Abstract:
Reservoir containing of fresh water is defined as artificial inland lake in terms of limnological terminology. In general, its research involves in both environmental hydraulics and aquatic ecosystem. Traditional research manners applied in those relevant disciplines mainly focus on individual area with less integrality and low efficiency of using modern technology: remote sensing. A novel remote-sensing-based technology: computational remote sensing technology is already proposed. In this field, the unique technique of it can automatically detect water surface shown in remote sensing imagery and discover water body hidden in the corresponding digital elevation model. It has successfully applied in the applications more than hydraulics. In this research, the attention is mainly drawn to seeking for an effective manner to quickly confirm a reliable elevation for the surface of clear water body inclusive of the effective and accurate manner of gaining data of other parameters of reservoir with geomorphological feature so as to quickly determine the distribution of depths of water body and apply it into diverse researches and applications associated with relevant disciplines such as environmental hydraulics. All relevant data measured and found from both fields and products of remote sensing can be seamlessly transferred and integrated with each other to model and perform any kind relevant task. Detailed illustrations of core topics combining with diverse deep theories and basic law of geometry are clearly given and pointed out for further interdisciplinary researches.
Keywords:
Environmental Hydraulics, Reservoir, Limnology, Aquatic ecosystem, Computational remote sensing technology
1 Introduction
Studying aquatic ecosystem of inland lake or river is always associated with its morphometric conditions. To understand and effectively model ecosystem of lakes, it is first necessary to determine their bathymetry and varying depths. Although bathymetry can be performed by echo-sounding equipment with GPS (geographical positioning systems) to determine each point’s exact position, such manner can be replaced by the fast-developing technique of technology in remote sensing.
1.1 About generation of computational remote sensing technology and its unique features
In 2014, author firstly discovered bathymetric data hidden DEM (Digital Elevation Model)[2-4] in the world. The implementation is very convenient to discover water body and accurate to calculate water surface area and volume of water body by means of the unique technique created by author, and such unique technique was proposed to name it computational remote sensing technology (CRST). Thus, by means of remote sensing technology, data transfer, any relevant research and application in the field of science and engineering can be directly performed, and dramatically reduce a lot of cost and save much experimental time. That is because the main data used in infrastructural applications are directly extracted from diverse products of remote sensing. Therefore, the quality of infrastructural applications is kept at high level of accurateness.
The attention to CRST is being paid globally. It has very unique and powerful ability to identify hidden phenomena and verify the confused facts through high scientific calculation by means of the data gained from divers sources and being shamelessly transferred into the same scientific and mathematical platform: one specific geolocation.
In contrary to CRST, the traditional GIS (Geographical Information System)–based approach has many inherent drawbacks. Although it is powerful in dealing with vector-based applications, it is very difficult in discovering hidden phenomena in the products of remote sensing, especially in verifying the outcomes. It often relies on limited- capacity vision to assess them. Furthermore, without scientific data being transferred, it is impossible for GIS–based techniques to deal with massive and complex cases existing in diverse natural sciences and engineering employed by a lot of professional knowledge and advanced engineering mathematics.
Accordingly, CRST was firstly created by author in 2009 and generated by high requirements of infrastructural applications. It is an advanced and comprehensive technology integrating knowledge of whole relevant disciplines, in other words all relevant scientists and engineers are able to work together under the frame of CRST. It is powerful, novel and always in the fast development. Some features of CRST are to be presented and demonstrated in the context of this research.
1.2 Literature Review Relating Depth and Other Parameters to Limnological Studies
In practice, the distribution of depths, water surface area and volume of water body and perimeter of lake or reservoir are very important parameters and data wildly applied in investigation and application of environmental-hydraulic science and engineering. Such application can be found from numerous practical areas such as that lake surface area is used to define fetch and estimate mixing depths in New Zealand lakes[5]; study of how wind, fetch, and water depth influence on the distribution of sediments[6];investigating chemical composition of lake: dissolved oxygen transports in lakes and relevant researches[7-10] inclusive of specific study case how fish lives on the necessary concentration of it[9], biochemical distribution and circulation[11, 12] ; thermal stratified lake[13-18] and organisms living in different thermal layers[19-21]; focus on lake hydrodynamics[22-26]; photosynthesis[27].
As seen from the technical reports from global massive researches, studying aquatic system of lake is a complex process employing massive interdisciplinary knowledge, such detailed researches are already defined into the scope of a specific discipline: limnology. The brief illustration of aquatic system of lake, calculating distribution of slopes in lake bottom and modelling temperature varying with depth is given in Figure1,Figure 2 and Figure 3 respectively for quickly understanding how much important desired data are.
An Effective Manner of Determining Clear Water Depths and Relevant Parameters for Complex Geometric Shape of Reservoir by Computational Remote Sensing Technology
Figure 1 Overall synopsis of limnological enviroment
Figure 2 distribution of slopes in water bottom
Figure 3 Vertical temperature profile with certain turbulent and molecular diffusion coefficient along depth
Author Carl Y. H. Jiang
Remote Sensing Geoscience and Engineering Consulting, Australia
