A multivariate econometric approach for domestic water demand modeling: An application to Kathmandu, Nepal

Babel, Mukand S.; Gupta, Ashim; Pradhan, Prita

doi:10.1007/s11269-006-9030-6

Cited by 99 publications

(42 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this term is different across regions as domestic water withdrawal is influenced not only by socioeconomic and climatic conditions but also by water policies and strategies (Babel et al, 2007). Here, we use the observed monthly water use data in 30 urban centers and counties (Table 2) to calibrate R in different regions.…”

Section: Domesticmentioning

confidence: 99%

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

Huang¹,

Hejazi²,

Li³

et al. 2017

Preprint

View full text Add to dashboard Cite

20Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scale, due to a lack of observations at local and seasonal time scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5 degree) sectoral water 25 withdrawal dataset for the period 1971-2010, which distinguishes six water use sectors, i.e. irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that global total water withdrawal has increased significantly during 1971-2010, mainly driven by the increase of irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern 30 China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of annual total irrigation water withdrawal in mid and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-551 Manuscript under review for journal Hydrol. Earth Syst. Sci. Discussion started: 15 September 2017 c Author(s) 2017. CC BY 4.0 License.2 withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual scales. The reconstructed gridded water withdrawal dataset is open-access, and can be used for examining issues related to water withdrawals at fine spatial, temporal and sectoral scales.

show abstract

Section: Domesticmentioning

confidence: 99%

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

Huang¹,

Hejazi²,

Li³

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…Until late, much of literature approaches demand for water in communities from a consumer's perspective [1][2][3][4][5][6][7]. Under this approach, the major influencing factors to demand for water are household income as well as price elasticity of the water.…”

Section: Introductionmentioning

confidence: 99%

“…This is vital for the planning how much to produce in the next period of time to match the consumer demand. For example, [2,5,7] used multivariate analysis, artificial neural networks and time series analysis respectively to predict short term demand of up to a couple of weeks. There is however need to go beyond just an hour, or a day, or just weeks.…”

Section: Introductionmentioning

confidence: 99%

Supplier’s view of water demand for a city: modelling the influencing factors

Fodya

Harley

2014

WIT Transactions on the Built Environment

View full text Add to dashboard Cite

An efficient system operates at equilibrium. Likewise, in the water business, companies aim to produce just enough water to match what is being demanded by its consumers. While consumers perceive income and price elasticity as their main influencing factors to water demand, suppliers have a different see altogether, and their factor differ from city to city. For example, Zomba City's supply company, Southern Region Water Board, lists daily and seasonal consumption fluctuations as well as population dynamics as its three major influencing factors to determine demand for water. This paper presents a model to predict water demand for Zomba city as influenced by the three aforementioned factors. With daily consumption data for Zomba City recorded from 2009 to 2013, and converted to standard hourly data by the weighting method, the parameters for daily fluctuations, seasonal fluctuations as well as population dynamics were determined. Sums of 24 hourly data readings generated from the model were compared with the daily recordings and a linear relationship was observed. In terms of predicting, the model is able to show that the existing infrastructure can sustain the current population, at least at the current growth rate for the next 17.8 years and that the reservoir, Mulunguzi Dam, has enough water for not only the city but the whole Zomba District for the next 5,500 years also. Equally, such capacity has the potential to supply the whole Malawi population for the next 42 years.

show abstract

“…Many studies have been conducted to estimate domestic water use in recent years, adopting various techniques (Nyong and Kanaroglou 2001, Liu et al 2003, Babel et al 2007, Yurdusev and Firat 2009. Such studies were mainly focused on urban centres and mega-cities (Liu et al 2003, Babel et al 2007, Chu et al 2009, Wei et al 2009, Yurdusev and Firat 2009, or limited to one season or year (Nyong and Kanaroglou 2001, Machingambi and Manzungu 2003, Makoni et al 2004. For instance, Liu et al (2003) applied the ANN technique to model and forecast water demand in urban areas.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Liu et al (2003) applied the ANN technique to model and forecast water demand in urban areas. Babel et al (2007) developed a multiplecoefficient water demand forecast and management model for domestic water use considering various socio-economic, climatic and policy-related factors. Keshavarzi et al (2006) identified the factors that affect domestic water use in rural areas.…”

Section: Introductionmentioning

confidence: 99%

Spatially explicit estimation of domestic water use in the arid region of northwestern China: 1985–2009

Guo

Chen

Shen

et al. 2013

Hydrological Sciences Journal

View full text Add to dashboard Cite

Determination of the spatial and temporal trends in domestic water use is vital for making adequate and sustainable water management strategies, especially in arid regions. In this study, domestic water-use models considering socio-economic factors were developed to analyse spatial and temporal trends in domestic water use at a resolution of 4 km × 4 km in the arid region of northwestern China in the period 1985-2009. The results indicate that total annual domestic water use increased from 305.34 × 10 6 m 3 /year in 1985 to 1188.53 × 10 6 m 3 /year in 2009. Per capita domestic water use increased rapidly, especially in urban areas. A spatial disparity in per capita domestic water use and total annual domestic water use was apparent. The pressure of high domestic water use on water resources was found in some river basins, particularly the Shiyang River basin. The presented models can be successfully applied for estimating domestic water use in this region. However, there are several uncertainties due to the lack of data. Despite these uncertainties, the modelling results can provide important information for managers and planners on sustainable water use in this region. Furthermore, these models have the potential to be applied for estimation of future domestic water use in other regions.

show abstract

A multivariate econometric approach for domestic water demand modeling: An application to Kathmandu, Nepal

Cited by 99 publications

References 5 publications

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

Supplier’s view of water demand for a city: modelling the influencing factors

Spatially explicit estimation of domestic water use in the arid region of northwestern China: 1985–2009

Contact Info

Product

Resources

About