Hydrograph separation method based on a hydrological model and a chemical-statistical approach

There is a wide spectrum of different hydrograph separation methods including empirical, numerical, chemical and physical. Hydrograph separation studies to quantify the respective contributions of different runoff components has been performed based on the physically-based runoff formation ECOMAG model (Suchkova, Motovilov, 2019) and chemical monitoring data. Firstly, parameters of the ECOMAG model were calibrated against runoff measurements on the river catchment (area 1 360 km²) in European Russia. Besides, the water quality monitoring hydrochemical data on electrical conductivity, chemical oxygen demand, base cations (Na+, K+) as a tracers applied to precise of parameters of the physically-based model and reduce the uncertainty of estimated runoff components. Results show the subsurface (soil) water prevails in the total mean annual runoff (46%), surface runoff and groundwater flow have 22, and 32% respectively. The study demonstrates that data from regular monitoring of water quality (more than 100 samples per year) can be used as a reliable tracer for quantifying the genetic structure of river runoff.

The next step is to compare different approaches to the separation of the base flow, such as the trace-based method, the graphical method (straight line, Kudelin method), the filtering method (HYSEP), the digital filter (recursive digital filter). The results of two-component hydrographic separation show that the use of different separation methods is contradictory. For example, one or two parameters of the filtering and digital filter method were very sensitive. The advantages of automated methods are obvious and consist in using only daily flow data. Unfortunately, these empirical and numerical methods of hydrograph separating are not based on hydrological considerations and physical processes. Thus, the advantage of a physically-based method of separating hydrographs using a chemical-statistical approach as a reference provides the possibility of reliable assessment of water sources in runoff for planning water protection measures and water use.

This study was supported by the Russian Science Foundation project no. 22-27-00598, https://rscf.ru/en/project/22-27-00598/

References

Suchkova K.V., Motovilov Yu.G. Sensitivity Assessment of a Runoff Formation Model in the Mozhaisk Reservoir River Basin, Water Resources, 2019, Vol. 46, Suppl. 2, pp. S40–S50.