Using stable isotopes and hydrometric data to estimate snowmelt contributions to the Bow River, Alberta, Canada

摘要

The province of Alberta (Canada) relies mainly on river water for domestic, industrial and irrigation uses. The Bow River Basin (BRB) provides a large component of this water in southern Alberta. A strong economy in Alberta driven by the oil and gas industry has intensified population growth and agricultural activity in the region. The population growth has put severe strains on the currently available water resources, particularly since Rocky Mountain streamflows have also been declining over the past 100 years. The objective of this ongoing study is to determine whether stable isotope techniques are a suitable tool to assess the contribution of snowmelt to runoff in the Bow River in order to facilitate runoff predictions. The study area stretches from the headwaters of the Bow River in the Rocky Mountains to Calgary, approximately 250 km downstream. Show (2007) and river water samples (2004-2007) were collected weekly to monthly. The isotopic composition of the snowpack in the headwater regions and the isotopic composition of runoff in headwater creeks and streams were determined and compared with each other. The δ~(18)O values of the 2007 snowpack varied between -24.0 %o and -18.0 ‰ with lower values occurring in January and February. Maximum snow water equivalents (SWE) and snow depths were reached in late April with average δ~(18)O values of -21.8 ‰, while summer precipitation was characterized by δ~(18)O values around -17 ‰. The mean δ~(18)O value of the Bow River in the headwater region was -20.0 ‰ (2004-2007). Since the δ ~(18)O value of the Bow River is within 2 ‰ of the δ~(18)O value of the snowpack, it indicates that snowmelt is a major source of water contributing to riverine flow either through direct runoff or via groundwater discharge. A better understanding of how snowmelt contributes to riverine runoff will help with water management strategies and facilitate runoff predictions under future climate change scenarios predicting less snowpack and earlier snowmelt.