Modeling of aquifer vulnerability index using deep learning neural networks coupling with optimization algorithms.

A reliable assessment of the aquifer contamination vulnerability is essential for the conservation and management of groundwater resources. In this study, a recent technique in artificial intelligence modeling and computational optimization algorithms have been adopted to enhance the groundwater contamination vulnerability assessment. The original DRASTIC model (ODM) suffers from the inherited subjectivity and a lack of robustness to assess the final aquifer vulnerability to nitrate contamination. To overcome the drawbacks of the ODM, and to maximize the accuracy of the final contamination vulnerability index, two levels of modeling strategy were proposed. The first modeling strategy used particle swarm optimization (PSO) and differential evolution (DE) algorithms to determine the effective weights of DRASTIC parameters and to produce new indices of ODVI-PSO and ODVI-DE based on the ODM formula. For strategy-2, a deep learning neural networks (DLNN) model used two indices resulting from strategy-1 as the input data. The adjusted vulnerability index in strategy-2 using the DLNN model showed more superior performance compared to the other index models when it was validated for nitrate values. Study results affirmed the capability of the DLNN model in strategy-2 to extract the further information from ODVI-PSO and ODVI-DE indices. This research concluded that strategy-2 provided higher accuracy for modeling the aquifer contamination vulnerability in the study area and established the efficient applicability for the aquifer contamination vulnerability modeling.

Laboratory and field study on changes in water quality and increase in dissolved iron during riverbank filtration.

Changes in the water quality by the riverbank filtration (RBF) process were investigated in the field-scale demonstration sites. The overall water quality was improved by RBF, but Fe2+ concentration significantly increased in the riverbank-filtered water more than in the river water. This result would be caused by the interaction between the iron minerals and the river water in the aquifer and the influx of the hinterland groundwater into RBF wells. Dissolution properties of iron from the aquifer soils cored at the sites were evaluated through incubation experiment considering various values of redox potential (Eh), dissolved oxygen (DO), and hydrogen-ion concentration exponent (pH). These results presented that at the incubator with the final Eh of 470 mV, DO of 3.4, and pH of 4.53, the iron from the aquifer soil was most dissolved, and the pyrite and siderite contents in the aquifer soil decreased significantly from 11.5 to 6.22% and from 50.8 to 24.5%, respectively. Based on changes of ion concentrations (such as Fe2+, Fe3+, SO42- and NO3-) and iron species in the incubators, it was believed that pyrite and siderite minerals in the aquifer soils cause an increase in the Fe2+ concentration with the absence of DO and an increase in the Fe2+ and Fe3+ concentrations with the presence of DO. The dissolution rates of iron minerals into Fe2+ and Fe3+ were dependent on Eh, pH, and DO and were more sensitive to Eh and pH than DO. The results of this study can provide information on RBF site selection and its operation.

Applicability of a sharp-interface model for estimating steady-state salinity at pumping wells--validation against sand tank experiments.

A numerical sharp-interface model of saltwater and freshwater behavior was validated against experiments conducted in two small scale sand tanks. A simple algorithm was proposed to determine saltwater and freshwater withdrawal rates at a pumping well at which a total pumping rate was specified. Model estimates were compared with transient salinity breakthroughs and steady-state salinities of water extracted from pumping wells in the sand tanks. Experimental scenarios included various combinations of freshwater pumping and injection and saltwater pumping. The corresponding Nash-Sutcliffe model efficiency was 0.95, which showed that the agreement between observations and computed results was satisfactory.

Analytical design curves to maximize pumping or minimize injection in coastal aquifers.

Explicit algebraic equations are derived to determine approximate maximum pumping rates or minimum injection rates to limit sea water intrusion to a prespecified distance from the coastline. The equations are based on Strack's (1976) single-potential solution. The maximum pumping rates and minimum injection rates applied at wells with uniform spacing to control the inland movement of the fresh water-salt water interface in a coastal aquifer could be calculated from Strack's (1976) solution without the need of a numerical optimization algorithm. When wells are distributed in a simple fashion, the maximum intrusion location can be identified precisely for pumping cases and approximately for injection cases. For pumping cases, critical points are the limit of allowable salt water intrusion, whereas no such limit exists for injection cases. Once an application site is identified, a series of design curves for pumping and injection rates can be developed for arbitrary intrusion limits. When a user is interested only in the largest pumping rates associated with critical points, one design curve can yield complete information.

Evaluation of antifouling activity of eight commercially available organic chemicals against the early foulers marine bacteria and Ulva spores.

Environmental impacts caused by tin and copper based commercial antifouling (AF) paints were proved to be detrimental to aquatic ecosystems. Therefore, a search of environmental friendly AF compounds to be used in marine paint to protect the surface of maritime developmental structures from the unwanted biofouling is a burning issue of the present time. Commercially available eight organic chemicals--allyl isothiocyanate, beta-myrecene, cis-3-hexenyl acetate, citral, ethyl heptanoate, eugenol, methyl caproate, and octyl alcohol were evaluated forAF activities using both laboratory and field assays. The test chemicals were found to repel the target motile marine bacteria--Alteromonas marina, Bacillus atrophaeus, Roseobactergallaeciensis and Shewanella oneidensis and motile spores of the green alga, Ulva pertusa. The bacterial and Ulva spore repulsion activities of the test chemicals were measured by chemotaxis and agar diffusion methods respectively interestingly these test chemicals were less toxic to the test fouling species. The toxicity of the test chemicals was measured by using antibiotic assay disks against the bacteria and motility test against Ulva spores. Moreover, in field assay, all test chemicals showed a perfect performance ofAF activity showing no fouling during the experimental period of one year Such results and commercial as well as technical feasibility of the test chemicals firmly showed the possibility of using as alternatives of the existing toxic AF agents.