The subantarctic Prince Edward Islands (PEIs, 47◦S-38◦E) are classified as isolated and hostile regions, in which the terrestrial and marine ecosystems are relatively simple and extremely sensitive to perturbations. The island’s location, between the Subantarctic Front (SAF) and the Polar Front (PF), bordering the Antarctic Circumpolar Current (ACC) provides an ideal natural laboratory for studying how organisms, ecological processes and ecosystems respond to a changing climate in the Southern Ocean. Recent studies have proposed that climate changes reported at the islands may correspond in time to a southward shift of the ACC and in particular of the SAF. This southward migration in the geographic position of major ocean fronts is likely to coincide with dramatic changes in the distribution of species and total productivity of this region. However, there are other sources of variability in the hydrodynamic conditions around the PEIs: upstream of the islands, at the South West Indian Ridge (SWIR), a region of high eddy kinetic activity produces mesoscale features that directly irrigate the PEIs and may impact their marine environment. Based on satellite altimetry in that region, the positions of the SAF and PF were found to be highly variable at interannual and monthly time scales. They also revealed a significant long-term southward trend which was highlighted at the Southern Ocean scale. The mesoscale activity also showed an interannual and intra-annual variability and a decrease in eddy kinetic energy over 24 years was observed in the region. At a more local scale, we highlighted that the archipelago’s environment was impacted by the mesoscale features produced at the SWIR. The temperature, the mixed layer and velocities recorded between the islands were clearly affected by the eddies passing in the vicinity of the PEIs. Moreover, a large signal dominating the main current time series appeared to be a tidal signal, another important driver of variability of the circulation in between the two islands. On a second hand, an idealised model configuration was designed for the PEIs region to study the mesoscale eddy properties and the physical mechanisms of their formation at the ridge. The Eddy Available Potential Energy revealed a maximum of energy around 800 m depth, confirming the deep reaching characteristic of the eddy originated in the region and suggested the presence of a local energy source at this depth. This eddies activity was shown to be the result of a combination of barotropic and baroclinic instabilities occurring at the ridge. Finally, we investigated on the potential consequences of a southward shift of the SAF in the region of the islands. Because the model was idealised, it allowed us to simulate an SAF southward shift by shifting the initial and boundary conditions. The main result was the clear decrease of mesoscale activity in the region which could potentially impact the ecosystems of the PEIs.

Developing countries have been rapidly urbanising over the last decades, resulting in major environmental pressures and increased vulnerability to natural disasters. A complex combination of factors, including climate change, land use change, poorly implemented regulation and a lack of integrated planning has often resulted in environmental degradation and disproportionate impacts of natural disasters affecting millions worldwide, particularly in tropical cities. The main aim of this study is to understand the effects of land-use and climate change on flooding in the Greater Port-Harcourt watershed. The specific research objectives were: to understand the historical and future land use /land cover changes; to understand the magnitude of change in hydrologic and hydraulic conditions due to land-use and climate changes; to assess the influence of different forest mitigation scenarios on peak-discharge; and to make recommendations on how to improve future planning using insights from this study. Methodologically, the post-classification change detection method was applied to examine the extent and nature of historical LULC changes using remotely sensed data. Future LULC changes were estimated by superimposing the 2060 digitised Masterplan map on the year 2003 baseline imagery. Hydrologic changes were assessed using HEC-HMS model, while changes in the hydraulic condition were assessed using HEC-RAS model. Model output was further used to map flood hazards, flood zones and damage potential. Priority areas and infrastructure at risk were identified by means of their location in flood zones and exposure to floods with high damage potential. On the extent of change, this study revealed that urbanisation and loss of agricultural land had been the dominant and intensive land use change in the watershed. Urbanisation is projected to almost double its 2003 extent by 2060 and is likely to remain the dominant force of land use change. On the nature of change, this study found that urban land was the most dynamic in terms of gross gain and net change. It exhibited the grossest gain (about 9% of the watershed) and the grossest loss leading to a high net change of about 8.6%. In fact, the most prominent transition was the conversion of agricultural land (about 422km2) to urban land, and roughly 93.3% of all conversions to urban land resulted from agricultural land. On the process of change, urban land mainly experienced a net-type of change (change in quantity), whereas changes in agricultural land was more of a swap-type of change (change in location). Importantly, the study reveals that the impact on flood flow was historically significant (about 68%) and is projected to amplify in future, however, these changes are largely attributed to increased storm size. Urbanisation is likely to have little or no impact on annual maximum peak flow at the watershed scale; however, urbanisation is projected to have a considerable impact on peak flow in a number of subbasins, which could have severe implications for flash flooding in those subbasins. Similarly, afforestation could have little or no impact on future maximum peak flow when assessed at the watershed scale. Although some subbasins experienced changes in peak flow, the effect of forest is variable. The study concludes that although the impact of urbanisation is projected to be insignificant at the watershed scale, it could also increase flood risk due to increasing developments in floodplains and channel encroachment. Priority infrastructure and areas requiring urgent flood risk management include the Port-Harcourt seaports, Onne seaport, the University of Science and Technology and cement factory. Priority areas in the Masterplan are mainly in the south (Phase 3), comprising of the Air force base and the residential area near Onne seaport. Lastly, approximately 8.1km and 189m of road and rail network are at greater risk of flooding by means of their exposure to floods with the highest damage potential. Based on this study, I have furthered understanding by showing that the transition to urban land category was dominated by net changes (i.e. changes in quantity). I have also furthered understanding by showing that substantial changes in future urban land-use may not have significant effect on flood parameters. My main contribution to knowledge is that despite the high rate of urbanisation in the GPH watershed and its minimal impact on flooding (which could be due the large size of the storm and watershed), urbanisation could still increase flood risk due to greater exposure of elements at risk in the flood plains to damaging floods. Based on the results, the study recommends that the development authorities should integrate both structural measures (mainly for flood defence around existing developments) and non-structural measures (primarily for future developments). For flood risk management research, this study recommends that conclusions about the effects of urbanisation should not be made solely on the basis of changes in hydrology and river hydraulics, however researchers should also consider the exposure of important elements at risk within the floodplains under study to better understand the effects of urbanisation. Moreover, to better understand urbanisation effects on runoff dynamics in other watersheds, this study recommends that research efforts should be concerted in understanding subbasin-scale changes given that the effects of urbanisation are more pronounced in smaller basins.

The knowledge of flow hydrodynamics within the next decades is of particular importance in many practical applications. In this study, a methodological improvement has been made to the evaluation of the flow hydrodynamics under climate change. This research, indeed, proposes an approach which includes the methods that can consider the climate change impact on the flow in estuaries, gulfs, etc. It includes downscaling methods to project the required climate variables through the next decades. Here, two statistical downscaling methods, namely, Nearest Neighbouring and Quantile-Quantile techniques, are developed and implemented in order to predict the wind speed over the study area. Wind speed has an essential role in flow field and wave climatology in estuaries and gulfs. In order to make the proposed methodology computationally efficient, the flow in the estuary is simulated by a large-scale model. The finite volume triangular C-grid is analysed and shown to have advantages over the rectangular (finite difference) one. The dispersion relation analysis is performed for both gravity and Rossby waves that have crucial effects in oceanic models. In order to study the unstructured characteristic of the triangular grids, various isosceles triangles with different vertex angles are considered. Moreover, diverse well-known second-order time stepping techniques such as Leap-Frog, Adams-Bashforth and improved Euler are studied in combination with the C-grid semi discrete method. The fully discrete method is examined through several numerical experiments for both linear and non-linear cases. The results of the large-scale model provide the boundary conditions to the local coastal model. In order to model the flow over a local coastal area, a well-balanced positivity preserving central-upwind method is developed for the unstructured quadrilateral grids. The quadrilateral grid can effectively simulate complex domains and is shown to have advantages over the triangular grids. The proposed central-upwind scheme is well-balanced and preserve the positivity. Therefore, it is capable of modelling the wetting and drying processes that may be the case in many local coastal areas. It is also confirmed that the proposed method can well resolve complex flow features. The local model incorporates the outputs of the downscaling and large-scale flow models and evaluates the flow hydrodynamics under changing climate.

The world is urbanizing at an unprecedented rate, and cities are dominantly and increasingly becoming hubs for agglomerations of human population and economic activities, as well as major sources of environmental problems. Accordingly, humanity′s pursuit of global sustainability is becoming increasingly reliant on urban sustainability. Unfortunately, the traditional approaches of urbanization and urban stormwater management are inappropriate from the sustainability standpoint. By removing vegetation and topsoil and creating impervious structures, urbanization destroys natural biodiversity and hydrological processes. As a result, urban societies are disconnected from nature and deprived of ecosystem services including flood control, fresh air, clean water, and natural beauty. Due to disrupted hydrology, an urban landscape transforms most rainwater into stormwater runoff which is conveyed off the site through a system of curb-gutter-pipe, called gray infrastructure. While gray infrastructure efficiently mitigates the problem of flash floods in urban areas, it results in multiple other adverse environmental consequences such as loss of freshwater from urban landscapes, transfer of pollutants to receiving waters, and an increased potential of downstream flooding. Green infrastructure (GI) is regarded as a sound alternative that manages stormwater by revitalizing the natural processes of soil, water, and vegetation, and restoring ecosystem structures and functions. Thus, the approach re–establishes the lost socio–ecological connectivity and regenerates ecosystem services. However, despite being inevitably important for urban sustainability, and despite being the object of unrelenting expert advocacy for more than two decades, the approach is yet to become a mainstream practice. To widely implement GI, cities need to address two critical challenges. First, urban stormwater managers and decision makers should be ensured that the approach can adequately and reliably manage stormwater. In the time when flooding problems are rising due to climate change, this concern has become more prominent. Second, if there exist any other barriers, they should be replaced with strategies that help expedite the use of GI. This multidisciplinary research dealt with these two challenges. The study consisted of two major parts. In the first part, a computer model was developed for a combined sewer system of St. Louis, a city in the US state of Missouri, using U.S. EPA SWMM. Simulations for historical (1971-2000) and future (2041-2070) 50-yr 3-hr rainfall scenarios were then run on the model with and without GI. The simulation results showed a significant impact of increased precipitation on the system, which was considerably reduced after adding select GI measures to the modeled system. The following 4 types of GI were used: bio–retention cell, permeable pavement, green roof, and rain barrel. In the second part, a survey of relevant policies and governance mechanisms of eleven U.S. cities was conducted to identify potential barriers to GI and determine strategies to address them. The study also included the assessment of relevant city, state, and federal policies and governance structures. A total of 29 barriers were identified, which were grouped into 5 categories. Most of the identified barriers stem from cognitive barriers and socio–institutional arrangements. A total of 33 policies, also grouped into 5 groups, were determined to address the barriers. The investigation on governance revealed that current governance is highly technocratic and centralized, and hence has less opportunity for public involvement. Therefore, it is inherently inappropriate for GI, which requires extensive public involvement. This dissertation proposes a two–tier governance model suitable for implementing GI.

There is now a general consensus among scientists on occurrences of more and intense climatic disasters, floods and droughts, everywhere in the future. To act sooner and smarter against these negative impacts, we must shift our focus in better understanding of the future climate change and possible implications of that to better manage our water resources. Certainly, there is a link between the future effects of climate change on water resources and trends of climatic variables. In this study, by using Mann-Kendall trend analysis method, it is concluded that from 1961 to 2010 only temperature has an upward trend, in all the seasons and yearly, in all the 16 studied stations from north, middle and south of Sweden. Furthermore, runoff simulated by HBV model shows increasing trend in summer and winter which is in partially agreement with the recorded one that discerns a growth in the mentioned seasons, as well as yearly. What is more, potential evapotranspiration estimated by FAO Penman-Monteith equation and actual one simulated by CoupModel reveal a rise in spring for the former and both spring and winter for the latter. Other meteorological variables do not show any significant trend, while intensive precipitation increased in winter and summer in the majority of the stations. Comparing the runoffs simulated by CoupModel and HBV model shows that HBV works better for three selected stations which can enforce the claim that HBV works better for smaller fields.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第17876号 / 工博第3785号 / 新制||工||1579(附属図書館) / 30696 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 角 哲也, 教授 堀 智晴, 准教授 田中 賢治, 准教授 Sameh Ahmed Kantoush / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18555号 / 工博第3916号 / 新制||工||1602(附属図書館) / 31455 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 立川 康人, 教授 戸田 圭一, 准教授 KIM Sunmin / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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.

<p></p><p></p><p>Peatlands are the most efficient natural carbon sink on the planet. They are the most carbon-intensive storages than any other vegetation types. However, recent studies indicate that global peatlands can potentially release 6% of the global soil carbon into the atmosphere when they are drained or deforested. They cover only about 3% of the total global land area, but sequester over 30% of the Earth’s soil organic carbon. Peatlands in northern mid-to-high latitudes (45°-90°N) occupy ~90% of the global peatland area and account for ~80% of the total global peat organic carbon stock. Those peatlands are mainly located in Canada, Russia, and the USA. Peatlands in tropical regions cover ~10% of the global peatlands area and store 15-19% of the global peat organic carbon. They are mainly distributed in Southeast Asia and South and Central America. The temperature at the global scale has been rising since the middle of the last century and has accelerated during the last 40 years and the warming will continue in this century. The large storage of soil organic carbon within the peatlands can significantly respond to the changing climate by varying the roles between their carbon sink (from atmosphere to soil) and source (from soil to atmosphere) activities. This dissertation focuses on quantifying the soil organic carbon dynamics in North America and South America using mechanistically-based biogeochemistry models. </p><p></p><p>Peatlands in Alaska occupy 40 million hectares and account for ~10% of the total peatland area in northern mid-to-high latitudes. The regional soil organic carbon dynamics and its response to climate are still with large uncertainty. Most of the studies on peatlands to date are based on short-term site-level observation. This dissertation first used an integrated modeling framework that coupled the dynamics of hydrology, soil thermal regime, and ecosystem carbon and nitrogen to quantify the long-term peat carbon accumulation in Alaska during the Holocene. Modeled hydrology, soil thermal regime, carbon pools and fluxes and methane emissions were evaluated using long-term observation data at several peatland sites in Minnesota, Alaska, and Canada. The model was then applied for a 10,000-year (15 ka to 5 ka; 1 ka = 1000 cal yr before present) simulation at four peatland sites. The model simulations matched the observed carbon accumulation rates at fen sites during the Holocene (R^2= 0.88, 0.87, 0.38 and -0.05 for four sites respectively using comparisons in 500-year bins from 15 ka to 5 ka). The simulated (2.04 m) and observed peat depths (on average 1.98 m) also compared well (R^2 = 0.91). The early Holocene carbon accumulation rates, especially during the Holocene thermal maximum (HTM) (35.9 g 〖C m〗^(-2) yr^(-1)), were estimated up to 6-times higher than the rest of the Holocene (6.5 g 〖C m〗^(-2) yr^(-1)). It suggested that high summer temperature and the lengthened growing season resulted from the elevated insolation seasonality, along with wetter-than-before conditions might be major factors causing the rapid carbon accumulation in Alaska during the HTM. The sensitivity tests indicated that, apart from climate, initial water-table depth and vegetation canopy were major drivers to the estimated peat carbon accumulation. </p><p></p><p>To further quantify the regional long-term soil organic carbon accumulation rates and the current carbon stocks in Alaska, the second part of my research focused on quantifying the soil organic carbon accumulation in multiple Alaskan terrestrial ecosystems over the last 15,000 years for both peatland and non-peatland ecosystems. Comparable with the previous estimates of 25-70 Pg carbon (C) in peatlands and 13-22 Pg C in non-peatland soils within 1-m depth in Alaska using peat core data, our model estimated a total SOC of 36-63 Pg C at present, including 27-48 Pg C in peatland soils and 9-15 Pg C in non-peatland soils. Current living vegetation stored 2.5-3.7 Pg C in Alaska with 0.3-0.6 Pg C in peatlands and 2.2-3.1 Pg C in non-peatlands. The simulated average rate of peat soil C accumulation was 2.3 Tg C yr^(-1) with a peak value of 5.1 Tg C yr^(-1) during the Holocene Thermal Maximum (HTM) in the early Holocene, four folds higher than the average rate of 1.4 Tg C yr^(-1) over the rest of the Holocene. The accumulation slowed down, or even ceased, during the neo-glacial climate cooling after the mid-Holocene, but increased again in the 20th century. The model-estimated peat depths ranged from 1.1 to 2.7 m, similar to the field-based estimate of 2.29 m for the region. The changes in vegetation and their distributions were the main factors to determine the spatial variations of SOC accumulation during different time periods. Warmer summer temperature and stronger radiation seasonality, along with higher precipitation in the HTM and the 20th century might have resulted in the extensive peatland expansion and carbon accumulation. </p><p>Most studies on the role of tropical peatlands have focused on Indonesian peatlands. Few have focused on the Amazon basin, where peatlands remain intact and have been a long-term carbon sink. To address the problem, my third study quantified the carbon accumulation for peatland and non-peatland ecosystems in the Pastaza-Marañon foreland basin (PMFB), the most extensive peatland complex in the Amazon basin from 12,000 years before present to 2100 AD. Model simulations indicated that warming accelerated peat carbon loss while increasing precipitation accelerated peat carbon accumulation at millennial time scales. The uncertain parameters and spatial variation of climate were significant sources of uncertainty to modeled peat carbon accumulation. Under warmer and presumably wetter conditions over the 21st century, the warming effect on increasing peat carbon loss might overwhelm the wetter effect on increasing peat carbon accumulation. Peat soil carbon accumulation rate in the PMFB slowed down to 7.9 (4.3~12.2) g C m^(-2) yr^(-1) from the current rate of 16.1 (9.1~23.7) g C m^(-2) yr^(-1) and the region might turn into a carbon source to the atmosphere at -53.3 (-66.8~-41.2) g C m^(-2) yr^(-1) (negative indicates source), depending on the level of warming. Peatland ecosystems showed a higher vulnerability than non-peatland ecosystems as indicated by the ratio of their soil carbon density changes (change of soil carbon/existing soil carbon stock) ranging from 3.9 to 5.8). This was primarily due to larger peatlands carbon stocks and more dramatic responses of their aerobic and anaerobic decompositions in comparison with non-peatland ecosystems under future climate conditions. Peatland and non-peatland soils in the PMFB might lose up to 0.4 (0.32~0.52) Pg C by 2100 AD with the largest loss from palm swamp. The carbon-dense Amazonian peatland might switch from a current carbon sink into a source in the 21st century.</p><p>Peatlands are important sources and sinks for greenhouse gases (carbon dioxide and methane). Their carbon (C) balance between soil and atmosphere remains unquantified due to the large data gaps and uncertainties in regional peat carbon estimation. My final study was to quantify the C accumulation rates and C stocks within North America peatlands over the last 12,000 years. I find that 85-174 Pg C have been accumulated in North American peatlands over these years including 0.37-0.76 Pg C in subtropical peatlands in this region. During the 10- 8 ka period, the warmer and wetter conditions might have played an important role in stimulating peat C accumulation by enhancing plant photosynthesis. The enhanced peat decomposition due to warming through the Holocene slows down carbon accumulation in the region.</p><div><br></div><p><br></p>

Malgré des conditions sèches qui prédominent depuis les années 1970, l’Afrique de l’Ouest a subi au cours des deux dernières décennies des épisodes d’inondations sévères qui ont provoqué de nombreux décès et dommages socio-économiques. L’émergence de ce nouveau problème montre une nouvelle facette de la sensibilité de cette région aux changements hydro-climatiques, appelant à une meilleure caractérisation de l’aléa inondation, des processus qui le génèrent, ainsi que la mise en place de méthodes permettant de projeter les évolutions futures de cet aléa pour mieux s’en prémunir.Dans ce contexte, la thèse cherche à répondre à trois questions principales :1) L’augmentation des dommages liés aux inondations s’est-elle accompagnée d’une intensification des crues extrêmes en Afrique de l’Ouest?2) Comment modéliser les orages de mousson, premier facteur de génération du ruissellement, afin d’explorer l’impact de leurs caractéristiques sur les crues?3) Compte tenu des changements climatiques à l’œuvre dans la région, à quelles tendances hydro-climatiques peut-on s’attendre dans le futur ?Dans un premier temps, on évalue l’évolution des crues en Afrique de l’Ouest au cours des soixante dernières années en utilisant de méthodes basées sur la théorie de valeurs extrêmes. Les résultats montrent une augmentation forte des événements hydrologiques extrêmes depuis les années 1970s dans les sous-bassins Sahéliens du fleuve Niger et depuis les années 1980s dans les sous-bassins soudano-guinéens du fleuve Sénégal. Les niveaux de retour calculés à partir des modèles non-stationnaires dépassent ceux qui ont été calculés avec un modèle stationnaire avec plus de 95% de certitude pour les périodes de retour les plus courtes (<10 ans).On présente ensuite des développements récents apportés à un simulateur stochastique d’orages de mousson à meso-échelle (StochaStorm). Ils incluent: une modélisation de l’occurrence de ces orages, la représentation explicite des valeurs de pluie extrêmes et une amélioration du schéma temporel d’intensité infra-événementielle. Implémenté et évalué à partir des donnés haute-résolution de l’observatoire AMMA-CATCH, le générateur montrent de très bonnes capacités à reproduire les propriétés des orages, confirmant son potentiel pour des études d’impact hydrologique.Enfin, une chaîne de modélisation est élaborée afin de proposer des projections hydrologiques pour le futur sur un bassin sahélien de meso-échelle (Dargol, 7000 km²). L’originalité de cette chaîne provient de la prise en compte du continuum d’échelles entre climat global et impact local à travers la représentation du régime des pluies à l’échelle des orages de mousson, dont les propriétés d’occurrence et d’intensité ont des impacts majeurs sur la réponse hydrologique. La chaîne de modélisation inclut le modèle climatique CP4-Africa, unique modèle à convection explicite fournissant des simulations de long terme en Afrique ; une méthode de débiaisage statistique; le simulateur Stochastorm ; et un modèle pluie-débit spécifiquement adapté aux processus hydrologique sahéliens. La chaine est évaluée sur une période de contrôle 1997-2006 puis utilisée pour des projections futures montrant une hausse par un facteur 1,5 des débits maximum annuels et un doublement des volumes moyens annuels à l’horizon 2100.Les résultats ont des implications majeures notamment pour l’ingénierie hydrologique. Les méthodes actuellement utilisées pour appréhender les risques hydrologiques dans la région ne prennent pas en compte la non-stationnarité hydro-climatique risquant de sous-évaluer l’aléa hydrologique et sous-dimensionner les ouvrages hydrauliques utilisés pour s’en protéger. La thèse suggère aussi quelques pistes afin mieux définir les trajectoires hydrologiques passées et futures en incluant, au-delà des précipitations, les changements sociétaux et environnementaux, leurs interactions et rétroactions dans les approches de modélisation. / The semi-arid regions of West Africa are known for their dry conditions which have predominated since the 1970s. In recent years, however, West Africa has witnessed a series of severe flooding events which caused widespread fatalities and socioeconomic damages. The emergence of this new problem demonstrates the sensitivity of the region to changes in the hydroclimatic system and calls for an improved characterization of flood hazard and the mechanisms that generate it. It also signals the need to develop projections for how flood hazard may evolve in the future in order to inform appropriate adaptation measures.In this context, the following PhD thesis seeks to answer three main questions:1) Is there a significant trend in extreme streamflow in West Africa, or are the documented flooding events isolated incidences?2) How can one model mesoscale convective systems, the primary driver of runoff in the region, in order to explore the properties of precipitation that drive streamflow?3) Based on potential climate change in the region, what trends might be observed in streamflow in the future?First, changes in extreme hydrological events West Africa over the past 60 years are evaluated by applying non-stationary methods based on extreme value theory. Results show a strong increasing trend in extreme hydrological events since the 1970s in the Sahelian Niger River basin and since the 1980s in the Sudano-Guinean catchments in the Senegal River basin. Return levels calculated from non-stationary models are determined to exceed those calculated from a stationary model with over 95% certainty for shorter return periods (<10 years).Next, recent developments are presented for a stochastic precipitation simulator (Stochastorm) designed for modeling mesoscale convective storms, the main rainfall source in the Sahel. Developments include a model for storm occurrence, the explicit representation of extreme rainfall values, and an improvement in the modeling of sub-event intensities. Using high-resolution data from the AMMA-CATCH observatory, simulation outputs were confirmed to realistically represent key characteristics of MCSs, showing the simulator’s potential for use in impact studies.Finally, a modeling chain for producing future hydrological projections is developed and implemented in a Sahelian river basin (Dargol, 7000km2). The chain is original as it is the first attempt in West Africa to encompass the continuum of scales from global climate to convective storms, whose properties have major impacts on hydrological response and as a result local flood risk. The modeling chain components include the convection-permitting regional climate model (RCM) CP4-Africa, the only RCM (to date) explicitly resolving convection and providing long-term simulations in Africa; a bias correction approach; the stochastic precipitation generator Stochastorm; and a rainfall-runoff model specifically developed for Sahelian hydrological processes. The modeling chain is evaluated for a control period (1997-2006) then for future projections (ten years at the end of the 21st century). Hydrological projections show that peak annual flow may become 1.5-2 times greater and streamflow volumes may double or triple on average near the end of the 21st century compared to 1997-2006 in response to projected changes in precipitation.The results raise critical issues notably for hydrological engineering. Current methods used to evaluate flood risk in the region do not take non-stationarity into account, leading to a major risk of underestimating potential floods and undersizing the hydraulic infrastructure designed for protecting against them. It is also suggested to not only consider rainfall changes but also societal and environmental changes, interactions, and feedbacks in order to better attribute past hydrological hazards and their future trajectories to related causes.