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In many parts of the world, watershed management practices have been extremely effective. However, implementation of soil and water conservation technologies in the humid African highlands, while beneficial in the short term, were remarkably unsuccessful in the long term. Insights from community knowledge perspectives have revealed that alternative methods are needed. Although conservation practices are designed to conserve water in semi-arid areas, safely draining excess water is needed in humid areas. The objective of this paper is to review current watershed management approaches used in humid regions as exemplified by those used in Ethiopian highlands and then based on these findings propose more effective practices. Although current government sponsored practices primarily protect the hillsides, direct run-off is generated from areas that become saturated on valley bottoms near rivers and on specific parts of the hillsides with degraded soils (or with highly permeable surface soils) and with perched water tables on slowly permeable horizons at shallow depths. In these areas, direct run-off is increasing with deforestation and the soil degradation, demanding additional drainage ways that evolve in the form of gullies. Therefore, watershed management interventions for erosion control should prioritize revegetation of degraded areas, increasing sustainable infiltration, and rehabilitating gullies situated at saturated bottomlands.

Saturation-excess runoff is the major runoff mechanism in humid well-vegetated areas where infiltration rates often exceed rainfall intensity. While the Soil and Water Assessment Tool (SWAT) is one of the most widely used models, it predicts runoff based mainly on soil and land use characteristics, and is implicitly an infiltration-excess runoff type of model. Previous attempts to incorporate the saturation-excess runoff mechanism in SWAT fell short due to the inability to distribute water from one Hydrological Response Unit (HRU) to another. This paper introduces a modified version of SWAT, referred to as SWAT-Hillslope (SWAT-HS). This modification improves the simulation of saturation-excess runoff by redefining HRUs based on wetness classes, and by introducing a surface aquifer with the ability to route interflow from “drier” to “wetter” wetness classes. Mathematically, the surface aquifer is a non-linear reservoir that generates rapid subsurface stormflow as the water table in the surface aquifer rises. The SWAT-HS model was tested in the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region of New York, USA. SWAT-HS predicted discharge well with a Nash-Sutcliffe Efficiency of 0.68 and 0.87 for daily and monthly time steps. Compared to the original SWAT model, SWAT-HS predicted less surface runoff and groundwater flow and more lateral flow. The saturated areas predicted by SWAT-HS were concentrated in locations with a high topographic index and were in agreement with field observations. With the incorporation of topographic characteristics and the addition of the surface aquifer, SWAT-HS improved streamflow simulation and gave a good representation of saturated areas on the date that measurements were available. SWAT-HS is expected to improve water quality model predictions where the location of the surface runoff matters.

Objective To assess if pregnancies among women with Addison's disease (AD) are at higher risk of adverse maternal and neonatal outcomes. Design Population-based retrospective cohort study. Setting/Population All births in the United States’ Healthcare Cost and Utilization Project-Nationwide Inpatient Sample from 2003 to 2011. Methods Baseline characteristics were compared between women with AD and those without, and prevalence over time was measured. Logistic regression was used to estimate the effect of AD on maternal and neonatal outcomes by calculating the crude and adjusted odds ratios (OR) and corresponding 95% confidence intervals (95% CI). Results We calculated a prevalence of AD in pregnancy of 5.5/100 000, increasing from 5.6 to 9.6/100 000 (P = 0.0001) over the 9-year study period. Compared with women without AD, women with AD were more likely to deliver preterm (OR 1.50, 95% CI 1.16–1.95), deliver by caesarean section (OR 1.32, 95% CI 1.08–1.61), have impaired wound healing (OR 4.28, 95% CI 2.55–7.18), develop infections (OR 2.44, 95% CI 1.66–3.58) and develop thromboembolism (OR 5.21, 95% CI 2.15–12.63), require transfusions (OR 6.69, 95% CI 4.69–9.54), and have prolonged postpartum hospital admissions (OR 5.71, 95% CI 4.37–7.47). Maternal mortality was significantly higher than in the comparison group (OR 22.30, 95% CI 6.82–72.96). Congenital anomalies (OR 3.62, 95% CI 2.05–6.39) and small-for-gestational age infants (OR 1.78, 95% CI 1.15–2.75) were more likely in these pregnancies. Conclusions Addison's disease significantly increases the risk of severe adverse maternal and neonatal outcomes, so pregnant women with AD are best managed in tertiary-care centres. Tweetable abstract Pregnancies complicated by Addison's disease have an increased risk of adverse maternal and neonatal outcomes.

The New York City water supply region, located in the Catskill Mountains in upstate New York, has always had a historically variable snow cover, with consequent effects on the magnitude of spring runoff and the relative importance of winter vs. spring periods on annual hydrologic and nutrient budgets. Simulations show that under present conditions (1966–2005), on average 38% (12–70%) of the annual total dissolved phosphorus load occurs during winter (November– February) while future predictions (2046–2065 and 2081–2100) show winter nutrient loads may account for an average of 46% (18–73%) of the annual load. It is expected that changes in the timing of nutrient loading will lead to some increase in phytoplankton growth under isothermal conditions prior to the onset of thermal stratification, a reduced bloom coinciding with the onset of thermal stratification, and on an annual basis somewhat lower levels of biomass. However, future climate simulations using two different one dimensional reservoir water quality models show no strong relationship between changes in algal biomass and the proportion of winter nutrient loading. The lack of a winter response calls into question model assumptions concerning the growth potential of phytoplankton under deeply mixed low light conditions, as well as factors influencing the bioavailability of nutrients input during the winter period. This illustrates the pitfalls of simulating future climate conditions,when the seasonality of model drivers has changed and processes regulating winter conditions are not strongly represented.

Recent works have indicated that climate change in the northeastern United States is already being observed in the form of shorter winters, higher annual average air temperature, and more frequent extreme heat and precipitation events. These changes could have profound effects on aquatic ecosystems, and the implications of such changes are less understood. The objective of this study was to examine how future changes in precipitation and temperature translate into changes in streamflow using a physically based semidistributed model, and subsequently how changes in streamflow could potentially impact stream ecology. Streamflow parameters were examined in a New York City water supply watershed for changes from model-simulated baseline conditions to future climate scenarios (2081-2100) for ecologically relevant factors of streamflow using the Indicators of Hydrologic Alterations tool. Results indicate that earlier snowmelt and reduced snowpack advance the timing and increase the magnitude of discharge in the winter and early spring (November-March) and greatly decrease monthly streamflow later in the spring in April. Both the rise and fall rates of the hydrograph will increase resulting in increased flashiness and flow reversals primarily due to increased pulses during winter seasons. These shifts in timing of peak flows, changes in seasonal flow regimes, and changes in the magnitudes of low flow can all influence aquatic organisms and have the potential to impact stream ecology.

Recent studies have indicated that potential future climate change may lead to changes in the timing and quantity of snowpack accumulation and winter (November to April) streamflow patterns including increased streamflow and turbidity in early winter and a slight reduction in turbidity loads at the time of traditional early spring run-off. In this study, we examine the potential effects of these predicted changes on reservoir turbidity levels. Our analysis focuses on Ashokan Reservoir, NY, which can at times receive significant watershed turbidity inputs mainly from stream channel erosion from the Esopus Creek. Both measured and simulated turbidity loads and climatology are input to CE-QUAL-W2 (W2), a reservoir turbidity transport model that can simulate reservoir turbidity and other water quality parameters. The W2 model is applied to estimate the effects of hydroclimatology on effective settling rates and turbidity transport as a result of differences in reservoir thermal structure during summer and winter events. Simulations suggest that the effective settling velocity is substantially lower at low temperatures during winter time. Winter average stream flow is simulated to increase by 12% and 20%, which leads to increases in reservoir turbidity by 11% and 17% for the future period 2046–2065 and 2081–2100, respectively. From a seasonal perspective, a change in timing of peak streamflow with increased flows during the winter and slightly reduced flows during early spring leads to increased average reservoir turbidity during winter and slightly decreased in-reservoir turbidity during early spring and summer. Copyright © 2013 John Wiley & Sons, Ltd.

Rain-on-snow (ROS) runoff events are important hydro-meteorological phenomenon due to their association with flooding. The severity of ROS runoff events depends on the magnitude of the precipitation, air temperature elevation, snow water equivalent (SWE), and areal extent of the antecedent snowpack. Examining the consequences of these factors acting together creates challenges for both flood prediction and flood risk assessments. This study provides information on the spatial patterns, and seasonality of ROS events in New York. We examine the spatial and temporal variability of ROS events for water years 2004 to 2012 from SNOw Data Assimilation System products for New York. Liquid and solid precipitation, snow depth, snowmelt, SWE, maximum and minimum temperature, hydrograph characteristics, and annual peak flow are examined. There is significant positive correlation of ROS days and ROS triggered events with elevation and negative correlation of these events with increasing air temperature. Our study shows that ROS events are dominant in high elevation areas of Adirondack and Catskill regions, and their distribution varies with month. Cumulative runoffs from ROS events are generally greater than the rain-only runoff events. The majorities of annual peak flows in the study watersheds are the results of ROS events and lasted from a few days to many weeks. Copyright © 2013 John Wiley & Sons, Ltd.

Snow is a substantial component of historical annual precipitation in New York City (NYC) water supply watersheds in the Catskill Mountains, and the pattern of snow accumulation and snowmelt has important implications for the management of the reservoirs and watersheds that are part of the NYC water supply. NYC currently estimates reservoir basin-scale snowpack throughout the snow season by extrapolation from biweekly snow survey data. These estimates are complemented by the NOAA Snow Data Assimilation System (SNODAS) product. Snowpack models are used in short-term projections to support reservoir operations and long-term simulations to evaluate the potential effects of climate change, land use change, and watershed management on the water supply. We tested three snowpack estimation approaches compared with snow survey data: the lumped-parameter temperature index approach from the Generalized Watershed Loading Function (GWLF) watershed model, a spatially distributed temperature index (SDTI) model, and the spatially distributed NOAA SNODAS product. Of the spatially distributed approaches, SNODAS estimated the spatial variability of snow water equivalent (SWE) among snow survey sites within a basin better than the SDTI model. All three snowpack estimation approaches, including the lumped-parameter GWLF model, performed well in estimating basin-wide SWE for most of the basins studied. Copyright © 2013 John Wiley & Sons, Ltd.

This study focuses on the impact of changes in winter streamflow on in-stream turbidity in the Esopus Creek watershed, one of the New York City (NYC) water supply watersheds. Projected changes in daily precipitation and air temperature from a suite of five global climate models (GCMs) and three emission scenarios for future periods 2046–2065 and 2081–2100 were downscaled for the study region. The simulated climate scenarios were used to project future streamflows using the Generalized Watershed Loading Functions—Variable Source Area (GWLFVSA) watershed model. Seasonal turbidity rating curves based on measured historical streamflow and stream turbidity were used in combination with the simulated streamflow for generating future stream turbidity scenarios. Results indicate increase in future ambient stream turbidity from November to March and a decrease during April. These results are the effects of increased winter rainfall, reduced snowfall, and a shift to early timing of spring snowmelt runoff causing an increase in streamflow during early winter. It also suggests a reduction in the traditional peak streamflow around April that is expected to occur in this region. As a result, our models simulate a consistent increase in the low to medium percentile range of turbidity values associated with low to medium range of streamflows and no apparent change in high percentile turbidity values associated with high streamflows.

The ability of Global Climate Models (GCMs) to simulate observed meteorologic and hydrologic variables is an important indicator of the reliability of these models to project future climate conditions. In this study we evaluate the ability of GCMs participating in the Intergovernmental Panel for Climate Change’s (IPCC) Fourth Assessment Report (AR4) to simulate variability in the snow water equivalent (SWE) in New York City Water Supply watersheds located northwest of NYC in the Catskill Mountains. SWE is estimated using an empirical temperature-based degree day model. Inputs to this model are either measured historical meteorological (1961-2000) data or GCM model output for the same historical period. The evaluation of the GCMs is based on a skill score developed using probability distribution functions derived from the time series of simulated snowpack. From the skill scores (SS) calculated, the GCMs are ranked based on their ability to simulate the snowpack. These results have implications for selecting a subset of GCM simulations for climate change impact assessments in New York City’s water supply. Results show that the GFDL 2.0 (gf001) model has the highest SS (0.93) and CCSM (ncc09) model has the lowest SS (0.26). Based on the SS, the GCM ensemble members are classified into three categories high, medium and low performance. The PDFs for the three performance classes show the largest between-model variability for models in low performance class. Differences difference between the means and medians of observation-based and GCM-based simulation were also greatest in the low performance class.

Snowfall is an important part of the yearly water balance for the Catskill Mountains in New York State, the location of water supply reservoirs for New York City. Recent studies have shown that the effects of climate change on the hydrology of the Catskills will most likely create (1) a decrease in the proportion of precipitation falling as snow, (2) a shift in the timing of snowmelt that will cause snowmelt-supplemented streamflow events to occur earlier in the fall and winter, and (3) a decrease in the magnitude of traditionally high April streamflow. The shift in timing of snowmelt-influenced streamflow events is measured by the winter-early spring centre of volume (WSCV), defined as the Julian Day on which half the total streamflow volume from January to May occurs. Studies of streamflow, precipitation, and temperature trends in the last 50 years have shown that the WSCV is already earlier by about 5–10 days. This study investigates the use of watershed-scale snowpack and snowmelt algorithms that are incorporated in two existing watershed water quality models, Generalized Watershed Loading Functions-Variable Source Area (GWLF-VSA) and Soil and Water Assessment Tool (SWAT), to capture the potential effects of climate change on the timing and magnitude of streamflow during the late fall, winter, and early spring for the Catskill Mountain region. The GWLF-VSA model reasonably simulated the recent shifts in the winter streamflow timing, with simulations over the previous 50-year period yielding shifts in WSCV of 2–15 days. The SWAT model yielded similar results as the GWLF-VSA simulations. Scenarios of potential climate change 100 years in the future showed a similar shift in direction of timing winter streamflow, but at a larger magnitude than observed to date with WSCV occurring 15–20 days earlier. Copyright © 2011 John Wiley & Sons, Ltd.

Snow is an important component of the water resources of New York State and the watersheds and reservoirs of New York City (NYC) water supply. In many of the NYC water supply watersheds the hydrologic regimes of high-elevation headwaters are linked to streamflow and channel processes in low-elevation stream reaches that serve as inputs to water supply reservoirs. To better simulate this linkage there is a need to understand spatial variations in snowpack and snowmelt. Snowmelt hydrology is an important component of the Soil and Water Assessment Tool (SWAT) model in watersheds where spring runoff is strongly affected by melting snow. This study compares model simulated snowpack and snowmelt at different elevation bands with snow survey data available for the Cannonsville reservoir watershed. Simulations examine the effects of parameterising the SWAT snowmelt sub-model using 1, 3, and 5 elevation bands by comparison with measured snow and streamflow. Comparison between measured and simulated snowpack produced correlation coefficients ranging from 0·35 to 0·85. Simulations of both daily and seasonal streamflow, improved when using 3 elevation bands with r2 of 0·73 and ENS of 0·72. Streamflow simulations showed slightly lower model performance when basin elevation was assumed to be equal to snow survey site elevation, due to the snow survey sites being somewhat biased toward lower elevations. The effect of climate change was also evaluated and showed that under higher air temperatures in future climate change scenarios, SWAT indicated more precipitation falling as rain, increased and earlier snowmelt, and a reduced snowpack leading to a change in the pattern of streamflow, particularly during winter and early spring. Copyright © 2011 John Wiley & Sons, Ltd.

This study focuses on the effect of projected changes in rainfall, snow accumulation and snowmelt, and consequent changes in the timing of runoff on NYC water supply system storage and operation as simulated by the NYC reservoir system Operational Analysis and Simulation of Integrated Systems (OASIS) model. The Generalized Watershed Loading Functions—Variable Source Area (GWLF-VSA)—watershed model is used with future climate scenarios derived from different General Circulation Models (GCMs) to simulate future inflows to reservoirs that are part of the New York City Water Supply System (NYCWSS). Future scenarios that use current system operation rules and demands, but changed reservoir inflows, suggest that changes in precipitation and snowmelt will affect regional water availability on a seasonal basis. The combined effect of projected increases in winter air temperatures, increased winter rain, and earlier snowmelt may result in more runoff during winter. This will cause reservoir storage levels, water releases and spills to increase during the winter and earlier reservoir refill in the spring. An overall increase in precipitation will result in a reduction in number of days the system is under drought conditions, despite increased evapotranspiration later in the year. Copyright © 2011 John Wiley & Sons, Ltd.

Many water quality models use some form of the curve number (CN) equation developed by the Soil Conservation Service (SCS; U.S. Depart of Agriculture) to predict storm runoff from watersheds based on an infiltration-excess response to rainfall. However, in humid, well-vegetated areas with shallow soils, such as in the northeastern USA, the predominant runoff generating mechanism is saturation-excess on variable source areas (VSAs). We reconceptualized the SCS–CN equation for VSAs, and incorporated it into the General Watershed Loading Function (GWLF) model. The new version of GWLF, named the Variable Source Loading Function (VSLF) model, simulates the watershed runoff response to rainfall using the standard SCS–CN equation, but spatially distributes the runoff response according to a soil wetness index. We spatially validated VSLF runoff predictions and compared VSLF to GWLF for a subwatershed of the New York City Water Supply System. The spatial distribution of runoff from VSLF is more physically realistic than the estimates from GWLF. This has important consequences for water quality modeling, and for the use of models to evaluate and guide watershed management, because correctly predicting the coincidence of runoff generation and pollutant sources is critical to simulating non-point source (NPS) pollution transported by runoff. Copyright  2007 John Wiley & Sons, Ltd.

A previous modeling study used the Generalized Watershed Loading Functions (GWLF) model to simulate stream-flow, and nutrient and sediment loads to Cannonsville Reservoir from the West Branch Delaware River (WBDR). We made several model revisions, calibrated key parameters, and tested the original GWLF model and a revised GWLF model using more recent data. Model revisions included: addition of unsaturated leakage between unsaturated and saturated subsurface reservoirs; revised timing of sediment export; inclusion of urban sediments and dissolved nutrients; tracking of particulate nutrients from point sources; and revised timing of septic system loads. The revision of sediment yield timing resulted in significant improvements in monthly sediment and particulate phosphorus predictions as compared to the original model. Addition of unsaturated leakage improved hydrologic predictions during low flow months. The other model changes improve realism without adding significant model complexity or data requirements. Goodness of fit of revised model predictions versus stream measurements, as measured by the Nash-Sutcliff coefficient of model efficiency, exceeded 0.8 for streamflow-0.7 for sediment yield and dissolved nitrogen (N) and 0.6 for particulate and dissolved phosphorus (P). The revised GWLF model, with limited calibration, provides reasonable estimates of monthly streamflow, and nutrient and sediment loads in the Cannonsville watershed.

Using high speed cinematography and videography, we determined that unrestrained Drosophila melanogaster can initiate flight in two different ways, which we have designated Type 1 and Type 2 flight initiation. Type 1 behaviour is executed when the fly initiates flight ‘voluntarily’. Type 2 behaviour is executed in response to a visual stimulus and is presumably an escape response. During both types of flight initiation, the fly pushes off from the substratum using only the mesothoracic legs. The mesothoracic legs extend at the coxo-trochanteric, femoro-tibial and tibio-metatarsal joints. Although the movements of the legs are similar during both Type 1 and Type 2 flight initiation, the movements of the wings are different. Prior to the onset of leg extension, during Type 1 flight initiation, the wings are raised and rotated from their resting position to a preflight position dorsal to the thorax. The wings are held in this upright position for several milliseconds and then rapidly depressed during leg extension. Prior to Type 2 flight initiation, by contrast, the wings are not raised and rotated, nor are the wings depressed during leg extension. Thus Type 1 flight initiation involves simultaneous leg extension and wing depression, whereas Type 2 flight initiation involves only leg extension.

The anatomy of the motor neurons innervating six direct flight muscles in Drosophila melanogaster has been investigated by using a horseradish peroxidase backfilling technique. The somata of these motor neurons are arranged in two distinct clusters ipsilateral to the muscle they innervate. One cluster of cell bodies is located in the ventrolateral region between the prothoracic neuromere and the mesothoracic leg-related neuropil and the other is situated dorsally and posteriorly to the mesothoracic leg-related neuropil. Axons from somata in the ventrolateral cluster run in the anterior dorsal mesothoracic nerve, while axons from somata in the other cluster run in the mesothoracic accessory nerve. This distribution of somata and axons is discussed in the light of the morphological similarity and proximity of these functionally related muscles. On the basis of the branching patterns of their neurites, direct flight muscle motor neurons can be classified as stubbly, fibrous or tufted. The terminal arborizations of the motor neurons over the direct flight muscles are also morphologically specialized. Both the central and the peripheral morphological specializations of the direct flight muscle motor neurons correlate with the activity patterns exhibited by their associated muscles during flight and courtship song.