• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.185-185
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• 2019

Sustaining future wheat production is challenged by anthropogenically forced climate warming and drying led by increased concentration of greenhouse gases all around the globe. Warming stresses, originating from the elevated $CO_2$ concentration, are continuously reported to have negative impacts on wheat growth and yield. Yet, elevated $CO_2$ concentration, despite being disparagingly blamed for promoting warming, is also associated with a phenomenon called $CO_2$ enrichment; in which wheat yield can improve due to the enhanced photosynthesis rates and less water loss through transpiration. The conflicting nature of climate warming and $CO_2$ enrichment and their interplay can have specific implications under different environments. It is established form the field and simulation studies that the two contrasting phenomena would act severely in their own respect under arid and semi-arid environments. Wheat is a dietary staple for masses in Pakistan. The country's wheat production system is under constant stress to produce more from irrigated agricultural lands, primarily lying under arid to semi-arid environments, to meet the rapidly growing domestic needs. This work comprehensively examines the warming impacts over wheat yield and water productivity (WP), with and without the inclusion of $CO_2$ enrichment, under semi-arid environment of Punjab which is the largest agricultural province of Pakistan. Future wheat yields and WPs were simulated by FAO developed AquaCrop model v 5.0. The model was run using the bias-correction climate change projections up to 2080 under two representative concentration pathways (RCP) scenarios: 4.5 and 8.5. Wheat yield and WPs decreased without considering the $CO_2$ enrichment effects owing to the elevated irrigation demands and accelerated evapotranspiration rates. The results suggested that $CO_2$ enrichment could help maintain the current yield and WPs levels during the 2030s (2021-2050); however, it might not withhold the negative climate warming impacts during the 2060s (2051-2080). Furthermore, 10 - 20 day backward shift in sowing dates could also help ease the constraints imposed by climate warming over wheat yields and WPs. Although, $CO_2$ enrichment showed promises to counteract the adverse climate warming impacts but the interactions between climate warming and $CO_2$ concentrations were quite uncertain and required further examination.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1037-1051
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• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Journal of the Korean Applied Science and Technology
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• v.39 no.1
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• pp.34-41
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• 2022

As the use of chemical products increases in daily life, the removal of dye waste has also emerged as an important environmental issue. This dye waste can be decomposed using a photocatalyst, and the photocatalyst can be synthesized very cost-effectively by using the sol-gel technology. The sol-gel technology is not only very useful for nanoscale film formation, but also can simply form multilayer structures. Using a multiple spin coating method, in this study, a ZnO film with a multilayered structure (3 layers, 5 layers) was formed by using zinc oxide (ZnO), which is effective in decomposing various dyes. For performance comparison, a ZnO film having a single layer structure by a single spin coating method was prepared as a control. Structural and elemental analysis of ZnO film was performed using an X-ray diffraction analyzer and an energy dispersive X-ray spectrometer. A nanowire-like surface morphology could be observed through a scanning electron microscope. Additionally, UV-Vis spectrophotometer was used to measure the absorbance of UV light. The ZnO film with a five-layer structure degraded the simulated methylene blue by 49% more than the ZnO film with a single-layer structure. In conclusion, it was found that ZnO having a multilayered structure is useful as a photocatalyst that decomposes methylene blue dye more effectively.