A remote sensing approach to determine environmental flows for wetlands of the Lower Darling River, New South Wales, Australia

Shaikh, Mohamedmaroof; Green, D.; Cross, Hardy

doi:10.1080/014311601300176024

Cited by 9 publications

(6 citation statements)

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“…Previous studies to determine the aerial extent of flooding have commonly involved optical satellite image analysis (Usachev, 1985;Walker et al, 1986;Townsend and Walsh, 1998;Overton et al, 1999;Shaikh et al, 2001;Sheng et al, 2001;Frazier et al, 2003), radar remote sensing (Townsend and Walsh, 1998) or an integration of remote sensing and GIS (Brivio et al, 2002). These methods have proved to be very useful and economical for large-area flood analysis.…”

Section: Mapping Flood Inundationmentioning

confidence: 97%

“…This project was commissioned to create such a model to provide input into the management decision process. Previous studies on modelling river flow and inundation have been undertaken for wetlands on the Darling River in New South Wales (Shaikh et al, 2001) and floodplains on Roanoke River in North Carolina (Townsend and Walsh, 1998) and the River Murray in Australia (Overton et al, 1999;Frazier et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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Modelling floodplain inundation on a regulated river: integrating GIS, remote sensing and hydrological models

Overton

2005

River Res. Applic.

101

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The lower River Murray in South Australia is highly regulated through weirs and water extraction for irrigation. Management of the river for environmental purposes requires an understanding of the extent of floodplain inundation from various flows and weir manipulations. This study aimed to produce a floodplain inundation model for the 600 km long and 1-5 km wide portion of the River Murray in South Australia from the New South Wales border to Lake Alexandrina. The model was developed using a Geographical Information System (GIS), remote sensing and hydrological modelling. Flood inundation extents were monitored from Landsat satellite imagery for a range of flows, interpolated to model flood growth patterns and linked to a hydrological model of the river. The resulting model can be analysed for flows ranging from minimum flow to a 1-in-13-year flood event for any month and weir configuration and has been independently tested using aerial photography to an accuracy of approximately 15% underestimate. The results have proven the approach for determining flood inundation over a large area at approximately one-tenth of the cost of detailed elevation and hydrodynamic modelling. The GIS model allows prediction of impacts on infrastructure, wetlands and floodplain vegetation, allowing quantitative analysis of flood extent to be used as an input into the management decision process.

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Section: Mapping Flood Inundationmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Modelling floodplain inundation on a regulated river: integrating GIS, remote sensing and hydrological models

Overton

2005

River Res. Applic.

101

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“…Information on river hydrology is required in the form of hydrographic time series data characterizing current and natural flow regimes at various points along the river (Galat and Lipkin 2000), including ecologically important low and peak flows. As many river ecosystems are characterized by low-gradient, spatially heterogeneous floodplain habitats, hydrographic flow regimes need to be translated into a spatial extent of inundation (Shaikh et al 2001, Overton 2005, Powell et al 2008. River ecosystems need to be classified and mapped based on their species composition and structure (Cunningham et al 2009), and their natural flow regime needs to be quantified (Verhoeven et al 2008, Merritt et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Ecohydrological and socioeconomic integration for the operational management of environmental flows

Bryan

Higgins

Overton

et al. 2013

Ecological Applications

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Abstract. Investment in and operation of flow control infrastructure such as dams, weirs, and regulators can help increase both the health of regulated river ecosystems and the social values derived from them. This requires high-quality and high-resolution spatiotemporal ecohydrological and socioeconomic information. We developed such an information base for integrated environmental flow management in the River Murray in South Australia (SA). A hydrological model was used to identify spatiotemporal inundation dynamics. River ecosystems were classified and mapped as ecohydrological units. Ecological response models were developed to link three aspects of environmental flows (flood duration, timing, and interflood period) to the health responses of 16 ecological components at various life stages. Potential infrastructure investments (flow control regulators and irrigation pump relocation) were located by interpreting LiDAR elevation data, digital orthophotography, and wetland mapping information; and infrastructure costs were quantified using engineering cost models. Social values were quantified at a coarse scale as total economic value based on a national survey of willingness-to-pay for four key ecological assets; and at a local scale using mapped ecosystem service values. This information was integrated using a constrained, nonlinear, mixed-integer, compromise programming optimization model and solved using a stochastic Tabu search algorithm. We tested the model uncertainty and sensitivity using 390 Monte Carlo model runs at varying weights of ecological health vs. social values. Integrating ecohydrological and socioeconomic information identified environmental flow management regimes that efficiently achieved both ecological and social objectives. Using an ecologically weighted efficient and socially weighted efficient scenario, we illustrated model outputs including a suite of cost-effective infrastructure investments and an operational plan for new and existing flow control structures including dam releases, weir height manipulation, and regulator operation on a monthly time step. Both the investments and management regimes differed substantially between the two scenarios, suggesting that the choice of weightings on ecological and social objectives is important. This demonstrates the benefit of integrating highquality and high-resolution spatiotemporal ecohydrological and socioeconomic information for guiding the investment in and operational management of environmental flows.

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“…For those images, the normalised difference water index (Xu, 2006) and unsupervised classification were used to differentiate between inundated and non-inundated pixels. These methods have been successfully used to map inundation across Australian floodplains using Landsat satellite imagery (Frazier and Page, 2000;Shaikh et al, 2001;Rayburg and Thoms, 2009;Thomas et al, 2010). The results from both methods were combined to estimate the area of floodplain inundation.…”

Section: Delineation Of Adaptive Phasesmentioning

confidence: 99%

Adaptive cycles of floodplain vegetation response to flooding and drying

Thapa¹,

Thoms²,

Parsons³

et al. 2016

Earth Surf. Dynam.

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Abstract.Flooding is a key driver of floodplain vegetation productivity. Adaptive cycles provide a model for examining the productivity of semi-arid floodplain vegetation in response to hydrology. We examined the response of vegetation productivity (measured as NDVI) through a hypothesised adaptive cycle to determine whether the cycle repeats over time and how it is affected by differently sized flood events. The area of floodplain inundation was associated with an adaptive cycle that repeated in four flood events through the following phases: wetting (exploitation phase), wet (conservation phase), drying (release phase) and dry (reorganisation phase). Vegetation productivity responses corresponded to these phases. The area and quality of floodplain vegetation productivity followed the hypothesised pattern of higher-quality vegetation vigour in the wetting and wet phases, lower vigour in the drying phase and lowest vigour in the dry phase. There were more transitions between NDVI classes in the wet phase, which was dominated by two-way transitions. Overall, the wetting, wet and drying phases were dominated by smaller-probability class changes, whereas in the dry phase, higher-probability class changes were more prominent. Although the four flood events exhibited an adaptive cycle the duration of the adaptive-cycle phases, and the nature of vegetation productivity response, differed with the character of the flood event. Vegetation response in two of the adaptive-cycle phases -the release and reorganisation phases -were as hypothesised, but in the exploitation and conservation phases, changes in vegetation productivity were more dynamic. The character of vegetation response through the adaptive cycle also indicates that semi-arid floodplain vegetation productivity is more vulnerable to changing state during the conservation and release phases and not during the exploitation and reorganisation phases as resilience theory suggests. Overall, the adaptive cycle represents a new model to improve our understanding of the complexity of change in semi-arid floodplain vegetation productivity through cycles of flooding and drying. Changes in vegetation productivity could initiate structural changes in floodplain vegetation communities, with commensurate influences on floodplain sediment dynamics.

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A remote sensing approach to determine environmental flows for wetlands of the Lower Darling River, New South Wales, Australia

Cited by 9 publications

References 0 publications

Modelling floodplain inundation on a regulated river: integrating GIS, remote sensing and hydrological models

Modelling floodplain inundation on a regulated river: integrating GIS, remote sensing and hydrological models

Ecohydrological and socioeconomic integration for the operational management of environmental flows

Adaptive cycles of floodplain vegetation response to flooding and drying

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