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Enregistrement W4396761923 · doi:10.2175/193864718825159350

Delivering Projects using Community Based Partnership to meet Chesapeake Bay TMDL Requirements in Prince George's County, MD and Key Lessons Learned

2024· article· en· W4396761923 sur OpenAlexaboutno aff
Srikanth Gorugantula, Roland Jones

Notice bibliographique

RevueProceedings of the Water Environment Federation · 2024
Typearticle
Langueen
DomaineEngineering
ThématiqueBIM and Construction Integration
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeorge (robot)Chesapeake bayGeneral partnershipKey (lock)Computer scienceBayEngineeringAeronauticsEnvironmental scienceOperations researchPolitical scienceComputer securityOceanographyCivil engineeringEstuaryGeologyLaw

Résumé

récupéré en direct d'OpenAlex

Delivering Projects using Community Based Partnership to meet Chesapeake Bay TMDL Requirements in Prince George's County, MD and Key Lessons LearnedAbstractPrince George's County, MD is located within the 80,000 square mile Chesapeake Bay watershed. EPA and the State of Maryland prepared the Chesapeake Bay Total Maximum Daily Load (Bay TMDL) for restoring the Chesapeake Bay's chemically, biologically and physically impaired waters. The Bay TMDL requires States, Counties and Cities within the watershed to limit the amount of Total Phosphorus, Total Nitrogen and Total Suspended Sediment that is discharged through point and non-point sources (urban stormwater runoff). Prince George's County combined meeting regulatory requirements with targeted local workforce and business development for this pioneering alternative delivery project. Prince George's County (County) and Corvias Infrastructure Solutions (CIS) developed the Clean Water Partnership (CWP) to design, build and maintain urban stormwater quality treatment best management practices (BMPs) to meet the County's Bay TMDL obligations. In addition to infrastructure improvements, the CWP balances risk, priorities, and social needs, through this Community Based Partnership (CBP). Bringing financing, engineering design firms, contractors, outreach and social/economic goals to this project, environmental compliance is being achieved with local economic growth and community involvement. This groundbreaking and innovative alternative delivery method is the first in the country and required a pioneering, dynamic and responsive team effort to meet the multiple program objectives. The two main CBP program elements include: 1) Environmental goals of design, permitting and construction of stormwater treatment devices, located throughout the 500-square mile County, to treat urban stormwater runoff. 2) Social and economic goals to meet aggressive target class utilization (40% for local, small and minority businesses) and local workforce (51% county resident utilization). Between 2016 and 2021, CWP has successfully implemented over 150 projects, certified over 300 BMP devices to help meet the County's MS4 stormwater permit requirements. In this process, CWP spent over $140 million in design and construction and reduced approximately 53,700 lb. of Total Nitrogen (TN), 7,300 lb. of Total Phosphorus (TP) and 4,405,100 lb. of Total Suspended Solids (TSS). In addition, more than 15,000 acres of drainage area is also treated to reduce pollutants to Chesapeake Bay. A key to the success of the CWP Program has been clear programmatic metrics including indicators and beneficiaries from day one. Primary program metrics focused on schedule/speed, scale economies and performance, community outreach, local disadvantaged subcontractor utilization, local subcontractor development, workforce utilization, and workforce development. Additional metrics were related to alternative compliance and partner programs, and project budget books and schedules. Moving forward, the CWP Team is focused on executing efficiencies to design and construct additional large pond retrofit projects and stream restoration projects based on their monitoring and tracking of BMP cost-effectiveness throughout earlier phases. In addition to complete data inventories on the number of BMPs built and drainage area managed, the CWP Team analyzed pollution removal and cost data of BMPs to determine Total Nitrogen, Total Phosphorus and Total Suspended Solids reduction for 10+ different types of BMPs. This performance summary information directly influenced the planning and siting of each subsequent phase of BMP design and construction. At the same time the Program Management team will continue to rely on performance data and think creatively to achieve its program goals and metrics in future phases. The CWP team has been focusing on asset management as the Program matures to its subsequent phases. This presentation will provide useful information for utility and public works department leaders, and stormwater management staff about creating or tailoring an existing program to meet large-scale targets for capital project delivery intended to meet water quality goals or other stormwater related objectives such as resiliency and flood risk reduction. Partnership goals, organizational structures and integrated delivery partners roles and responsibilities, and program metrics will be shared for discussion. Detailed information will also be presented related to specific program elements and BMP performance data that helped the CWP Team to achieve program milestones. As more communities face increasing regulation and climate-related threats to their stormwater infrastructure, bundling capital improvement projects for cost-effective and timely implementation may be necessary. The CWP Team will share lessons learned from their 6+ years of program execution, specific keys to success for other communities to consider and adaptive management strategies for future CWP success.This paper was presented at the WEF Collection Systems and Stormwater Conference, April 9-12, 2024.SpeakerGorugantula, SrikanthPresentation time13:30:0014:00:00Session time13:30:0015:00:00SessionCollaborative InitiativesSession number05Session locationConnecticut Convention Center, Hartford, ConnecticutTopicConstruction, Funding, Green Infrastructure, Laboratory Methods And Analysis, Program Management, Public Utility, Rates, Stormwater Control Measure, TMDLs, Water Quality, Watershed ManagementTopicConstruction, Funding, Green Infrastructure, Laboratory Methods And Analysis, Program Management, Public Utility, Rates, Stormwater Control Measure, TMDLs, Water Quality, Watershed ManagementAuthor(s)Gorugantula, SrikanthAuthor(s)S. Gorugantula1, R. Jones2Author affiliation(s)HDR 1; Corvias Infrastructure Solutions (CIS) 2SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Apr 2024DOI10.2175/193864718825159350Volume / Issue Content sourceCollection Systems and Stormwater ConferenceCopyright2024Word count22

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,133
Score d'incertitude au seuil0,383

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,056
Tête enseignante GPT0,258
Écart entre enseignants0,202 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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