vertical integration of spatial and hydraulic data for improved habitat

Hydro-ecology: Linking Hydrology and Aquatic Ecology (Proceedings of Workshop HW2 held at Birmingham, UK, July 1999). IAHS Publ. no. 266, 2001. 65

Vertical integration of spatial and hydraulic data for improved habitat modelling using geographic information systems

THOMAS B. HARDY & R. CRAIG ADDLEY Institute for Natural Systems Engineering, Utah State University, Logan, Utah, 84322-4110, USA

e-mai l : l i a r d v @ a a r o n . c e e . u s u . e d u

Abstract This paper highlights the application of several technologies for the spatial delineation and characterization of river ecosystems for evaluating fish habitat quantity and quality within geographic information systems (GIS). Multi-spectral digital imagery is utilized to delineate aquatic habitat types and riparian vegetation community distributions over entire basins. Derivation of high resolution digital terrain models for use in one-, two-, or three-dimensional hydraulic modelling from the integrated application of low elevation aerial photogrammetry with precision real-time GPS hydro-acoustic mapping of channel topographies, substrates, and two-dimensional velocity fields are demonstrated. The spatial characterization of the river using remotely sensed data and hydraulic modelling results based on the digital terrain models are vertically integrated in a GIS to derive habitat-based predictions in terms of quantity and quality. The use of a GIS for validation of modelling results is demonstrated for hydraulic model predictions and fish distributions relative to habitat quality and quantity. Key words habi ta t m o d e l l i n g ; h y d r a u l i c m o d e l l i n g ; G I S ; f i sher ies ; t w o - d i m e n s i o n a l habi ta t ; r ive rs ; spatial cha rac te r i za t ion ; in tegra t ion ; digi tal te r ra in m o d e l l i n g

INTRODUCTION

An important focus of the emerging state-of-the-art in ecohydraulics is the development, testing, and application of innovative methodologies, which can address the requirements of overlapping multidisciplinary components as well as meeting long-term monitoring and assessment needs. This focus also recognizes the necessity to address the efficacy of management decisions under adaptive management paradigms. Pragmatically, this dictates data acquisition and analyses at micro-habitat or reach levels and subsequent scaling to broader spatial and temporal domains (e.g. basin level) in a way that allows a wide away of discipline specific processes to be modelled. This includes the delineation of channel topography for use in hydrodynamlc modelling, water quality modelling, sediment transport modelling, aquatic resource utilization and habitat modelling, aquatic population dynamics, riparian community dynamics, and recreation. Furthermore, due to time and cost constraints at the application level, characterization of physical, chemical and biological processes are typically made at a relatively small number of specific locations during relatively short time periods. These data are then applied within the context of specific methodologies and the analytical or modelling results are used to infer process dynamics and their

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66 Thomas B. Hardy & R. Craig Addley

importance over much broader spatial and temporal scales. Although the assessment of these components has historically been undertaken from a narrowly defined or resource specific view, the current trend is toward more integrated data collection and linkages between simulation tools within GIS and integrated analysis systems. This trend in the use of GIS and integrated analysis systems also provides an expanded set of analytical capabilities to accomplish complex, integrated resource assessment and monitoring (Hardy, 1998). The following examples are used to illustrate the emerging multidisciplinary approach to river management which focuses on delineating the physical, chemical, and biological processes as well as their linkages within an assessment framework where both hydrology and hydraulic modelling represent the core of modelling the process linkages. The examples highlight the application of several emerging data acquisition techniques and GIS integrated analysis systems, that generate data suitable for reach specific process modelling, facilitate scaling of reach specific data to basin level domains, and address long-term monitoring data needs.

CHARACTERIZATION OF RIVERS—BASIN SCALE TO REACH SPECIFIC

Spatial characterizations at the basin scale

Comprehensive management of aquatic resources at the basin scale requires the adequate characterization of a spatial domain that encompasses many hundreds of kilometres or river throughout a particular basin, while requiring very specific detailed information at the study reach level. Furthermore, the specific data requirements for different disciplines often overlap at both these spatial scales. Advances in existing technologies can achieve the collection of quantitative data within water features (e.g. fish habitat) and out of water channel characteristics such as riparian community distribution. These technologies also provide data that are amendable for long-term monitoring requirements under adaptive management programmes for river basins (Goodwin & Hardy, 1999).

Satellite and airborne remote sensing platforms are now capable of acquiring digital imagery at high spatial and spectral resolution over extensive spatial domains (Baker, 1986; Muller et al, 1993; Milton et al, 1995; Hardy et al, 1994). Figure 1(a) represents the flight path of an airborne digital multi-spectral system utilized to obtain data at 0.5 m resolution from over 900 km of river during a one-week period. This GIS coverage is derived automatically from the on-board computer system, which interfaces with the remote sensing package and allows rectification of the flight path to a standardized map base. Figure 1(b) represents the GIS layer depicting the ground footprint of each successive image that has been linked to the map base so that resource managers and researchers can retrieve specific scenes. Figure 1 (c) illustrates a single 3-band false colour composite multi-spectral digital image that covers approximately 0.5 km of river channel. Figure 1(d) illustrates the GIS layer containing the linked image classification results for delineated riparian vegetation and fish habitat. The computer-based classification of these features is derived from the digital multi-spectral image. Basinwide results were utilized to establish the aerial extent and spatial locations for fish habitat and riparian community composition. This information

Vertical integration of spatial and hydraulic data for habitat modelling using GIS 67

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68 Thomas B. Hardy & R. CraigAddley

Fig. 1 (c) three-band false colour composite digital image of single scene; and (d) computer-based classification of vegetation and fish habitat features.


forms a set of base line or reference conditions for these features. The GIS system is now utilized for long-term monitoring of these features in support of the adaptive management programme within the basin and to aid in the selection of specific locations and spatial extent of intensive study reaches.

Spatial characterizations at the reach level

At each intensive study site, data collection efforts focus on a quantitative, process based, evaluation of flow, fish habitat utilization, long-term riparian community responses, sediment transport and other process-oriented studies. Data collection and modelling at intensive study sites include hydraulics, water quality, fish, and invertebrates. These are integrated in the GIS to aid in the extrapolation or linkage of intensive study site results to the broader spatial domain of the basin.

Although the previous illustrated characterizations at the basin level are important to understand broad spatial relationships, site-specific intensive characterizations are still required to understand physical, chemical, and ecological processes. For example, hydraulic modelling at the reach level is necessary to quantify and model the flow dependent linkages between such factors as sediment transport, water quality, and fish habitat. Advances in computer hardware and analytical software over the past decade provide access to a suite of advanced modelling capabilities. For many of these modelling systems, spatially accurate representations of the three-dimensional channel topographies are required at the reach level.

Soft-copy photogrammetry techniques using high resolution, low elevation (e.g. 360 m flying elevation) aerial photography can generate digital terrain models with less than 0.04 m horizontal and vertical spatial resolution for reaches in excess of several kilometres (Fig. 2). These techniques can provide acceptably accurate subsurface topographies under clear water conditions (Winterbottom & Gilvear, 1997; Gilvear et al, 1995; Hardy et al, 1994, Lane et al, 1999). Similar results can also be obtained under turbid water conditions with the integration of high precision GPS linked hydro-acoustic mapping of within water channel topographies (Fig. 2). These data are inherently GIS compatible and can be utilized for the quantitative detection of channel form changes in a spatially accurate quantitative manner desired by adaptive management and monitoring programmes. These data also provide a direct linkage between three-dimensional channel topographies and generation of accurate computational meshes necessary for use of higher-order hydraulic modelling approaches. Data in this form can also be used for a variety of physical, chemical and biological model development, calibration, verification, and validation efforts as part of adaptive management programmes. The GIS-based representation of the data also permits the overlay of other spatial layers such as vegetation, subsnate, or cover mapping which is important in the overall evaluation of aquatic, wildlife, and recreation resources.

VERTICAL INTEGRATION OF SPATIAL TOPOGRAPHY AND HABITAT MODELLING

The utilization of GIS as an integrative tool to organize component modelling results


provides the investigator with expanded opportunities for spatial representation and understanding of key physical, chemical, and ecological processes. The integration of the spatially explicit representation of the channel topography with hydraulic, water quality, and sediment dynamics allows the investigator to extend their analysis of the river mosaic to include physical and biotic metrics commonly used in landscape

Fig. 2 (a) High resolution low elevation aerial photograph created from scanned image and digital terrain model; (b) hydro-acoustic mapping track for bottom profding and three-dimensional velocity measurements.


ecology such as fractal dimension, dominance, contagion, habitat diversity, relative evenness, core areas, and edge effect. This has provided an important tool for the quantification of the linkage between the type, location, and extent of habitat features in river systems (Rinne, 1991; Freeman & Grossman, 1993; Fausch & White, 1981;

Fig. 2 (c) three-dimensional scene derived from draping aerial photograph on three-dimensional topography; and (d) three-dimensional channel topography with colour coded depth of flow.

Thomas B. Hardy & R. Craig Addley


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Fig. 3 (c) Example of GIS linked fish observations to hydraulic solutions; and (d) predicted vs observed fish locations based on a mechanistic based bioenergetic model for a stream reach.


Southall & Hubert, 1984; Addley, 1993; Stanford, 1994; Lobb & Orth, 1991; Rabeni & Jacobson, 1993; Bovee et al, 1994). These metrics describe various aspects of spatial heterogeneity in habitats that may be linked to functional responses of various species or community dynamics such as species dispersal, colonization potential, foraging efficiency, predator avoidance and species replacement (Li & Reynolds, 1994; Bain, 1995; Aadland, 1993; Jowett, 1992). The integration of spatial data and modelling results in GIS allows the use of statistical techniques useful in defining gradients of environmental variables. This includes depth and velocity, heterogeneity of habitat patch size, persistence of habitat types over ranges of discharges and other ecologically significant responses related to the spatial habitat mosaic (e.g. Jowett, 1992; Bain, 1995; Changeux, 1995; Barnard et al, 1995; Milner et al, 1995). These types of analyses and visual representation in GIS have the potential to expose previously unknown relationships between the habitat mosaic, community structure, and its function.

SPATIAL VALIDATION OF MODELLING RESULTS

Perhaps one of the more important advantages to the vertical integration of the spatial domain delineation, data collection efforts, and modelling results is the use of GIS to facilitate model(s) validation. Historical efforts, especially for fish habitat modelling have been restricted by the reliance on cross-sections for the hydraulic simulations of the hydrodynamic environment. The representation of the spatial domain in this manner has made habitat model validation particularly difficult since fish observations are rarely made coincident with the locations of cross-sections. The techniques described previously can now be utilized to integrate spatially accurate delineations of fish observation data within the GIS to allow better model validation (e.g. Guensch, 1999). The GIS can present a visual representation of the study reach in terms of its component spatial distributions of depth, velocity, substrate, cover, distance to features, water quality, etc., that permit a direct comparison between observed and predicted fish locations (Fig. 3). The GIS can then be utilized to derive a number of statistical characterizations to demonstrate the efficacy of the modelling approach(s). Validation results can then be utilized to better refine modelling approaches to observed patterns of fish habitat use in a quantitative manner. In many cases, the visualization of observed spatial distributions of target species within a study reach in light of component factors and unique combinations can lead to improved hypotheses of cause and effect and aid in the conceptual development of modelling approaches.

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vertical integration of spatial and hydraulic data for improved habitat

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