scholarly journals Urban Water Demand Simulation in Residential and Non-Residential Buildings Based on a CityGML Data Model

2020 ◽  
Vol 9 (11) ◽  
pp. 642 ◽  
Author(s):  
Keyu Bao ◽  
Rushikesh Padsala ◽  
Daniela Thrän ◽  
Bastian Schröter

Humans’ activities in urban areas put a strain on local water resources. This paper introduces a method to accurately simulate the stress urban water demand in Germany puts on local resources on a single-building level, and scalable to regional levels without loss of detail. The method integrates building geometry, building physics, census, socio-economy and meteorological information to provide a general approach to assessing water demands that also overcome obstacles on data aggregation and processing imposed by data privacy guidelines. Three German counties were used as validation cases to prove the feasibility of the presented approach: on average, per capita water demand and aggregated water demand deviates by less than 7% from real demand data. Scenarios applied to a case region Ludwigsburg in Germany, which takes the increment of water price, aging of the population and the climate change into account, show that the residential water demand has the change of −2%, +7% and −0.4% respectively. The industrial water demand increases by 46% due to the development of economy indicated by GDP per capita. The rise of precipitation and temperature raise the water demand in non-residential buildings (excluding industry) of 1%.

2020 ◽  
Vol 31 (2) ◽  
pp. 577
Author(s):  
Miguel Ángel Tobarra-González

In this article urban water demand is analyzed using data of 42 municipalities located in the Segura River Basin for the period 2000-2006. The econometric approach shows that price, income and population are the most important variables for explaining urban water demand changes. Water tariffs achieve moderate savings due to the price inelastic behavior of demand (-0,4). This is typical of necessary goods without substitutes. Calculus made shows that the increment in tariffs, necessary to reduce 10% consumption, means a consumer surplus reduction between 8 and 9,5 euros per person (and year). There is also a minimum of water consumption in homes, 84 litres per capita per day that cannot be affected by tariffs. Income and population increments have deeper impact than price for explaining changes in urban water demand. Predictions about these variables are major for a proper hydraulic management.


Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3400
Author(s):  
Mónica Maldonado-Devis ◽  
Vicent Almenar-Llongo

This paper deals with the question of unobservable heterogeneity and problems of scale in urban water demand. For this purpose, the determinants of domestic water consumption and the elasticities were estimated using a hierarchical model. For our empirical analysis, a household level data panel from Valencia (Spain) between 2009 and 2011 was available. Households were assigned to the city neighbourhoods to which they belong, which allowed us to incorporate the intra-urban scale into the analysis. In the estimate, the average price paid by each household in each bimonthly period was used due to the current tariff structure in Valencia. Regarding our results, there were differences in the consumption between the different neighbourhoods that were not independent of the average price paid by households. We found that 27% of the variability in consumption was explained by differences in household behaviour. In addition, an average price-elasticity in Valencia for all periods of −1.868 was obtained as well as a range of elasticities for the different neighbourhoods between (−1.53 and −1.21). From the results obtained, it is possible to extract relevant information for local water managers in order to apply economic instruments, prices and taxes to urban water demand.


2021 ◽  
Vol 1058 (1) ◽  
pp. 012066
Author(s):  
Salah L. Zubaidi ◽  
Hussein Al-Bugharbee ◽  
Yousif Raad Muhsin ◽  
Sadik Kamel Gharghan ◽  
Khalid Hashim ◽  
...  

2021 ◽  
Author(s):  
Shunyu Wu ◽  
Pingwei Zhao ◽  
Miaoshun Bai ◽  
Jingcheng Wang ◽  
Yang Lan

Author(s):  
Binaya Kumar Mishra ◽  
Shamik Chakraborty ◽  
Pankaj Kumar ◽  
Chitresh Saraswat

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