Distributed Lag Models for Hydrological Data

• Published in: Biometrics Vol. 69; no. 2; pp. 537 - 544
• Main Authors: Rushworth, Alastair M, Bowman, Adrian W, Brewer, Mark J, Langan, Simon J
• Format: Journal Article
• Language: English; French
• Published: United States Blackwell Publishers 01.06.2013; Blackwell Publishing Ltd; Wiley-Blackwell
• Subjects: Air pollution; BIOMETRIC PRACTICE; biometry; Biometry - methods; Biostatistics; Data Interpretation, Statistical; Distributed lag; hydrologic data; hydrologic models; Hydrology; Hydrology - statistics & numerical data; Mathematical models; Models, Statistical; P-splines; Rain; Rainfall; River flow; Rivers; Scotland; Time Factors; Time series; watershed hydrology; Scotland; Australia, Tasmania, Mountain R
• ISSN: 0006-341X; 1541-0420
• DOI: 10.1111/biom.12008

: The distributed lag model (DLM), used most prominently in air pollution studies, finds application wherever the effect of a covariate is delayed and distributed through time. We specify modified formulations of DLMs to provide computationally attractive, flexible varying‐coefficient models that are applicable in any setting in which lagged covariates are regressed on a time‐dependent response. We investigate the application of such models to rainfall and river flow and in particular their role in understanding the impact of hidden variables at work in river systems. We apply two models to data from a Scottish mountain river, and we fit to some simulated data to check the efficacy of our model approach. During heavy rainfall conditions, changes in the influence of rainfall on flow arise through a complex interaction between antecedent ground wetness and a time‐delay in rainfall. The models identify subtle changes in responsiveness to rainfall, particularly in the location of peak influence in the lag structure.