Identification of temporal consistency in rating curve data: Bidirectional Reach (BReach)

Abstract

In this paper, a methodology is developed to identify consistency of rating curve data based on a quality analysis of model results. This methodology, called Bidirectional Reach (BReach), evaluates results of a rating curve model with randomly sampled parameter sets in each observation. The combination of a parameter set and an observation is classified as nonacceptable if the deviation between the accompanying model result and the measurement exceeds observational uncertainty. Based on this classification, conditions for satisfactory behavior of a model in a sequence of observations are defined. Subsequently, a parameter set is evaluated in a data point by assessing the span for which it behaves satisfactory in the direction of the previous (or following) chronologically sorted observations. This is repeated for all sampled parameter sets and results are aggregated by indicating the endpoint of the largest span, called the maximum left (right) reach. This temporal reach should not be confused with a spatial reach (indicating a part of a river). The same procedure is followed for each data point and for different definitions of satisfactory behavior. Results of this analysis enable the detection of changes in data consistency. The methodology is validated with observed data and various synthetic stage‐discharge data sets and proves to be a robust technique to investigate temporal consistency of rating curve data. It provides satisfying results despite of low data availability, errors in the estimated observational uncertainty, and a rating curve model that is known to cover only a limited part of the observations.

Consistency assessment of rating curve data in various locations using Bidirectional Reach (BReach)

“…For instance, errors in hydrological or hydraulic model results that are caused by changes in a river's situation can (if they lead to inconsistency of the rating curve data as well) be avoided by using known consistent stage-discharge time periods for model evaluation. Methods to detect and describe this temporal (in)consistency have been studied by several authors (see Van Eerdenbrugh et al, 2016, for a more extensive review). McMillan et al (2010) assumed that changes in rating curve behavior are mainly caused by floods and that periods in between are consistent.…”

“…Therefore, Van Eerdenbrugh et al (2016) have developed a methodology to enable the detection of consistent periods in stage-discharge data. It is called Bidirectional Reach (BReach) and considers a period to be consistent if no consecutive and systematic deviations from a current situation occur that exceed observational uncertainty.…”

“…Despite the methodology's ability to account for a limited model deficiency (Sect. 2.2.4 and Van Eerdenbrugh et al, 2016), this additionally advocates a well-considered choice of a model structure.…”

“…Van Eerdenbrugh et al (2016) discuss that in the methods mentioned above, the assessment of temporary or permanent changes of the hydraulic regime requires assumptions or decisions that more or less influence eventual results. Moreover, most of the methods start from a definitive choice of a rating curve model and comprehend an assessment of its parameters distribution.…”

“…In Van Eerdenbrugh et al (2016), one observed and several synthetic data sets are used to evaluate and test the robustness of the methodology. The methodology was shown to perform well, with robust results despite decreased data availability, erroneous estimations of measurement uncertainty and even a partially deficient rating curve model.…”