The role of climate conditions and groundwater on baseflow separation in Urmia Lake Basin, Iran

Study region: Urmia Lake basin, Iran. Study focus: An accurate estimation of baseflow provides useful information for various aspects of water resources management. Baseflow estimation is subject to many uncertainties because it cannot be measured directly. This study aims to quantify the influence of uncertainties on the baseflow separation in the Urmia Lake basin, Iran. Herein, long-term observational data was used to evaluate the stability and reliability of baseflow estimation. Seven baseflow separation methods were compared with the mass balance filter (MBF) as a reference method. Here, two indicators including the average annual baseflow coefficient (BFC) and the baseflow index (BFI) were used to assess the impact of climate condition on baseflow separation. In addition, we investigated two sources of uncertainty in the digital filter methods: the recession constant (& alpha;) value and the approximation of groundwater recharge. New hydrological insights for the region: Eckhardt's method exhibited a better estimate of the baseflow during both wet and dry years, and exhibited acceptable accuracy during peak flows, even during multiple events. The results of uncertainties among the filter methods revealed that the Lynie & Holick (LH) algorithm and Eckhardt's method were more sensitive to the amount of & alpha;. Moreover, Eckhardt's method demonstrated a more reliable estimation of the ratio of groundwater recharge to streamflow.

Automated summary

This study focuses on accurately estimating baseflow in the Urmia Lake basin, Iran, which is important for water resources management. The study evaluates the stability and reliability of baseflow estimation using long-term observational data. Seven baseflow separation methods are compared, and two indicators are used to assess the impact of climate conditions on baseflow separation. Additionally, the uncertainty sources in digital filter methods are investigated.