Nicolas Zegre

Comparison of NAIP orthophotography and RapidEye satellite imagery for mapping of mining and mine reclamation

National Agriculture Imagery Program (NAIP) orthophotography is a potentially useful data source for land cover classification in the United States due to its nationwide and generally cloud-free coverage, low cost to the public, frequent update interval, and high spatial resolution. Nevertheless, there are challenges when working with NAIP imagery, especially regarding varying viewing geometry, radiometric normalization, and calibration. In this article, we compare NAIP orthophotography and RapidEye satellite imagery for high-resolution mapping of mining and mine reclamation within a mountaintop coal surface mine in the southern coalfields of West Virginia, USA. Two classification algorithms, support vector machines and random forests, were used to classify both data sets. Compared to the RapidEye classification, the NAIP classification resulted in lower overall accuracy and kappa and higher allocation disagreement and quantity disagreement. However, the accuracy of the NAIP classification was improved by reducing the number of classes mapped, using the near-infrared band, using textural measures and feature selection, and reducing the spatial resolution slightly by pixel aggregation or by applying a Gaussian low-pass filter. With such strategies, NAIP data can be a potential alternative to RapidEye satellite data for classification of surface mine land cover.

Monitoring seasonal bat activity on a coastal barrier island in Maryland, USA

Research on effects of wind turbines on bats has increased dramatically in recent years because of significant numbers of bats killed by rotating wind turbine blades. Whereas most research has focused on the Midwest and inland portions of eastern North America, bat activity and migration on the Atlantic Coast has largely been unexamined. We used three long-term acoustic monitoring stations to determine seasonal bat activity patterns on the Assateague Island National Seashore, a barrier island off the coast of Maryland, from 2005 to 2006. We recorded five species, including eastern red bats (Lasiurus borealis), big brown bats (Eptesicus fuscus), hoary bats (Lasiurus cinereus), tri-colored bats (Perimyotis subflavus), and silver-haired bats (Lasionycteris noctivagans). Seasonal bat activity (number of bat passes recorded) followed a cosine function and gradually increased beginning in April, peaked in August, and declined gradually until cessation in December. Based on autoregressive models, inter-night bat activity was autocorrelated for lags of seven nights or fewer but varied among acoustic monitoring stations. Higher nightly temperatures and lower wind speeds positively affected bat activity. When autoregressive model predictions were fitted to the observed nightly bat pass totals, model residuals >2 standard deviations from the mean existed only during migration periods, indicating that periodic increases in bat activity could not be accounted for by seasonal trends and weather variables alone. Rather, the additional bat passes were attributable to migrating bats. We conclude that bats, specifically eastern red, hoary, and silver-haired bats, use this barrier island during migration and that this phenomenon may have implications for the development of near and offshore wind energy.

Corrected prediction intervals for change detection in paired watershed studies

Abstract Hydrological data may be temporally autocorrelated requiring autoregressive process parameters to be estimated. Current statistical methods for hydrological change detection in paired watershed studies rely on prediction intervals, but the current form of prediction intervals does not include all appropriate sources of variation. Corrected prediction intervals for the analysis of paired watershed study data that include variation associated with covariance and linear model parameter estimation are presented. We provide an example of their application to data from the Hinkle Creek Paired Watershed Study located in the western Cascade foothills of Southern Oregon, USA. Research implications of using the correct prediction limits and incorporating the estimation uncertainty of autoregressive process parameters are discussed. Editor D. Koutsoyiannis Citation Som, N.A., Zégre, N.P., Ganio, L.M. and Skaugset, A.E., 2012. Corrected prediction intervals for change detection in paired watershed studies. Hydrological Sciences Journal, 57 (1), 134–143.

Can brook trout survive climate change in large rivers? If it rains

We provide an assessment of thermal characteristics and climate change vulnerability for brook trout (Salvelinus fontinalis) habitats in the upper Shavers Fork sub-watershed, West Virginia. Spatial and temporal (2001-2015) variability in observed summer (6/1-8/31) stream temperatures was quantified in 23 (9 tributary, 14 main-stem) reaches. We developed a mixed effects model to predict site-specific mean daily stream temperature from air temperature and discharge and coupled this model with a hydrologic model to predict future (2016-2100) changes in stream temperature under low (RCP 4.5) and high (RCP 8.5) emissions scenarios. Observed mean daily stream temperature exceeded the 21°C brook trout physiological threshold in all but one main-stem site, and 3 sites exceeded proposed thermal limits for either 63- and 7-day mean stream temperature. We modeled mean daily stream temperature with a high degree of certainty (R2=0.93; RMSE=0.76°C). Predicted increases in mean daily stream temperature in main-stem and tributary reaches ranged from 0.2°C (RCP 4.5) to 1.2°C (RCP 8.5). Between 2091 and 2100, the average number of days with mean daily stream temperature>21°C increased within main-stem sites under the RCP 4.5 (0-1.2days) and 8.5 (0-13) scenarios; however, no site is expected to exceed 63- or 7-day thermal limits. During the warmest 10years, ≥5 main-stem sites exceeded the 63- or 7-day thermal tolerance limits under both climate emissions scenarios. Years with the greatest increases in stream temperature were characterized by low mean daily discharge. Main-stem reaches below major tributaries never exceed thermal limits, despite neighboring reaches having among the highest observed and predicted stream temperatures. Persistence of thermal refugia within upper Shavers Fork would enable persistence of metapopulation structure and life history processes. However, this will only be possible if projected increases in discharge are realized and offset expected increases in air temperature.

Climate, forest growing season, and evapotranspiration changes in the central Appalachian Mountains, USA

We analyzed trends in climatologic, hydrologic, and growing season length variables, identified the important variables effecting growing season length changes, and evaluated the influence of a lengthened growing season on increasing evapotranspiration trends for the central Appalachian Mountains region of the United States. We generated three growing season length variables using remotely sensed GIMMS NDVI3g data, two variables from measured streamflow, and 13 climate parameters from gridded datasets. We included various climate, hydrology, and phenology explanatory variables in two applications of Principle Components Analysis to reduce dimensionality, then utilized the final variables in two Linear Mixed Effects models to evaluate the role of climate on growing season length and evapotranspiration. The results showed that growing season length has increased, on average, by ~22 days and evapotranspiration has increased up to ~12 mm throughout the region. The results also suggest that a suite of climatic variables including temperature, vapor pressure deficit, wind, and humidity are important in growing season length change. The climatic variables work synergistically to produce greater evaporative demand and atmospheric humidity, which is theoretically consistent with intensification of the water cycle and the Clausius-Clapeyron relation, which states that humidity increases nonlinearly by 7%/K. Optimization of the evapotranspiration model was increased by the inclusion of growing season length, suggesting that growing season length is partially responsible for variations in evapotranspiration over time. The results of this research imply that a longer growing season has the potential to increase forest water cycling and evaporative loss in temperate forests, which may lead to decreased freshwater provisioning from forests to downstream population centers. Additionally, results from this study provide important information for runoff and evapotranspiration modelling and forest water management under changing climate.

Disturbance Hydrology: Preparing for an Increasingly Disturbed Future

This special issue is the result of several fruitful conference sessions on disturbance hydrology, which started at the 2013 AGU Fall Meeting in San Francisco and have continued every year since. The stimulating presentations and discussions surrounding those sessions have focused on understanding both the disruption of hydrologic functioning following discrete disturbances, as well as the subsequent recovery or change within the affected watershed system. Whereas some hydrologic disturbances are directly linked to anthropogenic activities, such as resource extraction, the contributions to this special issue focus primarily on those with indirect or less pronounced human involvement, such as bark-beetle infestation, wildfire, and other natural hazards. However, human activities are enhancing the severity and frequency of these seemingly natural disturbances, thereby contributing to acute hydrologic problems and hazards. Major research challenges for our increasingly disturbed planet include the lack of continuous pre and postdisturbance monitoring, hydrologic impacts that vary spatially and temporally based on environmental and hydroclimatic conditions, and the preponderance of overlapping or compounding disturbance sequences. In addition, a conceptual framework for characterizing commonalities and differences among hydrologic disturbances is still in its infancy. In this introduction to the special issue, we advance the fusion of concepts and terminology from ecology and hydrology to begin filling this gap. We briefly explore some preliminary approaches for comparing different disturbances and their hydrologic impacts, which provides a starting point for further dialogue and research progress.

High Frequency Trends in the Isotopic Composition of Superstorm Sandy

Reliable forecasts of extra-tropical cyclones such as Superstorm Sandy require accurate understanding of their thermodynamic evolution. Within such systems, the evaporation, transport, and precipitation of moisture alters stable isotope ratios of cyclonic waters and creates spatio-temporal isotopic patterns indicative of synoptic-scale processes. Here, high-frequency records of precipitation isotope ratios from four sites (West Lebanon, NH; Baltimore, MD; State College, PA; and Colcord, WV) are used to investigate the development of Sandy as the storm made landfall and moved inland. These high-frequency records are also combined with a Lagrangian backward transport model to create a general relationship between precipitation deuterium-excess and moisture source conditions. Based on this general relationship, the evolution of precipitation efficiency within Superstorm Sandy is mapped through time using a set of distributed isotope collections. These maps identify a region of high-precipitation efficiency near storm’s core where intense rainfall rates likely exceeded the resupply of moisture as well as outlying rain-bands of lower precipitation efficiency possibly influenced by entrainment of a mid-western cold front.