<p>Forest management involves numerous stochastic elements. To sustainably manage forest resources, it is crucial to acknowledge these sources as uncertainty or risk, and incorporate them in adaptive decision-making. Here, I developed several stochastic programming models in the form of passive or active adaptive management for natural mixed-species hardwood forests in Indiana. I demonstrated how to use these tools to deal with time-invariant and time-variant natural disturbances in optimal planning of harvests.</p> <p> Markov decision process (MDP) models were first constructed based upon stochastic simulations of an empirical forest growth model for the forest type of interest. Then, they were optimized to seek the optimal or near-optimal harvesting decisions while considering risk and uncertainty in natural disturbances. In particular, a classic expected-criterion infinite-horizon MDP model was first used as a passive adaptive management tool to determine the optimal action for a specific forest state when the probabilities of forest transition remained constant over time. Next, a two-stage non-stationary MDP model combined with a rolling-horizon heuristic was developed, which allowed information update and then adjustments of decisions accordingly. It was used to determine active adaptive harvesting decisions for a three-decade planning horizon during which natural disturbance probabilities may be altered by climate change.</p> <p> The empirical results can be used to make some useful quantitative management recommendations, and shed light on the impacts of decision-making on the forests and timber yield when some stochastic elements in forest management changed. In general, the increase in the likelihood of damages by natural disturbance to forests would cause more aggressive decisions if timber production was the management objective. When windthrow did not pose a threat to mixed hardwood forests, the average optimal yield of sawtimber was estimated to be 1,376 ft³/ac/acre, while the residual basal area was 88 ft²/ac. Assuming a 10 percent per decade probability of windthrow that would reduce the stand basal area considerably, the optimal sawtimber yield per decade would decline by 17%, but the residual basal area would be lowered only by 5%. Assuming that the frequency of windthrow increased in the magnitude of 5% every decade under climate change, the average sawtimber yield would be reduced by 31%, with an average residual basal area slightly around 76 ft²/ac. For validation purpose, I compared the total sawtimber yield in three decades obtained from the heuristic approach to that of a three-decade MDP model making <i>ex post</i> decisions. The heuristic approach was proved to provide a satisfactory result which was only about 18% lower than the actual optimum.</p> These findings highlight the need for landowners, both private and public, to monitor forests frequently and use flexible planning approaches in order to anticipate for climate change impacts. They also suggest that climate change may considerably lower sawtimber yield, causing a concerning decline in the timber supply in Indiana. Future improvements of the approaches used here are recommended, including addressing the changing stumpage market condition and developing a more flexible rolling-horizon heuristic approach.

There remain vast knowledge gaps in the global south as to how tourism will affect climate change and vice versa. Recent extreme weather events in southern Africa attributed to climate variability and change have led to speculation that, the Victoria Falls, is under threat from climate change. This research was aimed at examining the two-way linkage between tourism and climate change. The research adopted a pragmatism paradigm in a mixed-method case study. A number of research techniques were used to investigate the problem, namely: an online survey (n=427), secondary data analysis, field observation and interviews. Data analysis was done making use of Mann-Kendall Trend Analysis, QuestionPro analytics, Microsoft Excel Analysis Toolpak, Tools from ArcMap 10.3.1 and SPSS 24. Content analysis and thematic analysis was used to analyse secondary and interview data respectively. It emerged that the Victoria Falls is experiencing climate change, which resulted in statistically significant increase in temperature over the past 40 years of between 0.3°C and 0.75°C per decade. However, no significant changes in rainfall were noted, although there has been a seasonal shift in average rainfall onset. Weather extremes and annual rainfall point to increased occurrence and severity of extreme years of droughts and wetting which has in turn also affected waterflow regime at the waterfalls. The changes have a negative impact on wildlife, tourists, and tourism business in the area. The study also revealed that tourism is an equally significant driver of climate change through carbon emissions throughout its value chain. Carbon emissions from tourism value chain are set to increase in the foreseeable future despite efforts of going green by the industry owing to exponential growth of the industry. There is, therefore, a need for the industry to adapt, mitigate and intensify green tourism efforts to achieve sustainability. The study further suggests that there is a need for better communication and education to build resilience and capacity for the tourism industry to deal with climate change. Further research is suggested to ascertain the tourism threshold for the area, impact of climate change on wildlife and basin changes that led to water flow increase in the Zambezi River. / Environmental Sciences / Ph. D. (Environmental Management)

Increasing global mean temperature or global warming has the potential to affect the hydrologic cycle. In the 21st century, according to the UN Intergovernmental Panel on Climate Change (IPCC), alterations in the frequency and magnitude of high intensity rainfall events are very likely. Increasing trend of urbanization across the globe is also noticeable, simultaneously. These changes will have a great impact on water infrastructure as well as environment in urban areas. One of the impacts may be the increase in frequency and extent of flooding. India, in the recent years, has witnessed a number of urban floods that have resulted in huge economic losses, an instance being the flooding of Mumbai in July, 2005. To prevent catastrophic damages due to floods, it has become increasingly important to understand the likely changes in extreme rainfall in future, its effect on the urban drainage system, and the measures that can be taken to prevent or reduce the damage due to floods. Reliable estimation of future design rainfall intensity accounting for uncertainties due to climate change is an important research issue. In this context, rainfall intensity-duration-frequency (IDF) relationships are one of the most extensively used hydrologic tools in planning, design and operation of various drainage related infrastructures in urban areas. There is, thus, a need for a study that investigates the potential effects of climate change on IDF relationships. The main aim of the research reported in this thesis is to investigate the effect of climate change on Intensity-Duration-Frequency relationship in an urban area. The rainfall in Bangalore City is used as a case study to demonstrate the applications of the methodologies developed in the research Ahead of studying the future changes, it is essential to investigate the signature of changes in the observed hydrological and climatological data series. Initially, the yearly mean temperature records are studied to find out the signature of global warming. It is observed that the temperature of Bangalore City shows an evidence of warming trend at a statistical confidence level of 99.9 %, and that warming effect is visible in terms of increase of minimum temperature at a rate higher than that of maximum temperature. Interdependence studies between temperature and extreme rainfall reveal that up to a certain range, increase in temperature intensifies short term rainfall intensities at a rate more than the average rainfall. From these two findings, it is clear that short duration rainfall intensities may intensify in the future due to global warming and urban heat island effect. The possible urbanization signatures in the extreme rainfall in terms of intensification in the evening and weekends are also inferred, although inconclusively. The IDF relationships are developed with historical data and changes in the long term daily rainfall extreme characteristics are studied. Multidecedal oscillations in the daily rainfall extreme series are also examined. Further, non-parametric trend analyses of various indices of extreme rainfall are carried out to confirm that there is a trend of increase in extreme rainfall amount and frequency, and therefore it is essential to the study the effects of climate change on the IDF relationships of the Bangalore City. Estimation of future changes in rainfall at hydrological scale generally relies on simulations of future climate provided by Global Climate Models (GCMs). Due to spatial and temporal resolution mismatch, GCM results need to be downscaled to get the information at station scale and at time resolutions necessary in the context of urban flooding. The downscaling of extreme rainfall characteristics in an urban station scale pose the following challenges: (1) downscaling methodology should be efficient enough to simulate rainfall at the tail of rainfall distribution (e.g., annual maximum rainfall), (2) downscaling at hourly or up to a few minutes temporal resolution is required, and (3) various uncertainties such as GCM uncertainties, future scenario uncertainties and uncertainties due to various statistical methodologies need to be addressed. For overcoming the first challenge, a stochastic rainfall generator is developed for spatial downscaling of GCM precipitation flux information to station scale to get the daily annual maximum rainfall series (AMRS). Although Regional Climate Models (RCMs) are meant to simulate precipitation at regional scales, they fail to simulate extreme events accurately. Transfer function based methods and weather typing techniques are also generally inefficient in simulating the extreme events. Due to its stochastic nature, rainfall generator is better suited for extreme event generation. An algorithm for stochastic simulation of rainfall, which simulates both the mean and extreme rainfall satisfactorily, is developed in the thesis and used for future projection of rainfall by perturbing the parameters of the rainfall generator for the future time periods. In this study, instead of using the customary two states (rain/dry) Markov chain, a three state hybrid Markov chain is developed. The three states used in the Markov chain are: dry day, moderate rain day and heavy rain day. The model first decides whether a day is dry or rainy, like the traditional weather generator (WGEN) using two transition probabilities, probabilities of a rain day following a dry day (P01), and a rain day following a rain day (P11). Then, the state of a rain day is further classified as a moderate rain day or a heavy rain day. For this purpose, rainfall above 90th percentile value of the non-zero precipitation distribution is termed as a heavy rain day. The state of a day is assigned based on transition probabilities (probabilities of a rain day following a dry day (P01), and a rain day following a rain day (P11)) and a uniform random number. The rainfall amount is generated by Monte Carlo method for the moderate and heavy rain days separately. Two different gamma distributions are fitted for the moderate and heavy rain days. Segregating the rain days into two different classes improves the process of generation of extreme rainfall. For overcoming the second challenge, i.e. requirement of temporal scales, the daily scale IDF ordinates are disaggregated into hourly and sub-hourly durations. Disaggregating continuous rainfall time series at sub-hourly scale requires continuous rainfall data at a fine scale (15 minute), which is not available for most of the Indian rain gauge stations. Hence, scale invariance properties of extreme rainfall time series over various rainfall durations are investigated through scaling behavior of the non-central moments (NCMs) of generalized extreme value (GEV) distribution. The scale invariance properties of extreme rainfall time series are then used to disaggregate the distributional properties of daily rainfall to hourly and sub-hourly scale. Assuming the scaling relationships as stationary, future sub-hourly and hourly IDF relationships are developed. Uncertainties associated with the climate change impacts arise due to existence of several GCMs developed by different institutes across the globe, climate simulations available for different representative concentration pathway (RCP) scenarios, and the diverse statistical techniques available for downscaling. Downscaled output from a single GCM with a single emission scenario represents only a single trajectory of all possible future climate realizations and cannot be representative of the full extent of climate change. Therefore, a comprehensive assessment of future projections should use the collective information from an ensemble of GCM simulations. In this study, 26 different GCMs and 4 RCP scenarios are taken into account to come up with a range of IDF curves at different future time periods. Reliability ensemble averaging (REA) method is used for obtaining weighted average from the ensemble of projections. Scenario uncertainty is not addressed in this study. Two different downscaling techniques (viz., delta change and stochastic rainfall generator) are used to assess the uncertainty due to downscaling techniques. From the results, it can be concluded that the delta change method under-estimated the extreme rainfall compared to the rainfall generator approach. This study also confirms that the delta change method is not suitable for impact studies related to changes in extreme events, similar to some earlier studies. Thus, mean IDF relationships for three different future extreme events, similar to some earlier studies. Thus, mean IDF relationships for three different future periods and four RCP scenarios are simulated using rainfall generator, scaling GEV method, and REA method. The results suggest that the shorter duration rainfall will invigorate more due to climate change. The change is likely to be in the range of 20% to 80%, in the rainfall intensities across all durations. Finally, future projected rainfall intensities are used to investigate the possible impact of climate change in the existing drainage system of the Challaghatta valley in the Bangalore City by running the Storm Water Management Model (SWMM) for historical period, and the best and the worst case scenario for three future time period of 2021–2050, 2051–2080 and 2071–2100. The results indicate that the existing drainage is inadequate for current condition as well as for future scenarios. The number of nodes flooded will increase as the time period increases, and a huge change in runoff volume is projected. The modifications of the drainage system are suggested by providing storage pond for storing the excess high speed runoff in order to restrict the width of the drain The main research contribution of this thesis thus comes from an analysis of trends of extreme rainfall in an urban area followed by projecting changes in the IDF relationships under climate change scenarios and quantifying uncertainties in the projections.

[ES] La presente investigación es un aporte a la comprensión del abordaje del cambio climático local en Costa Rica, desde un posicionamiento que da un rol fundamental a la participación ciudadana y a la gobernanza climática. El estudio se justifica en la medida que el país definió una Estrategia Nacional de Cambio Climático para el año 2020, en la cual los municipios en análisis han sido parte de la primera experiencia que ha tenido el país de trabajar el tema de cambio climático a nivel local y además con enfoque participativo, implicando a gobiernos locales y diferentes actores sociales (sociedad civil). En este contexto, resultaba de interés analizar si han existido políticas y mecanismos de incentivos para los gobiernos locales y sociedad civil, así como, cuáles son los factores determinantes para fortalecer capacidades locales en el tema de cambio climático y, finalmente, si este tipo de iniciativas contribuyen al desarrollo sostenible local. Este estudio busca, por tanto, contribuir a la sistematización de experiencias de desarrollo local, en particular las relacionadas con procesos de planificación y gestión participativa, en la temática de cambio climático en el nivel local. Para ello se ha llevado a cabo el análisis de tres estudios de caso de municipios de Costa Rica que han emprendido el reto de incorporar en sus agendas locales el tema de cambio climático, con un enfoque participativo, integrando las dimensiones socioambientales, culturales, políticas y económicas. La investigación y análisis de las dimensiones relevantes en los estudios de caso, ha generado un modelo metodológico para iniciativas locales de cambio climático, que integra la perspectiva técnica y la participativa en la construcción de un sistema de indicadores locales que aporten nuevos conocimientos a los procesos de desarrollo local, y contribuyan con un marco de referencia para otras experiencias en el ámbito nacional o internacional. / [CA] La present investigació és una aportació a la comprensió de l'abordatge del canvi climàtic local a Costa Rica, des d'un posicionament que dona un rol fonamental a la participació ciutadana i a la governança climàtica. L'estudi es justifica en la mesura que el país va definir una Estratègia Nacional de Canvi Climàtic per a l'any 2020, en la qual els municipis d'anàlisi han sigut part de la primera experiència que ha tingut el país de treballar el tema de canvi climàtic a nivell local i a més amb enfocament participatiu, implicant governs locals i diferents actors socials (societat civil). En aquest context, resultava d'interés analitzar si han existit polítiques i mecanismes d'incentius per als governs locals i societat civil, així com, quins són els factors determinants per a enfortir capacitats locals en el tema de canvi climàtic, i, finalment, si aquest tipus d'iniciatives contribueixen al desenvolupament sostenible local. Aquest estudi busca, per tant, contribuir a la sistematització d'experiències de desenvolupament local, en particular les relacionades amb processos de planificació i gestió participativa, en la temàtica de canvi climàtic en el nivell local. Per a això s'han dut a terme l'anàlisi de tres estudis de cas de municipis de Costa Rica que han emprés el repte d'incorporar en les seues agendes locals el tema de canvi climàtic, amb un enfocament participatiu, integrant les dimensions socioambientales, culturals, polítiques i econòmiques. La investigació i anàlisi de les dimensions rellevants en els estudis de cas, ha generat un model metodològic per a iniciatives locals de canvi climàtic, que integra la perspectiva tècnica i la participativa en la construcció d'un sistema d'indicadors locals que aporten nous coneixements als processos de desenvolupament local, i contribuïsquen amb un marc de referència per a altres experiències en l'àmbit nacional o internacional. / [EN] This research is a contribution to understanding the approach to local climate change in Costa Rica, from a positioning that gives a fundamental role to citizen participation and climate governance. The study is justified to the extent that the country defined a National Climate Change Strategy for 2020, in which the municipalities under analysis have been part of the country's first experience of working on climate change at the local level and also with a participatory approach, involving local governments and different social actors (civil society). In this context, it is of interest to examine whether there have been policies and incentive mechanisms for local governments and civil society, as well as what are the determining factors for strengthening local capacities in the issue of climate change, and, finally, if such initiatives contribute to local sustainable development. This study therefore seeks to contribute to the systematization of local development experiences, in particular those related to participatory planning and management processes, in the theme of climate change at the local level. To this end, the analysis of three case studies of municipalities in Costa Rica that have undertaken the challenge of incorporating the issue of climate change into their local agendas, with a participatory approach, integrating the socio-environmental, cultural, political and economic dimensions. The research and analysis of the relevant dimensions in these case studies have generated a methodological model for local climate change initiatives, which integrates the technical and participatory perspective in the construction of a system of indicators to provide new knowledge to local development processes, and contribute to a framework of reference for other experiences at the national or international level. / Valerio Hernández, V. (2020). Estrategias locales de lucha contra el cambio climático con enfoque participativo: estudio de casos de la experiencia en Costa Rica, 2011-2018 [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/160886 / TESIS