A key issue in water resources management in China is the adoption of a total volume control framework of water supply at a regional level corresponding to socioeconomic development. This requires more efficient water demand management in order to achieve a balance between water supply and demand. The purpose of this paper is to conduct a thorough analysis of the water use structure of production sectors in order to identify the major impact factors and thus provide insights for demand management policy design. Taking Jiangsu Province as a case study, we compile a series of extended input-output (I-O) tables at a constant price and establish an I-O structural decomposition model. The major factors leading to change in water use by production sectors (primary, secondary and tertiary) in the Jiangsu Province during five time periods from 1997–2010 are categorized into structure effect, water use efficiency effect, and demand effect for each of three levels: (1) aggregated sectors, (2) sub-aggregated sectors, and (3) individual sectors. Within the study period, the demand effect consistently leads to an increase in water utilization and the increase effect becomes weaker over time, while the other two factors consistently lead to a decrease in water utilization and their dampening effect becomes stronger.
How risk assessments can make a city more resilient to weather extremes
Balancing water supply and demand—while addressing current and future vulnerabilities to extreme conditions such as drought—is essential to safeguarding the wellbeing of our communities. Is your city at risk? Identifying where cities have problems and determining how much is at risk is the first step to becoming a strong, resilient city. In states like California, water shortage is hardly a temporary problem, but there are very serious consequences that put local and state economies at risk. For...
World Bank: groundwater management specialist
The World Bank is currently looking for a senior water resources specialist specializing in groundwater management to join the South Asia water team. The World Bank’s regional portfolio is in South Asia comprises over $5 billion of lending, of which around half is for water supply and sanitation and half for water resource and irrigation projects and a strong focus in India. These projects span irrigation, major dams, river restoration, IWRM and river basin planning, water resources monitoring, modelling...
Senix Water Level Sensors Drive Irrigation Automation Project
Australia’s Water Crisis Irrigation management is serious business in Australia especially within the Murray-Darling Basin, a 1,000,000 square kilometer watershed that is home to Australia’s most productive agricultural land. The basin’s 23 rivers have some of the lowest and most variable flows in theworld. A massive system of dams, lakes and canals stores water from mountain snowmelt and seasonal rains and distributes it to farms and communities throughout the growing season. The Murray-Dar...
Water markets can support an improved water future
Fresh water touches every part of daily life – from drinking water and sanitation, to agriculture and energy production. Unfortunately, for nearly half of the world’s population, water scarcity is a growing issue with devastating impacts to our communities, economies and nature. In the past, countries have primarily turned to more supply-side infrastructure, including reservoirs and canals, as solutions to increasing water demands. But we can no longer build our way out of scarcity. We must find ways...
Source identification of sudden contamination based on the parameter uncertainty analysis
It is important to identify the source information after a sudden water contamination incident occurs in a water supply system. The accuracy of the simulation model's parameters determines the accuracy of the source information. However, it is difficult to obtain the true value of these parameters by existing methods, so reduction of the errors caused by the uncertainty of these parameters is a crucial problem. A source identification framework which considers the uncertainty of the model's sensitive parameters...