Groundwater Level Simulation Using Soft Computing Methods with Emphasis on Major Meteorological Components

Water Resources Management - Precise estimation of groundwater level (GWL) might be of great importance for attaining sustainable development goals and integrated water resources management....     

An Optimized Combination of Mine Water Control,Treatment, Utilization,and Reinjection for Environmentally Sustainable Mining: A Case Study

This paper presents a case study of an optimized combination of mine water control, treatment, utilization and reinjection to achieve the zero discharge of mine water. Mine water has been considered a hazard and pollution source during underground mining, so most mining enterprises directly discharge mine water to the surface after simple treatment, resulting in a serious waste of water. Moreover, discharging a large amount of mine water can destroy the original groundwater balance and cause serious environmental problems, such as surface subsidence, water resource reduction and contamination, and adverse impacts on biodiversity. The Zhongguan iron mine is in the major groundwater source area of the Hundred Springs of Xingtai, which is an area with a high risk of potential subsidence. To optimize the balance between mining and groundwater resources, a series of engineering measures was adopted by the Zhongguan iron mine to realize mine water control, treatment, utilization, and reinjection. The installation of a closed grout curtain has greatly reduced the water yield of deep stopes in the mine; the effective sealing efficiency reaches 80%. Nanofiltration membrane separation was adopted to treat the highly mineralized mine water; the quality of the produced water meets China’s recommended class II groundwater standard. Low-grade heat energy from the mine water is collected and utilized through a water-source heat pump system. Finally, zero mine water discharge is realized through mine water reinjection. This research provides a beneficial reference for mines with similar geological and hydrogeological conditions to achieve environmentally sustainable mining.

     

Research on Crop Irrigation Schedules Under Deficit Irrigation—A Meta-analysis

Water Resources Management - Increasing water consumption in agriculture due to global climate change has posed considerable challenges to food security, thus improving the efficiency of water...     

Psychrophilic hydrogen production from petrochemical wastewater via anaerobic sequencing batch reactor: techno-economic assessment and kinetic modelling

Independent hydrogen production from petrochemical wastewater containing mono-ethylene glycol (MEG) via anaerobic sequencing batch reactor (ASBR) was extensively assessed under psychrophilic conditions (15–25 °C). A lab-scale ASBR was operated at pH of 5.50, and different organic loading rates (OLR) of 1.00, 1.67, 2.67, and 4.00 gCOD/L/d. The hydrogen yield (HY) progressed from 134.32 ± 10.79 to 189.09 ± 22.35 mL/gMEG_initial at increasing OLR from 1.00 to 4.00 gCOD/L/d. The maximum hydrogen content of 47.44 ± 3.60% was achieved at OLR of 4.0 gCOD/L/d, while methane content remained low (17.76 ± 1.27% at OLR of 1.0 gCOD/L/d). Kinetic studies using four different mathematical models were conducted to describe the ASBR performance. Furthermore, two batch-mode experiments were performed to optimize the nitrogen supplementation as a nutrient (C/N ratio), and assess the impact of salinity (as gNaCl/L) on hydrogen production. HY substantially dropped from 62.77 ± 4.09 to 6.02 ± 0.39 mL/gMEG_initial when C/N ratio was increased from 28.5 to 114.0. Besides, the results revealed that salinity up to 10.0 gNaCl/L has a relatively low inhibitory impact on hydrogen production. Eventually, the cost/benefit analysis showed that environmental and energy recovery revenues from ASBR were optimized at OLR of 4.0 gCOD/L/d (payback period of 7.13 yrs).     

A GIS plug-in for Bayesian belief networks: Towards a transparent software framework to assess and visualise uncertainties in ecosystem service mapping

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

A zirconium-free glaze system for sanitary ceramics with SiO2-CaCO3-TiO2 composite opacifier containing anatase: Effect of interface combination among SiO2, CaCO3 and TiO2

TiO₂ is an ideal substitute to ZrSiO₄ ceramic opacifier, yet it is limited to application because of the undesirable yellowing resulting from rutile formation. Herein, the SiO₂-CaCO₃-TiO₂ composite opacifier (Si-Ca-Ti) was constructed. The glaze used Si-Ca-Ti presents a superior opacification performance than ZrSiO₄ opacified glaze without causing yellowing, showing L*, a*, b* values of 94.81, -0.67 and 3.23. By comparison, the glaze using SiO₂, CaCO₃, and TiO₂ mixture shows lower opacification and yellowish surface with L* and b* values of 92.99 and 5.36. It is revealed that there is a close interface bonding among SiO₂, CaCO₃ and TiO₂ in Si-Ca-Ti, which promotes their combination reaction to generate opacification phase titanite and inhibit rutile formation when sintering, resulting in the white surface and opacification improvement of the glaze. This study proposes a green and efficient strategy to achieve white and highly opacified glaze for sanitary ceramics, exhibiting good application prospect.