A new instream flow assessment method based on fuzzy habitat suitability and large scale river modelling

  • Authors:

  • S. Marsili-Libelli;E. Giusti;A. Nocita

  • Affiliations:

  • Department of Systems and Computers, University of Florence, Via S. Marta 3, 50139 Firenze, Italy;Department of Systems and Computers, University of Florence, Via S. Marta 3, 50139 Firenze, Italy;Museo di Storia Naturale, University of Florence, Via Romana 17, 50125 Firenze, Italy

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2013

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Abstract

This paper proposes an integrated tool for the assessment of fish habitat suitability based on synthetic hydraulic and water quality parameters. There are three innovative features in this study: (a) The proposed approach seeks to improve the capabilities of IFIM (Instream Flow Incremental Methodology) by extending the assessment to a larger spatial scale, which can be helpful for river managers in decision making. (b) The method is based on the suitability response of target species to hydraulic and water quality parameters through a fuzzy model, which is a novel application of a Takagi-Sugeno fuzzy logic. (c) The introduction of simulated river conditions enables the generation of a wide range of scenarios and the detection of potentially critical situations. After introducing the main algorithm, a sensitivity analysis is provided for the assessment of critical river segments and for ranking the influence of each parameter on the habitat. Then, a second algorithm is developed to produce an instream flow assessment method by determining the range of admissible flows that preserve the habitat suitability to a prescribed degree. The combined method is demonstrated with the application to two Italian rivers in the Tuscany region. In the case of the Arno River, the method highlights the habitat diversity for the two target species along its course, and the critical conditions that may develop during the summer low flow. In the case of the Serchio River, the analysis helps to assess habitat alterations likely to be caused by a planned diversion to feed a nearby lake. In both instances, with a minimum requirement of field data, this method shows its flexibility and seems better able to detect critical situations than the conventional IFIM approach.