We use cosmogenic 10Be analysis of fluvial sediments and bedrock to estimate erosion rates (103 – 106 year timescale) and to infer the distribution of post-orogenic geomorphic processes in the Blue Ridge Province in and around Shenandoah National Park, VA. Our sampling plan was designed to investigate relationships between erosion rate, lithology, slope, and basin area. Fifty-nine samples were collected from a variety of basin sizes (<1 – 3351 km2) and average basin slopes (7 - 26°) in each of four different lithologies that crop out in the Park: granite, metabasalt, quartzite, and siliciclastic rocks. The samples include bedrock (n = 5), fluvial sediment from single-lithology basins (n = 43), and fluvial sediment from multilithology basins (n = 11): two of these samples are from rivers draining streams exiting the eastern and western slopes of the Park (Rappahannock and Shenandoah Rivers). Inferred erosion rates for all lithologies for fluvial samples range from 3.8 to 24 m/My. The mean erosion rate for single-lithology basins in the Park is 11.6 ± 4.8 m/My. Singlelithology erosion rates ranges for fluvial samples are: granite (basin size = ~0.4-40 km2 and slope = 11-23°), 7.9–22 m/My; metabasalt (basin size = ~1-25 km2 and slope = 11-19°), 4.8–24 m/My; quartzite (basin size = ~0.1-9 km2 and slope = 12-23°), 4.7–17 m/My; and siliciclastic rocks (basin size = ~0.3-13 km2 and slope = 18-26°), 6.2–17 m/My. The mean erosion rate for multilithology basins (basin size = ~1-3351 km2 and slope = 7-22°) is 10.2 m/My, and individually for the Shenandoah River 7.3 m/My and the Rappahannock River 13.8 m/My. Bedrock erosion rates range from 2.4-13 m/My across all lithologies, with a mean erosion rate of 7.9 ± 5.0 m/My. Grain-size specific 10Be analysis of four samples showed no consistent trend of concentration with grain size. These data support Hack’s dynamic equilibrium model. Slope and erosion rate are not well correlated, and mean erosion rates are similar for different lithologies. Cosmogenicallydetermined erosion rates in Shenandoah Park are similar to or lower than those reported elsewhere in the Appalachians including those of Matmon and others (2003), 25 to 30 m/My for metaclastic rocks in the steep Great Smoky Mountains, Reuter and others (2004), 4 – 54 m/My in Susquehanna River basin for shale, sandstone, and schist, and Sullivan and others (2006), 6-38 m/My in the micaceous schist and gneiss of the Blue Ridge Escarpment. Cosmogenic erosion rates (integration over 104 yrs) in the Blue Ridge province of Shenandoah National Park are consistent with long-term unroofing rates (integration over 107 yrs) estimated from U-Th/He measurements (11-18 m/My) in samples collected near the Blue Ridge Escarpment by Spotila and others (2004), and fission tracks (20 m/My) in the Appalachians by Naeser and others (2005). The consistency of denudation rates integrated over very different periods of time suggests steady erosion most likely in balance with, and driving isostatic uplift of rock.

High-resolution physical and biogeochemical field data in central Lake Erie during the summers of 2008-2009 along with a three-dimensional numerical model were used to investigate the dynamics of basin scale waves and sediment resuspension mechanisms. In Chapter 2, the modal response of the Poincaré waves in the lake is assessed. The vertical mode-one Poincaré wave was found to be mostly dominant during the seasonal stratified period. The horizontal modal structure was also investigated in a sensitivity analysis, using the numerical model forced with real and idealized wind events. In Chapter 3, dynamics of bottom mixed layer (BML), primarily forced in the outer layer by surface seiches and Poincaré waves is studied for two 10-days representative intervals of weak and strong stratification. Shear velocity was calculated by least square fitting the well-known law-of-the-wall equation to observed near-bed velocity in a region of constant shear stress. Height of the BML is computed using water density (from water temperature) and compared with heights of logarithmic layer approximated using the law-of-the-wall equation and its modified form with buoyancy length scale term. Published equations for estimating BML heights are evaluated and modified for the lake. In Chapter 4, we investigate physical processes leading to sediment resuspension in the lake including surface waves (periods of 4-8s), up/downwelling events (periods of 3-4 day), and high frequency internal waves (periods of 5-45min). Temporal changes in near-bottom sediment resuspension are illustrated using changes in acoustic backscatter signals from current profilers and time series of turbidity measurements to identify the mechanism responsible for sediment resuspension. Resuspension is parameterized as a function of the critical velocity ~0.25ms-1 and from surface waves using linear wave theory. Finally, based on the critical velocity and sediment grain size analysis (from in-site field data), critical shear stress and Shields parameter are calculated and compared with previous observations in Lake Erie and in other locations suggesting a modified Shields diagram for silty bed materials. / Thesis (Ph.D, Civil Engineering) -- Queen's University, 2012-12-19 20:54:15.832

Soil salinity, a yield-limiting condition, has plagued crop production for centuries by reducing crop productivity. Research has introduced methods for successfully managing soil salinity. This research discusses the adaptation of established management methods to create new soil salinity management techniques. One adapted technique is an automated crop screening apparatus. A new design was created and successfully used in rapidly screening two strawberry cultivars to determine their tolerance to salinity. Screening crops and determining their tolerance to yield-limiting conditions are essential in managing soil salinity. Another salinity management tool used in this research was electromagnetic induction (EMI). EMI was used to complete a basin-scale inventory over an 18,000 ha study area in Cache County, Utah. The data obtained during the inventory were used to create EMI calibration models and a basin-scale map showing the spatial distribution of apparent soil electrical conductivity (ECa). These new methods for crop tolerance screenings and basin-scale salinity inventories will assist in successfully managing soil salinity and decrease its effect on the global food supply.

The aim of the thesis is to examine the Integrated Water Resource Management (IWRM) Planning that is recognized as the most appropriate approach in the international arena for the wise-use and sustainability of water resources. In this framework, the thesis has been organized in two major parts: Theoretical framework and the Konya Closed Basin case study analysis. The first part draws a theoretical framework on IWRM planning and discusses its principles, aims and implementation tools through an internationally accepted point of view. The second part, meanwhile, examines the interpretation of the IWRM planning in Turkey and its implementation in the case of the Konya Closed Basin IWRM Planning Process. The study reveals that only an integrated approach at the basin scale can solve the water demand problems of different human activities, which puts pressure on the carrying capacity of the water resources and their basins. Despite the inadequacies in the related institutional and legal frameworks in Turkey, Konya Closed Basin IWRM planning, especially Tuz Lake Management Plan studies, comes to forefront as a pioneering IWRM planning practice: The capacity building, public participation, and awareness raising principles of the IWRM planning approach have been positively realized during this planning process. Besides, the components of the plan are also compatible with the theory of IWRM planning, which consists of strategic, goal-oriented, and participatory planning approaches.

Utilising tidal currents as a renewable energy resource is presently under consideration to meet the requirements of increasing worldwide energy demand and the need to reduce carbon emissions. In this respect, in-stream tidal devices are proposed to convert the kinetic energy of currents into useful extractable power. In order to extract a useful amount of energy from tidal currents, the proposed devices need to be deployed in an array or farm-like format. Due to the thrust exerted by the devices within an array, the natural flow regime will inevitably be changed. In light of this, this study aims to estimate the maximum power that can be extracted by tidal turbine arrays and assess the far-field effects of energy extraction in the designated areas around the UK for various array configurations. In this thesis, the ocean tides are modelled using the long wave equations, commonly referred as the shallow water equations (SWEs). A numerical solver based on a Runge-Kutta discontinuous Galerkin finite element method is employed to solve the SWEs. One main advantage of the discontinuous Galerkin method is that it approximates the solution individually at each element, which allows for discontinuities within the solution system while ensuring mass conservation locally and globally. The selected numerical solver has been verified against several benchmark tests. It is then modified to include a line discontinuity to represent the effect of tidal turbine array(s) in a coastal basin. The algorithm implemented in the numerical solver involves a sub-grid model, which is based on Linear Momentum Actuator Disk Theory (LMADT) to approximate the local flow-field in the presence of the turbines. This near-field approach allows the flow velocity at the turbine to be estimated with a greater accuracy. As the power available to the turbines is related to the velocity at the turbine blades, the characterisation of the designated tidal site as a resource using LMADT may be more accurate than previously proposed methods. An additional advantage of using LMADT is that it provides a distinction between the power extracted by the turbines and the total amount of power that is removed from the tidal stream, including the wake mixing losses. The methodology employed in this thesis has been applied to two tidal basins around the UK; the Anglesey Skerries (a headland) and the Bristol Channel (an oscillating bay). A comprehensive unstructured triangular finite element model has been constructed to simulate the naturally occurring tides at these regions. The constructed model has then been validated against field measurement. The validated model is used to conduct parametric studies, which evaluate the importance of tidal array locations, configurations and operating conditions on the available power at the Anglesey Skerries and the Bristol Channel sites. The parametric study aims to evaluate a realistic upper limit of available power at each site considered. This study also provides a unique analysis to examine the potential tidal farm interactions by deploying several tidal arrays at both Anglesey Skerries and the Bristol Channel.

In the present work, methodology of statistical analysis of change evolved by Kundzewicz and Robson (204) is revised to obtain a robust methodology named as “Comprehensive Aproach” which addresses research gaps of earlier method, as also those found by literature review. Main aspects of the revised method are: 1) importance of graphical representations as first step, in which, if line spectrum has constant spectral density function then time series is random and no need of further trend detection, 2) importance of computation of statistical parameters of data for deciding type of step change test to be used and for cross checking results of exploratory data analysis (EDA), 3) application of EDA, statistical parameters and checking assumption(s) about the data by statistical test(s) is suggested and also results of these steps can be used to cross check results of each other, 4) suggested basis for selection of step change test(s) i.e. evaluation of two aspects of step change viz. detection and location of step change, 5) suggested basis for selection of trend detection tests i.e. evaluation of all four aspects of trend viz. magnitude, statistical significance, beginning and end of trend and nature of trend, 6) evaluation of regional significance is suggested as essential wherever applicable. The revised method i.e. “Comprehensive Approach” is applied for the trend detection of rainfall of seven homogenous rainfall regions and al India at annual, monthly and seasonal temporal scales for three time periods 1901-203, 1948-203 and 1970-203. Between 100 N to 300 N, there was marked increase in precipitation from 190 to 1950s, but decrease after about 1970 (Trenberth et al., 207). Thus starting years of three time periods are selected as 1901, 1948 and 1970. To have similarity of end year, in analysis periods given in chapters 1, 2 and chapters 3, 4; their end years are kept close to each other i.e. end year of analysis periods is 203 in chapters 1, 2 and end year of analysis periods is 204 in chapters 3, 4. Thus 203 are considered as common end year of three time periods. Burn and Elnur (202) sugested that least number of years required for ensuring statistical validity of results of trend detection are 25 years. So in the third time period (1970-203), the duration is 34 years which is more than 25 years. Three time periods are having data of 103 years (1901-203), 56 years (1948-203) and 34 years (1970- 203) so effect of different time durations on trend detection analysis results is studied. Also temporal scales used in trend detection analysis are annual, monthly and seasonal (4 seasons) thus presence of trend is assessed in these main temporal scales. Results of the analysis showed that, statistically significant trends are found in: 1) winter rainfall time series of peninsular India (PENIN) region for the time period 1901-203, 2) pre-monsoon rainfall time series of north west India (NWIND) and central north east India (CNEIN) regions for the time period 1948-203, 3) monsoon rainfall time series of west central India (WCIND) region for the time period 1948-203, 4) August month rainfall time series of north east India (NEIND) region for the time period 1901-203, 5) June month rainfall time series of NEIND region for the time period 1948-203, 6) Also regionally significant trends are detected in pre- monsoon rainfall time series of five homogeneous regions for the time period 1948-203. Regionally significant trends are detected in pre-monsoon rainfall time series of five homogeneous regions for the time period 1948-203. But effect of cross correlation between rainfall time series of stations of subdivisions and between the sub-divisions in a region is not accounted in the field/regional significance evaluation and Hegel et al. (207) suggested that reactions to external forcing in trends of regional precipitation trends exhibit weak signal to noise ratios and likely to exhibit strong variations in space because of dependency of precipitation on geographic parameters like pornography and atmospheric circulation. Thus attribution of precipitation is more difficult. Also Saikranthi et al. (2013) suggested that homogeneity of rainfall zones may change in future. So, attribution of trends detected in pre-monsoon rainfall time series of five homogeneous regions was not possible. The results of statistically significant trends are confirmed by smoothing curves, innovative trend analysis plots and Sen.’s slope estimates. Contributions by present trend detection study on rainfall of homogenous regions by using “Comprehensive Approach” method are: 1) modification of guidelines of statistical analysis of change to evolve a robust method termed as “Comprehensive Approach”, 2) systematic trend detection analysis is performed pertaining to the rainfall of core monsoon India (CORIN) region and homogeneous India (HOMIN) region, which was not done earlier, 3) systematic trend detection analysis is performed on the rainfall of al India and seven homogenous regions concurrently for aforesaid temporal scales and time periods (except regional significance evaluation only for five homogeneous regions), which was not done earlier, 4) Man Kendal test with block bootstrapping approach (MKBBS) test (not effected by serial correlation) is used for trend detection of serially correlated data and Man Kendal (MK) test is used for trend detection of serially uncorrelated data. Sen.’s slope is used for evaluation of trend magnitude, 5) evaluation of field/regional significance of trends in rainfall over five homogenous regions is performed, which was not done earlier, 6) Location of beginning, end and progress of trend in rainfall of all India and seven homogenous regions concurrently is performed, which was not done earlier. As mentioned aforesaid, attribution of regionally significant trends detected in pre-monsoon rainfall time series of five homogeneous regions for the time period 1948-203 was not possible because of non-accounting of effects of cross correlation, attribution of rainfall is difficult and homogeneity of rainfall zones may change in future as discussed above in detail. So a thorough investigation about trends in rainfall, three temperatures (minimum, mean and maximum) and stream flow at regional (basin) scale was proposed to be ascertained. As Tapi basin is exposed to occurrence of heavy floods (Joshi and Shah, 2014) and it is climatically sensitive (Bhamare and Agone, 201; Gosain et al. 206; Deshpande et al., 2016), it is considered as study area. The trend detection analysis of gridded data (chapter 4) and regional time series (chapter 3) of rainfall and three temperatures data (1971-204) along with that for station data of stream flow (1979-204) of five gauging stations (chapter 4) is carried out using “Comprehensive Approach” for all temporal scales. Common available end year of data of rainfall, temperature and stream flow was 204 as data after 204 was not available for stream flow for all five gauging stations. Also data of rainfall (0.50 x 0.50) was available from year 1971, which was common starting year among data of rainfall and three temperatures. Also common starting year of stream flow data was 1979. Because of unavailability of rainfall data (0.50 x 0.50) before 1971, the three time periods used in chapters 1 and 2 are not used in chapters 3 and 4, thus only one time period is used for rainfall and three temperatures (1971-204) and stream flow (1979-204). The analysis has shown the presence of regionally significant rends in the gridded data of annual mean temperature (Tmean) and winter Tmean over Tapi basin apart from significant trends found in regional time series of annual Tmean and winter Tmean of Tapi basin. Monthly, winter and pre- monsoon stream flow volume time series have also shown regionally significant trends over five gauging stations of Tapi basin. Main contributions of the trend detection analysis of hydro- climatic variables of Tapi basin are: 1) grid wise, regional scale and station wise trend detection of three temperatures, rainfall and stream flow respectively is performed, which was not done earlier, 2) regional significance evaluation of gridded data (rainfall and three temperatures) and station data of stream flow (five stream flow gauging stations) is performed, which was not done earlier, 3) all four aspects of trend of hydro-climatic variables are evaluated, which was not done earlier, 4) systematic trend detection study of gridded, regional and station data of hydro-climatic variables is performed in present study which was not done earlier. After detection of regionally significant trends, next step is finding the causal factors through attribution study. Once causal factors of climate change observed in given variable are found, then remedial measures can be carried out for minimizing the effect of these factors on climate change observed in given variable. There are three main methods of attribution found in literature viz. finger printing, optimal finger printing and artificial neural network (ANN) model. In finger printing method only the leading empirical orthogonal function (EOF) is used, so this method is conservative. In optimal finger printing, multivariate regression is used, which has certain assumptions which are difficult to be fulfilled in the case of climate studies as climate is essentially a non-linear dynamic system. ANN being non-linear in nature provides the required solution for the attribution problem related to climate. Attribution of regionally significant trends detected in monthly, winter and pre-monsoon stream flow volume time series of five gauging stations of Tape basin is not performed because five gauging stations were not representative of entire Tapi basin and two out of the five gauging stations have missing data greater than 15%. Number of significant monotonically increasing trends are more in winter gridded Tmean data as compared to annual gridded Tmean data. Thus attribution analysis of winter gridded Tmean data has given first priority followed by attribution of annual gridded Tmean data. ANN model is developed for the attribution of climate change observed in gridded data of winter Tmean and annual Tmean in three steps: 1) input variable selection (IVS) based on partial mutual information (PMI), 2) data splitting using k-means clustering method and Neyman allocation, 3) ANN model formulation by using best training algorithm among Levenberg-Marquardt (LM) algorithm, scaled conjugate gradient (SCG) algorithm and Broyden, Fletcher, Goldfarb, and Shano (BFGS) algorithm and optimum number of hidden neurons (varying from 1 to 3) corresponding to performance in terms of mean squared error (MSE) and to use these in final ANN model formulation with computation of performance evaluation measures (PEMs). Aforesaid third step is repeated for 50 iterations for each input forcing and given target output to minimize any random variation due to reinitialization of training algorithms. Also random variations due to initialization of ANN model are minimized by keeping initial weights and biases equal to zero. Final PEMs evaluated were the averages of 50 iterations as mentioned aforesaid. Target outputs used in two ANN attribution models are time series of regional winter Tmean and regional annual Tmean. Also in some cases of ANN model formulations, network parameters are kept less than number of data points in the training set for minimizing overriding. Inputs for ANN model were circulation indices and regional, global and national scale input variables. The inputs selected by PMI based input selection (PMIS) algorithm in the step of IVS of both ANN attribution models are seen to be subjected to natural and anthropogenic forcing, which undisputedly shows significant role of anthropogenic activities in observed climate change in aforesaid two gridded temperature variables. Also ranking of input forcing is performed in both the ANN attribution models according to their final PEM values. In the case of ANN attribution model for regional winter Tmean time series, dominant role of natural (‘nat’) input forcing is found behind the given climate change as compared to anthropogenic (‘anth’) input forcing. Among ‘anth’ inputs, effect of land cover (‘Landcover’) input forcing is found to be dominant as compared to green house gases (‘GHgases’) input forcing. Among ‘Landcover’ inputs, urban landcover input was found to be one of the important inputs. In the case of ANN attribution model for regional annual Tmean time series, dominant role of ‘anth’ input forcing is found behind the given climate change as compared to ‘nat’ input forcing. Among ‘anth’ inputs, there is dominant role of ‘Landcover’ input forcing as compared to ‘GHgases’ input forcing. Among ‘Landcover’ inputs, urban landcover input was found to be one of the important inputs. Contributions of attribution study are: 1) checking of input independence and significance by using PMI IVS method, which was not performed earlier, 2) division of data in such a way that al patterns of whole data are present in training, testing and validation subsets and the statistical properties of these subsets are similar to each other and to whole data, which was not performed earlier, 3) using LM, SCG and BFGS algorithms which are converging fatly as compared to Windrow-Hof algorithm and gradient descent algorithm. Also these three algorithms are les liable to be get stuck in local minima, 4) using land cover data as input forcing to ANN model used for attribution of climate change, which was not done earlier.

This doctoral thesis provides the first comprehensive study on the physical processes controlling hydrodynamics and transport in Lake Garda. The investigation is carried out in parallel on three different levels: data collection and analysis, three-dimensional numerical modeling and theoretical study. On the first level, data are collected by building up a network of research institutes and local administrations in the lake area. New data are acquired through traditional field campaigns (CTD, thermistor chains, satellite imagery), while a citizen-science approach, based on local knowledge harvesting, is successfully tested to gather qualitative data on surface circulation. On the second level, a three-dimensional modeling chain is set up, by coupling one-way a mesoscale atmospheric model to a hydrodynamic model. Both models are validated on multiple temporal and spatial scales, allowing to identify the main interactions between the weather forcing and the hydrodynamic response of the lake. Circulations in Lake Garda are found to be very sensitive to the thermal stratification, to the spatial distribution of the wind forcing and to the Earth’s rotation. Surface cyclonic gyre patterns develop in the lake as a residual outcome of alternating wind forcing of local breezes and differential acceleration induced by Earth’s rotation, whereas unidirectional currents flow under a nearly uniform and constant wind. Both model and observations evidences show that, under weak thermal stratification, Ekman transport activates a secondary circulations in the northern part of the lake, driving surface water to the deep layers and possibly preconditioning the lake for subsequent buoyancy-driven deep mixing events. On the third level, the relevance of the Coriolis term in the equations of motion for relatively narrow closed basins is analytically addressed. The classical Ekman problem is solved by including the presence of lateral boundaries and a new analytical solution is formulated. The validity of the new solution is proved by numerical tests of idealized domains of different size, geographical location and turbulent regime, and on Lake Garda as a real test case. The meaningful length scales are discussed, and the significance of Rossby radious as a reference horizontal scale is disproved for steady-state circulations driven by wind and planetary rotation.

Changes in land use and water use can greatly impact the cycling of water and water-borne substances. Increased redistribution of river water to irrigated fields can cause enhanced evapotranspiration and decreased river discharge. Additionally, the water quality can be affected by the external input of fertilisers and pesticides, and by changed pollutant transport pathways in expansive irrigation canal systems. This thesis examines basin-scale changes in water use, river discharge, water quality and nitrogen (N) loading under conditions of intensified irrigated agriculture, using the Aral Sea drainage basin (ASDB) with its two large rivers Syr Darya and Amu Darya in Central Asia as study area. Results show that more efficient irrigation techniques could reduce outtake of river water to the cotton fields in the ASDB by about 10 km3/year, while the corresponding river water saving at the outlet would be 60% lower. The result illustrates the importance of accounting for return flows of irrigation water in basin-scale water saving assessments. Moreover, a decrease in riverine N concentrations at the outlet of the Amu Darya River Basin (ADRB) was observed during a 40-year period of increasing N fertiliser input. The decrease was identified to be primarily caused by increased recirculation of river water in the irrigation system, leading to increased flow-path lengths and enhanced N attenuation. Decreasing N loads were shown to be primarily related to reduced discharge. N export from the basin may further decrease due to projected discharge reductions related to climate change. Furthermore, nutrients and metals were occasionally found at concentrations above drinking water guideline values in surface waters in the ADRB. However, metal concentrations in groundwater in the lower ADRB were subject to orders of magnitude higher health hazards. Projected decrease in downstream surface water availability would thus imply decreased access to water suitable for drinking. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Submitted. Paper 5: Manuscript.</p>