Vlaswinkel & Rankey, 2003 Annual Review CSL Morphometrics and scaling of tidal creek networks, Florida and Bahamas: Implications for facies distribution.

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Vlaswinkel & Rankey, 2003 Annual Review CSL Morphometrics and scaling of tidal creek networks, Florida and Bahamas: Implications for facies distribution in geologic models Brigitte Vlaswinkel & Eugene Rankey Annual Review Meeting, Oct 6 th 2003

Vlaswinkel & Rankey, 2003 Annual Review CSL Statement of Problem Geologic Model Scale-up Size, shape, distribution of facies Well placement Simulation Recovery Volumetrics

Vlaswinkel & Rankey, 2003 Annual Review CSL Purposes Quantify spatio-temporal patterns in tidal creek networks, Bahamas and South Florida Interpret patterns in terms of processes Discuss how quantification of the ‘rules’ can be used as conceptual or practical tools for geologic models of analog systems FOCUS: Tidal creeks - significant/dominant in sediment transport

Vlaswinkel & Rankey, 2003 Annual Review CSL Major Findings Tidal creek lengths have exponential length- frequency distributions Creek network metrics are consistent among networks within each area Creek and network attributes are predictable (stochastically) and there are distinct scaling relations

Vlaswinkel & Rankey, 2003 Annual Review CSL Study Locations Miami “Three Creeks” “Big Sable Creek”

Vlaswinkel & Rankey, 2003 Annual Review CSL Digitized on IKONOS data or orthophoto quads Analyzed in GIS Tidal Creek Networks © SpaceImaging

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Networks 5 km Andros South Florida 2 km

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Networks 1 km Active networks Stabilized networks

Vlaswinkel & Rankey, 2003 Annual Review CSL Horton (1945) stream numbering – fluvial channel segments Tidal Creek Networks Order 3 Order 2 Order

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Segments Segment length by network – geographic context Exponential distribution Andros

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Segments Segment length by network – geographic context South Florida Exponential distributions (North) (South)

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Segments–Interpretation Greater length of inflection = more shorter creeks Exponential distribution: consistent with stochastic processes Inflections: change in probability distribution, processes

Vlaswinkel & Rankey, 2003 Annual Review CSL Geographical influence.. Change systematically from north to south more abundant short creeks to south (probabilistically) more later…. Tidal Creek Segments- Interpretation Andros

Vlaswinkel & Rankey, 2003 Annual Review CSL Hack (1957) noted patterns in numbers and lengths of fluvial channels…. Similar patterns present in tidal flat creeks Tidal Creek Networks Predictable… Andros South Florida

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Network Structure Entropy: measure of network disorder r ij = probability of transition from a stream of order i into one of order j. E = 0 indicates a perfectly ordered system (streams of order i flow only into streams of order i+1).

Vlaswinkel & Rankey, 2003 Annual Review CSL Tidal Creek Network Structure E = 0 E > 0 E = 0 suggests network elaboration only by headward extension

Vlaswinkel & Rankey, 2003 Annual Review CSL  Creek networks are less ordered towards the south… Tidal Creek Network Structure Andros

Vlaswinkel & Rankey, 2003 Annual Review CSL Network Structure & Segment Length Entropy (disorder) correlates with Abundance of short creeks More shorter streams Less order southward R 2 = 0.94 Andros

Vlaswinkel & Rankey, 2003 Annual Review CSL Historical Changes Creeks extending headwards, new creeks forming First-order creeks most dynamic Andros

Vlaswinkel & Rankey, 2003 Annual Review CSL Facies and Creeks Qualitatively, ‘creeks control facies distribution’ Quantitative relation….

Vlaswinkel & Rankey, 2003 Annual Review CSL Conclusions Creek lengths of tidal flats on Andros Island and in South Florida have exponential length-frequency distributions Creek network metrics are consistent among networks within each area These results suggest that creek and network attributes are predictable (stochastically) and that there are distinct scaling relations