trust's ability to further define and achieve their goals.     

基于水质模拟的不确定条件下两阶段随机水资源规划模型

针对流域内不同企业的水资源分配及企业生产污染排放导致的水环境问题,运用区间两阶段随机规划的方法,耦合区间两阶段模型（ITSP）和区间水质模型（IS-P）,建立不确定两阶段随机水质-水量耦合规划模型（ITSP-SP）.该模型以流域内系统利益最大为目标函数,模拟了流域内各个企业的水量分配及排污过程中河道水质变化,并在保证河流水质达标前提下优化预计分配水量,调整企业生产规模.通过模型运算得到区间解,为管理者提供了多样的决策方案.并且,该模型充分考虑不确定因素对系统利益的影响,能够有效的规避系统决策失误及方案缺失现象.     

基于不同电力需求的中国减污降碳协同增效路径

当前我国同时面临改善生态环境质量和实现碳达峰碳中和两大战略任务,协同推进减污降碳已成为我国经济社会发展全面绿色转型的必然选择,电力部门在转型过程中将发挥重要作用.面向不同的电力需求情景,构建低成本实现碳达峰、碳中和的多目标模型,求解得出减污降碳协同增效最优路径方案.结果表明,在如期实现碳达峰、碳中和目标的前提下,减污和降碳协同性较好,两者协同控制可高效助力低碳转型的实现;优化电力部门发电结构是实现减污降碳协同增效的关键措施,研究期火电占比不断下降,清洁电力占比超过92.5%;不同电力需求下二氧化碳和主要大气污染物排放量有明显差异,其中二氧化碳排放量受电力需求影响最大,低电力需求、中等电力需求和高电力需求情景下峰值二氧化碳排放量分别为94.16亿、 104.09亿和107.46亿t,主要污染物二氧化硫、氮氧化物和颗粒物的排放同样表现出在低电力需求、中等电力需求和高电力需求情景下依次递增的趋势.电力需求的提高仅增加了电力部门内部发电结构调整的压力,未影响到其他部门的产量和活动水平,即电力需求导致的电力部门减排压力未表现出部门间传递的趋势.     

ECONOMIC ANALYSIS OF IRRIGATION PRODUCTION FUNCTIONS: AN APPLICATION OF LINEAR PROGRAMMING1

ABSTRACT: Economic analysis of irrigation production functions is discussed using linear programming. The method provides advantages over the partial one-crop type of analyses because it captures intercrop tradeoffs in water and land use in response to economic policies or changes in water supply. A numerical example is used.     

MULTIPLE CRITERIA ANALYSIS FOR WATER QUALITY MANAGEMENT IN THE NITRA BASIN1

ABSTRACT: This paper presents the implementation of one element of a decision support system (DSS) for regional water quality management, applied to the Nitra River Basin in Slovakia. A model-based, aspiration-led methodology for multicriteria decision support has been used for the study. Several reusable, modular software tools have been developed and implemented: a problem-specific generator to produce the core part of the mathematical programming model, tools for the generation and interactive modification of multicriteria problems, and a solver for the resulting mixed-integer optimization problem. Provided in the paper are the following: a complete formulation of the mathematical model (including the imbedded water quality model), a summary of the aspiration-reservation-led multiple criteria optimization approach applied to decision support, and an overview of results that illustrate the applied approach and provide some interesting insights to the case study.     

PROJECTED EFFECTS OF ENERGY POLICIES ON AGRICULTURAL WATER USE AND IRRIGATION1

ABSTRACT: A national and interregional programming model was used in projecting the impacts of alternative energy policies and prices on agricultural production, land use, and irrigation. The alternatives analyzed include (a) natural gas deregulation, (b) natural gas curtailment, (c) doubled energy prices, and (d) tripled energy prices. These alternatives are compared with a base alternative where prices and conditions are at normal levels. Restraints in the model control availability of water, land, nitrogen fertilizers, and energy. Water production functions were used to adjust water use to conform with projected energy prices and policies. Natural gas curtailment would have the largest effect on nitrogen use on irrigated land. Values or shadow prices for lands that remains in irrigation would increase under all of the alternatives because of reduced supply. Increased energy prices generally would increase use of surface water for irrigation and reduce use of ground water due to higher pumping costs. Reductions of 50 percent or more in ground water use would occur in the South Central and Western regions of the United States. Water supply prices increase under all of the alternatives; with the amount varying by regions and the policy or price situation.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Stochastic bycatch, informational asymmetry, and discarding

The existing literature (i) examines bycatch and discard behavior in a static framework and (ii) treats bycatch as a deterministic process uniform across vessels. Using a dynamic representative agent model in a two-stock resource, this paper explores strategic interactions between a social planner and two groups of harvesters, one of which imposes a stochastic “technological externality” (bycatch) on the other. In addition to limitations on entry and the number of trips taken in each industry, three bycatch control instruments are compared to the unconstrained case: taxes, trip limits, and value-based quotas. Implementation and enforcement costs aside, taxes dominate both types of quota, and value limits outperform trip limits by eliminating one type of discarding. In simulations, relative performance depends upon variance in the bycatch process, differences in the ex vessel prices of stocks, relative efficiency of the harvester types, and fixed costs on the trip and industry margins.