TY - JOUR
T1 - Water temperature forecasting for Spanish rivers by means of nonlinear mixed models
AU - Kamarianakis, Yiannis
AU - Ayuso, Sergio Velasco
AU - Rodríguez, Elena Cristóbal
AU - Velasco, Manuel Toro
N1 - Funding Information:
Yiannis Kamarianakis was partially supported by the National Science Foundation under Award DMS-1419593. The authors would like to thank the Spanish Environmental Department for providing the data, and three reviewers and the editor for their constructive comments. The analyzed datasets will be made freely available to download from the first author's website.
Publisher Copyright:
© 2016 The Authors.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - Study region: 43 rivers in Spain with measurement stations for air and water temperatures. Study focus: River water temperatures influence aquatic ecosystem dynamics. This work aims to develop transferable river temperature forecasting models, which are not confined to sites with historical measurements of air and water temperatures. For that purpose, we estimate nonlinear mixed models (NLMM), which are based on site-specific time-series models and account for seasonality and S-shaped air-to-water temperature associations. A detailed evaluation of the short-term forecasting performance of both NLMM and site-specific models is undertaken. Measurements from 31 measurement sites were used to estimate model parameters whereas data from 12 additional sites were used solely for the evaluation of NLMM. New hydrological insights for the region: Mixed models achieve levels of accuracy analogous to linear site-specific time-series regressions. Nonlinear site-specific models attain 1-day ahead forecasting accuracy close to 1 °C in terms of mean absolute error (MAE) and root mean square error (RMSE). Our results may facilitate adaptive management of freshwater resources in Spain in accordance with European water policy directives.
AB - Study region: 43 rivers in Spain with measurement stations for air and water temperatures. Study focus: River water temperatures influence aquatic ecosystem dynamics. This work aims to develop transferable river temperature forecasting models, which are not confined to sites with historical measurements of air and water temperatures. For that purpose, we estimate nonlinear mixed models (NLMM), which are based on site-specific time-series models and account for seasonality and S-shaped air-to-water temperature associations. A detailed evaluation of the short-term forecasting performance of both NLMM and site-specific models is undertaken. Measurements from 31 measurement sites were used to estimate model parameters whereas data from 12 additional sites were used solely for the evaluation of NLMM. New hydrological insights for the region: Mixed models achieve levels of accuracy analogous to linear site-specific time-series regressions. Nonlinear site-specific models attain 1-day ahead forecasting accuracy close to 1 °C in terms of mean absolute error (MAE) and root mean square error (RMSE). Our results may facilitate adaptive management of freshwater resources in Spain in accordance with European water policy directives.
KW - Predictive modeling
KW - River temperatures
KW - Spanish rivers
KW - Streams
KW - Thermal regimes
UR - http://www.scopus.com/inward/record.url?scp=84957837822&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84957837822&partnerID=8YFLogxK
U2 - 10.1016/j.ejrh.2016.01.003
DO - 10.1016/j.ejrh.2016.01.003
M3 - Article
AN - SCOPUS:84957837822
SN - 2214-5818
VL - 5
SP - 226
EP - 243
JO - Journal of Hydrology: Regional Studies
JF - Journal of Hydrology: Regional Studies
ER -