Evolutionary algorithms for multiobjective evaluation of watershed management decisions

نویسندگان

  • Misgana K. Muleta
  • John W. Nicklow
چکیده

The comprehensive and systematic management of watersheds is essential for reducing the adverse environmental impacts arising from anthropogenically caused erosion and subsequent sedimentation. This paper describes a computational methodology that is designed to serve as a watershed decision support system and is capable of controlling environmental impacts of non-point source pollution resulting from erosion. In the decision process, the methodology also accounts for other inseparable objectives such as economics and social dynamics of the watershed. This decision support tool was developed by integrating a comprehensive hydrologic model known as SWAT and state-of-the-art multiobjective optimization technique within the framework of a discrete-time optimal-control model. Strength Pareto Evolutionary Algorithm (SPEA), a multiobjective optimizer based on evolutionary algorithms, has been used to generate Pareto optimal sets. For demonstration purposes, the tool was applied to the Big Creek watershed located in Southern Illinois. Results indicate that the methodology is highly effective and has the potential to improve comprehensive watershed management.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimization of sediment rating curve coefficients using evolutionary algorithms and unsupervised artificial neural network

Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...

متن کامل

Multiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems

Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...

متن کامل

Decision Support for Watershed Management Using Evolutionary Algorithms

An integrative computational methodology is developed for the management of nonpoint source pollution from watersheds. The associated decision support system is based on an interface between evolutionary algorithms (EAs) and a comprehensive watershed simulation model, and is capable of identifying optimal or near-optimal land use patterns to satisfy objectives. Specifically, a genetic algorithm...

متن کامل

VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh)

One of the most important processes of erosion and sediment transport in streams is the river most complex engineering  issues.this process special effects on water quality indices, action suburbs floor and destroyed much damage to the river and also into the development plans  Lack of continuity sediment sampling and measurement of many existing stations. due to the low number of hydrometric s...

متن کامل

Joint Application of Artificial Neural Networks and Evolutionary Algorithms to Watershed Management

Artificial neural networks (ANNs) have become common data driven tools for modeling complex, nonlinear problems in science and engineering. Many previous applications have relied on gradient-based search techniques, such as the back propagation (BP) algorithm, for ANN training. Such techniques, however, are highly susceptible to premature convergence to local optima and require a trial-and-erro...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011