Employing Constructed Wetlands to Sustainably Manage Nutrient-Bearing Water: A Review with an Emphasis on Soil Behavior and Effluent Nutrient Reduction

Constructed wetlands are engineered structures designed to simulate processes of natural wetlands to mitigate anthropogenic organic and inorganic materials to shelter soil and water resources. This review focuses on the global interest in constructed wetland application to sustain soil health and water quality and water abundance. Engineering criterion remains a function of nutrient chemistry and load with suitability factors including the local soil and hydrogeology constraints, climate, vegetation selection, the degree of required influent improvement, and reactor types and sizes. Future research needs to focus on: 1) reactor designs criteria, 2) the biology of the microbial community, 3) selection criteria for native vegetation, and 4) criteria to reapply treated water to foster land productivity, especially for region’s experiencing water deficiencies.

Tile-Drain and Denitrification Bioreactor Water Chemistry for a Soybean (<i>Glycine max</i>(L.) Merr.)-Corn (<i>Zea mays</i>L.) Rotation in East-Central Missouri (USA)

Nitrogen transport from agriculture production fields raises the specter of environmental degradation of freshwater resources. Our objectives were to document and evaluate nitrate-N, ammonium-N, phosphorus and other nutrients emanating from a 40-ha controlled subsurface irrigation drainage technology coupled in series with a denitrification bioreactor. The intent of the denitrification bioreactor is to create an environment for anoxic microbial populations to support denitrification. We monitored the tile-drainage effluent and denitrification bioreactor water chemistry under a corn-soybean rotation to estimate the nutrient concentrations and the competence of the denitrification bioreactor to foster denitrification. Nitrate-N bearing tile drainage effluents ranged from less than 1.5 to 109 mg NO3- -N/L, with the nitrate concentration differences attributed primarily to the: 1) timing of nitrogen fertilization for corn, 2) soil mineralization and residue decomposition, and 3) intense rainfall events. The denitrification bioreactor was highly effective in reducing drainage water nitrate-N concentrations providing the rate of water flow through the denitrification bioreactor permitted sufficient time for equilibrium to be attained for the nitrate reduction reactions. The nitrate-N concentrations entering the denitrification bioreactor ranged from 0.4 to 103 mg NO3-?-N/L in 2018, whereas the outlet nitrate concentrations typically ranged from 0.3 to 5.2 mg NO3- -N/L in 2018. Nitrate tile-drainage effluent concentrations in 2019 were marginal, given soybeans obtain nitrogen from biological nitrogen fixation. Nutrient uptake by corn reduced the soil nitrate leaching pool and created nitrogen-bearing biomass, features important for formulating best management practices.

Semi-Markov adaptive critic heuristics with application to airline revenue management

The adaptive critic heuristic has been a popular algorithm in reinforcement learning(RL) and approximate dynamic programming(ADP) alike.It is one of the ?rst RL and ADP algorithms.RL and ADP algorithms are particularly useful for solving Markov decision processes(MDPs) that suffer from the curses of dimensionality and modeling.Many real-world problems,however,tend to be semi-Markov decision processes(SMDPs) in which the time spent in each transition of the underlying Markov chains is itself a random variable.Unfortunately for the average reward case,unlike the discounted reward case,the MDP does not have an easy extension to the SMDP.Examples of SMDPs can be found in the area of supply chain management,maintenance management,and airline revenue management.In this paper,we propose an adaptive critic heuristic for the SMDP under the long-run average reward criterion.We present the convergence analysis of the algorithm which shows that under certain mild conditions,which can be ensured within a simulator,the algorithm converges to an optimal solution with probability 1.We test the algorithm extensively on a problem of airline revenue management in which the manager has to set prices for airline tickets over the booking horizon.The problem has a large scale,suffering from the curse of dimensionality,and hence it is difficult to solve it via classical methods of dynamic programming.Our numerical results are encouraging and show that the algorithm outperforms an existing heuristic used widely in the airline industry.