Hydrologic and Water Quality Assessment of Miller Run: A Study of Bucknell University’s Impact

Human development causes degradation of stream ecosystems due to impacts on channel morphology, hydrology, and water quality. Urbanization, the second leading cause of stream impairment, increases the amount of impervious surface cover, thus reducing infiltration and increasing surface runoff of precipitation, which ultimately affects stream hydrologic process and aquatic biodiversity. The main objective of this study was to assess the overall health of Miller Run, a small tributary of the Bull Run and Susquehanna River watersheds, through an integrative hydrologic and water quality approach in order to determine the degree of Bucknell University’s impact on the stream. Hydrologic conditions, including stage and discharge, and water quality conditions, including total suspended solids, ion, nutrient, and dissolved metal concentrations, specific conductivity, pH, and temperature, were measured and evaluated at two sampling sites (upstream and downstream of Bucknell’s main campus) during various rain events from September 2007 to March 2008. The primary focus of the stream analysis was based on one main rain event on 26 February 2008. The results provided evidence that Miller Run is impacted by Bucknell’s campus. From a hydrologic perspective, the stream’s hydrograph showed the exact opposite pattern of what would be expected from a ‘normal’ stream. Miller run had a flashier downstream hydrograph and a broader upstream hydrograph, which was more than likely due to the increased amount of impervious surface cover throughout the downstream half of the watershed. From a water quality perspective, sediment loads increased at a faster rate and were significantly higher downstream compared to upstream. These elevated sediment concentrations were probably the combined result of sediment runoff from upstream and downstream construction sites that were being developed over the course of the study. Sodium, chloride, and potassium concentrations, in addition to specific conductivity, also significantly increased downstream of Bucknell’s campus due to the runoff of road salts. Calcium and magnesium concentrations did not appear to be impacted by urbanization, although they did demonstrate a significant dilution effect downstream. The downstream site was not directly affected by elevated nitrate concentrations; however, soluble reactive phosphorus concentrations tended to increase downstream and ammonium concentrations significantly peaked partway through the rain event downstream. These patterns suggest that Miller Run may be impacted by nutrient runoff from the golf course, athletic fields, and/or fertilizers applications on the main campus. Dissolved manganese and iron concentrations also appeared to slightly increase downstream, demonstrating the affect of urban runoff from roads and parking lots. pH and temperature both decreased farther downstream, but neither showed a significant impact of urbanization. More studies are necessary to determine how Miller Run responds to changes in season, climate, precipitation intensity, and land-use. This study represents the base-line analysis of Miller Run’s current hydrologic and water quality conditions; based on these initial findings, Bucknell should strongly consider modifications to improve storm water management practices and to reduce the campus’s overall impact on the stream in order to enhance and preserve the integrity of its natural water resources.

Geochemistry of sediment cores GeoB4901-3 and GeoB4901-8 from the southern flank of the Niger Fan

Time series of terrigenous source elements (Al, K, Ti, Zr) from core GeoB4901-8 recovered from the deep-sea fan of the Niger River record variations in riverine sediment discharge over the past 245,000 yr. Although the flux rates of all the elements depend on physical erosion, which is mainly controlled by the extent of vegetation coverage in central Africa, element/Al ratios reflect conditions for chemical weathering in the river basin. Maximum sediment input to the ocean occurs during cold and arid periods, when precipitation intensity and associated freshwater runoff are reduced. High carbonate contents during the same periods indicate that the sediment supply has a positive effect on river-induced marine productivity. In general, variations in the terrestrial signals contain a strong precessional component in tune with changes in low-latitude solar radiation. However, the terrestrial signal lags the insolation signal by several thousand years. K/Al, Ti/Al, and Zr/Al records reveal that African monsoonal precipitation depends on high-latitude forcing. We attribute the shift between insolation cycle and river discharge to the frequently reported nonlinear response of African climate to primary orbital configurations, which may be caused by a complex interaction of the secondary control parameters, such as surface albedo and/or thermohaline circulation.

Modeling Flood Stage-Duration-Frequency: A Risk Assessment of Critical Infrastructure in the Tidal Potomac

The service of a critical infrastructure, such as a municipal wastewater treatment plant (MWWTP), is taken for granted until a flood or another low frequency, high consequence crisis brings its fragility to attention. The unique aspects of the MWWTP call for a method to quantify the flood stage-duration-frequency relationship. By developing a bivariate joint distribution model of flood stage and duration, this study adds a second dimension, time, into flood risk studies. A new parameter, inter-event time, is developed to further illustrate the effect of event separation on the frequency assessment. The method is tested on riverine, estuary and tidal sites in the Mid-Atlantic region. Equipment damage functions are characterized by linear and step damage models. The Expected Annual Damage (EAD) of the underground equipment is further estimated by the parametric joint distribution model, which is a function of both flood stage and duration, demonstrating the application of the bivariate model in risk assessment. Flood likelihood may alter due to climate change. A sensitivity analysis method is developed to assess future flood risk by estimating flood frequency under conditions of higher sea level and stream flow response to increased precipitation intensity. Scenarios based on steady and unsteady flow analysis are generated for current climate, future climate within this century, and future climate beyond this century, consistent with the WWTP planning horizons. The spatial extent of flood risk is visualized by inundation mapping and GIS-Assisted Risk Register (GARR). This research will help the stakeholders of the critical infrastructure be aware of the flood risk, vulnerability, and the inherent uncertainty.

Precipitation-induced runoff and leaching from milled peat mining mires by peat types : a comparative method for estimating the loading of water bodies during peat pruduction

Precipitation-induced runoff and leaching from milled peat mining mires by peat types: a comparative method for estimating the loading of water bodies during peat production. This research project in environmental geology has arisen out of an observed need to be able to predict more accurately the loading of watercourses with detrimental organic substances and nutrients from already existing and planned peat production areas, since the authorities capacity for insisting on such predictions covering the whole duration of peat production in connection with evaluations of environmental impact is at present highly limited. National and international decisions regarding monitoring of the condition of watercourses and their improvement and restoration require more sophisticated evaluation methods in order to be able to forecast watercourse loading and its environmental impacts at the stage of land-use planning and preparations for peat production.The present project thus set out from the premise that it would be possible on the basis of existing mire and peat data properties to construct estimates for the typical loading from production mires over the whole duration of their exploitation. Finland has some 10 million hectares of peatland, accounting for almost a third of its total area. Macroclimatic conditions have varied in the course of the Holocene growth and development of this peatland, and with them the habitats of the peat-forming plants. Temperatures and moisture conditions have played a significant role in determining the dominant species of mire plants growing there at any particular time, the resulting mire types and the accumulation and deposition of plant remains to form the peat. The above climatic, environmental and mire development factors, together with ditching, have contributed, and continue to contribute, to the existence of peat horizons that differ in their physical and chemical properties, leading to differences in material transport between peatlands in a natural state and mires that have been ditched or prepared for forestry and peat production. Watercourse loading from the ditching of mires or their use for peat production can have detrimental effects on river and lake environments and their recreational use, especially where oxygen-consuming organic solids and soluble organic substances and nutrients are concerned. It has not previously been possible, however, to estimate in advance the watercourse loading likely to arise from ditching and peat production on the basis of the characteristics of the peat in a mire, although earlier observations have indicated that watercourse loading from peat production can vary greatly and it has been suggested that differences in peat properties may be of significance in this. Sprinkling is used here in combination with simulations of conditions in a milled peat production area to determine the influence of the physical and chemical properties of milled peats in production mires on surface runoff into the drainage ditches and the concentrations of material in the runoff water. Sprinkling and extraction experiments were carried out on 25 samples of milled Carex (C) and Sphagnum (S) peat of humification grades H 2.5 8.5 with moisture content in the range 23.4 89% on commencement of the first sprinkling, which was followed by a second sprinkling 24 hours later. The water retention capacity of the peat was best, and surface runoff lowest, with Sphagnum and Carex peat samples of humification grades H 2.5 6 in the moisture content class 56 75%. On account of the hydrophobicity of dry peat, runoff increased in a fairly regular manner with drying of the sample from 55% to 24 30%. Runoff from the samples with an original moisture content over 55% increased by 63% in the second round of sprinkling relative to the first, as they had practically reached saturation point on the first occasion, while those with an original moisture content below 55% retained their high runoff in the second round, due to continued hydrophobicity. The well-humified samples (H 6.5 8.5) with a moisture content over 80% showed a low water retention capacity and high runoff in both rounds of sprinkling. Loading of the runoff water with suspended solids, total phosphorus and total nitrogen, and also the chemical oxygen demand (CODMn O2), varied greatly in the sprinkling experiment, depending on the peat type and degree of humification, but concentrations of the same substances in the two sprinklings were closely or moderately closely correlated and these correlations were significant. The concentrations of suspended solids in the runoff water observed in the simulations of a peat production area and the direct surface runoff from it into the drainage ditch system in response to rain (sprinkling intensity 1.27 mm/min) varied c. 60-fold between the degrees of humification in the case of the Carex peats and c. 150-fold for the Sphagnum peats, while chemical oxygen demand varied c. 30-fold and c. 50-fold, respectively, total phosphorus c. 60-fold and c. 66-fold, total nitrogen c. 65-fold and c. 195-fold and ammonium nitrogen c. 90-fold and c. 30-fold. The increases in concentrations in the runoff water were very closely correlated with increases in humification of the peat. The correlations of the concentrations measured in extraction experiments (48 h) with peat type and degree of humification corresponded to those observed in the sprinkler experiments. The resulting figures for the surface runoff from a peat production area into the drainage ditches simulated by means of sprinkling and material concentrations in the runoff water were combined with statistics on the mean extent of daily rainfall (0 67 mm) during the frost-free period of the year (May October) over an observation period of 30 years to yield typical annual loading figures (kg/ha) for suspended solids (SS), chemical oxygen demand of organic matter (CODmn O2), total phosphorus (tot. P) and total nitrogen (tot. N) entering the ditches with respect to milled Carex (C) and Sphagnum (S) peats of humification grades H 2.5 8.5. In order to calculate the loading of drainage ditches from a milled peat production mire with the aid of these annual comparative values (in kg/ha), information is required on the properties of the intended production mire and its peat. Once data are available on the area of the mire, its peat depth, peat types and their degrees of humification, dry matter content, calorific value and corresponding energy content, it is possible to produce mutually comparable estimates for individual mires with respect to the annual loading of the drainage ditch system and the surrounding watercourse for the whole service life of the production area, the duration of this service life, determinations of energy content and the amount of loading per unit of energy generated (kg/MWh). In the 8 mires in the Köyhäjoki basin, Central Ostrobothnia, taken as an example, the loading of suspended solids (SS) in the drainage ditch networks calculated on the basis of the typical values obtained here and existing mire and peat data and expressed per unit of energy generated varied between the mires and horizons in the range 0.9 16.5 kg/MWh. One of the aims of this work was to develop means of making better use of existing mire and peat data and the results of corings and other field investigations. In this respect combination of the typical loading values (kg/ha) obtained here for S, SC, CS and C peats and the various degrees of humification (H 2.5 8.5) with the above mire and peat data by means of a computer program for the acquisition and handling of such data would enable all the information currently available and that deposited in the system in the future to be used for defining watercourse loading estimates for mires and comparing them with the corresponding estimates of energy content. The intention behind this work has been to respond to the challenge facing the energy generation industry to find larger peat production areas that exert less loading on the environment and to that facing the environmental authorities to improve the means available for estimating watercourse loading from peat production and its environmental impacts in advance. The results conform well to the initial hypothesis and to the goals laid down for the research and should enable watercourse loading from existing and planned peat production to be evaluated better in the future and the resulting impacts to be taken into account when planning land use and energy generation. The advance loading information available in this way would be of value in the selection of individual peat production areas, the planning of their exploitation, the introduction of water protection measures and the planning of loading inspections, in order to achieve controlled peat production that pays due attention to environmental considerations.

Why is there a short-term increase in global precipitation in response to diminished CO2 forcing?

Recently, it was found that a reduction in atmospheric CO2 concentration leads to a temporary increase in global precipitation. We use the Hadley Center coupled atmosphere-ocean model, HadCM3L, to demonstrate that this precipitation increase is a consequence of precipitation sensitivity to changes in atmospheric CO2 concentrations through fast tropospheric adjustment processes. Slow ocean cooling explains the longer-term decrease in precipitation. Increased CO2 tends to suppress evaporation/precipitation whereas increased temperatures tend to increase evaporation/precipitation. When the enhanced CO2 forcing is removed, global precipitation increases temporarily, but this increase is not observed when a similar negative radiative forcing is applied as a reduction of solar intensity. Therefore, transient precipitation increase following a reduction in CO2-radiative forcing is a consequence of the specific character of CO2 forcing and is not a general feature associated with decreases in radiative forcing. Citation: Cao, L., G. Bala, and K. Caldeira (2011), Why is there a short-term increase in global precipitation in response to diminished CO2 forcing?, Geophys. Res. Lett., 38, L06703, doi:10.1029/2011GL046713.

Modeling non-stationarity in intensity, duration and frequency of extreme rainfall over India

Significant changes are reported in extreme rainfall characteristics over India in recent studies though there are disagreements on the spatial uniformity and causes of trends. Based on recent theoretical advancements in the Extreme Value Theory (EVT), we analyze changes in extreme rainfall characteristics over India using a high-resolution daily gridded (1 degrees latitude x 1 degrees longitude) dataset. Intensity, duration and frequency of excess rain over a high threshold in the summer monsoon season are modeled by non-stationary distributions whose parameters vary with physical covariates like the El-Nino Southern Oscillation index (ENSO-index) which is an indicator of large-scale natural variability, global average temperature which is an indicator of human-induced global warming and local mean temperatures which possibly indicate more localized changes. Each non-stationary model considers one physical covariate and the best chosen statistical model at each rainfall grid gives the most significant physical driver for each extreme rainfall characteristic at that grid. Intensity, duration and frequency of extreme rainfall exhibit non-stationarity due to different drivers and no spatially uniform pattern is observed in the changes in them across the country. At most of the locations, duration of extreme rainfall spells is found to be stationary, while non-stationary associations between intensity and frequency and local changes in temperature are detected at a large number of locations. This study presents the first application of nonstationary statistical modeling of intensity, duration and frequency of extreme rainfall over India. The developed models are further used for rainfall frequency analysis to show changes in the 100-year extreme rainfall event. Our findings indicate the varying nature of each extreme rainfall characteristic and their drivers and emphasize the necessity of a comprehensive framework to assess resulting risks of precipitation induced flooding. (C) 2014 Elsevier B.V. All rights reserved.

Thermodynamic and dynamic contributions to future changes in regional precipitation variance: focus on the Southeastern United States

© 2014, Springer-Verlag Berlin Heidelberg.The frequency and severity of extreme events are tightly associated with the variance of precipitation. As climate warms, the acceleration in hydrological cycle is likely to enhance the variance of precipitation across the globe. However, due to the lack of an effective analysis method, the mechanisms responsible for the changes of precipitation variance are poorly understood, especially on regional scales. Our study fills this gap by formulating a variance partition algorithm, which explicitly quantifies the contributions of atmospheric thermodynamics (specific humidity) and dynamics (wind) to the changes in regional-scale precipitation variance. Taking Southeastern (SE) United States (US) summer precipitation as an example, the algorithm is applied to the simulations of current and future climate by phase 5 of Coupled Model Intercomparison Project (CMIP5) models. The analysis suggests that compared to observations, most CMIP5 models (~60 %) tend to underestimate the summer precipitation variance over the SE US during the 1950–1999, primarily due to the errors in the modeled dynamic processes (i.e. large-scale circulation). Among the 18 CMIP5 models analyzed in this study, six of them reasonably simulate SE US summer precipitation variance in the twentieth century and the underlying physical processes; these models are thus applied for mechanistic study of future changes in SE US summer precipitation variance. In the future, the six models collectively project an intensification of SE US summer precipitation variance, resulting from the combined effects of atmospheric thermodynamics and dynamics. Between them, the latter plays a more important role. Specifically, thermodynamics results in more frequent and intensified wet summers, but does not contribute to the projected increase in the frequency and intensity of dry summers. In contrast, atmospheric dynamics explains the projected enhancement in both wet and dry summers, indicating its importance in understanding future climate change over the SE US. The results suggest that the intensified SE US summer precipitation variance is not a purely thermodynamic response to greenhouse gases forcing, and cannot be explained without the contribution of atmospheric dynamics. Our analysis provides important insights to understand the mechanisms of SE US summer precipitation variance change. The algorithm formulated in this study can be easily applied to other regions and seasons to systematically explore the mechanisms responsible for the changes in precipitation extremes in a warming climate.

Subseasonal extremes of precipitation and active-break cycles of the Indian summer monsoon in a climate-change scenario

Changes to the behaviour of subseasonal precipitation extremes and active-break cycles of the Indian summer monsoon are assessed in this study using pre-industrial and 2 × CO2 integrations of the Hadley Centre coupled model HadCM3, which is able to simulate the monsoon seasonal cycle reasonably. At 2 × CO2, mean summer rainfall increases slightly, especially over central and northern India. The mean intensity of daily precipitation during the monsoon is found to increase, consistent with fewer wet days, and there are increases to heavy rain events beyond changes in the mean alone. The chance of reaching particular thresholds of heavy rainfall is found to approximately double over northern India, increasing the likelihood of damaging floods on a seasonal basis. The local distribution of such projections is uncertain, however, given the large spread in mean monsoon rainfall change and associated extremes amongst even the most recent coupled climate models. The measured increase of the heaviest precipitation events over India is found to be broadly in line with the degree of atmospheric warming and associated increases in specific humidity, lending a degree of predictability to changes in rainfall extremes. Active-break cycles of the Indian summer monsoon, important particularly due to their effect on agricultural output, are shown to be reasonably represented in HadCM3, in particular with some degree of northward propagation. We note an intensification of both active and break events, particularly when measured against the annual cycle, although there is no suggestion of any change to the duration or likelihood of monsoon breaks. Copyright © 2009 Royal Meteorological Society

Describing long-term trends in precipitation using generalized additive models

With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates

The intensity and distribution of daily precipitation is predicted to change under scenarios of increased greenhouse gases (GHGs). In this paper, we analyse the ability of HadCM2, a general circulation model (GCM), and a high-resolution regional climate model (RCM), both developed at the Met Office's Hadley Centre, to simulate extreme daily precipitation by reference to observations. A detailed analysis of daily precipitation is made at two UK grid boxes, where probabilities of reaching daily thresholds in the GCM and RCM are compared with observations. We find that the RCM generally overpredicts probabilities of extreme daily precipitation but that, when the GCM and RCM simulated values are scaled to have the same mean as the observations, the RCM captures the upper-tail distribution more realistically. To compare regional changes in daily precipitation in the GHG-forced period 2080-2100 in the GCM and the RCM, we develop two methods. The first considers the fractional changes in probability of local daily precipitation reaching or exceeding a fixed 15 mm threshold in the anomaly climate compared with the control. The second method uses the upper one-percentile of the control at each point as the threshold. Agreement between the models is better in both seasons with the latter method, which we suggest may be more useful when considering larger scale spatial changes. On average, the probability of precipitation exceeding the 1% threshold increases by a factor of 2.5 (GCM and RCM) in winter and by I .7 (GCM) or 1.3 (RCM) in summer.

Extreme precipitation and climate change: the potential impacts on flooding

Recent extreme precipitation events have caused widespread flooding to the UK. The prediction of the intensity of such events in a warmer climate is important for adaption strategies against future events. This study highlights the importance of using high-resolution models to predict these events. Using a high-resolution GCM it is shown that extreme precipitation events are predicted to become more frequent under the IPCC A1B warming scenario. It is also shown that current forecast models have difficulty in predicting the location, timing and intensity of small scale precipitation in areas with significant orography.

Future change of precipitation extremes in Europe: intercomparison of scenarios from regional climate mode

An analysis of the climate of precipitation extremes as simulated by six European regional climate models (RCMs) is undertaken in order to describe/quantify future changes and to examine/interpret differences between models. Each model has adopted boundary conditions from the same ensemble of global climate model integrations for present (1961–1990) and future (2071–2100) climate under the Intergovernmental Panel on Climate Change A2 emission scenario. The main diagnostics are multiyear return values of daily precipitation totals estimated from extreme value analysis. An evaluation of the RCMs against observations in the Alpine region shows that model biases for extremes are comparable to or even smaller than those for wet day intensity and mean precipitation. In winter, precipitation extremes tend to increase north of about 45°N, while there is an insignificant change or a decrease to the south. In northern Europe the 20-year return value of future climate corresponds to the 40- to 100-year return value of present climate. There is a good agreement between the RCMs, and the simulated change is similar to a scaling of present-day extremes by the change in average events. In contrast, there are large model differences in summer when RCM formulation contributes significantly to scenario uncertainty. The model differences are well explained by differences in the precipitation frequency and intensity process, but in all models, extremes increase more or decrease less than would be expected from the scaling of present-day extremes. There is evidence for a component of the change that affects extremes specifically and is consistent between models despite the large variation in the total response.

Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods

A precipitation downscaling method is presented using precipitation from a general circulation model (GCM) as predictor. The method extends a previous method from monthly to daily temporal resolution. The simplest form of the method corrects for biases in wet-day frequency and intensity. A more sophisticated variant also takes account of flow-dependent biases in the GCM. The method is flexible and simple to implement. It is proposed here as a correction of GCM output for applications where sophisticated methods are not available, or as a benchmark for the evaluation of other downscaling methods. Applied to output from reanalyses (ECMWF, NCEP) in the region of the European Alps, the method is capable of reducing large biases in the precipitation frequency distribution, even for high quantiles. The two variants exhibit similar performances, but the ideal choice of method can depend on the GCM/reanalysis and it is recommended to test the methods in each case. Limitations of the method are found in small areas with unresolved topographic detail that influence higher-order statistics (e.g. high quantiles). When used as benchmark for three regional climate models (RCMs), the corrected reanalysis and the RCMs perform similarly in many regions, but the added value of the latter is evident for high quantiles in some small regions.

The correlation of ULF waves and auroral intensity before, during and after substorm expansion phase onset

We present case studies of the evolution of magnetic wave amplitudes and auroral intensity through the late growth phase and the expansion phase of the substorm cycle. We present strong evidence that substorm-related auroral enhancements are clearly and demonstrably linked to ULF wave amplitudes observed at the same location. In most cases, we find that the highest correlations are observed when the magnetometer time series is advanced in time, indicating that the ULF wave amplitudes start to grow before measured auroral intensities, though interestingly this is not always the case. Further we discuss the four possible reasons that may be able to explain both the timing and the high correlations between these two phenomena, including: a simple coincidence, an artifact of instrumental effects, the response of the ionosphere to magnetic waves and auroral particle precipitation, and finally that ULF waves and auroral particle precipitation are physically linked. We discount coincidence and instrumental effects since in the studies presented here they are unlikely or in general will contribute negligible effects, and we find that the ionospheric response to waves and precipitation can explain some, but not all of the results contained within this paper. Specifically, ionospheric response to substorm waves and auroral precipitation cannot explain that the result that previous studies have shown, that onset of ULF wave activity and the onset of auroral particle precipitation occur at the same time and in the same location. This leaves the possibility that ULF waves and auroral particles are physically linked.