An entropy theory for the spatiotemporal patterns of the environmental matrix in the nearshore parameters

Abstract

Understanding the temporal and spatial variability of sediment transport at regional scales is of great value for various purposes; however, relevant studies are still limited and have yielded inconsistent findings about the primary controls on regional temporal and spatial variability of bed load sediment transport rate (BLSTR). In this paper, sediment transport was investigated by a combination of spatiotemporal patterns and entropy theory modelling. Effort has been made in this paper to develop an entropy theory by assuming the time-averaged wave height as a random variable and applying the disorder power index to derive wave height distribution and rate of bed load sediment transport in coastal zones for ocean management planning. To analyze the spatio-temporal patterns, this study uses: A method that needs a disorder power index (entropy-power), uses the long time (1970–2015 monthly) data were retrieved of six large-scale monitoring networks located in the Makran coastal area (located in southeastern Iran), and shows the index suitability for hydrological/marine ecosystem components analyses using a coastal area case study, and studies flow velocity speed, wave and spatio-temporal patterns of BLSTR each of which is dependent on time and has an important role in terrestrial coastal/ocean studies. The combined performance of the above mentioned variables is difficult to describe (although their spatio-temporal variability is mostly meaningful) and, regarding this context, entropy-power index shows signals useful to assess coastal engineering issues and makes the understanding of wave height and sediment transport parameters interactions possible at nearshore zone scales. The advantage of using the entropy theory is that it permits quantification of uncertainty associated with concentration and determination of parameters in terms of specified information, such as mean concentration.