Hybrid causal multivariate linear modelling (H_CMLM) method for the analysis of temporal rivers runoff

Abstract

This paper describes the joint development of two different methods for temporal riverś runoff assessment. This is performed through a hybrid approach by means of Multivariate General Linear Models (MGLM; inspired by MLR as a statistical method), and Causal Reasoning (CR; as non-linear ones). This innovative methodological approach, named Hybrid Causal Multivariate Linear Modelling (H-CMLM), is mainly aimed to empower the analysis of temporal hydrological records behaviour. H-CMLM has been successfully applied to three different Spanish basins (Adaja, Mijares and Porma) which were chosen due to their disparate features. Results were divided in quantitative and qualitative. Numerical results show a very high level of equivalence between the average value of temporal dependence provided by MLM module and the continuous behaviour of temporal dependence computed by CR module and visualized through Dependence Mitigation Graph (DMG). This high coherent outcome from both modules makes the analysis much more robust from a stochastic hydrology point of view. Values for average temporal dependence are very useful for the optimal dimensioning of hydraulic infrastructures like reservoirs. Furthermore, given the annual scale of the analysis, water planning and management of several water uses such as domestic water supply, agriculture, industrial demands, among others, can be highly assisted by this new H_C-MLM method.