As climate warms during the 21st century, the resultant changes in water availability are a vital issue for society, perhaps even more important than the magnitude of warming itself. Yet our climate models disagree in their forecasts of water availability, limiting our ability to plan accordingly. This thesis investigates future water availability projections from Coupled Ocean-Atmosphere General Circulation Models (GCMs), primarily using two water availability measures: soil moisture and the Supply Demand Drought Index (SDDI). Chapter One introduces methods of measuring water availability and explores some of the fundamental differences between soil moisture, SDDI and the Palmer Drought Severity Index (PDSI). SDDI and PDSI tend to predict more severe future drought conditions than soil moisture; 21st century projections of SDDI show conditions rivaling North American historic mega-droughts. We compare multiple potential evapotranspiration (EP) methods in New York using input from the GISS Model ER GCM and local station data from Rochester, NY, and find that they compare favorably with local pan evaporation measurements. We calculate SDDI and PDSI values using various EP methods, and show that changes in future projections are largest when using EP methods most sensitive to global warming, not necessarily methods producing EP values with the largest magnitudes. Chapter Two explores the characteristics and biases of the five GCMs and their 20th and 21st century climate projections. We compare atmospheric variables that drive water availability changes globally, zonally, and geographically among models. All models show increases in both dry and wet extremes for SDDI and soil moisture, but increases are largest for extreme drying conditions using SDDI. The percentage of gridboxes that agree on the sign of change of soil moisture and SDDI between models is very low, but does increase in the 21st century. Still, differences between models are smaller than differences between SDDI and soil moisture projections. Chapter Three addresses the three major differences between SDDI and soil moisture calculations that shed light on why their future projections diverge: evaporation approximations, dependence on previous months' conditions, and the inclusion of additional variables such as runoff. We implement various changes in SDDI and a GCM vegetation scheme to test the sensitivity of each measure and to evaluate which alterations increase the similarity between SDDI and soil moisture. In addition to deconstructing the differences between SDDI and soil moisture, we analyze their projections regionally in Chapter Four. In seven regions (the southwest U.S., southern Europe, eastern China, eastern Siberia, Australia, Uruguay and Colombia), we 1) assess the forecasts of future water availability changes, 2) compare the atmospheric dynamical processes that produce rainfall and drought in the real world to the way it occurs in individual GCMs, 3) determine how these processes change as global temperatures increase, and 4) identify the most likely scenarios for future regional water availability. Chapter Five summarizes key findings by chapter, enumerating this dissertation's contributions to the field. It then discusses the limitations of existing models and measures, and suggests potential solutions for overcoming their predictive shortfalls. Finally, the chapter concludes with a proposal for future research to expand upon this dissertation work. This thesis highlights the global and zonal differences between two water availability measures, SDDI and soil moisture and identifies regions where they agree and disagree in 21st century modeled scenarios. It provides an explanation for differing projections in soil moisture and SDDI and proves that it is possible to bring convergence to their future projections, which is also applicable to PDSI. Finally, a detailed analysis of climatic changes from five GCMs made it possible to present the most likely scenarios for 21st century water availability in seven regions.

O estudo apresenta os principais aspectos da operação de secagem térmica de lodos gerados em estações de tratamento de esgotos, os tipos de equipamentos disponíveis no mercado que podem ser utilizados para esse fim e o comportamento da sorção de umidade pelo material seco quando em contato com o ar ambiente. A operação de secagem térmica é uma alternativa para a diminuição do peso e volume de lodos, com conseqüente diminuição dos custos de transporte e disposição final. É considerada, também, um processo de melhoria da qualidade do lodo, pois elimina os microrganismos patogênicos e, ao mesmo tempo, preserva a matéria orgânica presente no lodo, aspectos de importância fundamental quando o lodo/biossólido seco vai ser utilizado na agricultura. Os equipamentos para secagem térmica podem ser diretos ou indiretos. Os principais tipos são: secador rotativo, de soleiras múltiplas, de leito fluidizado, por transporte pneumático e transportadores de esteira. Cada tipo possui vantagens e desvantagens em relação aos demais. A eficiência do processo de secagem térmica é influenciada por uma série de fatores, como: consumo específico de energia, tipo de equipamento utilizado e teores de umidade inicial e final do material. Nos ensaios de laboratório, mediu-se os teores de umidade de equilíbrio do lodo produzido na ETE Baureri, localizada na Região Metropolitana de São Paulo, sob diferentes condições de umidade relativa do ar ambiente. Com esses valores, obteve-se a curva de umidade de equilíbrio do material. Como resultado dessa experiência conclui-se que para cada umidade relativa do ar ambiente há um teor de umidade de equilíbrio do lodo. / The study presents the main aspects of a thermal drying operation of the sludge produced by wastewater treatment plants, the types of equipment likely to be used for this purpose and the sorption behavior of the water contents by the dry material when in contact with the air. The thermal drying operation is an alternative to reduce the weight and volume of the sludge production with a resulting decrease in transportation and final disposal costs. It is also deemed to be a process that improves the sludge quality because includes the elimination of pathogenic microorganisms while preserving the existing organic matter of the sludge, which are aspects of the utmost importance whenever the dry biosolid will be used as fertilizer in agriculture. The thermal drying equipment can be direct or indirect. The main types are: rotary dryers, multi-tray dryers, fluid bed dryers, flash dryers, and conveyor dryers. Each type presents advantages and disadvantages when compared to one another. The efficiency of the thermal drying process is affected by several aspects, such as specific consumption of energy, type of equipment used, and initial and final water contents of the material. The laboratory tests measured the equilibrium moisture contents of the sludge produced by Barueri Wastewater Treatment Plant, located in the São Paulo Metropolitan Region, under different conditions of environment relative humidity. Based on these measurements, an equilibrium moisture curve of the material was obtained. The major conclusion of the experiment was that to each environment relative humidity there is a corresponding equilibrium moisture of the sludge.

abstract: Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction, drought monitoring, and weather forecasting. Empirical evidences have demonstrated the existence of emergent relationships and scale invariance properties in θ fields collected from the ground and airborne sensors during intensive field campaigns, mostly in natural landscapes. This dissertation advances the characterization of these relations and statistical properties of θ by (1) analyzing the role of irrigation, and (2) investigating how these properties change in time and across different landscape conditions through θ outputs of a distributed hydrologic model. First, θ observations from two field campaigns in Australia are used to explore how the presence of irrigated fields modifies the spatial distribution of θ and the associated scale invariance properties. Results reveal that the impact of irrigation is larger in drier regions or conditions, where irrigation creates a drastic contrast with the surrounding areas. Second, a physically-based distributed hydrologic model is applied in a regional basin in northern Mexico to generate hyperresolution θ fields, which are useful to conduct analyses in regions and times where θ has not been monitored. For this aim, strategies are proposed to address data, model validation, and computational challenges associated with hyperresolution hydrologic simulations. Third, analyses are carried out to investigate whether the hyperresolution simulated θ fields reproduce the statistical and scaling properties observed from the ground or remote sensors. Results confirm that (i) the relations between spatial mean and standard deviation of θ derived from the model outputs are very similar to those observed in other areas, and (ii) simulated θ fields exhibit the scale invariance properties that are consistent with those analyzed from aircraft-derived estimates. The simulated θ fields are then used to explore the influence of physical controls on the statistical properties, finding that soil properties significantly affect spatial variability and multifractality. The knowledge acquired through this dissertation provides insights on θ statistical properties in regions and landscape conditions that were never investigated before; supports the refinement of the calibration of multifractal downscaling models; and contributes to the improvement of hyperresolution hydrologic modeling. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018

Chiu, Ming Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 139-155). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgements --- p.v / Table of Contents --- p.vii / List of Tables --- p.xi / List of Figures --- p.xiii / List of Plates --- p.xiv / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.1.1 --- Environment of Hong Kong --- p.1 / Chapter 1.1.1.1 --- Flat land area --- p.1 / Chapter 1.1.1.2 --- Population --- p.2 / Chapter 1.1.1.3 --- Climate --- p.2 / Chapter 1.1.2 --- Landslides in Hong Kong --- p.4 / Chapter 1.1.2.1 --- Landslide history --- p.4 / Chapter 1.1.2.2 --- Government actions on landslide prevention --- p.7 / Chapter 1.1.3 --- Slopes in Hong Kong --- p.8 / Chapter 1.1.4 --- Slope stabilization --- p.10 / Chapter 1.1.4.1 --- Conventional methods of slope stabilization --- p.10 / Chapter 1.1.4.2 --- Biotechnical stabilization --- p.13 / Chapter 1.2 --- Situation in Hong Kong --- p.16 / Chapter 1.2.1 --- Slope protection in the past --- p.16 / Chapter 1.2.2 --- Government action on improving slope appearance --- p.16 / Chapter 1.2.3 --- Proprietary slope greening techniques --- p.19 / Chapter 1.3 --- Vegetation growth on slopes --- p.22 / Chapter 1.3.1 --- Basic requirements of plants --- p.22 / Chapter 1.3.2 --- Potential problems of proprietary systems on shotcreted cut slopes --- p.24 / Chapter 1.3.2.1 --- Steep gradient --- p.24 / Chapter 1.3.2.2 --- Thin soil --- p.24 / Chapter 1.3.2.3 --- Rainfall seasonality --- p.25 / Chapter 1.4 --- Current study --- p.26 / Chapter 1.4.1 --- Objectives --- p.26 / Chapter 1.4.2 --- Significance --- p.26 / Chapter 1.4.3 --- Thesis layout --- p.27 / Chapter Chapter 2 --- Soil water status and vegetation of cut slopes --- p.30 / Chapter 2.1 --- Introduction --- p.30 / Chapter 2.2 --- Materials and methods --- p.36 / Chapter 2.2.1 --- Study site --- p.36 / Chapter 2.2.2 --- In situ measurements and substrate sampling --- p.43 / Chapter 2.2.3 --- Physical properties of substrates on slopes --- p.43 / Chapter 2.2.3.1 --- Slope angle --- p.43 / Chapter 2.2.3.2 --- Substrate thickness --- p.43 / Chapter 2.2.3.3 --- Soil moisture --- p.43 / Chapter 2.2.3.4 --- Soil texture --- p.43 / Chapter 2.2.3.5 --- Bulk density --- p.44 / Chapter 2.2.3.6 --- Water retention capacity --- p.44 / Chapter 2.2.4 --- Chemical properties of substrates on slopes --- p.44 / Chapter 2.2.4.1 --- pH --- p.44 / Chapter 2.2.4.2 --- Conductivity --- p.45 / Chapter 2.2.4.3 --- Organic matter --- p.45 / Chapter 2.2.4.4 --- Total Kjeldahl nitrogen --- p.45 / Chapter 2.2.4.5 --- Mineral nitrogen (ammonium and nitrate) --- p.45 / Chapter 2.2.4.6 --- Carbon:Nitrogen --- p.46 / Chapter 2.2.4.7 --- Total phosphorus --- p.46 / Chapter 2.2.4.8 --- Available phosphorus --- p.46 / Chapter 2.2.4.9 --- Major extractable cations --- p.46 / Chapter 2.2.5 --- Green coverage on slopes --- p.46 / Chapter 2.2.6 --- Statistical analysis --- p.47 / Chapter 2.3 --- Results --- p.47 / Chapter 2.3.1 --- Rainfall characteristics --- p.47 / Chapter 2.3.2 --- Soil moisture --- p.49 / Chapter 2.3.3 --- Green coverage --- p.52 / Chapter 2.3.4 --- Physical properties of substrate on slopes --- p.55 / Chapter 2.3.5 --- Chemical properties of substrate on slopes --- p.57 / Chapter 2.4 --- Discussion --- p.61 / Chapter 2.4.1 --- Soil moisture and vegetation growth --- p.61 / Chapter 2.4.2 --- Soil nutrients and vegetation growth --- p.66 / Chapter 2.4.3 --- Other substrate properties and vegetation growth --- p.69 / Chapter 2.5 --- Summary --- p.75 / Chapter Chapter 3 --- Surface runoff and soil erosion of cut slopes --- p.76 / Chapter 3.1 --- Introduction --- p.76 / Chapter 3.2 --- Materials and methods --- p.84 / Chapter 3.2.1 --- Study site --- p.84 / Chapter 3.2.2 --- Experimental setup --- p.84 / Chapter 3.2.3 --- Surface runoff and soil loss --- p.88 / Chapter 3.2.4 --- Nutrient loss in runoff --- p.89 / Chapter 3.2.4.1 --- Total Kjeldahl Nitrogen --- p.89 / Chapter 3.2.4.2 --- Mineral nitrogen (ammonium and nitrate) --- p.89 / Chapter 3.2.4.3 --- Total phosphorus --- p.89 / Chapter 3.2.4.4 --- Available phosphorus --- p.90 / Chapter 3.2.5 --- Other substrate properties --- p.90 / Chapter 3.2.5.1 --- Soil texture --- p.90 / Chapter 3.2.5.2 --- Bulk density --- p.90 / Chapter 3.2.5.3 --- Soil compaction --- p.90 / Chapter 3.2.5.4 --- Water retention capacity --- p.90 / Chapter 3.2.5.5 --- Organic matter --- p.90 / Chapter 3.2.6 --- Vegetation coverage and green coverage on slope --- p.91 / Chapter 3.2.7 --- Statistical analysis --- p.91 / Chapter 3.3 --- Results --- p.91 / Chapter 3.3.1 --- Meteorological characteristics --- p.91 / Chapter 3.3.2 --- Surface runoff and runoff coefficient --- p.92 / Chapter 3.3.2.1 --- Surface runoff and runoff coefficient between different treatments --- p.92 / Chapter 3.3.2.2 --- Surface runoff and runoff coefficient between different proprietary systems --- p.97 / Chapter 3.3.3 --- Soil loss --- p.98 / Chapter 3.3.3.1 --- Soil loss between different treatments --- p.98 / Chapter 3.3.3.2 --- Soil loss between different proprietary systems --- p.99 / Chapter 3.3.4 --- Nutrient loss --- p.99 / Chapter 3.3.4.1 --- Nutrient loss between different treatments --- p.99 / Chapter 3.3.4.2 --- Nutrient loss between different proprietary systems --- p.104 / Chapter 3.3.5 --- Substrate properties of proprietary systems --- p.104 / Chapter 3.3.6 --- Vegetation coverage and green coverage --- p.107 / Chapter 3.3.7 --- Relationship between rainfall and erosional parameters --- p.110 / Chapter 3.4 --- Discussion --- p.117 / Chapter 3.4.1 --- Surface runoff and runoff coefficient between different treatments --- p.117 / Chapter 3.4.2 --- Relationship between rainfall characteristics and surface runoff --- p.122 / Chapter 3.4.3 --- Soil loss between different treatments --- p.125 / Chapter 3.4.4 --- "Relationship between rainfall characteristics, surface runoff and soil loss" --- p.126 / Chapter 3.4.5 --- Nutrient loss between different treatments --- p.128 / Chapter 3.4.6 --- Surface runoff and erosional losses between different proprietary systems --- p.129 / Chapter 3.5 --- Summary --- p.132 / Chapter Chapter 4 --- Conclusions --- p.134 / Chapter 4.1 --- Summary of major findings --- p.134 / Chapter 4.2 --- Implications of the study --- p.136 / Chapter 4.3 --- Limitations of the study --- p.137 / Chapter 4.4 --- Suggestions for further investigation --- p.138 / References --- p.139 / Appendices --- p.156

O estudo apresenta os principais aspectos da operação de secagem térmica de lodos gerados em estações de tratamento de esgotos, os tipos de equipamentos disponíveis no mercado que podem ser utilizados para esse fim e o comportamento da sorção de umidade pelo material seco quando em contato com o ar ambiente. A operação de secagem térmica é uma alternativa para a diminuição do peso e volume de lodos, com conseqüente diminuição dos custos de transporte e disposição final. É considerada, também, um processo de melhoria da qualidade do lodo, pois elimina os microrganismos patogênicos e, ao mesmo tempo, preserva a matéria orgânica presente no lodo, aspectos de importância fundamental quando o lodo/biossólido seco vai ser utilizado na agricultura. Os equipamentos para secagem térmica podem ser diretos ou indiretos. Os principais tipos são: secador rotativo, de soleiras múltiplas, de leito fluidizado, por transporte pneumático e transportadores de esteira. Cada tipo possui vantagens e desvantagens em relação aos demais. A eficiência do processo de secagem térmica é influenciada por uma série de fatores, como: consumo específico de energia, tipo de equipamento utilizado e teores de umidade inicial e final do material. Nos ensaios de laboratório, mediu-se os teores de umidade de equilíbrio do lodo produzido na ETE Baureri, localizada na Região Metropolitana de São Paulo, sob diferentes condições de umidade relativa do ar ambiente. Com esses valores, obteve-se a curva de umidade de equilíbrio do material. Como resultado dessa experiência conclui-se que para cada umidade relativa do ar ambiente há um teor de umidade de equilíbrio do lodo. / The study presents the main aspects of a thermal drying operation of the sludge produced by wastewater treatment plants, the types of equipment likely to be used for this purpose and the sorption behavior of the water contents by the dry material when in contact with the air. The thermal drying operation is an alternative to reduce the weight and volume of the sludge production with a resulting decrease in transportation and final disposal costs. It is also deemed to be a process that improves the sludge quality because includes the elimination of pathogenic microorganisms while preserving the existing organic matter of the sludge, which are aspects of the utmost importance whenever the dry biosolid will be used as fertilizer in agriculture. The thermal drying equipment can be direct or indirect. The main types are: rotary dryers, multi-tray dryers, fluid bed dryers, flash dryers, and conveyor dryers. Each type presents advantages and disadvantages when compared to one another. The efficiency of the thermal drying process is affected by several aspects, such as specific consumption of energy, type of equipment used, and initial and final water contents of the material. The laboratory tests measured the equilibrium moisture contents of the sludge produced by Barueri Wastewater Treatment Plant, located in the São Paulo Metropolitan Region, under different conditions of environment relative humidity. Based on these measurements, an equilibrium moisture curve of the material was obtained. The major conclusion of the experiment was that to each environment relative humidity there is a corresponding equilibrium moisture of the sludge.

First order fire effects in mixed grass and tallgrass prairies may differ between current and historic fire regimes. To determine potential differences, the thermal dynamics of nine prescribed grassland fires and six experimental fires were evaluated. Fires were instrumented with dataloggers and arrays of up to twelve thermocouples set at heights ranging from -5 cm to 300 cm. Soil moisture and texture were documented, along with fuel characteristics. A series of experimental fires allowed soil moisture to be manipulated while minimizing other variables. Maximum temperature for the prescribed fires was 875°C at 75cm, and for the experimental fires 920°C at 10 cm. In experimental fires, the greatest temperature difference was at the surface with the dry substrate averaging 130°C higher than saturated. Average temperatures at -1 cm differed by 33°C. At 60°C, residence times in dry substrate averaged almost four minutes, while the average for saturated treatment was only 1 second. Surface residence times on dry substrate averaged over 7 minutes, almost 3 times longer than saturated. Soil moisture was shown to influence relative humidity and fine fuel moisture near the ground surface. An increased evaporation of soil water at the surface is suggested by a slight drop in subsurface temperatures as the flaming front moves over the surface. These data suggest that soil moisture affects fire intensity, decreasing temperatures at all levels of a fire. Temperatures and residence times were compared with data from studies documenting temperatures significantly affecting seed germination and edaphic effects at and below the surface. Temperatures increasing the germination of some seeds were found at all heights. Temperatures documented can be expected to decrease organic matter content and aggregate stability at the surface, slightly increasing erodibility. Thermal dynamics from the fires in this study represent a broad range of grassland fires under conditions common for prescribed fire. Soil moisture appears to significantly affect temperatures and residence times below, at, and above the soil surface. Data were compared with output from FOFEM 5.2 to access the applicability of FOFEM for use in mixed grass and tallgrass prairie. FOFEM consistently underestimated soil heating by up to 419°C.

One of the major processes in lumber industry is wood drying. This process consumes large amounts of energy and capital, and due to the length of time it takes, it acts as a governing factor in lumber production levels. Development of improvements in processes and equipment used in wood drying can be expedited through computer simulation of various drying procedures. These numerical simulations depend on the accuracy of numerical models representing wood transport properties, including functional dependency of liquid permeability through wood with respect to local saturation level. Data available in the literature mainly represent wood permeability properties at fully saturated levels. This is an indication of steady state flow methods used in determining these values which are based on wide spread use of similar methods utilized in studies on fluid flow through soil. This research determines unsaturated wood permeability using transient liquid flow methods that are more representative of actual drying process. Initially saturated wood samples are spun in a low speed centrifuge to induce liquid migration through the cell structures. Transient local moisture profiles along the sample are measured using a scanning gamma ray densitometer. Numerical integration and curve fitting procedures are used to process these data. Finally, utilizing liquid continuity equation the functional dependency of permeability with respect to saturation is calculated. Some permeability results appear to be reasonable when compared with actual wood behavior during drying. Measurement procedures prove to yield accurate results for moisture content and saturation levels in wood with less than 5% relative error in average saturation level of .75. However, due to natural inhomogeneities in wood cellular structure, the final calculated results for unsaturated permeability show high levels of uncertainty (up to 112% relative error).

Thesis (MSC.Agriculture)) --University of Limpopo, 2009. / The aim of this experiment was to evaluate the effect of moisture stress on tomato, using non-destructive remote sensing techniques and agronomic traits under field and greenhouse conditions. Two tomato cultivars Roma VF and Flora Dade were used for the trial. The soil was fertilized optimally for all nutrients to avoid other stresses except water stress; a 2x2 factorial experiment was conducted using two levels of water regimes (stressed vs. control (non-stressed)) having four replicates and two cultivars using a Completely Randomized Design. Pots were put under greenhouse and field conditions. Canopy temperature was measured using an infrared thermometer, NDVI values were recorded using a green seeker hand-held optical sensor unit and stomatal opening were determined using a leaf porometer. Other agronomic traits including days taken for 50% flowering, plant height, number of fruits per plant and fruit yield per plant were recorded. Leaf temperature in stressed plants was high as compared to non-stressed plants, whereas NDVI and stomata conductance values were low. Number of fruits per plant was low; each plant had 4.00 fruits under field conditions and 5.00 fruits per plant under greenhouse conditions as compared to 9.00 fruits under field conditions and 13.00 under greenhouse conditions for non stressed plants. Stressed plants were shorter as compared to non-stressed plants and days taken for 50% flowering were delayed in both cultivars for stressed plants. Stressed plants showed a sign of stress at early stages of plant development. Most of these signs were found on the plants rather than on the fruits, the shape of the main stem of a growing plant was one of the good indicators as it became thin and stringy under stressed conditions. The experiment showed that it is possible to evaluate the effect of moisture stress on tomato by the use of canopy temperature, NDVI, stomatal conductance and agronomic traits.

Many problems of management of irrigated soils require a knowledge of the soil moisture status and its relationship to plant growth before they can be solved.

Water moves in soil in response to potential gradients. The basic equation for this movement is the generalized flow equation: v = - KV0 in which v is volume of water passing through a unit area in unit time, K is the conductivity coefficient, V is the gradient operator (vector), and V 0 is the potential gradient.