A seasonally occurring summer hypoxic (low oxygen) zone in the northern Gulf of Mexico is the second largest in the world. Reductions in nutrients from agricultural cropland in its watershed are needed to reduce the hypoxic zone size to the national policy goal of 5,000 km 2 (as a 5-y running average) set by the national Gulf of Mexico Task Force's Action Plan. We develop an integrated assessment model linking the water quality effects of cropland conservation investment decisions on the more than 550 agricultural subwatersheds that deliver nutrients into the Gulf with a hypoxic zone model. We use this integrated assessment model to identify the most cost-effective subwatersheds to target for cropland conservation investments. We consider targeting of the location (which subwatersheds to treat) and the extent of conservation investment to undertake (how much cropland within a subwatershed to treat). We use process models to simulate the dynamics of the effects of cropland conservation investments on nutrient delivery to the Gulf and use an evolutionary algorithm to solve the optimization problem. Model results suggest that by targeting cropland conservation investments to the most cost-effective location and extent of coverage, the Action Plan goal of 5,000 km 2 can be achieved at a cost of $2.7 billion annually. A large set of costhypoxia tradeoffs is developed, ranging from the baseline to the nontargeted adoption of the most aggressive cropland conservation investments in all subwatersheds (estimated to reduce the hypoxic zone to less than 3,000 km 2 at a cost of $5.6 billion annually).waters are proliferating worldwide, impacting more than 400 coastal marine systems (1, 2). A major cause of their formation and persistence is nutrient pollution (from agricultural, urban, and other sources) delivered from their watersheds. Excess nutrients threaten not only coastal waters (3), but also pose problems within the watersheds (4), diminishing the quantity and quality of the ecosystem services they provide (5-7). For example, 55 percent of US streams are in "poor" condition (4), drinking water supplies are compromised by high nitrate concentrations, harmful algal blooms risk human health, and commercial fisheries are threatened. The second-largest hypoxic zone in the global ocean is in the northern Gulf of Mexico and covers an area averaging more than 14,500 km 2 in the summers of 2004 through 2013 (8). The documentation of this pervasive phenomenon led to the 2008 Action Plan for Reducing, Mitigating, and Controlling Hypoxia in the northern Gulf of Mexico (9). The Action Plan, a joint federal-state effort, set the goal of reducing the size of Gulf hypoxia to less than 5,000 km 2 over a 5-y period.Current analysis of the sources of nutrient loads from the Mississippi-Atchafalaya River Basin (hereafter referred to as the Mississippi Basin) into the Gulf indicate that agricultural sources in the watershed contribute 80% of the delivered nitrogen (N) and more than 60% of the delivered phosphorus (P) (10).A number of cr...
Nonpoint-source pollution remains a troubling source of water quality problems despite decades of economics research on the matter. Among the chief difficulties for addressing the issue are the property rights assignments implicit in the current policy environment that favor agricultural nonpoint-source pollution, the unobservability of field-level emissions, and complex fate and transport relationships linking them to ambient water quality. Theoretical and practical considerations lead to the focus on observable abatement actions (conservation practices). Biophysical models are increasingly more capable of linking abatement actions to policyrelevant water quality outcomes. If costs of abatement actions are known, finding the least-cost mix of abatement actions is possible, while incorporating the nonlinearity of the pollution process. When costs are not known or information is incomplete, regulators can rely on flexible incentive-based programs, but the design of such programs is complicated by the complexities of emission aggregation. In this work, we focus on the regulator capable of focusing on nonpointsource emitters. We address the design and performance of three practice-based approaches, ranging from the command-and-control approach mandating practices, to the more flexible performance standard approach where farmers are free to select the optimal mix of on-farm conservation practices, to a fully flexible approach where credits for conservation practices are freely tradable. We do so by utilizing the representation of the nonlinear emission aggregation (fate and transport) process (the Soil and Water Assessment Tool model), and consider cases ranging from the regulator having perfect information on the costs of conservation practices to no information at all. We show how workable programs utilizing the biophysical models and simulation-optimization approaches can be designed, and assess their performance relative to the efficient case. We find that flexible programs perform well both in terms of cost and water quality goals attainment. In particular, a trading program designed around an approximation of the nonlinear pollution process performs well, relative to first-best under no information on the cost of conservation practices.
Water quality problems associated with agricultural nonpoint-source pollution remain significant in the majority of US watersheds. In this dissertation, I present a theoretical model of water quality that captures the main characteristics of agricultural pollution (the unobservability and the interactions between the field-level emissions, the imperfect knowledge of the abatement costs), propose and empirically estimate a simplified proxy model for the complex process that characterizes the fate and the transport of agricultural pollutants, and apply this model in a variety of empirical studies to evaluate alternative policy programs designed to improve water quality. Under a linear approximation of the abatement function, more flexible policies like the performance standard or trading program may outperform a command-and-control program in
We present a general, dynamic model of within-season harvesting competition in a fishery managed with individual transferable quotas. Markov-Perfect equilibrium harvesting and quota purchase strategies are derived using numerical collocation methods. We identify rent loss caused by a heterogeneous-in-value fish stock, congestion on the fishing ground, revenue competition and stock uncertainty. Our results show that biological, technological and market conditions under which rents will be dissipated in a standard individual transferable quota program are fairly special. These findings provide new insights for designing rights-based programs capable of generating resource rent in marine fisheries. KeywordsMarkov Perfect equilibrium, Markov Perfect Nash equilibrium, individual transferable quotas, production externalities, resource rent AbstractWe present a general, dynamic model of within-season harvesting competition in a fishery managed with individual transferable quotas. Markov-Perfect equilibrium harvesting and quota purchase strategies are derived using numerical collocation methods. We identify rent loss caused by a heterogeneous-in-value fish stock, congestion on the fishing ground, revenue competition and stock uncertainty. Our results show that biological, technological and market conditions under which rents will be dissipated in a standard individual transferable quota program are fairly special. These findings provide new insights for designing rights-based programs capable of generating resource rent in marine fisheries.
Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g., 5,12,20 ) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization.Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulationoptimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods 3,4,9,10,[13][14][15][17][18][19]22,23,25 . In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model 7 with a multiobjective evolutionary algorithm SPEA2 26, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and userspecified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices. Video LinkThe video component of this article can be found at
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.