Theoretical and Methodological Approaches to Assessing the Natural Resource Potential of Agricultural Landscapes Using the Harrington’s Desirability Function

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Authors: Aidos Omarov, Zhumakhan Mustafayev, Irina Skorintseva, Gulnar ALDAZHANOVA, Amanzhol Kuderin, Askhat Toletayev
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Abstract

The aim of this study is to develop theoretical and methodological approaches to assessing the natural resource potential of agricultural landscapes, which includes climatic, soil, land, biological, and water resources. The research methodology was based on the materialist theory of scientific knowledge, methods of mathematical modeling of natural conditions and processes, as well as the use of the Harrington’s desirability function. Based on the study, a model of a system of dimensionless criteria and evaluation indicators has been developed, which are used to determine the natural resource potential of agricultural landscapes (a composite indicator). On this basis, the scale of coded values for specific indicators and the Harrington’s desirability scale are calculated (complex indicator). The proposed mathematical model is a generalized Harrington’s desirability function, which varies from 0 to 1 and is divided into seven subranges (scales): (0–0.17) – catastrophic; (0.17–0.27) – very poor; (0.27–0.37) – poor; (0.37–0.50) – satisfactory; (0.50–0.63) – average; (0.63–0.83) – good; and (0.83–1.00) – very good. These gradations correspond to the general approaches used in assessing the natural resource potential of agricultural landscapes. The proposed methodology and algorithm for assessing the natural resource potential of agricultural landscapes make it possible to determine the degree of desirability according to the value of its function, and can be used for predicting the state of the natural environment.

Fields of Study & Subjects

Soil and Land Suitability Analysis Sustainable Agricultural Systems Analysis Geography and Environmental Studies

Publication details

Journal / source
Preprints.org
Publication date
27 January 2026
Document type
Preprint