Impact of a Changing Environment on Drainage System Performance

Kleidorfer, Manfred; Mikovits, Christian; Jasper-Tönnies, Alrun; Huttenlau, Matthias; Einfalt, Thomas; Rauch, Wolfgang

doi:10.1016/j.proeng.2014.02.105

Cited by 38 publications

(28 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These values are in accordance to the size of the cities. For Wroclaw, WFblue is dominating (36 Mm³/year), the 2 respectively, it appears that the largest total WF of 6665 m 3 /year·ha is reached for Innsbruck (Figure 2b). A very close value of 6339 m 3 /year·ha was obtained for Vicenza and a relatively small value of 4240 m 3 /year·ha is reached for Wroclaw.…”

Section: Resultsmentioning

confidence: 98%

“…As such, it includes water balances at local level to support water management without addressing the consequences of water use in a more comprehensive water footprint sustainability assessment [12]. To better support informed decisions, recent scientific developments recommend adopting additional assessment such as the water scarcity or availability assessment [2,12,[38][39][40]. For example, Bayart et al [38] has presented the water impact index that allows the integration of consumptive and degradative water use of a process unit.…”

Section: Discussionmentioning

confidence: 99%

“…In the urban environment, Manzardo et al [11] proposed to limit accounting of WFgreen to green areas, such as The blue water footprint (WF blue ) is the consumption of blue water resources, i.e., surface and groundwater withdrawn and not returned to the same water body [12]. According to this definition and its adaptation done by Manzardo et al [11] it is proposed that WF blue in urban area accounts for the part of rainwater that evaporates from impervious surfaces Q imperm (such as roads and car parks) (m 3 /a) and from water surfaces (rivers, ponds) Q water (m 3 /a), water that is lost due to heating and cooling processes Q therm (heating plants) (m 3 /a), water exported outside the city boundary Q exp (m 3 /a), loss of supply water during transportation Q tl (m 3 /a), water consumed by the citizens and services and stored for a long term usage Q del (m 3 /a) WF blue = Q imperm + Q water + Q therm + Q exp + Q tl + Q del (2) If the impermeable area is further subdivided into transportation area A transp (m 2 ), roof area A roof (m 2 ), and paved area A paved (m 2 ) the volume of water evaporated from impervious surfaces can be calculated using the following formula…”

Section: Urban Water Footprint Accounting Formulationmentioning

confidence: 99%

“…Looking forward to the next few decades, it seems likely that there will be a significant expansion in urban water infrastructure. Additionally, urban development, especially the sealing of surfaces and land use change, put pressure on urban infrastructure and quality of water discharged to the water bodies [2]. model, it is compared with the results of Manzardo et al [11].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Simplified Direct Water Footprint Model to Support Urban Water Management

Fiałkiewicz

Burszta‐Adamiak

Kolonko-Wiercik

et al. 2018

Water

View full text Add to dashboard Cite

Abstract:Water resources conservation corresponding to urban growth is an increasing challenge for European policy makers. Water footprint (WF) is one of the methods to address this challenge. The objective of this study was to develop a simplified model to assess the WF of direct domestic and non-domestic water use within an urban area and to demonstrate its effectiveness in supporting new urban water management strategies and solutions. The new model was tested on three Central European urban areas with different characteristics i.e., Wroclaw (Poland), Innsbruck (Austria), and Vicenza (Italy). Obtained WFs varied from 291 dm 3 /(day·capita) in Wroclaw, 551 dm 3 /(day·capita) in Vicezna to 714 dm 3 /(day·capita) in Innsbruck. In addition, WF obtained with the proposed model for the city of Vicenza was compared with a more complex approach. The results proved the model to be robust in providing reasonable results using a small amount of data.

show abstract

Section: Resultsmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Urban Water Footprint Accounting Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simplified Direct Water Footprint Model to Support Urban Water Management

Fiałkiewicz

Burszta‐Adamiak

Kolonko-Wiercik

et al. 2018

Water

View full text Add to dashboard Cite

show abstract

“…Auch die Saisonalität verschiebt sich: weniger Ereignisse im Sommer, jedoch mehr Ereignisse im Winter und Frühjahr (Dobler et al, 2012). Darüber hinaus weisen u. a. BMLFUW (2010) (Kleidorfer et al, 2014).…”

Section: Hochwasserunclassified

Kapitel 6: Der Einfluss des Klimawandels auf die Anthroposphäre

König¹,

Loibl²,

Steiger³

et al. 2014

Österreichischer Sachstandsbericht Klimawandel 2014

View full text Add to dashboard Cite

Evaluation of distributed BMPs in an urban watershed—High resolution modeling for stormwater management

Fry

Maxwell²,

McCray³

et al. 2017

Hydrological Processes

View full text Add to dashboard Cite

The urban environment modifies the hydrologic cycle resulting in increased runoff rates, volumes, and peak flows. Green infrastructure, which uses best management practices (BMPs), is a natural system approach used to mitigate the impacts of urbanization onto stormwater runoff. Patterns of stormwater runoff from urban environments are complex, and it is unclear how efficiently green infrastructure will improve the urban water cycle. These challenges arise from issues of scale, the merits of BMPs depend on changes to small‐scale hydrologic processes aggregated up from the neighborhood to the urban watershed. Here, we use a hyper‐resolution (1 m), physically based hydrologic model of the urban hydrologic cycle with explicit inclusion of the built environment. This model represents the changes to hydrology at the BMP scale (~1 m) and represents each individual BMP explicitly to represent response over the urban watershed. Our study varies both the percentage of BMP emplacement and their spatial location for storm events of increasing intensity in an urban watershed. We develop a metric of effectiveness that indicates a nonlinear relationship that is seen between percent BMP emplacement and storm intensity. Results indicate that BMP effectiveness varies with spatial location and that type and emplacement within the urban watershed may be more important than overall percent.

show abstract

Impact of a Changing Environment on Drainage System Performance

Cited by 38 publications

References 9 publications

Simplified Direct Water Footprint Model to Support Urban Water Management

Simplified Direct Water Footprint Model to Support Urban Water Management

Kapitel 6: Der Einfluss des Klimawandels auf die Anthroposphäre

Evaluation of distributed BMPs in an urban watershed—High resolution modeling for stormwater management

Contact Info

Product

Resources

About