Novel Organic Polymeric and Molecular Thin-Film Devices for Photonic Applications

The primary objective of this thesis is to explore the functionalities of new classes of novel organic materials and investigate their technological feasibilities for becoming novel photonic components. First, we discuss the unique polarization properties of optical chiral waveguides. Through a detailed experimental polarization analysis on planar waveguides, we show that eigenmodes in planar chiral-core waveguides are indeed elliptically polarized and demonstrate waveguides having modes with polarization eccentricity of 0.25, which agrees very well with recent theory. This is, to the best of our knowledge, the first experimental demonstration of the mode ellipticities of the chiral-core optical waveguides. In addition, we also examine organic magneto-optic materials. Verdet constants are measured using balanced homodyne detection, and we demonstrate organic materials with Verdet constants of 10.4 and 4.2 rad/T · m at 1300 nm and 1550 nm, respectively. Second, we present low-loss waveguides and microring resonators fabricated from perfluorocyclobutyl copolymer. Design, fabrication and characterization of these devices are addressed. We demonstrate straight waveguides with propagation losses of 0.3 dB/cm and 1.1 dB/cm for a buried channel and pedestal structures, respectively, and a microring resonator with a maximum extinction ratio of 4.87 dB, quality factor Q = 8554, and finesse F = 55. In addition, from a microring-loaded Mach-Zehnder interferometer, we demonstrate a modulation response width of 30 ps and a maximum modulation depth of 3.8 dB from an optical pump with a pulse duration of 100 fs and a pulse energy of 500 pJ when the signal wavelength is initially tuned close to one of the ring resonances. Finally, we investigate a highly efficient organic bulk heterojunction photodetector fabricated from a blend of P3HT and C60. The effect of multilayer thin film interference on the external quantum efficiency is discussed based on numerical modeling. We experimentally demonstrate an external quantum efficiency ηEQE=87±2% under an applied bias voltage V = −10 V, leading to an internal quantum efficiency ηIQE≈97%. These results show that the charge collection efficiency across the intervening energy barriers can indeed reach near 100% under a strong electric field

Evaluating the effectiveness of HOCl application on odor reduction and earthworm population growth during vermicomposting of food waste employing Eisenia fetida.

Vermicomposting has been recommended as an eco-friendly method to transform organic waste into nutrient resources with minimum energy input. However, odor and pest issues associated with this method limit the use of vermicomposting, especially in indoor conditions. This study evaluated the effectiveness of applying hypochlorous acid (HOCl) to deodorize the vermicomposting process and improve the breeding environment for earthworms (Eisenia fetida). The deodorization performance of HOCl was compared by measuring the amount of ammonia (NH3) and amine (R-NH2) released from the decaying process of two types of food waste: HOCl-treated (HTW) waste and non-treated waste (NTW). The total and individual weights of earthworms in the waste treated with HOCl was measured to evaluate the impact on earthworm reproduction after applying HOCl. The results showed that HOCl application could reduce NH3 by 40% and R-NH2 by 80%, and increase the earthworm population size and total weight by up to 29% and 92%, respectively, compared to the control group. These results suggest that HOCl application is potentially an efficient method to control the odor and to boost earthworm reproduction and thus facilitate vermicomposting for improved food waste treatment and environmental quality

Hydroclimatic Impact Assessment Using the SWAT Model in India—State of the Art Review

The Soil and Water Assessment Tool (SWAT) has been widely employed to assist with decision making and management planning for assessing and mitigating the impact of climate change. This model has gained popularity in India as the country is facing increasing water issues under projected climate changes. However, a systematic review of the literature that discusses the applicability of the model, the impact assessment process, and the interpretation of the modeling results in India remains lacking. We synthesized and reviewed 110 recent SWAT modeling studies (published from 2012 to 2022) that evaluated the impact of future climate change on water resources in India to identify research gaps that need to be filled to advance SWAT modeling practices for impact assessments. The review revealed that the SWAT model provided acceptable accuracy statistics in most (90%) of the studies reviewed. Half of these studies identified the base curve number (CN2) as the parameter to which the water balance is the most sensitive; thus, this parameter was included in the calibration process. The accuracy of SWAT modeling is closely associated with the accuracy of the weather data fed to the model. However, extreme events, including heavy storm events and severe droughts, were rarely considered in climate change impact assessments using the SWAT model. Most studies downscaled global-scale climate modeling outputs to local weather stations when applying the SWAT model using various methods, such as the delta change method, multiple linear regression method, gamma–gamma transformation, fitted histogram equalization, and quantile mapping. Further, most studies investigated the performance of the SWAT model before applying the model to quantify the future hydrological consequences of projected climate change in a subsequent scenario analysis. This review suggests that further evaluations of the characteristics and development processes of existing climate data products are needed to effectively consider extreme events in impact assessments. In addition, this review finds that climate change impact modeling has been improved with advances in climate projection preparation, including ensemble averaging, bias correction, and downscaling methods. This regional review of current SWAT modeling practices for climate change impact assessments can be used to create reliable future hydrological projections in India

Regionalization of a Rainfall-Runoff Model: Limitations and Potentials

Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization

Regionalization of a Rainfall-Runoff Model: Limitations and Potentials

Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization.Y

Investigating the applicability and assumptions of the regression relationship between flow discharge and nitrogen concentrations for load estimation

The regression relationship between water discharge rates and nutrient concentrations can provide a quick and straightforward way to estimate nutrient loads. However, recent studies indicated that the relationship might produce large biases in load estimates and, therefore, may not be applicable in certain types of cases. The goal of this study is to explore the theoretical reasons behind the selective applicability of the regression relationship between flow rates and nitrate + nitrite concentrations. For this study, we examined daily flow and nitrate + nitrite concentration observations made at the outlets of 22 watersheds monitored by the Heidelberg Tributary Loading Program (HTLP). The statistical relationship between the flow rates and concentrations was explored using regression equations offered by the LOAD ESTimator (LOADEST). Results demonstrated that the use of the regression equations provided nitrate + nitrite load estimates at acceptable accuracy levels (NSE≥0.35 and |PBIAS|≤30.0%) in 14 watersheds (64 % of 22 study watersheds). The regression relationships provided highly biased results at eight watersheds (36 %), implying their limited applicability. The heteroscedasticity of the residuals led to the high bias and resulting inaccurate regression, which was commonly found in watersheds where low flow had high nitrate + nitrite concentration variations. Conversely, the regression relationships provided acceptable accuracy for watersheds that had a relatively constant variance of the nitrate + nitrite concentrations. The results indicate that the homoscedasticity of residuals is the key assumption to be satisfied to estimate nitrate + nitrite loads from a statistical regression between flow discharge and nitrate + nitrite concentrations. The transport capacity (capacity-limited) concept implicitly assumed in the regression relationship between flow discharge and nitrate + nitrite concentrations is not always applicable, especially to agricultural areas in which nitrate + nitrite loads are highly variable depending on management practices (supply-limited). The findings suggest that the regression relationship should be carefully applied to areas in which intensive agricultural activities, including crop management and conservation practices, are implemented. Thus, the transport capacity concept is reasonably regarded to contribute to the homoscedasticity of residuals

Development of a Component-Based Modeling Framework for Agricultural Water-Resource Management

Because hydrologic responses of an agricultural watershed are influenced by many natural and man-made factors including pond/reservoir, management practices, and/or irrigation/drainage, strategies of hydrological modeling for the watershed must be case-dependent and thus carefully designed to effectively reflect their roles as critical hydrologic components in simulation processes. In this study, we propose a component-based modeling framework that accommodates a flexible modeling approach to consider a variety of hydrologic processes and management practices, especially irrigation-reservoir operation and paddy-farming practices, in watershed-scale modeling. The objectives of this study are twofold: to develop a COmponent-based Modeling Framework for Agricultural water-Resources Management (COMFARM) using an object-oriented programming technique, and to evaluate its applicability as a modeling tool to predict the responses of an agricultural watershed characterized with diverse land uses in a case study. COMFARM facilitates quick and easy development of watershed-specific hydrologic models by providing multiple interchangeable simulation routines for each hydrologic component considered. COMFARM is developed with the JAVA programming language, using Eclipse software. The framework developed in this study is applied to simulating hydrologic processes of the Seon-Am irrigation-district watershed consisting primarily of reservoir-irrigated rice paddies in South Korea. The application study clearly demonstrates the applicability of the framework as a convenient method to build models for hydrologic simulation of an agricultural watershed. The newly developed modeling framework, COMFARM is expected to serve as a useful tool in watershed management planning by allowing quick development of case-oriented analysis tools and evaluation of management scenarios customized to a specific watershed