scholarly journals Estimates of future water demand for selected water-service areas in the Upper Duck River basin, central Tennessee; with a section on Methodology used to develop population forecasts for Bedford, Marshall, and Maury counties, Tennessee, from 1993 through 2050

1996 ◽  
Keyword(s):  
River Basin ◽  
Water Demand ◽  
Water Service ◽  
Population Forecasts ◽  
Duck River ◽  
Service Areas

scholarly journals Assessing Future Water Demand and Associated Energy Input with Plausible Scenarios for Water Service Providers (WSPs) in Sub-Saharan Africa

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2169
Author(s):  
Pauline Macharia ◽  
Nzula Kitaka ◽  
Paul Yillia ◽  
Norbert Kreuzinger
Keyword(s):  
Water Supply ◽  
Water Demand ◽  
Energy Input ◽  
Service Providers ◽  
Sub Saharan Africa ◽  
Water Losses ◽  
Water Service ◽  
Current State ◽  
Per Capita ◽  
Sub Saharan

This study examined the current state of water demand and associated energy input for water supply against a projected increase in water demand in sub-Saharan Africa. Three plausible scenarios, namely, Current State Extends (CSE), Current State Improves (CSI) and Current State Deteriorates (CSD) were developed and applied using nine quantifiable indicators for water demand projections and the associated impact on energy input for water supply for five Water Service Providers (WSPs) in Kenya to demonstrate the feasibility of the approach based on real data in sub-Saharan Africa. Currently, the daily per capita water-use in the service area of four of the five WSPs was below minimum daily requirement of 50 L/p/d. Further, non-revenue water losses were up to three times higher than the regulated benchmark (range 26–63%). Calculations showed a leakage reduction potential of up to 70% and energy savings of up to 12 MWh/a. The projected water demand is expected to increase by at least twelve times the current demand to achieve universal coverage and an average daily per capita consumption of 120 L/p/d for the urban population by 2030. Consequently, the energy input could increase almost twelve-folds with the CSI scenario or up to fifty-folds with the CSE scenario for WSPs where desalination or additional groundwater abstraction is proposed. The approach used can be applied for other WSPs which are experiencing a similar evolution of their water supply and demand drivers in sub-Saharan Africa. WSPs in the sub-region should explore aggressive strategies to jointly address persistent water losses and associated energy input. This would reduce the current water supply-demand gap and minimize the energy input that will be associated with exploring additional water sources that are typically energy intensive.

scholarly journals Evaluation of Ecological Water Consumption in Yanhe River Basin Based on Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ting Guo ◽  
Huiying Yu
Keyword(s):  
Big Data ◽  
River Basin ◽  
Water Consumption ◽  
Water Demand ◽  
Environmental Water ◽  
Big Data Analysis ◽  
Ecological Environment ◽  
Sustainable Utilization ◽  
Runoff Change ◽  
Consumption Change

Starting from the main eco-environmental problems faced by water environment, taking Yanhe River Basin as an example, this paper discusses the theoretical connotation and evaluation calculation method of eco-environmental water consumption. In order to study the eco-environmental water consumption of Yanhe River Basin, a runoff driving factor mining method based on big data analysis is established in this paper. Aiming at the problem that the statistical law and genetic law of runoff change frequently in changing environment, the mining technology method of runoff key driving factors is proposed by combining traditional methods with big data analysis. The characteristic factors that have no significant impact on runoff change are removed, the implicit characteristic factors affecting runoff change are extracted, the driving relationship of hydrological, meteorological, and vegetation characteristic factors on ecological water consumption change is identified, and the key driving factors of ecological water consumption change are extracted, which lays a data foundation for ecological water consumption prediction based on machine learning. The economic water consumption based on eco-environmental water consumption in Yanhe River Basin in the future is predicted (including water demand in three aspects of industry, agriculture, and life); that is, the prediction is to meet the economic water demand on the basis of ensuring that the water consumption of ecological environment will not be occupied, which can effectively ensure the improvement of ecological environment function in Yanhe River Basin and is conducive to the sustainable utilization of water resources in Yanhe River Basin. The research is only based on a small watershed such as Yanhe River Basin, and the purpose of the research is to provide a reference for ecological environment protection and sustainable utilization of water resources in the Loess Plateau, even in the arid, semiarid, and semihumid areas of North China.

scholarly journals Domestic water demand forecasting in the Yellow River basin under changing environment

2018 ◽  
Vol 10 (3) ◽  
pp. 379-388
Author(s):  
Xiao-jun Wang ◽  
Jian-yun Zhang ◽  
Shamsuddin Shahid ◽  
Lang Yu ◽  
Chen Xie ◽  
...  
Keyword(s):  
River Basin ◽  
Water Demand ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Earth System ◽  
Domestic Water ◽  
Content Type ◽  
Domestic Water Demand ◽  
The Yellow River Basin

Purpose The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River. Design/methodology/approach The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios. Findings The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 108 to 62.20 × 108 m3 in year 2020 and between 73.32 × 108 and 89.27 × 108 m3 in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users. Originality/value The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.

The Jordan River basin: 3. Options for satisfying the current and future water demand of the five riparians

2009 ◽  
Vol 34 (2) ◽  
pp. 170-188 ◽  
Author(s):  
David J.H. Phillips ◽  
Anders Jägerskog ◽  
Anthony Turton
Keyword(s):  
River Basin ◽  
Water Demand ◽  
Jordan River ◽  
Jordan River Basin

scholarly journals Effects of climate change on agriculture water demand in lower Pak Phanang river basin, southern part of Thailand

2018 ◽  
Vol 192 ◽  
pp. 03043
Author(s):  
Natapon Kaewthong ◽  
Pakorn Ditthakit
Keyword(s):  
Climate Change ◽  
Land Use ◽  
River Basin ◽  
Water Demand ◽  
Land Development ◽  
Circulation Model ◽  
Climate Data ◽  
Global Circulation Model ◽  
Baseline Climate ◽  
Agriculture Water

The aim of the research is to analyse the effects on agricultural water demand in the Lower Pak Phanang River Basin area due to climate change. The climate data used in the analysis were rainfall, maximum, minimum, and average temperatures. The climate datasets were obtained from statistical downscaling of global circulation model under the CMIP5 project by means of bias correction with Optimizing Quantile Mapping implemented by the Hydro and Agro Informatics Institute. To determine agriculture water demand, reference evapotranspiration (ETo) based on Hargreaves method was calculated for both baseline climate data (1987-2015) and forecasted climate data in 2038. For agriculture water demand in the Pak Phanang river basin, we considered paddy field, palm oil, rubber, grapefruit, orchard, vegetable, ruzy and biennial crop, based on land use data of the Land Development Department of Thailand in 2012. The results showed that forecasted agriculture water demand in 2038 with existing land use data in 2012 will be increased with the average of 18.9% or 61.78 MCM as compared to baseline climate condition. Both water demand and supply management measures would be suitably prepared before facing unexpected situation.

scholarly journals Water resources planning in the Upper Niger River basin: Are there gaps between water demand and supply?

2019 ◽  
Vol 21 ◽  
pp. 176-194 ◽  
Author(s):  
Stefan Liersch ◽  
Samuel Fournet ◽  
Hagen Koch ◽  
Abdouramane Gado Djibo ◽  
Julia Reinhardt ◽  
...  
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Demand ◽  
Water Resources Planning ◽  
Demand And Supply ◽  
Water Demand And Supply ◽  
Niger River ◽  
Resources Planning

River Basin Management in the UK

1991 ◽  
Vol 23 (1-3) ◽  
pp. 57-64 ◽  
Author(s):  
M. A. House
Keyword(s):  
River Basin ◽  
River Basin Management ◽  
Regulatory Body ◽  
Basin Management ◽  
England And Wales ◽  
Water Service ◽  
Service Companies ◽  
The Uk

The Water Act 1989 has resulted in the reorganisation of the system of River Basin Management which has operated in England and Wales since the establishment of the 10 Water Authorities in 1974. On 1st September 1989 the Water Authorities were re-structured to produce 10 Water Service Companies and a new regulatory body, the National Rivers Authority. This presentation will summarise the changes to River Basin Management in England and Wales resulting from this reorganisation.

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