eprintid: 4206 rev_number: 24 eprint_status: archive userid: 351 dir: disk0/00/00/42/06 datestamp: 2016-01-15 02:04:50 lastmod: 2021-08-27 17:14:58 status_changed: 2016-01-15 02:04:50 type: monograph metadata_visibility: show item_issues_count: 2 creators_name: Kularathna, M. creators_name: Somlyody, L. creators_id: AL1690 creators_id: 1437 title: River Basin Water Quality Management Models: A State-of-the-Art Review ispublished: pub internal_subjects: iis_wat internal_subjects: iis_mod abstract: With the increasing human activities within river basins, the problem of water quality management is becoming increasingly important. Quality management can be achieved through control/prevention measures that have various economic and water quality implications. To facilitate the analysis of available management options, decision models are needed which represent the many facets of the problem. Such models must be capable of adequately depicting the hydrological, chemical and biological processes occurring in the river; while incorporating social, economic and political considerations within the decision framework. Management analyses can be performed using simulation, optimization, or both, depending on the management goal and the size and type of the problem. The critical issues in a management model are the nonlinearities, uncertainties, multiple pollutant nature of waste discharges, multiple objectives, and the spatial and temporal distribution of management actions. Literature on various management models were reviewed under the headings of linear, nonlinear and dynamic programming approaches; their stochastic counterparts, and combined or miscellaneous approaches. Dynamic programming was found to be an attractive methodology which can exploit the sequential decision problem pertaining to river basin water quality problems (downstream control actions do not influence water quality upstream). DP handles discrete decision variables which represent discrete management alternatives, and it is generic in the sense that both linear and non-linear water quality models expressing the relation between emissions and ambient quality levels can be incorporated. An example problem is presented which demonstrates the application of a DP-based management model to formulate least-cost strategies for the Nitra River basin in Slovakia. However, it is hardly possible for a single model to represent all the aspects of a complex decision problem. Different types of management models (e.g. deterministic vs stochastic models) have different capabilities and limitations. The only way to compensate for the deficiencies is to perform the analysis in a sensitivity style. The necessity for sensitivity analyses is further implied due to the fact that water quality problems are rather loosely formulated with respect to the quality and economic goals. date: 1994-01 date_type: published publisher: WP-94-003 iiasapubid: WP-94-003 price: 10 creators_browse_id: 2730 creators_browse_id: 1584 full_text_status: public monograph_type: working_paper place_of_pub: IIASA, Laxenburg, Austria pages: 45 coversheets_dirty: FALSE fp7_type: info:eu-repo/semantics/book citation: Kularathna, M. & Somlyody, L. (1994). River Basin Water Quality Management Models: A State-of-the-Art Review. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-94-003 document_url: https://pure.iiasa.ac.at/id/eprint/4206/1/WP-94-003.pdf