Qualitative reasoning about an ecological process: interpretation in hydroecology

Abstract Because of the frequent inefficiency of classical mathematical modelling to help the human operators in the supervision of biological processes, we present here a method based on qualitative reasoning concepts for simulating the interpretation of measurements, analyses, and observations, commonly done on aquatic ecosystems for management purposes. Once the domain variables are identified, their cause-effect dependences are represented as a directed graph. Each variable takes its value in a five-symbol set called quantity space (QS). These symbols … pp, p, m, f, ff…, correspond to expert qualifiers, like respectively: very low, low, medium, high, very high. A synthetic formalism is proposed to encode four types of knowledge rules: (1) translation of the numerical input values (i.e. measurements and results of analyses) into qualitative values; (2) translation of the linguistic observations into qualitative values; (3) formal calculus on QS, using six empirically defined operators, for propagating a top-down form of reasoning throughout the causal network, enabling the determination of the qualitative values of unmeasured variables from the values of their causes; (4) control of the execution of the reasoning. The software prototype, implemented in Prolog, has four main functions: short-term prediction of management parameters, causal explanation of the reasoning, state memorization, and choice of control variables in the causal network. These capabilities are illustrated by examples from an application enabling the interpretation of data in hydroecology. The relevance of a qualitative reasoning approach is emphasized, particularly for making empirical knowledge, typical of biological process control, operational.