Groundwater overexploitation in the North China Plain: A path to sustainability

TRAMA

Over-pumping of aquifers is a worldwide problem, mainly caused by agricultural water use. Among its consequences are the falling dry of streams and wetlands, soil subsidence, die-off of phreatophytic vegetation, saline water intrusion, increased pumping cost and loss of storage needed for drought relief.   Stopping or reversing the trend requires management interventions. The North China Plain serves as an example. A management system is set up for a typical county. It contains three components: monitoring, decision support based on modelling, and implementation in the field. Besides all monitoring data, the decision support module contains an irrigation calculator, a box model, and a distributed groundwater model to project the outcomes of different water allocation scenarios. In view of grain security, a solution combines an adaptation of the cropping system with imports of surface water from the South. The Open Access book does not only describe the problem and the path to its solution. It also gives access to nine manuals concerning methods used. They include computer programs and the game Save the Water. The Chinese experience should be of considerable interest to other regions in the world which suffer from over-pumping of aquifers.

SOMMARIO

Chapter 1 Introduction.- Chapter 2 Policy options of over-pumping control in the NCP.- Chapter 3 Cropping choices and farmers’ options.- Chapter 4 Decision support for local water authorities in Guantao County.- Chapter 5 Way forward.

AUTORE

Prof. Dr. Kinzelbach studied Physics in Mainz and Munich Universities in Germany and Environmental Engineering at Stanford, California. He earned his Ph. D. degree in Environmental Engineering in 1978 from Karlsruhe University in Germany. After professorships in Kassel and Heidelberg, he was appointed chair of hydromechanics and groundwater at ETH Zurich. His research focused on flow and transport processes in the aquatic environment with applications in remediation, waste isolation and sustainable management. He contributed to the development of groundwater modelling, including real time modelling, and the use of remote sensing data in geohydrology. He is known world-wide for his work in the field of sustainable groundwater management. He is recipient of the Henry Darcy medal of the EGU and fellow of the AGU. Since his retirement in 2014, he has been heading the Sino-Swiss groundwater management project. He is still active as a consultant to government on nuclear waste isolation and river rehabilitation.Dr. Haijing Wang earned a bachelor’s degree in Environmental Engineering in 1993 from Tsinghua University, Beijing. She received a master's degree (1996) and a doctoral degree (2000), both in Civil Engineering, from Hong Kong University of Science and Technology. After a lectureship in New Zealand and postdoctoral research in Germany and England, she settled in Switzerland. She was leading the Sino-Swiss science and technology cooperation program at ETH Zurich on behalf of the Swiss Federal government before she returned to science, specializing in remote sensing applications in the field of water resources. In 2010 she co-founded the private consulting firm hydrosolutions Ltd. in Zurich, Switzerland. Dr. Wang has extensive work experience in developing countries. Her research has a regional focus on Africa and China. Her connection with local academic institutions gives her a special angle to look at problems touching the local needs.Dr. Yu Li got his bachelor’s degree in Environmental Science in Zhejiang University of Technology, China, in 2009. He obtained a master’s degree (2012) and a Ph. D. degree (2016) at Politecnico di Milano, Milan, Italy, with a thesis on Water Resources Management under Changing Conditions. He spent a semester as a visiting scientist at Cornell University in the US, before moving to Switzerland as a Postdoc at ETH Zurich’s Institute of Environmental Engineering. His research interest focuses on the modelling of coupled human-water systems and their analysis under a changing environment. He is also an expert in hydro-informatics including skills such as multi-objective optimization, decision support, visual analytics, machine learning and data mining as applied in water systems analysis. He pioneered the development of a serious game on agricultural water management and its use as a survey tool for farmers’ behavioral analysis in China.Dr. Lu Wang got her bachelor’s degree (2007) from Hohai University in Nanjing, China, where she also earned her master’s degree (2009) in Hydrology and Water Resources Engineering. She obtained her Ph.D. degree (2015) from Delft University of Technology in the Netherlands with a thesis on flood risk assessment in the Huai River Basin under climate change.  She joined the Institute of Environmental Engineering at ETH Zurich as a postdoc in 2015. Her research interest focuses on climate change impacts on water resources, adaptation measures and the water-energy nexus. She is skilled in hydrological modelling, downscaling techniques, analysis of big data in hydrology and water resources, and field methods concerning groundwater.Dr. Ning Li got her bachelor’s degree in Engineering Geology at Shandong University of Science and Technology, China (2005). She obtained her master’s degree (2008) in Hydrology and Water Resources at China University of Geosciences, Beijing, China and her Ph.D. degree (2013) in Environmental Engineering at ETH Zurich, Switzerland with a thesis on sustainable water management in the Yanqi Basin, Xinjiang, China. During her Ph.D. study she spent time as a visiting scientist at MIT’s Department of Civil and Environmental Engineering. After her Ph.D. she joined ETH as a postdoc. She is an experienced hydrogeologist with a vast experience in integrated hydrological modelling of flow and solute transport in the aquatic environment, especially in groundwater. Her specialties are the quantification of model uncertainties, data assimilation and real time modelling, data driven modelling and machine learning.

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9789811658426
• Collana: Springer Water
• Dimensioni: 235 x 155 mm Ø 436 gr
• Formato: Copertina rigida
• Illustration Notes: XVIII, 157 p. 98 illus., 89 illus. in color. With online files/update.
• Pagine Arabe: 157
• Pagine Romane: xviii