Freshwater resources are subject to increasing pressure from a local to global scale. For many parts of the world groundwater is central to increasing water and food security. This is especially the case in regions such as the Kilombero Valley, Tanzania with highly variable or seasonal climates resulting in irregular access to surface water. With the background of scarce and deficient data on groundwater resources and the essential need of such information for wise management, this study aims at estimating the groundwater availability and variability in the Kilombero River Basin, Tanzania. A data set of drill logs provided information on soil types and related values of specific yield; depth of water tables; and depth to bedrock. These data enabled estimations of drainable water and (together with aquifer area) also quantification of the total groundwater volume. The latter was estimated to range between 48 km3 and 357 km3. The values are reasonable as an order of magnitude compared to previous quantifications and the annual water cycle in the valley. The spatial variability in drainable water was less than expected likely due to a high concentration of data points around the floodplain such that they have a similar physical setting. That mainly the valley bottom was covered by the data set indicates that findings reported here might be more appropriate for this specific area instead of the entire catchment. The methods applied give more uncertain results in high elevation areas with less aquifer depths, which could also be part of the explanation for the low spatial variability. However, a low variability indicates a homogenous access to groundwater on a regional level that should be positive in terms of mitigating competition over water. Due to uncertainties with the groundwater estimations, these results should not be overly interpreted but preferably used to indicate potential pathways forward for improvements of quantification approaches. Despite the wide uncertainty ranges the groundwater volumes that are easily accessible in the Kilombero Valley are not unlimited. In order to avoid inappropriate use of the groundwater resources, aquifer data must be considered in land-water management. Otherwise, conflicts are likely to increase due to competition over land and water resources.

<p> Wetland carbon sequestration is offset by carbon dioxide (CO₂) and methane (CH₄) emissions for which the magnitudes remain coarsely constrained. To better understand the spatial and temporal variations of gaseous carbon fluxes from marsh soils in a Mediterranean climate, I collected air and soil samples over the course of 10 months at Carpinteria Salt Marsh Reserve (CSMR) located in the County of Santa Barbara, California. The CSMR consists of four zones characterized by differences in elevation, tidal regime, soil properties, and vegetation. Twelve static chambers were deployed among two lower marsh zones, a mudflat, and a marsh-upland transition zone for fortnightly flux measurements from September 2015 to May 2016. In August 2015 and June 2016, soil cores up to 50 cm deep were extracted near the chambers, segmented by depth, and analyzed for soil moisture, bulk density, particle size distribution, electrical conductivity, pH, organic/inorganic carbon, and total nitrogen content. Averaged over the 9-month study period, the marsh-upland transition zone had the highest CO₂ fluxes at 5.3 &plusmn; 0.7 g CO₂ m^&ndash;2 d^&ndash;1, followed closely by the lower marsh zones (3.8 &plusmn; 0.6 g CO₂ m^&ndash;2 d^&ndash;1 and 2.8 &plusmn; 0.7 g CO₂ m^&ndash;2 d^&ndash;1), which were one order of magnitude higher than the CO₂ fluxes from the mudflat (0.4 &plusmn; 0.1 g CO₂ m^&ndash;2 d^&ndash;1). The CO₂ fluxes varied significantly on a seasonal scale but were not consistently correlated with environmental variables measured. The CH₄ fluxes had no clear seasonal patterns, but overall CH₄ flux rates from the lower marsh zones (2.2 &plusmn; 1.5 mg CH₄ m^&ndash;2 d^&ndash;1 and 1.9 &plusmn; 0.2 mg CH₄ m^&ndash;2 d^&ndash;1) surpassed those from the mudflat (0.2 &plusmn; 0.06 mg CH₄ m^&ndash;2 d^&ndash;1) by an order of magnitude, and the marsh-upland transition zone was a net methane sink (-0.07 &plusmn; 0.1 mg CH₄ m^&ndash;2 d^&ndash;1). The CH₄ fluxes correlated well with most soil properties by zone. Our results show that soil gaseous carbon fluxes from a coastal salt marsh vary by salt marsh zone.</p><p>

This thesis outlines results from an investigation of radon and radon daughter concentrations in limestone caves, from a geographical and geological perspective Investigations were conducted at all geographical scales, ranging from a national investigation in the four major caving regions of England and Wales to a detailed survey within a single cave in the Peak District. The measured radon concentrations in some limestone caves in England and Wales are amongst the highest ever recorded in the world Significant spatial and temporal variations were recorded m concentrations at all scales, within a single cave, between caves in the same region and between different regions Additionally, seasonal and diurnal variations in concentrations were highlighted. External climatic variables and the cave radon budget were demonstrated to account for variations in cave radon concentrations Within limestone caves seven primary sources of radon were identified and the relative importance of each to the overall radon budget was determined Sediments and the contaming limestone rock were the major sources although in certain cases water and the soil were demonstrated to be influential Models were developed to predict cave radon concentrations within a single cave However, these could not be transposed to predict radon concentrations in other caves in the same region or other regions The users of limestone caves were identified, their potential exposure times were examined and legislation concerning their exposure was discussed Four groups were identified as being at risk from radon while underground, and three groups were identified as bemg at little risk Methods by which the risk from radon exposure can be reduced were examined

No description available.

Wind energy is planned to play a major role in UK and Scottish Governments achieving renewable energy targets. The Southern Uplands of Scotland are a prime resource for wind and also home to the Eskdalemuir seismological station, a component of the International Monitoring System of the Comprehensive Nuclear-Test Ban Treaty. Previous work demonstrated that large wind turbines generate vibrations at frequencies significant to Eskdalemuir which are transferred into the ground and can be detected at many kilometres. In order to protect its capabilities, a 50 km consultation zone is enforced around Eskdalemuir for all new wind turbine developments, regardless of size. In this thesis, an integrated approach combines multiphysics modelling and seismic monitoring to characterise the vibrations from small wind turbines ( < 50 kW) to assess their effect on Eskdalemuir. Four wind turbines, differing in power, hub height and tower structure, have been monitored using a combination of accelerometers and seismometers attached to the tower and buried in the ground at distances up to 200 m from the turbine. Surface waves are shown to be the predominant wave type originating from the turbines; however, body waves are also present. The waves attenuate at a rate inversely proportional to the distance from the turbine, confirming that the sensors lie within the near-field radiation zone of the tower. Wind speed is shown to affect the tower vibration amplitude differently for each turbine. Visualisation of the bending modes and radiation patterns in the ground have been obtained through multiphysics modelling and this, together with seismic monitoring, has permitted the frequency peaks in the monitored spectrum to be identified as originating from either the turbine or an alternative source. Importantly, it has been shown that the algorithm currently used to assess wind farm vibrations around Eskdalemuir may not be suitable for small wind turbines.

As projections of future climate raise concerns over water availability and extreme hydrological events, global hydrology models are increasingly being employed to better understand our global water resources and how they may be affected by climate change. Being a relatively recent development in hydrological science, global hydrology modelling has not yet undergone the same level of assessment and evaluation as catchment scale hydrology modelling. Until now, global hydrology models have presented just one deterministic model output for use in scientific research. Recently, multi-model ensembles have compared these outputs for different global models, but this has been done prematurely as the uncertainties within individual models have yet to be understood. This study demonstrates a rigorous uncertainty investigation of the 123 parameters within the Mac-PDM global hydrology model over 21 global river catchments. Mac-PDM was selected for its relative simplicity amongst global hydrology models, and its suitability for application using high performance computer clusters. A new version of the model, Mac-PDM.14 is provided, with updated soil and vegetation classifications. This model is then subjected to a 100,000 parameter realisation Generalised Likelihood Uncertainty Estimation (GLUE) experiment, requiring 40 days of high performance computing time, and outputting over 2Tb of data. The top performing model parameterisation from this experiment provides an annual average error of 47% when compared to observed records, a 45% improvement over the previous version of the model, Mac-PDM.09. Given the computational expense of such an experiment, smaller sample sizes of parameter realisations are explored. Whilst the top performing parameterisation in a sample size as small as 1,000 can perform almost as well as that from 100,000 parameterisations, the number of good parameterisations is fewer, and the range of model uncertainty may therefore be significantly underestimated. Mac-PDM.14 is shown to have a lower mean absolute relative error than all models involved in both the Water and Global Change (WATCH) project and the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP). Parameter uncertainty is compared to model uncertainty, and the uncertainty range between the models within the WATCH and ISI-MIP projects is comparable to the parameter uncertainty within Mac-PDM.14. Catchment specific calibrations of the global hydrology model are explored, and it is demonstrated that the model performance is improved by 22 to 92%, for the Niger and the Yangtze respectively, with catchment specific parameter values over a global calibration. Approximate Bayesian Rejection is applied to explore the catchment specific parameter values that result in good parameter performance. Few trends can be identified from this analysis, which suggests that Mac-PDM may be over-parameterised. Catchment specific calibrations in both high latitude and arid to semi-arid regions show significant improvement over global calibration, which indicate a deficiency in model structure; the addition of a glacier component to Mac-PDM is recommended. Model calibrations are validated using the ISI-MIP forcing dataset, and the best model performance gives an error of 44%. This is a betterment on the performance with the WATCH forcing data used in calibration, and so implies that models not need to be recalibrated every time new forcing datasets are employed. This research highlights that the performance of global hydrology models can be significantly improved by running a parameter uncertainty assessment, and that in catchment scale studies, catchment specific calibration should be carefully considered. Furthermore, the uncertainty within individual global hydrology models is an important consideration that should not be overlooked as these models are increasingly included in ensembles and interdisciplinary studies.

Abstract not available.

The goal of this thesis aims two fundamental points. The first consists in making the development on the optimal spectral index to characterize the dynamics of a forest cover of a fir tree independently of the internal (underlying soil, topography, saturation and linearity) and external disturbing factors (BRDF and atmosphere) to covers starting from the data of simulation. The second point makes it possible to compare for the first time the potential of three spectral resolutions different (fine, average and broad) from sensors MODIS-EOS, VEGETATION-SPOT and AVHRR-NOAA to minimize the disturbing effects on the indices of vegetation in forest medium. The results obtained show that in general, the influence of the disturbing effects on the indexes of vegetation are complex. There is not only one component which dominates the met variations, but rather, of the combined influences of several factors. (Abstract shortened by UMI.)

Information on intensity-duration-frequency (IDF) of rainfall is commonly required for the design, construction, and management of many water resources projects involving natural hazards, due to extreme rainfall events. Design storms (DS) are determined from IDF relationships. Many hydraulic structures (dams, weirs, culverts, storm sewer systems, etc.) are designed to serve 50 years or more into the future. Yet, these structures are being sized for the climatic conditions based on the past records, before climate change. Thus, new design methods accounting for climatic change are needed to prevent potential losses and damages resulting from under-design. This research addresses the issue of the effect of climate change on design storms. The major objectives of this study are to detect trends in extreme rainfall, and to estimate anticipated changes in return periods of extreme rainfall events due to trends. In this study, trends (which might be attributed to climate change) are estimated for different durations of annual extreme rainfall using the regional average Mann-Kendall's S trend test. Numerical analysis was performed on 44 rainfall stations from the province of Ontario, Canada for a 20 and 25 year time frame. (Abstract shortened by UMI.)

This study is the second attempt to use the Basal Temperature of Snow (BTS) method to map permafrost in mountainous regions of northwestern Canada. It differs from the first study which took place in Wolf Creek in terms of (1) the methodology used to evaluate BTS, (2) the strategy used to avoid spatial autocorrelation in residuals, and (3) the climatic regions investigated. Two study areas, part of the Ruby Range (61&deg; 12' N, 138&deg; 19' W) and Haines Summit (59&deg; 37' N, 136&deg; 27' W) were selected for BTS sampling based on differing climatic conditions and previous knowledge of permafrost elevations from active rock glaciers. A total of 30 BTS measurements were made in the Ruby Range in the winter of 2006 and a total of 77 BTS values were obtained in the Haines Summit area during 2005 and 2006. From these results, modeled BTS surfaces were created using elevation and potential incoming solar radiation as independent variables in a multiple linear regression. At Haines Summit, potential incoming solar radiation was not significant in the model and thus was dropped. The surface of modeled BTS was then combined with a physical validation of permafrost presence completed during the late-summer of 2005 in a logistic regression. The modeled results produced permafrost probability maps for both study areas. Based on modeled results, permafrost underlies an estimated 282 km2 or 66% of the Ruby Range study area and 23--236 km 2 or 43--44% of the Haines Summit study area. An attempt was made to use the linear model derived in the Ruby Range at Haines Summit in order to examine the possibility of expanding predictions into new areas. Although the results produced similar total amounts of permafrost, the spatial distribution differed: permafrost probabilities were reduced at high elevations while lower elevation sites exhibited increased probabilities. The results of the model transfer illustrate the importance of the pit data in determining the total amount of permafrost, while knowledge of BTS ranges contributes to the spatial distribution of permafrost. With further study it is likely that generic models can be derived for areas of similar climate.