Hydrological transport modelAn hydrological transport model is a mathematical model used to simulate the flow of rivers, streams, groundwater movement or drainage front displacement, and calculate water quality parameters. These models generally came into use in the 1960s and 1970s when demand for numerical forecasting of water quality and drainage was driven by environmental legislation, and at a similar time widespread access to significant computer power became available.
Simulated annealingSimulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. For large numbers of local optima, SA can find the global optima. It is often used when the search space is discrete (for example the traveling salesman problem, the boolean satisfiability problem, protein structure prediction, and job-shop scheduling).
Surface runoffSurface runoff (also known as overland flow or terrestrial runoff) is the unconfined flow of water over the ground surface, in contrast to channel runoff (or stream flow). It occurs when excess rainwater, stormwater, meltwater, or other sources, can no longer sufficiently rapidly infiltrate in the soil. This can occur when the soil is saturated by water to its full capacity, and the rain arrives more quickly than the soil can absorb it. Surface runoff often occurs because impervious areas (such as roofs and pavement) do not allow water to soak into the ground.
Multi-objective optimizationMulti-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective is a type of vector optimization that has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives.
Mathematical optimizationMathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.
Soil biomantleThe soil biomantle can be described and defined in several ways. Most simply, the soil biomantle is the organic-rich bioturbated upper part of the soil, including the topsoil where most biota live, reproduce, die, and become assimilated. The biomantle is thus the upper zone of soil that is predominantly a product of organic activity and the area where bioturbation is a dominant process. Soil bioturbation consists predominantly of three subsets: faunalturbation (animal burrowings), floralturbation (root growth, tree-uprootings), and fungiturbation (mycelia growth).
Soil formationSoil formation, also known as pedogenesis, is the process of soil genesis as regulated by the effects of place, environment, and history. Biogeochemical processes act to both create and destroy order (anisotropy) within soils. These alterations lead to the development of layers, termed soil horizons, distinguished by differences in color, structure, texture, and chemistry. These features occur in patterns of soil type distribution, forming in response to differences in soil forming factors.
Genetic algorithmIn computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.
VertisolA vertisol is a Soil Order in the USDA soil taxonomy and a Reference Soil Group in the World Reference Base for Soil Resources (WRB). It is also defined in many other soil classification systems. In the Australian Soil Classification it is called vertosol. Vertisols have a high content of expansive clay minerals, many of them belonging to the montmorillonites that form deep cracks in drier seasons or years.
GleysolA gleysol is a wetland soil (hydric soil) that unless drained is saturated with groundwater for long enough to develop a characteristic colour pattern. The pattern is essentially made up of reddish, brownish, or yellowish colours at surfaces of soil particles and/or in the upper soil horizons mixed with greyish/blueish colours inside the peds and/or deeper in the soil. Gleysols are also known as Gleyzems, meadow soils, Aqu-suborders of Entisols, Inceptisols and Mollisols (USDA soil taxonomy), or as groundwater soils and hydro-morphic soils.
