A Multiobjective Optimization Model for Lake Eutrophication Control

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Flood Frequency Analysis Using Copula with Mixed Marginal Distributions

In flood frequency analysis, a flood event is mainly characterized by peak flow, volume and duration. These three variables or characteristics of flood are random in nature and mutually correlated. In this article, a methodology is developed to derive bivariate joint distributions of the flood characteristics using the concept of copula considering a set of parametric and nonparametric marginal distributions for peak flow, volume and duration to mathematically model the correlated nature among them. A set of parametric distribution functions, and nonparametric methods based on kernel density estimation and orthonormal series are used to determine the marginal distribution functions for peak flow, volume and duration. In conventional method of flood frequency analysis, the marginal distribution functions of peak flow, volume and duration are assumed to follow some specific parametric distribution function. The concept of copula relaxes the restriction of traditional flood frequency analysis by selecting marginals from different families of probability distribution functions for flood characteristics. The present work performs a better selection of marginal distribution functions for flood characteristics by parametric and nonparametric estimation procedures, and demonstrates how the concept of copula may be used for establishing joint distribution function with mixed marginal distributions. The methodology is demonstrated with seventy years streamflow data of Red River at Grand Forks of North Dakota, US. The research work reported here is already submitted by the authors as a manuscript for review to Water Resources Research, AGU.https://ir.lib.uwo.ca/wrrr/1017/thumbnail.jp

A Web-based Flood Informat ion System

The web has become a major source of information for many water resources management tasks. With the growing popularity of the Internet, it provides a convenient, accessible way to provide the public with flood-related information. The present study focuses on web dissemination of information on flood risk and vulnerability to different types of users; general public, decision makers, and professionals. By gearing the display and representation of risk to each user, the information can be better understood and facilitate the flood management process. A user-friendly web-based flood information system is developed to provide flood risk, different components of flood vulnerability, exposures and hazards by postal codes. Geographic Information System (GIS) is used to facilitate the data processing, calculations and data management. It also provides spatial distribution of data, and the opportunity to ‘map’ vulnerability. Vulnerability refers to the susceptibility of an area to damage. Vulnerability, as considered in this study includes physical, economic, infrastructural, and social components. By identifying the areas of high risk and vulnerability, it is possible to make more informed flood management decisions. The present study has introduced an infrastructural component of risk which addresses the vulnerability of roads, railways, road bridges and critical structures (hospitals, schools, fire stations, etc.). All components of vulnerability are standardized and represented using a value between zero and one. The overall vulnerability for different postal code regions is determined by ‘averaging’ all components of vulnerability. The developed methodology for determining different components of vulnerability and risk is demonstrated for six major damage centers (i.e., London, St. Marys, Ingersoll, Mitchell, Stratford and Woodstock) in the Upper Thames River basin, Ontario, Canada. The relevant data are collected from Statistics Canada, Upper Thames River Conservation Authority, Canadian Homebuyers Guide, and the GIS databases at The University of Western Ontario.https://ir.lib.uwo.ca/wrrr/1018/thumbnail.jp

Physical, Economical, Infrastructural and Social Flood Risk -- Vulnerability Analyses in GIS

An exhaustive knowledge of flood risk, vulnerability and exposure in different spatial locations is essential for developing an effective flood mitigation strategy for a watershed. In the present study, a flood risk-vulnerability analysis is performed. All four components of flood vulnerability: (a) physical; (b) economic; (c) infrastructure and (d) social, are evaluated individually using a Geographic Information System (GIS) environment. The proposed methodology estimates the impact on infrastructure vulnerability due to inundation of critical facilities, emergency service stations, and road bridges. The components of vulnerability are combined to determine the overall vulnerability. The patterns of land use and soil type are considered as two major components of flood exposure. Flood hazard maps, overall vulnerability and exposure are used to finally compute the flood risk at different locations in the watershed. The proposed methodology is implemented to six major damage centers in the Upper Thames River watershed, located in south-western Ontario of Canada to assess the flood risk. A web-based information system is developed for systematic presentation of the flood risk, vulnerability and exposures by postal code regions or Forward Sortation Areas (FSAs). The system is designed to provide support for different users, i.e., general public, decision-makers and water management professionals. An interactive analysis tool is developed within the web-based information system to assist in evaluation of the flood risk in response to a change in land use pattern.https://ir.lib.uwo.ca/wrrr/1019/thumbnail.jp

Modeling and Simulation of Thermal Grill Illusion Using Neurophysiological Theory

The Thermal Grill Illusion (TGI) is a temperature-based perceptual illusion in which innocuous warm and cold stimuli evoke pain when applied simultaneously in a juxtaposed pattern. Based on neurophysiological and psychological findings, several theories have been proposed to explain the mechanisms behind TGI. However, the significance of an analytical model for TGI is not addressed in the literature. This study focuses on developing an analytical model based on the 'disinhibition theory' to predict the intensity of TGI pain. A psychophysical experiment on perceived TGI pain was first conducted, and then an analytical model was developed. The model's objective is to predict the neuronal activity of pain-sensitive HPC (Heat-Pinch-Cold) nerve fibers by leveraging the existing popular models of warm and cold receptors. An experimental thermal grill setup was used to provide five temperature differences between warm and cold grills (each repeated three times). Participants rated the perceived TGI pain sensation on a Likert scale of one to ten. Both the experimental results and the simulation showed a monotonically increasing relationship between temperature differences and the perceived TGI intensity. The proposed model bridges the gap between neurophysiological and psychophysical knowledge of TGI, potentially aiding thermal display designs

Satellite altimetry for Indian reservoirs

Satellite radar altimetry has immense potential for monitoring fresh surface water resources and predicting the intra-seasonal, seasonal, and inter-annual variability of inundated surface water over large river basins. As part of the Preparation for the Surface Water and Ocean Topography mission scheduled for launch in mid-2022, the present study aimed to evaluate the performance of radar altimetry over the inland water bodies of India. The Joint Altimetry Satellite Oceanography Network (Jason) and Satellite with ARgos and ALtiKa (SARAL/AltiKa) data were used to derive the water levels of 18 major reservoirs in India by incorporating the geophysical and propagation corrections into the radar range. In situ gauge data were used to evaluate the performance of the altimetry-derived water level time series from 2008 to 2019. The results showed a strong correlation between Jason-2 and in situ data with the determination coefficient (R2) and root mean squared error (RMSE) ranging from 0.96 to 0.99 and from 0.28 m to 1.62 m, respectively. The Jason-3 data had the highest correlation with the in situ observation (R2 = 0.99) and the lowest correlation (R2 = 0.82), with RMSE values ranging from 0.11 m to 1.18 m. With an R2 range of 0.93–0.99 and an RMSE range of 0.20–1.05 m, the SARAL/AltiKa mission presented greater accuracy than the Jason altimetry mission. The estimated water levels can be utilized in remote, inaccessible, or ungauged areas and in international transboundary rivers for water storage and river discharge estimations. However, the accuracy of remotely sensed data depends on such factors as along-track distance, water body area, and geographical and terrain conditions near water bodies.publishedVersio

Northward propagation of the Inter Tropical Convergence Zone and strengthening of Indian summer monsoon rainfall

Since 2002, there has been a clear increase in Indian summer monsoon rainfall (ISMR). We demonstrate that this increase is associated with a change in the dynamics of the Intertropical Convergence Zone (ITCZ). Using a recently‐released reanalysis product from 1980‐2016, we show that the ITCZ has strengthened and propagated northward since 2002. Analysis of the total energy‐budget reveals an increase in energy divergence and atmospheric diabatic heating, which is consistent with the changes in the ITCZ. Although global aerosol optical depth shows a significant positive trend during 1980‐2016, it has declined over many parts of India since 2002. We put forward the hypothesis that this is the driver of the changing characteristics of the ITCZ. Our results suggest that changes in the dynamics of the ITCZ, together with changes in the energy/moisture‐budget, are responsible for the strengthening of ISMR since 2002, consistent with the emergence of a greenhouse‐gas induced signal