Water-level recession characteristics in isolated pools within non-perennial streams. (August 2022)

• Record Type: Journal Article
• Authors: Yu, Songyan; Burrows, Ryan M.; Shanafield, Margaret; Kennard, Mark J.
• Is Part Of: Advances in water resources. Volume 166(2022)
• Publication Date: 2022-08
• Subjects: Aquatic refuges -- Flow intermittency -- Sub-surface flow -- Resistance -- Resilience -- Eastern Australia; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2022.104267
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: Water level in isolated pools connected to groundwater recedes at a constant rate. The recession rates vary considerably amongst cease-to-flow periods within one stream. The recession rates are significantly different between nearby streams. This study provides new knowledge of water level recession in hyporheic flow phase. Abstract: Persistent surface water pools within non-perennial streams provide critical refuges for freshwater species by facilitating their survival during extended dry periods. However, our understanding of how pool water levels recede is limited, hindering our ability to quantify and predict aquatic refuge persistence. We characterise variations in water-level recession rates based on one year of water-level measurements in five non-perennial streams. Most of the observations show that the water level recedes at a constant rate after streamflow ceases in our study streams, a rate often significantly higher than that during low-flow periods. However, water-level recession rates varied considerably amongst cease-to-flow periods within pools in the same non-perennial stream and between nearby streams. The constancy of water-level recession during a cease-to-flow period is applicable to other non-perennial streams, but a detailed understanding of the factors influencing recession rates is needed for prediction in ungauged streams and identifying persistent aquatic refuges across river networks.