Road salt application planning tool for winter de-icing operations

Trenouth, William R.; Gharabaghi, Bahram; Perera, Nandana

doi:10.1016/j.jhydrol.2015.03.004

Cited by 50 publications

(24 citation statements)

References 23 publications

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“…Given the sensitivity of FrAMES‐NACL to interannual variability of winter snowfall, which drives loading via road salt applications, adoption of loading recommendations may reduce chloride impairment within several seasons throughout much of the moderately developed MRW. Reduced loading to the watershed is achieved using a combination of education, liability reduction (New Hampshire Revised Statutes, 2016), deicing fleet management technology, location‐specific melt prediction (Trenouth et al, 2015), or stormwater management systems (Trenouth et al, 2018). Using a combination of these strategies, Toronto achieved lower than recommended application rates (∼1 g Cl mm −1 m −2 ) (Perera et al, 2009; Kilgour et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

Controls of Chloride Loading and Impairment at the River Network Scale in New England

et al. 2018

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Chloride contamination of rivers due to nonpoint sources is increasing throughout developed temperate regions due to road salt application in winter. We developed a river-network model of chloride loading to watersheds to estimate road salt application rates and investigated the meteorological factors that control riverine impairment by chloride at concentrations above thresholds protective of aquatic organisms. Chloride loading from road salt was simulated in the Merrimack River watershed in New Hampshire, which has gradients in development density. After calibration to a regional network of stream chloride data, the model captured the distribution of regional discharge and chloride observations with efficiencies of 93 and 75%, respectively. The estimate of road salt application is within uncertainties of inventoried estimates of road salt loading and is 122 to 214% greater than recommended targets. Model predictions of chloride showed seasonal variation in chloride concentrations despite a large groundwater storage pool. Interannual variation of mean summer chloride concentration near the outlet varied up to 18%, and the total river length exceeding impairment thresholds varied 12%. Annual snowfall, which drives road salt loading, correlated with chloride impairment only in headwater streams, whereas concentration variability at the outlet was driven primarily by dilution from clean runoff-draining undeveloped forested areas of the watershed. The role of summer meteorology complicates the protection of freshwater systems from chloride contamination.

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Section: Resultsmentioning

confidence: 99%

Controls of Chloride Loading and Impairment at the River Network Scale in New England

et al. 2018

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“…When vehicles travel quickly, they generate heat by friction between the tires and the pavement (Trenouth et al, ). The annual average daily traffic (AADT) is often used to measure traffic volumes, but it is not available in our case study.…”

Section: Methodsmentioning

confidence: 99%

“…Snowmelt volume. Trenouth, Gharabaghi, and Perera () introduced the modified temperature index model (MTIM) to predict the volume of snowmelt. MTIM uses two meteorological characteristics (air and base temperature) as well as plowing and salting information.…”

Section: Literature Reviewmentioning

confidence: 99%

Street‐segment‐based salt and abrasive prediction for winter maintenance using machine learning and GIS

Ahabchane

Trépanier

2018

Transactions in GIS

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Salting operations are essential but expensive in northern winters. We aim to predict the quantity of salt and abrasive needed for a specific road segment for each hour. An estimate of the quantity allows managers to better manage the loads in the trucks and to propose optimal vehicle routes based on the forecast, which will allow them to optimize costs. This article uses machine‐learning techniques based on truck telemetry data, weather conditions, and segment attributes. Geographic information systems (GIS) allow us to exploit the street‐network characteristics, which were ignored by previous prediction models. The results show that the XGBoost method performs better than other techniques (R2 = 0.83).

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“…Hallberg et al, 2007;Safadoust et al, 2016). During winter road maintenance activities it is common to remove snow and ice through a combination of ploughing, road salt and sand applications, and the latter of these activities can contribute a substantial amount of granular material to the road surface, making it available for runoff during rain or melt events (Helmreich et al, 2010;Trenouth et al, 2015). In tropical climates changing seasons are strongly linked with changing rainfall patterns, and this is reflected indirectly via the ADP, RD and RFI terms (Al-Badii and Shuhaimi-Othman, 2014).…”

Section: Seasonal Effects (Season)mentioning

confidence: 99%

“…Pulverization of the road surface by traffic movement can lead to the release of additional pollutants, including hydrocarbons and sediments (Bäckstrom et al, 2004;Ball et al, 1998). Winter maintenance activities may entail the direct application of sand and or salt to roadways (Betts et al, 2014(Betts et al, , 2015Perera et al, 2010Perera et al, , 2013Trenouth et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Highway runoff quality models for the protection of environmentally sensitive areas

Trenouth

Gharabaghi

2016

Journal of Hydrology

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Road salt application planning tool for winter de-icing operations

Cited by 50 publications

References 23 publications

Controls of Chloride Loading and Impairment at the River Network Scale in New England

Controls of Chloride Loading and Impairment at the River Network Scale in New England

Street‐segment‐based salt and abrasive prediction for winter maintenance using machine learning and GIS

Highway runoff quality models for the protection of environmentally sensitive areas

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