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Large mouth bass juvenile abundance

Average SAV biomass SAV probability of presence

Water depth Turbidity Velocity

High turn-over between floating and submerged species

Using remote sensing to monitor past changes and assess future scenarios for waterways in the Sacramento-San Joaquin Delta, California USA

Maria J. Santos, Erin L. Hestir, Shruti Khanna and Susan L. Ustin

Historically, deltas have been extensively affected both by natural processes and human intervention

Understanding drivers, predicting impacts and optimizing

solutions to delta problems requires a holistic approach spanning many sectors, disciplines and fields of expertise

Deltas are ideal model systems to understand the effects of the interaction between social and ecological domains, as they face unprecedented disturbances and threats to their biological and ecological sustainability.

Introduction

The challenge for deltas is to meet the goals

of supporting biodiversity and ecosystem processes while also provisioning fresh water resources for

human use

The SSJ Delta has

undergone a process of land reclamation for

agriculture

http://web.stanford.edu/group/west/c gi-bin/projects/delta/map/index.html

HyMap

Spectrometer

Collected Jun 2004 to Jun 2008 3m pixel resolution

400-2500nm

126 spectral bands at 10nm sampling

~65 flightline mosaic

AVIRIS-ng

Collected Nov 2014 and Sep 2015 ~2.5 m pixel resolution

380-2510nm

481 spectral bands at 5nm sampling ~61 flightline mosaic

Extends the record:

1

Monitoring biological invasions and their cascading effects

Floating species occupy 1-8% of the waterways

classification accuracy>80% Khanna et al. 2011

Ustin et al. 2014

Emergent SAV Water

Water hyacinth Pennywort Water primrose Soil

Submerged species occupy 6-15% of the waterways

classification accuracy>90%

Santos et al. 2016

Conrad et al. 2016

Durand et al. 2016 Submerged (SAV) and Floating (FAV) vegetation

Submerged species disperse both radially and long distance

Submerged species have increased in recent years

2

Monitoring changes in turbidity and sediments

Submerged vegetation provides habitat for invasive fish who prey upon native

endangered fish species

4

Land use/land cover change

Submerged vegetation probability of presence is related to low turbidity and

velocity

The Sacramento-San Joaquin Delta

One of 25 global

hotspots for biodiversity

50 native species listed under the ESA

One of the most invaded ecosystems in the world 1

2

3

$5.3 billion economic output Declining sediment supply Saline intrusion eastward

Marshland reclaimed for agriculture

Highly vulnerable to climate variability & change

Cohen & Carlton 1998; Luoma et al. 2015

1 2 3 4 5

Sentinel-2 is a next generation satellite mission that will provide researchers with improved temporal (5 days revisit) and spatial (10m).

Monitoring inland water quality monitoring using the European Space Agency’s Spot-5 Take-5 (S5T5) experiment as a proxy for full Sentinel-2 data.

1

2

Ade and Hestir 2016

3

Modeling water temperature change

Lidar data used to predict the effects of tree removal on water temperature

Hestir et al. 2012

Greenberg et al. 2012

Deltas will be further affected both by ongoing land cover and climate changes.

Remote sensing offers an enormous potential to detect, predict and monitor the processes of change and the drivers of change in deltas and their social-ecological interactions

Conclusions

New missions and sensors expand upon the capacity exemplified in here: higher spatial, temporal and spectral resolution.

We show some examples of remote sensing applications to study biodiversity, ecology, water quality and land use/land cover changes, which benefits from existing data and sensors.

Thanks to Christiane Ade for water quality maps and to Jonathan Greenberg for the temperature maps

Acknowledgements

Funding from California Department of Boating and Waterways, NASA, California Department of Fish and Game, University of California Davis Bare Earth First Return Vegetation Height Tree Crown Map

0 2 4 6 8 10 12 14 16 18 20

0 20 40 60 80 100

Distance from water (m)

Height (m a.s.l.)

Levee height Levee vegetation height

Levee profile and tree detection

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