Calibrating a flow model in an irrigation network: Case study in Alicante, Spain

Modesto Pérez-Sánchez,P Amparo López-Jiménez,Francisco J Sánchez-Romero,Helena M Ramos

doi:10.5424/sjar/2017151-10144

Abstract

The usefulness of models depends on their validation in a calibration process, ensuring that simulated flows and pressure values in any line are really occurring and, therefore, becoming a powerful decision tool for many aspects in the network management (i.e., selection of hydraulic machines in pumped systems, reduction of the installed power in operation, analysis of theoretical energy recovery). A new proposed method to assign consumptions patterns and to determine flows over time in irrigation networks is calibrated in the present research. As novelty, the present paper proposes a robust calibration strategy for flow assignment in lines, based on some key performance indicators (KPIF) coming from traditional hydrological models: Nash-Sutcliffe coefficient (non-dimensional index), root relative square error (error index) and percent bias (tendency index). The proposed strategy for calibration was applied to a real case in Alicante (Spain), with a goodness of fit considered as “very good” in many indicators. KPIF parameters observed present a satisfactory goodness of fit of the series, considering their repeatability. Average Nash-Sutcliffe coefficient value oscillated between 0.30 and 0.63, average percent bias values were below 10% in all the range, and average root relative square error values varied between 0.65 and 0.80.

Highlights

The management of water distribution networks (WDNs) is increasingly based on use of models as decision support tools, in performance and energy efficiency implications (Rodriguez-Diaz et al, 2010; Arbat et al, 2013; Cabrera et al, 2014)
A new proposed method to assign consumptions patterns and to determine flows over time in irrigation networks is calibrated in the present research
The present paper proposes a robust calibration strategy for flow assignment in lines, based on some key performance indicators (KPIF) coming from traditional hydrological models: Nash-Sutcliffe coefficient, root relative square error and percent bias

Summary

Introduction

The management of water distribution networks (WDNs) is increasingly based on use of models as decision support tools, in performance and energy efficiency implications (Rodriguez-Diaz et al, 2010; Arbat et al, 2013; Cabrera et al, 2014). Water management becomes more efficient when a deep knowledge of the network is done by modelling (Carravetta et al, 2012; Pardo et al, 2013; Cabrera et al, 2014; Butera & Balestra, 2015; Emec et al, 2015; Delgoda et al, 2016), increasing the sustainability of the whole system and decreasing the water footprint (Corominas, 2010; Ramos et al, 2010a,b) This knowledge of the network (mainly flows and pressure) allows the design of strategies to transform the WDNs in multipurpose systems (Choulot, 2010).

Methods

Results

Conclusion