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The objective of this research is to deliver an unprecedented study of hourly SWAT model simulations of discharge in two local watersheds (around 50 km2). An urbanized watershed and a forest watershed across northwest Delaware and northeastern US were selected. Both watersheds are developed and vulnerable to flash flood. Very high resolution (2 m) topography and land use information were used to depict complex urban landscape. The model calibration and validation were performed on 2010 and 2011, starting with 2009 as model spin-up period. Satisfactory fitness results were achieved at both forest and urbanized watershed, with the Nash–Sutcliff coefficients of 0.68 and 0.77, R2 of 0.7 and 0.78, and percent bias of 1.5 and 9.3, respectively. The calibration results showed that the 2-m land use accurately captured the impervious surface due to 8.9% adjustment of curve number. But, greater steepness of slope derived from 2-m DEM leads to faster runoff than reality, which means 2-m DEM does not accurately depict the topography and finer detail DEM is needed to capture the local topographic variation. To reproduce the seasonality of discharge at hourly time step, additional examination of parameters influencing baseflow was needed as part of local sensitivity test. For the peak flow dynamic simulation, substantial adjustments were performed for parameters conditioning runoff travel time, such as Manning roughness. We found hourly SWAT is a reliable modelling tool for local level watersheds but needs deliberate attention to the input selection of land use and DEM and calibration process.

The impacts of extreme climates on two watersheds vulnerable to hazards of drought and flooding are examined. Using 2-m resolution topography and land use information, county level soil survey data, meteorology and hydrology data, two daily SWAT models were calibrated in years 2008 to 2010 and validated in years 2012 to 2014. Using the two calibrated models, the meteorology inputs of historical extreme wet (1996) and dry years (1964–65) was selected for daily streamflow simulation using the present land surface and evaluation of changes in the urban hydrology system. Good fit results between simulated and observed streamflow values were achieved for both watersheds, with Nash-Sutcliff coefficient and R2 higher than 0.69 for calibration and 0.66 for validation. The wet year simulation showed that the majority of peakflow events have not increased in both rivers, but baseflow decreased in the upper Christina River in comparison to 1996 records. The dry year simulation indicated that urban development over the last 55 years has led to lower baseflow and greater streamflow variability in both watersheds. The results suggest that improvements are needed in this urban ecosystem to prepare for extreme droughts like the 1960s, and effective stormwater management practices should continue for controlling stormwater runoff. Both these improvements will build resilience in the urban environment.

Background The Antarctic minke whale (Balaenoptera bonaerensis) is a relatively small baleen whale species and is well suited to life in the Antarctic pack ice. Information on their individual movement and distribution patterns is largely unknown due to their association with sea ice habitat where direct observations are limited. The primary objectives of this study are (1) to use satellite telemetry to quantify the movement patterns, distribution, and presumed foraging areas of Antarctic minke whales and (2) to assess the environmental conditions that are associated with areas used by minke whales along the western Antarctic Peninsula. Results Individual movement patterns from three Antarctic minke whales fitted with ARGOS-linked transmitters were analyzed with respect to environmental conditions. Behavioral states were identified using the Multi-Scale Straightness Index. Satellite telemetry revealed disparate behavioral patterns between these three individuals. Generalized additive model analysis demonstrated environmental variables, particularly sea ice, bathymetry, and sea surface temperature, are the best predictors of presumed foraging areas. Conclusions Satellite telemetry from three individuals revealed Antarctic minke whale summer foraging spaces are highly individualized but can generally be associated with pack ice habitat over the continental shelf. The coupled relationship between minke whales, krill, and sea ice suggests that these whales may be sensitive to changes in sea ice concentration, extent, and duration, making them particularly vulnerable to climate change.

This paper develops a multiobjective optimization model to consider transportation impacts of the future development of land. The output of the model is the best location and type of land use that has minimal negative transportation effects and uses the maximum available public transportation infrastructure. It provides tools for both planners and transportation engineers and enables them to consider different scenarios of possible policies and land development. Since multiple objectives and their nonlinear structures are considered, the model is solved using mixed integer nonlinear programming. The final results are shown in both tabular and graphical format. The effectiveness of the model is applied to the northern part of New Castle County, Delaware. The results show that the model successfully finds the best locations for both residential and commercial land uses in order to meet several criteria discussed in the paper.

This work evaluates two distinct calculations of central tendency for sea-ice thickness and quantifies the impact such calculations have on ice volume for the Southern Ocean. The first calculation, area-weighted average thickness, is computed from polygonal ice features and then upscaled to regions. The second calculation, integrated thickness, is a measure of the central value of thickness categories tracked across different scales and subsequently summed to chosen regions. Both methods yield the same result from one scale to the next, but subsequent scales develop diverging solutions when distributions are strongly non-Gaussian. Data for this evaluation are sea-ice stage-of-development records from US National Ice Center ice charts from 1995 to 1998, as proxy records of ice thickness. Results show regionally integrated thickness exceeds area-weighted average thickness by as much as 60% in summer with as few as five bins in thickness distribution. Year-round, the difference between the two calculations yields volume differences consistently >10%. The largest discrepancies arise due to bimodal distributions which are common in ice charts based on current subjective-analysis protocols. We recommend that integrated distribution be used for regional-scale sea-ice thickness and volume estimates from ice charts and encourage similar testing of other large-scale thickness data archives.

During late winter 2007, coincident measurements of sea ice were collected using various sensors at an ice camp in the Beaufort Sea, Canadian Arctic. Analysis of the archived data provides new insight into sea-ice isostasy and its related R-factor through case studies at three scales using different combinations of snow and ice thickness components. At the smallest scale (R-factor is allowed to vary: ranging from 2 to 12, with mean of 5.17, mode of 5.88 and skewed distribution. At regional scales, underwater, airborne and spaceborne platforms are always missing thickness variables from either above or below sea level. For such situations, realistic agreement is found by applying small-scale skewed ranges for the R-factor. These findings encourage a broader isostasy solution as a function of potential energy and length scale. Overall, results add insight to data collection strategies and metadata characteristics of different thickness products.

Chickaloon Flats, Kenai National Wildlife Refuge, is a 10,000 ha tidal mudflat complex on the Kenai Peninsula in southcentral Alaska. It is a protected coastal estuary stopover area along the Pacific Flyway, covering 7% of the total estuarine intertidal area from Cook Inlet to Prince William Sound. Because Chickaloon Flats is historically an important avian migratory stopover and has relative regional importance in terms of estuarine intertidal area, there was a need to evaluate the current vegetation and determine any changes since the last ground study in 1972. We collected land cover data at a sample of ground-truthed points on Chickaloon Flats during 2009–2010 to evaluate existing vegetation communities as compared to historic 1970–71 values. A maximum likelihood supervised classification was performed on 2005 Landsat TM imagery to create an updated land cover classification of Chickaloon Flats. We used two different analytical approaches to show that the most notable changes in land cover types from 1975–2005 were the increase in early successional communities and a decline in unvegetated mud. Additionally, inland land cover types, which represent the more stable marsh-like communities, decreased in area as a whole. The documented changes in vegetation composition and structure over the four decade study period are attributable to elevation changes from sediment accretion and post-1964 Earthquake subsidence. As a result, evidence points to reduced shorebird use of the Flats.

Childers, D.P.; Madsen, J.A.; Krantz, D.E., and Deliberty, T.L., 2019. Constraining the geometry of subsurface paleochannels beneath Delaware Bay and the Mid-Atlantic inner continental she...

Uncertainties due to spatial resolution (E R) of gridded sea-ice thickness (z) distributions remain largely unquantified. We address this issue using remotely sensed and in situ observations of the Southern Ocean (south of −60°) to determine appropriate data sources based on length scales for continental-scale sea-ice studies. Sea-ice thickness is not normally distributed such that the mean, median, and mode are distinct from each other. Averaging only retains the mean value, reducing bias and natural variability as z is aggregated to coarse resolutions. The rate of smoothing as a function of resolution influences the sea-ice thickness distribution represented by each product. Analysis of E R for 1° through 5° resolutions shows absolute E R increasing with grid-cell size and sea-ice extent in both datasets. The absolute E R for gridded thickness distribution ranges from 0.02 to 0.40 m at 1° and from 0.03 to 0.78 m at 5°. The E R value and slope (m) is lower (E R≤0.20 m, m

Local food systems receive increasing attention as a potential solution to problems in the globalized food system, and the promotion of agriculture and urban sustainability. Despite the centrality of geography of place in the study and practice of local food systems, methods of geographical analysis examining local food systems are just beginning to develop. In this paper we argue that spatial research methods are central to the understanding and evaluation of different components of local food systems. We use the city of Philadelphia as an example to explore the socio-spatial structure of the current local food system, and the integration of remote sensing and GIS techniques to estimate land potential for urban food production.

Antarctic sea-ice thickness and concentration derived from satellite-based ice charts are compared to contemporaneous ship-based estimates of the same parameters collected in the Ross Sea between 130°W and 160°E from 1995 to 1998. Thickness variability exists on the scale of individual ice-chart polygons (tens of kilometers), but found compatible with WMO thickness ranges except in areas with high concentration of ridging. Very good agreement is found between the thickness distributions on the regional scale of the Ross Sea with an annual (climatological) average thickness of 0.65 m for the ice charts in comparison to 0.76 m for the ship-based measurements. Given these analyses, we proceed by examining resulting annual cycle and interannual sea-ice thickness and volume estimates for the Ross Sea region resolved to weekly time intervals. The weekly thickness estimates show the influence of thicker ice advected from the Amundsen Sea, new ice produced adjacent to Ross Ice Shelf, and changes in the Ross Sea polynya. The relationship between weekly ice extent and volume indicate a lag (one to nine weeks) of volume (mass) due to thickness processes during the growth season which differs from lateral extent in 1996-1998, while both extent and volume are more similar during the melt season. The maximum extent and volume occur simultaneously in 1995-1997, but in 1998 the volume peak lags extent by almost 5 weeks. Moreover, thickness variability is found to be more sensitive than extent to climate events during the 1996 La Nina and 1997/98 El Nino episodes. We postulate, therefore, that ice thickening processes evolve somewhat independent of sea-ice extent. These results contradict some existing model studies which show that sea-ice thickness and extent co-vary. Hence, the thickness estimates here demonstrate the importance of measured ice thickness which responds distinctly different from extent in response to dynamic and thermodynamic processes during the annual cycle.

Traffic congestion during peak hours has become one of the major problems affecting the road networks. GPS, in coordination with data retrieving software has been used for various purposes ranging from commercial utilization (route guidance systems) to monitoring traffic by different transportation organizations. In this research, collection of travel time and delay data on a congested network is used to obtain results that enable a commuter to make intelligent choices regarding his or her route. Travel time and delay data retrieved from a GPS instrument attached to a test vehicle traversing the study area during peak hours has been used to determine an optimal route between any given origin and destination in the area. The data collected on each road segment was analyzed and fitted into distributions. Using these distributions, the estimated travel time on each segment was inferred and the probability of being delayed was determined. The travel time and delay data in the form of Microsoft Access tables was imported into the GIS and programmed using a Visual Basic code, such that a user-friendly tool written in Visual Basic using ArcObjects was developed which provides the user with the optimal route between two selected points in the network, the travel time required to traverse the route, and the probability of being delayed on the route. In addition to this data, travel time maps are generated for the network, which provide a visual display illustrating the road network around a reference point for a given time.

Using a hydrologic model to estimate daily soil moisture at 258 evaluation locations over a 30-year period, the spatial variability and persistence of soil moisture across Oklahoma is examined. The Soil and Water Assessment Tool (SWAT) uses readily available meteorological inputs with detailed land surface information. Spatial variability of soil moisture across Oklahoma is extremely dynamic and exhibits a remarkable range of individual characteristics due to the heterogeneous land surface. An autocorrelation analysis is used to evaluate the persistence of soil moisture at each evaluation location. In general, soil moisture across Oklahoma persists from 5 to 10 weeks in the eastern portion of Oklahoma to over 30 weeks in western Oklahoma as a result of the large-scale climatic variability of precipitation supply and evapotranspiration demand. However, the lags are not spatially coherent due to the heterogeneity of the land surface. Land surface characteristics potentially influencing the persistence of so...

The temporal variability of soil moisture is examined for Oklahoma, where diverse land surface, soils, and precipitation regimes exist. Using readily available meteorological, vegetation, and soils data, a hydrologic model was used to estimate daily soil moisture at 258 evaluation locations for the 30 year period from 1 January 1962 through 31 December 1991. A geographic information system (GIS) was used for the analysis, to take advantage of its powerful analysis capabilities and visualization tools. Results document the long-term average soil moisture conditions, the variability that occurred during this 30 year period and the temporal scale of soil moisture variability for Oklahoma. On average, the soil moisture conditions in both winter and spring in Oklahoma are about 70% of field capacity and decrease to below 30% during the summer. Thus, the seasonal cycle is pronounced, although periods of wetter and drier conditions are evident. Overall, the period from 1962 through to early 1967, 1970–72, and 1976 through to 1981 were drier than the long-term average soil moisture conditions. By contrast, wetter soil moisture conditions prevailed in late 1972 through to early 1975 and 1985 to the early months of 1988, where winter and spring soil moisture values often exceeded the long-term average. An empirical estimate of the temporal consistency in soil moisture over Oklahoma is 53 days (1.8 months), and the amount of variance explained by the soil moisture (red noise) signal is 86%. No significant seasonal differences in the temporal autocorrelation were observed. Copyright © 2003 Royal Meteorological Society

This study constructs a regional scale climatology of tropical convection and precipitation from more than 15 years of monthly outgoing longwave radiation (OLR) and precipitation data on 2.5°× 2.5° latitude-longitude grid to examine the spatial and temporal patterns and variability of convection and precipitation in the Amazon Basin. A linear regression analysis also detects if any trends exist in the two datasets. The region of study extends from 15°N to 25°S and 30° to 80°W that encompass the Amazon Basin and surrounding fringe areas for the period from January 1979 through December 1995 for the OLR data and up to 1996 for the precipitation dataset. The basin-average mean monthly and seasonal climatology serve as a ‘baseline’ reference for comparison with the full time series of basin-average monthly OLR and precipitation to illustrate the interannual variability and identify anomalous periods of wet and dry conditions. A linear trend analysis of OLR data found small negative values across the Amazon Ba...

Soil moisture is a critical component of the earth system and plays an integrative role among the various subfields of physical geography. This paper highlights not just how soil moisture affects atmospheric, geomorphic, hydrologic, and biologic processes but that it lies at the intersection of these areas of scientific inquiry. Soil moisture impacts earth surface processes in such a way that it creates an obvious synergistic relationship among the various subfields of physical geography. The dispersive and cohesive properties of soil moisture also make it an important variable in regional and microclimatic analyses, landscape denudation and change through weathering, runoff generation and partitioning, mass wasting, and sediment transport. Thus, this paper serves as a call to use research in soil moisture as an integrative and unifying theme in physical geography. © The Author(s) 2010.

Gage-induced biases in monthly precipitation are estimated and removed at 1818 stations across the continental United States from 1950 through 1987. Deleterious effects of the wind and wetting losses on the interior walls of the gage were considered. These “corrected” estimates were obtained using site-specific information including wind speed, shelter-height air temperature, gage height, and sheltering. Wind speed and air temperature were interpolated at stations for which these data were not available using a spherically-based, nearest neighbor interpolation procedure. Results indicate that, as expected, biases are greater in the winter than the summer owing to the increased problems (particularly wind-induced) of measuring snowfall. In summer, percent errors range between 4 and 6 percent over nearly three-quarters of the United States with slightly larger errors over the Rocky Mountains. By contrast, winter biases are highly correlated with snowfall totals and percentage errors increase poleward, mimicking patterns of snowfall frequency. Since these biases are not trivial, they must be accounted for in order to obtain accurate and reliable time-series. If these biases are not properly addressed, serious errors can be introduced into climate change, hydrologic modeling, and environmental impact research.

[1] Ship-based observations are used to describe regional and seasonal changes in the thickness distribution and characteristics of sea ice and snow cover thickness around Antarctica. The data set comprises 23,373 observations collected over more than 2 decades of activity and has been compiled as part of the Scientific Committee on Antarctic Research (SCAR) Antarctic Sea Ice Processes and Climate (ASPeCt) program. The results show the seasonal progression of the ice thickness distribution for six regions around the continent together with statistics on the mean thickness, surface ridging, snow cover, and local variability for each region and season. A simple ridge model is used to calculate the total ice thickness from the observations of level ice and surface topography, to provide a best estimate of the total ice mass, including the ridged component. The long-term mean and standard deviation of total sea ice thickness (including ridges) is reported as 0.87 ± 0.91 m, which is 40% greater than the mean level ice thickness of 0.62 m. Analysis of the structure function along north/south and east/west transects revealed lag distances over which sea ice thickness decorrelates to be of the order of 100–300 km, which we use as a basis for presenting near-continuous maps of sea ice and snow cover thickness plotted on a 2.5 � 5.0 grid.