Modeling the nexus across water supply, power generation and environment systems using the system dynamics approach: Hehuang Region, China

Abstract Nexus approaches address the complex interconnections across coupled systems, providing a new and effective way to identify the dynamics of coevolution process. The connections across water supply, power generation and environment (WPE) systems are increasingly tight and thus can be profiled as a WPE nexus. This paper aims to model the WPE nexus in the China’s Hehuang Region by using the system dynamics approach. Six nonlinear ordinary differential equations of storage, water supply, power generation, population, biomass, and environmental awareness are formulated to dominate the coevolution process. Their constitutive relations are then obtained from observed data to complete the WPE nexus model. The results show that the system dynamics approach is competent in modeling the WPE nexus of the Hehuang Region. The coevolution process is divided into four cyclic stages (i.e., exploitation, deterioration, depression and recovery stages) and terminates with a stationary cycling after thousands of years. The dynamics of state variables are explicitly interpreted to show how different driving variables affect the variations of system states. The observations obtained by modeling the nexus are insightful, improving the understanding of interactions across coupled systems.

[1]  G. Rasul.  Food, water, and energy security in South Asia: A nexus perspective from the Hindu Kush Himalayan region☆ , 2014 .

[2]  Hugh Kelley,et al.  Multi-scale analysis of a household level agent-based model of landcover change. , 2004, Journal of environmental management.

[3]  A. Ye,et al.  High-resolution simulation of the spatial pattern of water use in continental China , 2016 .

[4]  Sharon Kingsland,et al.  The Refractory Model: The Logistic Curve and the History of Population Ecology , 1982, The Quarterly Review of Biology.

[5]  Murugesu Sivapalan,et al.  A prototype framework for models of socio-hydrology: identification of key feedback loops and parameterisation approach , 2014 .

[6]  Atul K. Jain,et al.  System of Systems Model for Analysis of Biofuel Development , 2015 .

[7]  Dedi Liu,et al.  A Model for the Optimal Allocation of Water Resources in a Saltwater Intrusion Area: A Case Study in Pearl River Delta in China , 2009 .

[8]  C. Marchetti,et al.  Human population dynamics revisited with the logistic model: How much can be modeled and predicted? , 1996 .

[9]  Murugesu Sivapalan,et al.  An integrated modeling framework for exploring flow regime and water quality changes with increasing biofuel crop production in the U.S. Corn Belt , 2014 .

[10]  Muaz A. Niazi,et al.  Agent-based computing from multi-agent systems to agent-based models: a visual survey , 2011, Scientometrics.

[11]  Wolfgang Lutz,et al.  Population--development--environment : understanding their interactions in Mauritius , 1995 .

[12]  D. Conway,et al.  China’s water–energy nexus: greenhouse-gas emissions from groundwater use for agriculture , 2012 .

[13]  Murugesu Sivapalan,et al.  Socio-hydrologic perspectives of the co-evolution of humans and water in the Tarim River basin, Western China: the Taiji-Tire model , 2013 .

[14]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[15]  C. Robinson.  Dynamical Systems: Stability, Symbolic Dynamics, and Chaos , 1994 .

[16]  John M. Anderies,et al.  On modeling human behavior and institutions in simple ecological economic systems. , 2000 .

[17]  J. Pittock,et al.  The energy-water nexus: managing the links between energy and water for a sustainable future. , 2010 .

[18]  D. Conway,et al.  Tracing the water-energy-food nexus: description, theory and practice , 2015 .

[19]  T. Shah,et al.  Groundwater socio-ecology and governance: a review of institutions and policies in selected countries , 2005 .

[20]  M. Qadir,et al.  Crop and irrigation management strategies for saline-sodic soils and waters aimed at environmentally sustainable agriculture. , 2003, The Science of the total environment.

[21]  Shamsuddin Shahid,et al.  Impact of climate change on regional irrigation water demand in Baojixia irrigation district of China , 2016, Mitigation and Adaptation Strategies for Global Change.

[22]  Pan Liu,et al.  Derivation of Aggregation-Based Joint Operating Rule Curves for Cascade Hydropower Reservoirs , 2011 .

[23]  C. Ringler,et al.  The nexus across water, energy, land and food (WELF): potential for improved resource use efficiency? , 2013 .

[24]  Population — Development — Environment , 1994 .

[25]  S. Jain,et al.  Basin perspectives on the Water–Energy–Food Security Nexus , 2013 .

[26]  Janaine Z. Coletti,et al.  A model of the socio‐hydrologic dynamics in a semiarid catchment: Isolating feedbacks in the coupled human‐hydrology system , 2015 .

[27]  Pan Liu,et al.  Optimal design of seasonal flood limited water levels and its application for the Three Gorges Reservoir , 2015 .

[28]  S. Sorooshian,et al.  Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data , 1996 .

[29]  G. Blöschl,et al.  Debates—Perspectives on socio‐hydrology: Capturing feedbacks between physical and social processes , 2015 .

[30]  D. E. Rheinheimer,et al.  Parameter uncertainty analysis of reservoir operating rules based on implicit stochastic optimization. , 2014 .

[31]  Günter Blöschl,et al.  Time scale interactions and the coevolution of humans and water , 2015 .

[32]  Li An,et al.  Annals of the Association of American Geographers Agent-based Modeling in Coupled Human and Natural Systems (chans): Lessons from a Comparative Analysis , 2022 .

[33]  J. Allan,et al.  Virtual Water - the Water, Food, and Trade Nexus. Useful Concept or Misleading Metaphor? , 2003 .

[34]  P. Krause,et al.  COMPARISON OF DIFFERENT EFFICIENCY CRITERIA FOR HYDROLOGICAL MODEL ASSESSMENT , 2005 .

[35]  Inas El-Gafy,et al.  System Dynamic Model for Crop Production, Water Footprint, and Virtual Water Nexus , 2014, Water Resources Management.

[36]  Pan Liu,et al.  Evaluating the marginal utility principle for long-term hydropower scheduling , 2015 .

[37]  Miao Wang,et al.  An agent-based model for risk-based flood incident management , 2011 .

[38]  D. Deryng,et al.  Climate and southern Africa's water–energy–food nexus , 2014 .

[39]  Murugesu Sivapalan,et al.  Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health : Murrumbidgee River Basin, Australia , 2014 .

[40]  M. Sivapalan,et al.  From channelization to restoration: Sociohydrologic modeling with changing community preferences in the Kissimmee River Basin, Florida , 2016 .

[41]  I. Rodríguez‐Iturbe,et al.  Socio‐hydrology: Use‐inspired water sustainability science for the Anthropocene , 2014 .

[42]  Samuel R. Schubert,et al.  Agricultural water management in water-starved countries: challenges and opportunities , 2003 .

[43]  Natali Hritonenko,et al.  Mathematical Modeling in Economics, Ecology and the Environment , 1999 .

[44]  G. Björklund,et al.  Regional Options for Addressing the Water, Energy and Food Nexus in Central Asia and the Aral Sea Basin , 2012 .

[45]  G. Blöschl,et al.  Socio‐hydrology: A new science of people and water , 2012 .

[46]  H. Venema,et al.  The Water-Energy-Food Security Nexus: Towards a practical planning and decision-support framework for landscape investment and risk management , 2013 .

[47]  G. Rasul,et al.  The nexus approach to water–energy–food security: an option for adaptation to climate change , 2016 .