Estimated use of water in the Delaware River Basin in Delaware, New Jersey, New York, and Pennsylvania, 2010

Hutson, Susan S.; Linsey, Kristin S.; Ludlow, Russell A.; Reyes, Betzaida; Shourds, Jennifer L.

doi:10.3133/sir20155142

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…The Delaware Bay estuary is a coastal plain estuary that drains an area of about 35,000 km 2 across Pennsylvania, New Jersey, New York, Delaware, and Maryland (Hutson et al 2016). The Delaware River, its main tributary, contributes $ 60% of the annual freshwater to the total discharge of the estuary, with the Schuylkill River contributing an additional 15% and no other single tributary contributing more than 1% (Sharp et al 1986) (Fig.…”

Section: Geographical Settingmentioning

confidence: 99%

“…In the mid‐Atlantic region of North America, the Delaware River Basin supplies drinking water for 15 million people including nearly half of the population of New York City (Hutson et al 2016). Water resources in the basin are jointly managed by four states and the federal government to meet demand while also maintaining downstream flow and water quality objectives (Mandarano and Mason 2013).…”

mentioning

confidence: 99%

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Deep learning of estuary salinity dynamics is physically accurate at a fraction of hydrodynamic model computational cost

Gorski,

Cook,

Snyder

et al. 2024

Limnology & Oceanography

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Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state‐of‐the‐art modeling approaches use hydrodynamic models, which can produce accurate results but are limited by significant computational costs. We developed a machine learning (ML) model to predict the 250 mg L−1 Cl− isochlor, also known as the “salt front,” using daily river discharge, meteorological drivers, and tidal water level data. We use the ML model to predict the location of the salt front, measured in river miles (RM) along the Delaware River, during the period 2001–2020, and we compare predictions of the ML model to the hydrodynamic Coupled Ocean–Atmosphere‐Wave‐Sediment Transport (COAWST) model. The ML model predicts the location of the salt front with greater accuracy (root mean squared error [RMSE] = 2.52 RM) than the COAWST model does (RMSE = 5.36); however, the ML model struggles to predict extreme events. Furthermore, we use functional performance and expected gradients, tools from information theory and explainable artificial intelligence, to show that the ML model learns physically realistic relationships between the salt front location and drivers (particularly discharge and tidal water level). These results demonstrate how an ML modeling approach can provide predictive and functional accuracy at a significantly reduced computational cost compared to process‐based models. In addition, these results provide support for using ML models in operational forecasting, scenario testing, management decisions, hindcasting, and resulting opportunities to understand past behavior and develop hypotheses.

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Section: Geographical Settingmentioning

confidence: 99%

mentioning

confidence: 99%

Deep learning of estuary salinity dynamics is physically accurate at a fraction of hydrodynamic model computational cost

Gorski,

Cook,

Snyder

et al. 2024

Limnology & Oceanography

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show abstract

“…The Delaware River Basin spans 13,539 square miles from southern New York to the Delaware Bay and is home to more than 8 million people who both rely on and affect its water quality. 50 Urban watersheds like the Delaware River Basin are increasingly polluted by excess nutrients from private land management decisions. 51 Household actions, such as fertilizing lawns, have increased nitrogen and phosphorus loads through surface runoff.…”

Section: Study Design Samplementioning

confidence: 99%

A story induces greater environmental contributions than scientific information among liberals but not conservatives

Byerly

Ferraro

et al. 2021

One Earth

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“…Power generation sector is further categorized into thermoelectric and hydroelectric generation power sectors. Based on a United States Geological Survey report, water withdrawals for thermoelectric power generation are considered offstream withdrawals, and therefore included in the calculation of total water withdrawal (Hutson et al, 2010). However, water used for hydroelectric power is not considered a withdrawal because water flowing through a dam is considered as an instream use (Ludlow et al, 2000).…”

Section: Basin Description and Water Use Sectorsmentioning

confidence: 99%

Reservoir Operations & Water Allocation Model: New York City Delaware River Basin Reservoirs

Tezcan¹,

Olson²,

Gurian³

2018

Turkish Journal of Water Science and Management

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The New York City (NYC) reservoirs in the Delaware River Basin are essential sources for goods and services, such as drinking water supply, recreation, power generation, and a host of ecosystem services. The reservoirs are located at the headwaters of the Delaware River, which supply water to New York, New Jersey, Pennsylvania and Delaware. However, the river is vulnerable to water shortages under changing climate conditions and needs to be managed wisely. This study developed a hydrologic model within the Stella modeling software for the NYC reservoirs to determine how historical reservoir management policies perform at meeting water demands in the basin and out-of-basin. The model provides information to better understand the interconnected effects of demands from water use sectors under different climate conditions, and to help addressing water shortages under water-stressed conditions. The model simulates reservoir releases based on inflows to reservoirs, water demand by sectors and historical reservoir management policies. The model predictions were compared with historical data to assure that the model was operating in the designed manner. The impact of this study extends directly to decision makers for water resources management, and stakeholders who rely on water resources in the basin.

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Estimated use of water in the Delaware River Basin in Delaware, New Jersey, New York, and Pennsylvania, 2010

Cited by 4 publications

References 5 publications

Deep learning of estuary salinity dynamics is physically accurate at a fraction of hydrodynamic model computational cost

Deep learning of estuary salinity dynamics is physically accurate at a fraction of hydrodynamic model computational cost

A story induces greater environmental contributions than scientific information among liberals but not conservatives

Reservoir Operations & Water Allocation Model: New York City Delaware River Basin Reservoirs

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