B102-03
The Role of Lake to River Connectivity in Runoff Generation in Canada and Alaska
The Role of Lake to River Connectivity in Runoff Generation in Canada and Alaska
Tuesday, 15 December 2020: 11:36
Virtual
Abstract:
Canada has the world’s greatest density of lakes. Lakes are known to play a significant role in the region’s hydrology and are well regarded as sentinels of climate change as
any changes observed in lakes is a foreboding of land surface impacts to come in the future. The role of lakes in downstream runoff generation is still poorly understood, and
this is mainly due to the difficulty of quantifying the time varying connectivity between lakes and river channels, which is arguably the dominant mechanism of surface water
conveyance, especially in areas of high limnicity. In this work, we develop a method to quantify the role of time varying lake-to-channel connectivity on runoff prediction using a
novel lake storage estimation method and downstream hydrograph analysis. The method involves: 1) using a time series of surface water changes (Landsat based) to
characterize lake storage, and quantifying seasonal scale dynamics in lakes and river network connectivity; 2) identifying potential channel initiation points from the water
masks that define variable source areas (VSA); 3) delineating river networks by initiating the network with temporally and spatially varying VSAs and following topographic
contours downstream to the stream gauge and identifying their connectivity with lakes; 4) quantifying the runoff signature of lakes as visible from downstream hydrographs;
and finally 5) developing a network based model that accounts for lake-channel-connectivity to improve runoff prediction. In doing so, we seek to quantify the role of
surface connectivity in the Canadian surface hydrologic system. Our results confirm our hypothesis that changes in lake-to-channel connectivity significantly contributes to
surface runoff. This variability, which is observable from space, can be used to improve runoff prediction in ungauged basins.
any changes observed in lakes is a foreboding of land surface impacts to come in the future. The role of lakes in downstream runoff generation is still poorly understood, and
this is mainly due to the difficulty of quantifying the time varying connectivity between lakes and river channels, which is arguably the dominant mechanism of surface water
conveyance, especially in areas of high limnicity. In this work, we develop a method to quantify the role of time varying lake-to-channel connectivity on runoff prediction using a
novel lake storage estimation method and downstream hydrograph analysis. The method involves: 1) using a time series of surface water changes (Landsat based) to
characterize lake storage, and quantifying seasonal scale dynamics in lakes and river network connectivity; 2) identifying potential channel initiation points from the water
masks that define variable source areas (VSA); 3) delineating river networks by initiating the network with temporally and spatially varying VSAs and following topographic
contours downstream to the stream gauge and identifying their connectivity with lakes; 4) quantifying the runoff signature of lakes as visible from downstream hydrographs;
and finally 5) developing a network based model that accounts for lake-channel-connectivity to improve runoff prediction. In doing so, we seek to quantify the role of
surface connectivity in the Canadian surface hydrologic system. Our results confirm our hypothesis that changes in lake-to-channel connectivity significantly contributes to
surface runoff. This variability, which is observable from space, can be used to improve runoff prediction in ungauged basins.