Climate change could aggravate periodic and chronic shortfalls of water, particularly in arid and semi-arid areas of the world (IPCC, 2001). Climate change is likely to accelerate the global hydrological cycle, with increase in temperature, changes in precipitation patterns, and evapotranspiration affecting the water quantity and quality, water availability and demands. The various components of a surface water resources system affected by climate change may include the water availability, irrigation demands, water quality, hydropower generation, ground water recharge, soil moisture etc. It is prudent to examine the anticipated impacts of climate change on these different components individually or combinedly with a view to developing responses to minimize the climate change induced risk in water resources systems. Assessment of climate change impacts on water resources essentially involves downscaling the projections of climatic variables (e.g., temperature, humidity, mean sea level pressure etc.) to hydrologic variables (e.g., precipitation and streamflow), at regional scale. Statistical downscaling methods are generally used in the hydrological impact assessment studies for downscaling climate projections provided by the General Circulation Models (GCMs). GCMs are climate models designed to simulate time series of climate variables globally, accounting for the greenhouse gases in the atmosphere. The statistical techniques used to bridge the spatial and temporal resolution gaps between what GCMs are currently able to provide and what impact assessment studies require are called as statistical downscaling methods. Generally, these methods involve deriving empirical relationships that transform large-scale simulations of climate variables (referred as the predictors) provided by a GCM to regional scale hydrologic variables (referred as the predictands). This general methodology is characterized by various uncertainties such as GCM and scenario uncertainty, uncertainty due to initial conditions of the GCMs, uncertainty due to downscaling methods, uncertainty due to hydrological model used for impact assessment and uncertainty resulting from multiple stake holders in a water resources system. The research reported in this thesis contributes towards (i) development of methodologies for climate change impact assessment of various components of a water resources system, such as water quality, water availability, irrigation and reservoir operation, and (ii) quantification of GCM and scenario uncertainties in hydrologic impacts of climate change. Further, an integrated reservoir operation model is developed to derive optimal operating policies under the projected scenarios of water availability, irrigation water demands, and water quality due to climate change accounting for various sources of uncertainties. Hydropower generation is also one of the objectives in the reservoir operation. The possible climate change impact on river water quality is initially analyzed with respect to hypothetical scenarios of temperature and streamflow, which are affected by changes in precipitation and air temperature respectively. These possible hypothetical scenarios are constructed for the streamflow and river water temperature based on recent changes in the observed data. The water quality response is simulated, both for the present conditions and for conditions resulting from the hypothetical scenarios, using the water quality simulation model, QUAL2K. A Fuzzy Waste Load Allocation Model (FWLAM) is used as a river water quality management model to derive optimal treatment levels for the dischargers in response to the hypothetical scenarios of streamflow and water temperature. The scenarios considered for possible changes in air temperature (+1 oC and +2 oC) and streamflow (-0%, -10%, -20%) resulted in a substantial decrease in the Dissolved Oxygen (DO) levels, increase in Biochemical Oxygen Demand (BOD) and river water temperature for the case study of the Tunga-Bhadra River, India. The river water quality indicators are analyzed for the hypothetical scenarios when the BOD of the effluent discharges is at safe permissible level set by Pollution Control Boards (PCBs). A significant impairment in the water quality is observed for the case study, under the hypothetical scenarios considered. A multi-variable statistical downscaling model based on Canonical Correlation Analysis (CCA) is then developed to downscale future projections of hydro¬meteorological variables to be used in the impact assessment study of river water quality. The CCA downscaling model is used to relate the surface-based observations and atmospheric variables to obtain the simultaneous projection of hydrometeorological variables. Statistical relationships in terms of canonical regression equations are obtained for each of the hydro-meteorological predictands using the reanalysis data and surface observations. The reanalysis data provided by National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used for the purpose. The regression equations are applied to the simulated GCM output to model future projections of hydro-meteorological predictands. An advantage of the CCA methodology in the context of downscaling is that the relationships between climate variables and the surface hydrologic variables are simultaneously expressed, by retaining the explained variance between the two sets. The CCA method is used to model the monthly hydro-meteorological variables in the Tunga-Bhadra river basin for water quality impact assessment study. A modeling framework of risk assessment is developed to integrate the hydro¬meteorological projections downscaled from CCA model with a river water quality management model to quantify the future expected risk of low water quality under climate change. A Multiple Logistic Regression (MLR) is used to quantify the risk of Low Water Quality (LWQ) corresponding to a threshold DO level, by considering the streamflow and water temperature as explanatory variables. An Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is adopted to evaluate the future fractional removal policies for each of the dischargers by including the predicted future risk levels. The hydro-meteorological projections of streamflow, air temperature, relative humidity and wind speed are modeled using MIROC 3.2 GCM simulations with A1B scenario. The river water temperature is modeled by using an analytical temperature model that includes the downscaled hydro-meteorological variables. The river water temperature is projected to increase under climate change, for the scenario considered. The IFWLAM uses the downscaled projections of streamflow, simulated river water temperature and the predicted lower and upper future risk levels to determine the fraction removal policies for each of the dischargers. The results indicate that the optimal fractional removal levels required for the future scenarios will be higher compared to the present levels, even if the effluent loadings remain unchanged. Climate change is likely to impact the agricultural sector directly with changes in rainfall and evapotranspiration. The regional climate change impacts on irrigation water demands are studied by quantifying the crop water demands for the possible changes of rainfall and evapotranspiration. The future projections of various meteorological variables affecting the irrigation demand are downscaled using CCA downscaling model with MIROC 3.2 GCM output for the A1B scenario. The future evapotranspiration is obtained using the Penman-Monteith evapotranspiration model accounting for the projected changes in temperature, relative humidity, solar radiation and wind speed. The monthly irrigation water demands of paddy, sugarcane, permanent garden and semidry crops quantified at nine downscaling locations covering the entire command area of the Bhadra river basin, used as a case study, are projected to increase for the future scenarios of 2020-2044, 2045-2069 and 2070-2095 under the climate change scenario considered. The GCM and scenario uncertainty is modeled combinedly by deriving a multimodel weighted mean by assigning weights to each GCM and scenario. An entropy objective weighting scheme is proposed which exploits the information contained in various GCMs and scenarios in simulating the current and future climatology. Three GCMs, viz., CGCM2 (Meteorological Research Institute, Japan), MIROC3.2 medium resolution (Center for Climate System Research, Japan), and GISS model E20/Russell (NASA Goddard Institute for Space Studies, USA) with three scenarios A1B, A2 and B1 are used for obtaining the hydro-meteorological projections for the Bhadra river basin. Entropy weights are assigned to each GCM and scenario based on the performance of the GCM and scenario in reproducing the present climatology and deviation of each from the projected ensemble average. The proposed entropy weighting method is applied to projections of the hydro-meteorological variables obtained based on CCA downscaling method from outputs of the three GCMs and the three scenarios. The multimodel weighted mean projections are obtained for the future time slice of 2020-2060. Such weighted mean hydro-meteorological projections may be further used into the impact assessment model to address the climate model uncertainty in the water resources systems. An integrated reservoir operation model is developed considering the objectives of irrigation, hydropower and downstream water quality under uncertainty due to climate change, uncertainty introduced by fuzziness in the goals of stakeholders and uncertainty due to the random nature of streamflow. The climate model uncertainty originating from the mismatch between projections from various GCMs under different scenarios is considered as first level of uncertainty, which is modeled by using the weighted mean hydro-meteorological projections. The second level of uncertainty considered is due to the imprecision and conflicting goals of the reservoir users, which is modeled by using fuzzy set theory. A Water Quantity Control Model (WQCM) is developed with fuzzy goals of the reservoir users to obtain water allocations among the different users of the reservoir corresponding to the projected demands. The water allocation model is updated to account for the projected demands in terms of revised fuzzy membership functions under climate change to develop optimal policies of the reservoir for future scenarios. The third level of uncertainty arises from the inherent variability of the reservoir inflow leading to uncertainty due to randomness, which is modeled by considering the reservoir inflow as a stochastic variable. The optimal monthly operating polices are derived using Stochastic Dynamic Programming (SDP), separately for the current and for the future periods of 2020-2040 and 2040-2060 The performance measures for Bhadra reservoir in terms of reliability and deficit ratios for each reservoir user (irrigation, hydropower and downstream water quality) are estimated with optimal SDP policy derived for current and future periods. The reliability with respect to irrigation, downstream water quality and hydropower show a decrease for 2020-2040 and 2040-2060, while deficit ratio increases for these periods. The results reveal that climate change is likely to affect the reservoir performance significantly and changes in the reservoir operation for the future scenarios is unable to restore the past performance levels. Hence, development of adaptive responses to mitigate the effects of climate change is vital to improve the overall reservoir performance.

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abstract: The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the Coupled Model Intercomparison Project (CMIP); these simulations are ensemble-averaged to construct projections for the 21st century climate. However, a significant degree of bias and variability in the model simulations for the 20th century climate is well-known at both global and regional scales. Based on that insight, this study provides an alternative approach for constructing climate projections that incorporates knowledge of model bias. This approach is demonstrated to be a viable alternative which can be easily implemented by water resource managers for potentially more accurate projections. Tests of the new approach are provided on a global scale with an emphasis on semiarid regional studies for their particular vulnerability to water resource changes, using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model archives. This investigation is accompanied by a detailed analysis of the dynamical processes and water budget to understand the behaviors and sources of model biases. Sensitivity studies of selected CMIP5 models are also performed with an atmospheric component model by testing the relationship between climate change forcings and model simulated response. The information derived from each study is used to determine the progressive quality of coupled climate models in simulating the global water cycle by rigorously investigating sources of model bias related to the moisture budget. As such, the conclusions of this project are highly relevant to model development and potentially may be used to further improve climate projections. / Dissertation/Thesis / Ph.D. Mechanical Engineering 2013

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Created in 2018, the Climate Fresk workshop aims to raise awareness on climate change issues in an engaging and accessible way. This thesis draws on Social Interactionism, Uses and Gratification and Sociocultural Theory of Learning to conceptualize the workshop’s communicative strategies for conveying the complexities of climate change to the workshop participants. Through a synthetization of insights from various disciplines and exploration of innovative communication strategies, the study bridges the gap between knowledge and action, contributing to the semi-underexplored field of communication roles in game-based learning approaches to climate change education. Key findings reveal that tools such as informational materials, visuals, simplified scientific data, and creative techniques significantly enhance participants' understanding of climate change. The emphasis on group autonomy and collective discussions fosters a deeper understanding of climate change's complexities, highlighting the necessity for collective action. These results underscore the potential of effective communication in educational workshops to inspire individuals and communities to proactively respond to climate change, through collaborative action and by shifting the focus from individual to broader community-based efforts.

<p> Despite the absence of a binding global climate agreement, many advanced economies have enacted or attempted major national climate reforms over the past two decades. What accounts for variation between countries in the timing and ambition of these national climate policies? In this dissertation, I draw on literatures from comparative political economy, public policy and environmental politics to develop a new theory of climate policy conflict that explains national climate policymaking trajectories across advanced economies.</p><p> My argument proceeds in two parts. First, I detail a recurrent pattern of climate policy conflict that I describe as the <i>logic of double representation</i>. When the climate threat emerged in the late 1980s, this new issue exposed latent differences in the material interests of otherwise similar economic stakeholders, particularly labor and business actors. As a result, climate policy opponents became embedded in both left-leaning and right-leaning political coalitions. In political systems where organized labor was allied with the largest left-wing party and emissions-intensive businesses were allied with the largest right-wing party, a `double representation' of emissions-intensive economic interests resulted. In these cases, parties on both sides of the ideological spectrum had factions representing the interests of carbon-intensive constituencies within climate policy debates. This dynamic privileged carbon polluters' voice in climate policymaking.</p><p> Second, I argue there is an interaction between these cross-cutting climate policy preferences and domestic political institutions. Domestic political institutions can either strongly or weakly reinforce the logic of double representation, depending on carbon-dependent economic actors' access to climate policy design. This access is shaped by policymaking institutions, for instance through corporatist links between economic stakeholders and policymakers. Access is also a function of political organizations, for instance through historically contingent links between labor or business associations and political parties. I show how carbon-dependent economic actors' differential access to climate policy design creates two distinct causal pathways that can both lead to climate policy enactment. The first pathway occurs when carbon polluters control climate policy design. In this pathway, producer-friendly climate policies are enacted with little political conflict. The second pathway occurs when carbon polluters have more limited influence on climate policy design. This pathway leads to less producer-friendly policies and greater political conflict. I then show how institutional differences between countries condition the prevalence of these two pathways, helping to explain cross-national differences in national climate policies' timing and content.</p><p> I develop and test this account of national climate policy conflict using detailed qualitative analysis of climate politics in three advanced economies: Norway, the United States and Australia. In each case, I process-trace the dynamics of political decisionmaking on national climate reforms from the emergence of climate change as a political threat in the 1980s to the present. This analysis draws from 101 semi-structured interviews across all three countries conducted between 2013 and 2015, including conversations with former heads of state, party leaders, cabinet ministers, elected officials, senior bureaucrats, business executives, labor leaders, and environmental advocates. The analysis also draws from government documents, stakeholder publications, media reports and archival records. Finally, I probe the generalizability of my analysis by testing whether the causal processes identified within the dissertation's three primary cases extend to two shadow cases: Germany and Canada.</p><p> To date, many climate policy proponents have focused on international institutions to facilitate climate policy cooperation. However, my distributive-institutional account of national climate policymaking suggests that climate policy inaction is less rooted in the absence of a binding global agreement and instead results from domestic distributive conflict over climate policymaking. The presence of a global climate agreement will not automatically bridge domestic divisions. Instead, efforts to manage the global climate crisis should recognize that climate policymaking requires a fundamental renegotiation of the economic institutions that structure advanced economies. Understanding the conditions under which climate policy advocates can win in distributive climate conflict will involve moving beyond economic frames in evaluating the efficacy of climate reforms, rethinking the importance of collective action institutions to climate risk mitigation, and tailoring policy instruments to strategically address carbon polluters' differentiated influence on climate policy design.</p>

<p> The population and industrial complexes of Choctaw County obtains much of its water from an aquifer system in the Tertiary age Wilcox unit of the Mississippi Embayment. Utilizing 20 years of physical chemistry (P-Chem) analysis, potentiometric groundwater records of Choctaw County public water wells as well as industrial P-Chem analysis and surface and ground water level records from an industrial complex, this study examined the changes to the hydrosphere that has taken place since 1995. Analysis of the hydrosphere shows that over the last 20 years, there has been a drop in the potentiometric surface of the Wilcox aquifer system. The analysis also shows changes in the P-Chem of the hydrosphere, changes such as a decrease in the concentration of free CO2 and chloride, and fluctuations of Alkalinity. Comparisons between groundwater records taken from the industrial complex and other locations around Choctaw County, show little variation in the physical chemistry.</p>

A widely observed tracer in the field of oceanography is dissolved oxygen (O2). A tracer crucial to ocean biogeochemical cycles, O2 plays an active role in chemical processes, marine life, and ecosystems. Recent advances in observation and numerical simulation have introduced opportunities for furthering our understanding of the variability and long-term changes in oceanic O2. This work examines the underlying mechanisms driving O2 variability and long-term changes. It focuses on two distinct time-scales: intra-seasonal variability (i.e., a time scale of less than a month) and centennial changes in O2. The first half of this work analyzes state-of-the-art observations from a profiling float in an investigation of the mechanisms driving the intra-seasonal variability of oceanic O2. Observations from the float show enhanced intra-seasonal variability (i.e., a time scale of about two weeks) that could be driven by isopycnal heaving resulting from internal waves or tidal processes. Observed signals could result from aliased signals from internal waves or tides and should be taken into account in analyses of the growing observational dataset. The methods proposed in this study may be useful for future analyses of high-frequency tracer variability associated with mesoscale and sub-mesoscale processes. Using outputs from state-of-the-art earth system models and a suite of sensitivity experiments based on a general circulation and biogeochemistry ocean model, the second half of this work focuses on investigating mechanisms regulating centennial changes in O2. It explores the aspect of anthropogenic climate change (e.g., changes in the sea surface temperature and wind stress fields) that significantly impacts oceanic O2, focusing specifically on tropical oxygen minimum zones. Results suggest that ocean heating induces a water mass shift, leads to decrease apparent oxygen utilization (AOU) in the tropical thermocline. The AOU decrease compensates the effect of decrease in oxygen saturation due to the ocean warming. Our sensitivity experiments show that both physically (i.e., age) and biologically (i.e., the oxygen utilization rate) driven AOU will contribute almost equally to controlling changes in oceanic O2 in the next century. However, additional sensitivity experiments indicate that physically and biologically driven AOU balance has regional characteristics. We need to address the unanswered question of how varying large-scale oceanic circulations regulate this balance and answer fundamental questions that lead to a more comprehensive understanding of the mechanisms that control the variability and the future evolution of oceanic O2.

Recent (post-1950s) climate change impacts on society and ecosystems have been recognised globally. However these global impacts are not uniform at regional or local scales. Despite research progress on such scales there are still gaps in the knowledge as to 'what' is happening and 'where'? The goal of this study addresses some of these gaps by analysing climate variability and vegetation response at the furthest south westerly peninsula of the United Kingdom. This research is focused on West Cornwall (South West England) - an area dominated by a strong maritime influence. The first part of this PhD research analysed archive and contemporary instrumental data in order to detect any trends in climate variability. The weather data was retrieved from the Met Office archive for Camborne 1957-2010 and Culdrose 1985-2011 stations; Trengwainton Garden (1940-2010), and from the Royal Cornwall Polytechnic Society, for Falmouth (1880-1952) and Helston (1843-1888). The data showed positive trends in mean annual and maximum temperature with the largest trend magnitude in the 20th and 21st century. Seasonal temperature change varies locally with the highest increase in autumn spring and summer. Precipitation trends were only positive for the 19th century for Helston. Correlation between precipitation data and North Atlantic Oscillation (NAO index) was negative, however the opposite result was detected when the NAO index was correlated with temperatures. Surprisingly, return period analysis showed a decrease in the frequency and intensity of extreme precipitation events post 1975 for Camborne and Trengwainton Garden stations. The second part of this study analysed changes in vegetation distribution in West Cornwall using historical and contemporary vegetation records. Historical vegetation records were used from the Flora of Cornwall collection of herbarium records and contemporary vegetation records which were available online, containing mainly the 'New Atlas of British and Irish flora'. Data sets were geo-referenced using ArcGIS in order to analyse changes in species geographical distribution pre and post-1900. Analysis showed that historical vegetation records can be used to assess any changes in geographic distributions of vegetation. Analysis for the area of West Cornwall showed a loss of range for 18 species, for 6 species this loss was larger than 50% of the area, and there was no change in overall range area for 10 species. Ellenberg values and environmental indicator values showed that they can be used as an indicator of environmental change, showing a decrease in species with lower January temperatures. Analysis also showed an increase in moderate wetter species, where species with extreme low and high precipitation environmental indicator values showed a greater loss. Furthermore species with a higher requirement for light showed a loss as well as species with lower nitrogen values. To analyse the loss of species at the local scale, West Cornwall was divided into three areas (North Border Cells, Central West Cornwall Cells and South Border Cells). The highest loss of 11 species was detected for South Border Cells, where the loss for Central West Cornwall Cells was 6 and for North Border Cells 8 species. It was found that 17 species were experiencing loss on different local sites. For 9 of these 17 species, change at the local scale was different to the national scale change at the individual species level, group level and habitat level. Furthermore, the whole area of West Cornwall lost two species post-1900, with a different loss locally. This showed that species could be protected locally in appropriate microclimate refugia, which will be of benefit for the preservation of regional identity ecosystem services and overall genetic pool of the species.

Scientific knowledge is often relied upon for informing crucial societal decisions. Where this knowledge is uncertain, and/or where these decision are made amidst a contexted political landscape, science tends to become the focus of intense scrutiny, as has been evident throughout the history of climate change politics. One consequence is that instead of "scientising" decision-making, science itself becomes more explicitly politicised. This thesis argues that in order to contribute to contemporary debates about the governance of science, it is essential to move beyond the question of whether or not policy-relevant scientific knowledge is credibly and to examine how scientific knowledge is made to be credible. Drawing upon the concept of co-production and other insights from Science & Technology Studies (STS), this thesis presents a detailed examination of how research into the health impacts of climate change (infectious diseases especially) gradually gained in prominence in both public health and climate change circles. Particular analytical attention is paid to an epistemic community of climate change and health (CCH) researchers, following the ways in which they interacted with global political entities such as the World Health Organization (WHO) and the Intergovernmental Panel of Climate Change (IPCC). Based upon in-depth interviews with actors intimately involved in CCH research, this thesis documents how the rise of CCH research influenced and was influenced by particular scientific and political contexts related to the governance of climate change as well as emerging infectious disease. The examination of a longstanding controversy surrounding CCH research reveals many socio-economic and political assumptions embedded in it, further demonstrating its contingency. However, despite that CCH research is both uncertain and contested, actors in the political world often need to know what the state-of-the-art of the field is. To examine the implications of this, the CCH controversy as treated by the assessment reports of the Intergovernmental Panel on Climate Change (IPPC) is explored. Although IPCC follows a complicated set of procedures aimed at ensuring scientific and political legitimacy, this thesis demonstrates that values and normative judgements are important components of scientific assessments, helping to co-construct particular science-policy orderings at the expense of alternative ones. Amidst ongoing debates about how to shore-up the credibility of climate change science and politics, this thesis argues that the way in which IPCC assessments are currently performed, as well as their tendency to present findings as "consensus", may undermine their political and scientific credibility.