scholarly journals A Method for Modeling Urban Water Infrastructures Combining Geo-Referenced Data

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2299
Author(s):  
Imke-Sophie Rehm ◽  
John Friesen ◽  
Kevin Pouls ◽  
Christoph Busch ◽  
Hannes Taubenböck ◽  
...  
Keyword(s):  
Spatial Data ◽  
Water Distribution ◽  
Optimization Methods ◽  
Distribution Networks ◽  
Urban Water ◽  
Local Climate ◽  
Urban Structures ◽  
Local Climate Zones ◽  
Science And Politics ◽  
The One

Water distribution networks are the backbone of any municipal water supply. Their task is to supply the population regardless of the respective demand. High resilience of these infrastructures is of great importance and has brought these infrastructures into the focus of science and politics. At the same time, the data collected is highly sensitive and often openly unavailable. Therefore, researchers have to rely on models that represent the topology of these infrastructures. In this work, a model is developed that allows the topology of an urban water infrastructure to be mapped using the example of Cologne, Germany by combining freely available data. On the one hand, spatial data on land use (local climate zones) are used to disaggregate the water demand within the city under consideration. On the other hand, the parallelism of water and urban transportation infrastructures is used to identify the topology of a network by applying optimization methods. These networks can be analyzed to identify vulnerable areas within urban structures.

scholarly journals Bottom-Up Generation of Peak Demand Scenarios in Water Distribution Networks

2020 ◽  
Vol 13 (1) ◽  
pp. 31
Author(s):  
Enrico Creaco ◽  
Giacomo Galuppini ◽  
Alberto Campisano ◽  
Marco Franchini
Keyword(s):  
Water Distribution ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Peak Demand ◽  
Long Time ◽  
Cross Correlations ◽  
User Demand ◽  
One Year ◽  
The One ◽  
Best Fit

This paper presents a two-step methodology for the stochastic generation of snapshot peak demand scenarios in water distribution networks (WDNs), each of which is based on a single combination of demand values at WDN nodes. The methodology describes the hourly demand at both nodal and WDN scales through a beta probabilistic model, which is flexible enough to suit both small and large demand aggregations in terms of mean, standard deviation, and skewness. The first step of the methodology enables generating separately the peak demand samples at WDN nodes. Then, in the second step, the nodal demand samples are consistently reordered to build snapshot demand scenarios for the WDN, while respecting the rank cross-correlations at lag 0. The applications concerned the one-year long dataset of about 1000 user demand values from the district of Soccavo, Naples (Italy). Best-fit scaling equations were constructed to express the main statistics of peak demand as a function of the average demand value on a long-time horizon, i.e., one year. The results of applications to four case studies proved the methodology effective and robust for various numbers and sizes of users.

Urban water storage capacity inferred from observed evapotranspiration recession 

2021 ◽  
Author(s):  
Harro Jongen ◽  
Gert-Jan Steeneveld ◽  
Jason Beringer ◽  
Krzysztof Fortuniak ◽  
Jinkyu Hong ◽  
...  
Keyword(s):  
Storage Capacity ◽  
Water Storage ◽  
Urban Water ◽  
Natural Forests ◽  
Local Climate ◽  
Water Storage Capacity ◽  
Vegetation Fraction ◽  
Local Climate Zones ◽  
Order Of Magnitude ◽  
Neighborhood Scale

<p>The amount and dynamics of urban water storage play an important role in mitigating urban flooding and heat. Assessment of the capacity of cities to store water remains challenging due to the extreme heterogeneity of the urban surface. Evapotranspiration (ET) recession after rainfall events during the period without precipitation, over which the amount of stored water gradually decreases, can provide insight on the water storage capacity of urban surfaces. Assuming ET is the only outgoing flux, the water storage capacity can be estimated based on the timescale and intercept of its recession. In this paper, we test the proposed approach to estimate the water storage capacity at neighborhood scale with latent heat flux data collected by eddy covariance flux towers in eleven contrasting urban sites with different local climate zones, vegetation cover and characteristics and background climates (Amsterdam, Arnhem, Basel, Berlin, Helsinki, Łódź, Melbourne, Mexico City, Seoul, Singapore, Vancouver). Water storage capacities ranging between 1 and 12 mm were found. These values correspond to e-folding timescales lasting from 2 to 10 days, which translate to half-lives of 1.5 to 7 days. We find ET at the start of a drydown to be positively related to vegetation fraction, and long timescales and large storage capacities to be associated with higher vegetation fractions. According to our results, urban water storage capacity is at least one order of magnitude smaller than the known water storage capacity in natural forests and grassland.</p>

Study on Safety Evaluation Method for Water Distribution Networks Based on LS-SVM

2011 ◽  
Vol 243-249 ◽  
pp. 5003-5008
Author(s):  
Zhi Tao Wang ◽  
Jing Yu Su ◽  
Wei Wang
Keyword(s):  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Influential Factors ◽  
Water Distribution Networks ◽  
Security Level ◽  
Urban Water ◽  
Ann Model ◽  
Svm Model

To evaluate the security of urban water distribution network, one model based on LS-SVM was put forth. On the basis of summary and analysis of influential factors for urban water distribution network security, a set of indexes used in the evaluation model above was constructed. The nonlinear mapping between the water distribution networks security classification and its conditions were learned from the finite samples and a water distribution network example was simulated using this model. In addition, the BP ANN model was used to simulate the same example. Through the analysis of the result of the actual security level, the security level acquired by the LS-SVM model and BP ANN model, it may be found that the result acquired by the LS-SVM model has high accuracy, and may used in actual engineering.

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