Combining metamodelling and stochastic dynamic programming for the design of reservoir release policies

Increasing worldwide water withdrawal for irrigation purposes requires a more efficient management of water resources and an accurate description of irrigation water demand. This paper, with the aim of thinking 'in blue and green water terms', proposes a new approach for the design of release policies in reservoir systems serving irrigation districts. It is based on the solution of an optimal control problem, where the dynamics of the irrigation demand is modelled through a metamodel, i.e. a simple model identified on the basis of the data produced by a distributed-parameter, conceptual model. The metamodel inherits the physical description of the distributed-parameter model and, at same time, is sufficiently simple to allow the solution of the optimal control problem with stochastic dynamic programming. The proposed approach is tested on a real-world case study, the management of the Lake Como system, for which it provides satisfactory results.

[1]  Daniele de Rigo,et al.  Neuro-dynamic programming for designing water reservoir network management policies , 2007 .

[2]  Davide Maggi,et al.  Coupled SVAT-groundwater model for water resources simulation in irrigated alluvial plains , 2004, Environ. Model. Softw..

[3]  Holger R. Maier,et al.  Water Distribution System Optimization Using Metamodels , 2005 .

[4]  Rodolfo Soncini-Sessa,et al.  Meta-model of an irrigation district distributed-parameter model , 2008 .

[5]  Timothy W. Simpson,et al.  Metamodels for Computer-based Engineering Design: Survey and recommendations , 2001, Engineering with Computers.

[6]  Malin Falkenmark.  The Ven Te Chow Memorial Lecture: Environment and Development: Urgent Need for a Water Perspective , 1991 .

[7]  Richard C. Peralta,et al.  Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm , 1999 .

[8]  Jack P. C. Kleijnen,et al.  A methodology for fitting and validating metamodels in simulation , 2000, Eur. J. Oper. Res..

[9]  Thomas E. Croley,et al.  Application of a distributed large basin runoff model in the Great Lakes basin , 2007 .

[10]  Michael Cantoni,et al.  Systems engineering for irrigation systems: Successes and challenges , 2005 .

[11]  S. Vedula,et al.  An Integrated Model for Optimal Reservoir Operation for Irrigation of Multiple Crops , 1996 .

[12]  Peter C. Young,et al.  Data-based mechanistic modelling of environmental, ecological, economic and engineering systems. , 1998 .

[13]  P. P. Mujumdar,et al.  Optimal reservoir operation for irrigation of multiple crops , 1992 .

[14]  Andrea Emilio Rizzoli,et al.  TwoLe: a software tool for planning and management of water reservoir networks , 1999 .

[15]  Andrea Castelletti,et al.  Water reservoir control under economic, social and environmental constraints , 2008, Autom..

[16]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[17]  B. Ortuani,et al.  Simulation supported scenario analysis for water resources planning: a case study in northern Italy. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.

[18]  Jacob W. Kijne,et al.  Unlocking the water potential of agriculture , 2003 .

[19]  Carlo Piccardi,et al.  Stochastic dynamic programming for reservoir optimal control: Dense discretization and inflow correlation assumption made possible by parallel computing , 1991 .

[20]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[21]  Raphael T. Haftka,et al.  Surrogate-based Analysis and Optimization , 2005 .

[22]  R. Young,et al.  AGNPS: A nonpoint-source pollution model for evaluating agricultural watersheds , 1989 .

[23]  Andrea Castelletti,et al.  A DSS for planning and managing water reservoir systems , 2003, Environ. Model. Softw..

[24]  Ning Wang,et al.  Review: Wireless sensors in agriculture and food industry-Recent development and future perspective , 2006 .

[25]  Andrea Castelletti,et al.  Integrated and Participatory Water Resources Management. Theory , 2007 .

[26]  J. T. Croton,et al.  WEC-C: a distributed, deterministic catchment model -- theory, formulation and testing , 2001, Environ. Model. Softw..

[27]  P. Young,et al.  Identification of non-linear stochastic systems by state dependent parameter estimation , 2001 .

[28]  Robert W. Blanning,et al.  The construction and implementation of metamodels , 1975 .

[29]  Alexander V. Lotov,et al.  Interactive Decision Maps: Approximation and Visualization of Pareto Frontier , 2004 .

[30]  Andrea Castelletti,et al.  Coupling real-time control and socio-economic issues in participatory river basin planning , 2007, Environ. Model. Softw..

[31]  Quirin Schiermeier,et al.  Water: A long dry summer , 2008, Nature.

[32]  Andrea Castelletti,et al.  Integration, participation and optimal control in water resources planning and management , 2008, Appl. Math. Comput..

[33]  J. Arnold,et al.  SWAT2000: current capabilities and research opportunities in applied watershed modelling , 2005 .