The role of climate conditions and groundwater on baseflow separation in Urmia Lake Basin, Iran
Roya Narimani, Changhyun Jun, Somayeh Moghimi Nezhad, Sayed M. Bateni, Jinwook Lee, Jongjin Baik
Abstract
Urmia Lake basin, Iran. 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 (α) value and the approximation of groundwater recharge. 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 α. Moreover, Eckhardt’s method demonstrated a more reliable estimation of the ratio of groundwater recharge to streamflow.