A Multi-disciplinary Modelling Approach for Discharge Reconstruction in Irrigation Canals: The Canale Emiliano Romagnolo (Northern Italy) Case Study

Agriculture is the biggest consumer of water in the world, and therefore, in order to mitigate the effects of climate change, and consequently water scarcity, it is important to reduce irrigation water losses and to improve the poor collection of hydraulic status data. Therefore, efficiency has to be increased, and the regulation and control flow should be implemented. Hydraulic modelling represents a strategic tool for the reconstruction of the missing hydraulic data. This paper proposes a methodology for the unmeasured offtake and flowing discharge estimation along the open-canal Canale Emiliano Romagnolo (CER), which is one of the major irrigation infrastructures in Northern Italy. The “multi-disciplinary approach” that was adopted refers to agronomic and hydraulic aspects. The tools that were used are the IRRINET management Decisional Support System (DSS) and the SIC2 (Simulation and Integration of Control for Canals) hydraulic software. Firstly, the methodology was developed and tested on a Pilot Segment (PS), characterized by a simple geometry and a quite significant historical hydraulic data availability. Then, it was applied on an Extended Segment (ES) of a more complex geometry and hydraulic functioning. Moreover, the available hydraulic data are scarce. The combination of these aspects represents a crucial issue in the irrigation networks in general.

[1]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[2]  J. B. Dent,et al.  Systems Simulation in Agriculture , 1979, Springer Netherlands.

[3]  J. Cunge,et al.  Practical aspects of computational river hydraulics , 1980 .

[4]  Steve Harrison,et al.  Validation of agricultural expert systems , 1991 .

[5]  David G. Mayer,et al.  Regression of real-world data on model output: An appropriate overall test of validity , 1994 .

[6]  Pierre Legendre,et al.  Evaluation of simple statistical criteria to qualify a simulation , 1996 .

[7]  A. Battilani,et al.  INFLUENCE OF WATER TABLE, IRRIGATION AND ROOTSTOCK ON TRANSPIRATION RATE AND FRUIT GROWTH OF PEACH TREES , 1997 .

[8]  Luis S. Pereira,et al.  Regional analysis of irrigation water requirements using kriging: Application to potato crop (Solanum tuberosum L.) at Tras-os-Montes , 1999 .

[9]  D. Renault.  Aggregated hydraulic sensitivity indicators for irrigation system behavior , 2000 .

[10]  Subhash C. Jain,et al.  Open-Channel Flow , 2000 .

[11]  Larry J. Weber,et al.  Submergence Effects on Discharge Coefficients for Rectangular Orifices , 2000 .

[12]  Narendra Singh Raghuwanshi,et al.  Application of unsteady flow hydraulic-model to a large and complex irrigation system , 2002 .

[13]  G. Hoogenboom,et al.  Determination of spatial water requirements at county and regional levels using crop models and GIS: An example for the State of Parana, Brazil , 2002 .

[14]  Luciano Mateos,et al.  SIMIS: the FAO decision support system for irrigation scheme management , 2002 .

[15]  A. Battilani,et al.  WATER TABLE LEVEL EFFECT ON THE WATER BALANCE AND YIELD OF TWO PEAR ROOTSTOCK , 2004 .

[16]  A. Battilani.  REGULATED DEFICIT OF IRRIGATION (RDI) EFFECTS ON GROWTH AND YIELD OF PLUM TREE , 2004 .

[17]  R. Barker,et al.  Evolution of irrigation in south and southeast Asia , 2004 .

[18]  Jacques-Eric Bergez,et al.  Estimating irrigation demand for water management on a regional scale: I. ADEAUMIS, a simulation platform based on bio-decisional modelling and spatial information , 2004 .

[19]  Xavier Litrico,et al.  Experimental validation of a methodology to control irrigation canals based on Saint-Venant equations ☆ , 2005 .

[20]  Paul Dourish,et al.  Implications for design , 2006, CHI.

[21]  Luis Orlindo Tedeschi,et al.  Assessment of the adequacy of mathematical models , 2006 .

[22]  Iven M. Y. Mareels,et al.  Control of Large-Scale Irrigation Networks , 2007, Proceedings of the IEEE.

[23]  Carlo Giupponi,et al.  Decision Support Systems for implementing the European Water Framework Directive: The MULINO approach , 2007, Environ. Model. Softw..

[24]  Shaohua Chen,et al.  Absolute poverty measures for the developing world, 1981–2004 , 2007, Proceedings of the National Academy of Sciences.

[25]  Adrian Laycock.  Irrigation Systems: Design, Planning and Construction , 2007 .

[26]  Paul Jeffrey,et al.  On the appropriateness of public participation in Integrated Water Resources Management: some grounded insights from the Levant , 2008 .

[27]  Narendra Singh Raghuwanshi,et al.  Development and Application of Hydraulic Simulation Model for Irrigation Canal Network , 2008 .

[28]  Erik Weyer,et al.  Control design for an irrigation channel from physical data , 2008 .

[29]  Eric Viala,et al.  Water for food, water for life a comprehensive assessment of water management in agriculture , 2008 .

[30]  Yuanjie Li,et al.  Irrigated Area Maps and Statistics of India Using Remote Sensing and National Statistics , 2009, Remote. Sens..

[31]  Guy Fipps,et al.  Developing a modeling tool for flow profiling in irrigation distribution networks , 2009 .

[32]  F. Molle.  Water scarcity, prices and quotas: a review of evidence on irrigation volumetric pricing , 2009 .

[33]  P. Troch,et al.  Determination of the Manning roughness coefficient influenced by vegetation in the river Aa and Biebrza river , 2009 .

[34]  Luciano Mateos,et al.  Simulation of automatic control of an irrigation canal , 2010 .

[35]  Dennis Wichelns,et al.  Investing in water for food, ecosystems, and livelihoods: an overview of the Comprehensive Assessment of Water Management in Agriculture. , 2010 .

[36]  Laurence Smith,et al.  Agricultural water management and poverty linkages , 2010 .

[37]  Jacques Sau,et al.  Sequential Monte Carlo hydraulic state estimation of an irrigation canal , 2010 .

[38]  Muhammad Latif,et al.  Improving Operational Performance of Farmers Managed Distributary Canal using SIC Hydraulic Model , 2010 .

[39]  Malin Falkenmark,et al.  Managing water in agriculture for food production and other ecosystem services , 2010 .

[40]  Jacques Sau,et al.  Data assimilation for real-time estimation of hydraulic states and unmeasured perturbations in a 1D hydrodynamic model , 2009, Math. Comput. Simul..

[41]  Volumetric water control in a large-scale open canal irrigation system with many smallholders: The case of Chancay-Lambayeque in Peru , 2011 .

[42]  Roberto Genovesi,et al.  IRRINET: Large Scale DSS Application for On-farm Irrigation Scheduling , 2013 .

[43]  Stefania Munaretto,et al.  Irrigation water governance in practice: the case of the Canale Emiliano Romagnolo district, Italy , 2014 .

[44]  Mohamed F. Sauida.  Calibration of submerged multi-sluice gates , 2014 .

[45]  M. Todorović,et al.  Improving water-efficient irrigation: Prospects and difficulties of innovative practices , 2014 .

[46]  N. Rajaratnam,et al.  Solutions to Rectangular Sluice Gate Flow Problems , 2015 .

[47]  Cagatay Tanriverdi,et al.  Assessment of Irrigation Schemes in Turkey: Cropping Intensity, Irrigation Intensity and Water Use , 2015 .

[48]  João Luiz Becker,et al.  Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model , 2015 .

[49]  Sakila Haque.  Impact of Irrigation on Cropping Intensity and Potentiality of Groundwater in Murshidabad District of West Bengal, India , 2015 .

[50]  Ramchand Oad,et al.  Implementation of a Decision Support System for Improving Irrigation Water Delivery: Case Study , 2015 .

[51]  N. St-Pierre.  Comparison of model predictions with measurements: A novel model-assessment method. , 2016, Journal of dairy science.

[52]  Sufen Wang,et al.  An Improved Analytic Hierarchy Process Method for the evaluation of agricultural water management in irrigation districts of north China , 2017 .

[53]  D. Masseroni,et al.  Prospects for Improving Gravity-Fed Surface Irrigation Systems in Mediterranean European Contexts , 2017 .

[54]  Ping Guo,et al.  A flexible decision support system for irrigation scheduling in an irrigation district in China , 2017 .

[55]  Pierre-Olivier Malaterre,et al.  Discharge estimation under uncertainty using variational methods with application to the full Saint‐Venant hydraulic network model , 2017 .

[56]  Qingfeng Miao,et al.  Basin Irrigation Design with Multi-Criteria Analysis Focusing on Water Saving and Economic Returns: Application to Wheat in Hetao, Yellow River Basin , 2018 .

[57]  Franck Mercier,et al.  River discharge estimation under uncertainty from synthetic SWOT-type observations using variational data assimilation , 2018 .