{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/44021"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/44021","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Sector-Targeting for Controlling Nutrient Loadings: A Case Study of the North Fork of the Shenandoah River Watershed","abstract":"The main purpose of Total Maximum Daily Loads (TMDL) is to achieve a water quality standard. The economic costs of reducing nutrient loadings are often not taken into account during development. In this study, sector targeting is used to minimize the total cost of nutrient reduction by targeting sectors with lower costs per unit of pollution reduction. This study focuses on targeting nitrogen (N) and phosphorus (P) loading reductions from three sectors: agricultural, point source, and urban non-point source, in the North Fork watershed. Linear programming optimization models were created to determine an optimal solution that minimized total compliance cost to implement BMPs subject to targeted loading reductions in N and P in the watershed. The optimal solution for each sector using uniform allocation and sector targeting were compared for N and P loading reductions separately and N and P reductions simultaneously. The difference between sector targeting and uniform allocation showed the sector targeting was the more cost effective approach to achieve the desired nutrient reduction compared to uniform allocation. From the agricultural sector, cropland and hayland buffers provided the best options for reducing both N and P. Urban BMPs are least efficient in term of nutrient reduction and cost. Similarly, for point source upgrade, Broadway has the lowest cost of upgrade per unit of N or P reduction. This study implies that both stakeholders and policymakers can use targeting to achieve nutrient reduction goals at lower costs. The policymakers can incorporate economic considerations in the TMDL planning process which can help in developing a cost-effective tributary strategy and cost-share program.","abstract_html":"The main purpose of Total Maximum Daily Loads (TMDL) is to achieve a water quality standard. The economic costs of reducing nutrient loadings are often not taken into account during development. In this study, sector targeting is used to minimize the total cost of nutrient reduction by targeting sectors with lower costs per unit of pollution reduction. This study focuses on targeting nitrogen (N) and phosphorus (P) loading reductions from three sectors: agricultural, point source, and urban non-point source, in the North Fork watershed. Linear programming optimization models were created to determine an optimal solution that minimized total compliance cost to implement BMPs subject to targeted loading reductions in N and P in the watershed. The optimal solution for each sector using uniform allocation and sector targeting were compared for N and P loading reductions separately and N and P reductions simultaneously. The difference between sector targeting and uniform allocation showed the sector targeting was the more cost effective approach to achieve the desired nutrient reduction compared to uniform allocation. From the agricultural sector, cropland and hayland buffers provided the best options for reducing both N and P. Urban BMPs are least efficient in term of nutrient reduction and cost. Similarly, for point source upgrade, Broadway has the lowest cost of upgrade per unit of N or P reduction. This study implies that both stakeholders and policymakers can use targeting to achieve nutrient reduction goals at lower costs. The policymakers can incorporate economic considerations in the TMDL planning process which can help in developing a cost-effective tributary strategy and cost-share program.","abstract_has_math":false,"creators":["Singh, Bibek B."],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Agricultural and Applied Economics","degree_department":"Agricultural and Applied Economics","school":null,"contributors":[],"advisors":[],"committee_chairs":["Bosch, Darrell J.","Pease, James W."],"committee_members":["Stephenson, Stephen Kurt"],"year":2011,"date_issued":"2011-07-22","date_published":"2011-07-22","updated_at":"2026-07-22T22:19:18Z","subjects":["Linear Programming","Cost-Effectiveness","Uniform Allocation","Sector Targeting","North Fork","Virginia","Chesapeake Bay","BMP"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-07292011-162124"],"render_values":[{"text":"etd-07292011-162124","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/44021","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Bosch, Darrell J.","Pease, James W."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Stephenson, Stephen Kurt"]},{"key":"dc:contributor.department","label":"Department","values":["Agricultural and Applied Economics"]},{"key":"dc:creator","label":"Author","values":["Singh, Bibek B."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:41:45Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:41:45Z","2011-08-18"]},{"key":"dc:date.issued","label":"Date","values":["2011-07-22"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural and Applied Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Linear Programming","Cost-Effectiveness","Uniform Allocation","Sector Targeting","North Fork","Virginia","Chesapeake Bay","BMP"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-07292011-162124"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/44021"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The main purpose of Total Maximum Daily Loads (TMDL) is to achieve a water quality standard. The economic costs of reducing nutrient loadings are often not taken into account during development. In this study, sector targeting is used to minimize the total cost of nutrient reduction by targeting sectors with lower costs per unit of pollution reduction. This study focuses on targeting nitrogen (N) and phosphorus (P) loading reductions from three sectors: agricultural, point source, and urban non-point source, in the North Fork watershed. Linear programming optimization models were created to determine an optimal solution that minimized total compliance cost to implement BMPs subject to targeted loading reductions in N and P in the watershed. The optimal solution for each sector using uniform allocation and sector targeting were compared for N and P loading reductions separately and N and P reductions simultaneously. The difference between sector targeting and uniform allocation showed the sector targeting was the more cost effective approach to achieve the desired nutrient reduction compared to uniform allocation. From the agricultural sector, cropland and hayland buffers provided the best options for reducing both N and P. Urban BMPs are least efficient in term of nutrient reduction and cost. Similarly, for point source upgrade, Broadway has the lowest cost of upgrade per unit of N or P reduction. This study implies that both stakeholders and policymakers can use targeting to achieve nutrient reduction goals at lower costs. The policymakers can incorporate economic considerations in the TMDL planning process which can help in developing a cost-effective tributary strategy and cost-share program."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Sector-Targeting for Controlling Nutrient Loadings: A Case Study of the North Fork of the Shenandoah River Watershed"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Bosch, Darrell J.","Pease, James W."],"dc:contributor.committeemember":["Stephenson, Stephen Kurt"],"dc:contributor.department":["Agricultural and Applied Economics"],"dc:creator":["Singh, Bibek B."],"dc:date.accessioned":["2014-03-14T21:41:45Z"],"dc:date.available":["2014-03-14T21:41:45Z","2011-08-18"],"dc:date.issued":["2011-07-22"],"dc:description.abstract":["The main purpose of Total Maximum Daily Loads (TMDL) is to achieve a water quality standard. The economic costs of reducing nutrient loadings are often not taken into account during development. In this study, sector targeting is used to minimize the total cost of nutrient reduction by targeting sectors with lower costs per unit of pollution reduction. This study focuses on targeting nitrogen (N) and phosphorus (P) loading reductions from three sectors: agricultural, point source, and urban non-point source, in the North Fork watershed. Linear programming optimization models were created to determine an optimal solution that minimized total compliance cost to implement BMPs subject to targeted loading reductions in N and P in the watershed. The optimal solution for each sector using uniform allocation and sector targeting were compared for N and P loading reductions separately and N and P reductions simultaneously. The difference between sector targeting and uniform allocation showed the sector targeting was the more cost effective approach to achieve the desired nutrient reduction compared to uniform allocation. From the agricultural sector, cropland and hayland buffers provided the best options for reducing both N and P. Urban BMPs are least efficient in term of nutrient reduction and cost. Similarly, for point source upgrade, Broadway has the lowest cost of upgrade per unit of N or P reduction. This study implies that both stakeholders and policymakers can use targeting to achieve nutrient reduction goals at lower costs. 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