Thermal evaluation of urbanization using a hybrid approach

Ketabchy, Mehdi; Sample, David J.; Wynn-Thompson, Theresa; Yazdi, Mohammad Nayeb

doi:10.1016/j.jenvman.2018.08.016

Cited by 24 publications

(17 citation statements)

References 64 publications

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“…NSE values range from −∞ to +1 and they index the quality of the modeling procedure. Values of <0.5, 0.5-0.7 and >0.7 were respectively considered as unsatisfactory, satisfactory and good (Ketabchy et al 2018). The relationship between RMSE and modeling performance is such that lower values of RMSE represent a better modeling performance.…”

Section: Objective Functionsmentioning

confidence: 99%

Assessing the Performance of a Hydrological Tank Model at Various Spatial Scales

Goodarzi

Amiri

Azarneyvand

et al. 2020

JWMM

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In this study we investigated the performance of the Tank hydrologic model in predicting rainfall-runoff using a descriptive-analytical approach, including objective error measures and flow signatures (mean annual specific runoff, mean flow duration curves, normalized low flow and high flow indexes, coefficient of variation, and hydrograph flashiness). Because hydrological processes vary at different scales, three watersheds located in three significantly different environments, which are examples of small (15 km 2), medium (215 km 2) and large (542 km 2) watersheds, were selected to evaluate the performance of the hydrologic model. We found that Neka (the small watershed) has a large water budget with a steep flow slope, including both extremely low flow (lowest) and high flow (highest), a very high variation, and a flashy hydrograph (0.21 ≤ HF ≤ 0.41). Ghezel-Ozan (the medium watershed) also has a large water budget with a fairly steep flow slope, an extremely low flow and a moderate high flow, a moderate variation, and a very steady hydrograph (0.01 ≤ HF ≤0.02). Babolroud (the large watershed) possesses a moderate water budget with a moderate flow slope, a below-average low flow, a moderate high flow, an average variation, and a fairly flashy hydrograph (0.22 ≤ HF ≤ 0.28). The quality of rainfall-runoff modeling was good to satisfactory for the medium and large watersheds as shown by the two error metrics (1.32 ≤ RMSE ≤ 2.58, 0.61 ≤ NSE ≤ 0.8). However, the small watershed performance, especially in the validation period, was unsatisfactory (4.66 ≤ RMSE ≤ 5.33, 0.21 ≤ NSE ≤ 0.51). The limitations identified should be considered for medium watersheds. The Tank model is highly recommended for use in hydrologic predictions of large watersheds.

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Section: Objective Functionsmentioning

confidence: 99%

Assessing the Performance of a Hydrological Tank Model at Various Spatial Scales

Goodarzi

Amiri

Azarneyvand

et al. 2020

JWMM

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“…Pervious surfaces allow for infiltration, which is one of the most effective processes for runoff heat mitigation (Chapman, Wawiernia, and Kieweg 2008) because water is cooled as it travels through colder soils. Infiltration also replenishes groundwater, contributing to baseflow, which has cooling benefits (Dugdale, Bergeron, and St-Hilaire 2013;Ketabchy et al 2018;LeBlanc, Brown, and FitzGibbon 1997). Baseflow helps buffer thermal fluctuations.…”

Section: Factors Of Stream Temperaturementioning

confidence: 99%

“…However, this model also has limitations. MINUHET has no point source discharge input, assumes spatially uniform meteorological inputs, has inflexible component property requirements, produces less accurate results of modeled watersheds larger than 0.1 km 2 , and compared to more robust hydrologic and hydraulic models such as SWMM, lacks hydraulically relevant structural details (Herb et al 2010a;Ketabchy et al 2018).…”

Section: Review Of the Minuhet Modelmentioning

confidence: 99%

“…Additional case studies evaluated MINUHET performance for various sized mixeduse watersheds: a 0.05 km 2 residential watershed in Plymouth, Minnesota (Janke et al 2013), a 0.13 km 2 commercial site in Hastings, Minnesota (Herb 2008), and a 75% developed 14.1 km 2 watershed in Blacksburg, Virginia (Ketabchy et al 2018). Dew point temperature and soil saturated hydraulic conductivity were the recurring parameters that produced the greatest model sensitivities (Herb 2008;Janke et al 2013;Ketabchy et al 2018). Dew point temperatures significantly influence initial runoff temperatures because MINUHET assumes that precipitation temperatures are equal to dew point temperatures, especially during lighter storms (Janke et al 2013;Ketabchy et al 2018).…”

Section: Review Of the Minuhet Modelmentioning

confidence: 99%

“…Dew point temperature and soil saturated hydraulic conductivity were the recurring parameters that produced the greatest model sensitivities (Herb 2008;Janke et al 2013;Ketabchy et al 2018). Dew point temperatures significantly influence initial runoff temperatures because MINUHET assumes that precipitation temperatures are equal to dew point temperatures, especially during lighter storms (Janke et al 2013;Ketabchy et al 2018). Additionally, simulated runoff for scenarios with large amounts of pervious areas is highly sensitive to soil hydraulic conductivity because the property is a significant variable in the Green-Ampt method for infiltration (Janke et al 2013).…”

Section: Review Of the Minuhet Modelmentioning

confidence: 99%

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Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Chen

Hodges²,

Dymond

2020

J American Water Resour Assoc

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Stream ecosystems are increasingly at risk for thermal impairment as urbanization intensifies, resulting in more heated runoff from impervious cover that is less likely to be cooled naturally. While several best management practices, including bioretention filters, have been able to reduce thermal pollution, success has been limited. The extent of thermal mitigation required to prevent ecological damage remains unknown. A calibrated runoff temperature model of a case study watershed in Blacksburg, VA was developed to determine the cumulative treatment volume of bioretention filters required to reduce thermal impacts caused by runoff from development in the watershed to regulated biologically acceptable levels. A future build out scenario of the study watershed was also analyzed. Results from this study established that runoff thermal pollution cannot be fully reduced to goal thresholds during all storms using bioretention filter retrofits. While retrofitting significantly decreased temperatures and heat exports relative to the controls, increasing treatment volumes did not really enhance mitigation. Alternate thermal mitigation methods that actively remove runoff volume should be considered where more thermal mitigation is required.

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Green roof vegetation management alters potential for water quality and temperature mitigation

et al. 2021

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The global increase of urban impervious land cover poses a significant threat to the integrity of river ecosystems. Hence, it is critical to assess the efficiency of green roofs (GR) to mitigate the negative impacts of urbanization on river ecosystems, such as thermal surges and pollutants. In this study, we evaluated the ecohydrological behaviour of two fully established GR under differing management regimes at the Chicago Botanical Gardens from July to September 2019. The drainage outflow from a non‐vegetated roof, a managed GR (perennial native and non‐native plants) and an unmanaged GR (perennial natural prairie vegetation) were monitored, and thermal dynamics, dissolved organic matter (DOM) composition and nitrate concentration assessed. The managed GR runoff had a lower DOC concentration and less humic‐like DOM signal (SUVA254) compared to the unmanaged GR. In contrast, lower concentrations of nitrate and more recalcitrant DOM (less protein‐like compounds relative to humic‐like compounds) were associated with the unmanaged GR. The unmanaged GR also displayed a greater capacity to reduce thermal surges associated with storm events. Our study provides new information on the implications of GR management for water quality with particular relevance to the urban stream syndrome. Further, the impacts of GR management on the mitigation of thermal surges and DOM composition can help to improve future GR design, as these ecohydrological responses have been largely overlooked to date. Our findings can support future urban planning, particularly for scenarios where green infrastructures are used to mitigate the impacts of climate change on urban river ecosystems.

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Thermal evaluation of urbanization using a hybrid approach

Cited by 24 publications

References 64 publications

Assessing the Performance of a Hydrological Tank Model at Various Spatial Scales

Assessing the Performance of a Hydrological Tank Model at Various Spatial Scales

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Green roof vegetation management alters potential for water quality and temperature mitigation

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