Hana Moidu
UC Berkeley
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ABSTRACT:
Intermittent streams comprise much of the global river network, and are expected to become more prevalent as a result of climate change. Characterizing the expansion and contraction of intermittency in stream networks, and understanding how sensitive these dynamics are to climatic variability, is critical for predicting the trajectory of hydrologic regimes in a changing climate. Here, we consider the spatial patterns of stream intermittency, focusing on wetted channel conditions at the end of the dry season, and identify land cover, physiographic, and climate variables that influence surface water presence and variability across years. We trained statistical models with wetted channel mapping data from 25 streams over 7 years to predict both the spatial and interannual variability of the wetted channel network. The data used to train these models is published here.
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Created: April 28, 2021, 5:16 a.m.
Authors: Moidu, Hana · Mariska Obedzinski · Stephanie Carlson · Theodore Grantham
ABSTRACT:
Intermittent streams comprise much of the global river network, and are expected to become more prevalent as a result of climate change. Characterizing the expansion and contraction of intermittency in stream networks, and understanding how sensitive these dynamics are to climatic variability, is critical for predicting the trajectory of hydrologic regimes in a changing climate. Here, we consider the spatial patterns of stream intermittency, focusing on wetted channel conditions at the end of the dry season, and identify land cover, physiographic, and climate variables that influence surface water presence and variability across years. We trained statistical models with wetted channel mapping data from 25 streams over 7 years to predict both the spatial and interannual variability of the wetted channel network. The data used to train these models is published here.