RT Journal Article
T1 Persistent neural calibration for discharges modelling in drought-stressed catchments
A1 Pulido Calvo, Inmaculada
A1 Gutiérrez Estrada, Juan Carlos
A1 Sanz Fernández, Víctor
AB Cross-sector coordination between all water uses and the environmental flows is an essential target for achieving sustainable management in any hydrographic region. In this framework, a novel neural approach was developed and implemented, by the software ANNPI 1.0, to characterise and infer of the discharges regime in a specific basin using only a few attributes as independent variables. The calibration procedure is controlled by the Persistence Index (PI), which is function of a determined estimation lead-time, to facilitate the dynamic character of these simulations. A model validation was carried out in the Lower Guadiana Transboundary Basin, in the Southwest Iberian Peninsula, characterised by moderate and severe drought cyclical events. The best neural approaches included as input variable, between others, the Standardized Precipitation Index at a twelve-month scale SPI(12) that is indicator of hydrological drought, obtaining results statistically very good with determination coefficients higher to 0.77, Nash-Sutcliffe Efficiency coefficients higher to 0.75, Kling-Gupta Efficiency coefficients higher to 0.87 and Persistence Indexes higher to 0.60 in three of the four reservoirs analysed. These accuracy measures showed the ability of the software ANNPI 1.0 to reduce the naïve effect in the forecasting of streamflows time series and could therefore facilitate the development of decision-support systems to make reliable reservoir water balance simulations which will allow to assess future water availability to ensure the main ecosystem services.
PB Elsevier
SN 0957-4174
SN 1873-6793 (electrónico)
YR 2024
FD 2024-03
LK https://hdl.handle.net/10272/23714
UL https://hdl.handle.net/10272/23714
LA eng
NO Pulido-Calvo, I., Gutiérrez-Estrada, J.C., & Sanz-Fernández, V. (2024). Persistent neural calibration for discharges modelling in drought-stressed catchments. In Expert Systems with Applications (Vol. 249, p. 123785). Elsevier BV. https://doi.org/10.1016/j.eswa.2024.123785
NO This work was supported by VALAGUA project –Valorização ambiental e gestão integrada da água e dos habitats no Baixo Guadiana transfronteiriço– (POCTEP 0007_VALAGUA_5_P), cofunded by the European Regional Development Fund, ERDF, through the Interreg V-A Spain-Portugal program (POCTEP) 2014–2020.Funding for open access charge: Universidad de Huelva / CBUA.
DS Repositorio Institucional de la Universidad de Huelva
RD 31 may 2026