Ecological Indicators (Jun 2021)

Upstream flows drive the productivity of floodplain ecosystems in tropical Queensland

  • Christopher E. Ndehedehe,
  • Alex O. Onojeghuo,
  • Ben Stewart-Koster,
  • Stuart E. Bunn,
  • Vagner G. Ferreira

Journal volume & issue
Vol. 125
p. 107546

Abstract

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Rivers in tropical systems across the world are well known for their strong connections with floodplain wetlands. However, increased water needs and changing climate could drive water-management policy that leads to major changes in flow or surface water availability. These changes could have deleterious effects on ecological functions and ecosystem services provided by these freshwater ecosystems (e.g., groundwater recharge, food sources for fish, etc.). In this study, we introduce a cloud-based monitoring framework using multi-resolution satellite observations (2007-2020), historical surface inundation (1984-2015), and gauge data to better understand these connections in a large river catchment in tropical Queensland (Mitchell River catchment). A key driver and indicator of floodplain productivity, surface water inundation and aquatic biomass distribution respectively, are investigated to provide insight that underpins the prioritization of future surface water developments in this region. Results show that the characteristics of floodplain inundation; loss, persistence, gain and frequency, vary in time and space, and are driven by climate variability. The largest gain (7200 Ha) and persistence (8437 Ha) in total surface inundation were observed in the wet seasons during the periods of 2007-2019, respectively. In the downstream catchment, permanent water surface area was approximately 4.5% (of the total downstream region) compared to the upstream region (2.7%). There is a higher proportion of new permanent water features (16.8%) and new seasonal (30%) surface water classes in the upstream are in contrast to the downstream section (0.7% and 9.6%, respectively). Using multivariate statistics, floodplain productivity was linked to inter-annual changes in flow and rainfall. A partial least squares regression (PLSR) model shows upstream flows drive changes in total floodplain inundation (observed vs predicted, r=0.95,p=0.000). Flows and local rainfall accounted for approximately 60% (r=0.77,p=0.005) and 25% (r=0.50,p=0.120) of the variability in total floodplain inundation, respectively. Different PLSR modelling scenarios confirmed that upstream flows are primary drivers of floodplain inundation and substantial lost in total surface inundation could happen if flows are altered. Just as local rainfall has limited impact on total floodplain inundation (r=0.92,p=0.000; for model excluding local rainfall), aquatic plant biomass accumulations are also strongly associated with upstream flows (e.g., r = 0.82). Given the dependence of downstream water level (r = 0.89) and floodplain inundation on upstream flows, sustainable management of river flows in the Mitchell River is fundamentally important to floodplain productivity.

Keywords