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.Additional key words: water management; calibration model; Key Performance Indicators.Correspondence should be addressed to P. Amparo López-Jiménez: palopez@upv.es
Abbreviations used: E (Nash-Sutcliffe coefficient); KPIF (key performance indicators for goodness of fit); O (observed values); P (simulated values); PBIAS (percent bias); RMSE (root mean square error); RN (random number); RRSE (root relative square error); SCADA (supervisory control and data acquisition); WDN (water distribution network).
Funding:The authors received no specific funding for this work.