Distributions and characteristics of dissolved organic matter in temperate coastal waters (Southern North Sea)

The spatial and temporal distributions of chromophoric dissolved organic matter (CDOM) and dissolved organic carbon (DOC) was studied in the East-Frisian Wadden Sea (Southern North Sea) during several cruises between 2002 and 2005. The spatial distribution of CDOM in the German Bight shows a strong gradient towards the coast. Tidal and seasonal variations of dissolved organic matter (DOM) identify freshwater discharge via flood-gates at the coastline and pore water efflux from tidal flat sediments as the most important CDOM sources within the backbarrier area of the Island of Spiekeroog. However, the amount and pattern of CDOM and DOC is strongly affected by various parameters, e.g. changes in the amount of terrestrial run-off, precipitation, evaporation, biological activity and photooxidation. A decoupling of CDOM and DOC, especially during periods of pronounced biological activity (algae blooms and microbial activity), is observed in spring and especially in summer. Mixing of the endmembers freshwater, pore water, and open sea water results in the formation of a coastal transition zone. Whilst an almost conservative behaviour during mixing is observed in winter, summer data point towards non-conservative mixing.     

Response to “Limitations in the Hilbert Transform Approach to Locating Solar Cycle Terminators” by R. Booth

Solar Physics - The Maunder Minimum (1645?–?1715) was unique in terms of solar-cycle amplitudes and sunspot-position distributions registered in the last four centuries; however,...     

Linking runoff response to burn severity after a wildfire

Extreme floods often follow wildfire in mountainous watersheds. However, a quantitative relation between the runoff response and burn severity at the watershed scale has not been established. Runoff response was measured as the runoff coefficient C, which is equal to the peak discharge per unit drainage area divided by the average maximum 30 min rainfall intensity during each rain storm. The magnitude of the burn severity was expressed as the change in the normalized burn ratio. A new burn severity variable, hydraulic functional connectivity Φ was developed and incorporates both the magnitude of the burn severity and the spatial sequence of the burn severity along hillslope flow paths. The runoff response and the burn severity were measured in seven subwatersheds (0·24 to 0·85 km²) in the upper part of Rendija Canyon burned by the 2000 Cerro Grande Fire near Los Alamos, New Mexico, USA. A rainfall–discharge relation was determined for four of the subwatersheds with nearly the same burn severity. The peak discharge per unit drainage area was a linear function of the maximum 30 min rainfall intensity I₃₀. This function predicted a rainfall intensity threshold of 8·5 mm h^?1 below which no runoff was generated. The runoff coefficient was a linear function of the mean hydraulic functional connectivity of the subwatersheds. Moreover, the variability of the mean hydraulic functional connectivity was related to the variability of the mean runoff coefficient, and this relation provides physical insight into why the runoff response from the same subwatershed can vary for different rainstorms with the same rainfall intensity. Copyright © 2007 John Wiley & Sons, Ltd.     

Comparative performance analysis of climate re-analysis approaches in Angola

This paper examines the performance of three climate re-analysis datasets in Angola, namely the ERA-40, NCEP-r1 and JRA-55, by comparing annual and seasonal estimates of precipitation, surface air temperature and evaporation with ground observation measurements. The observational dataset describes a region poorly covered by international climate databases and it is believed that most of its data have not been used in the data assimilation procedures of the climate models. This paper therefore provides a fresh look at the performance of these climate re-analysis datasets in a vast area where distance and civil war have hindered ground monitoring efforts. The re-analysis exercises offer better temperature estimates than precipitation estimates. When offered, the evaporation estimates from all three products are very poor. The three products are able to describe the main features of the spatial distribution of average annual precipitation and temperature, but struggle to reproduce the temporal changes of these variables. The results from a set of performance criteria show that the correlation between the observed ground measurements and re-analysis estimates is poor overall and the NSE values indicate that the average measured value at each location is usually a better estimate than the re-analysis estimate.

EDITOR A. Castellarin

ASSOCIATE EDITOR S. Kanae     

Seabed sediments and foraminifera over the Lido Inlet: Comparison between 1983 and 2006 distribution patterns

Extensive sampling in the Lagoon and Gulf of Venice during the 1980s provided material to establish ‘base’ conditions for subsequent studies of distributions of benthic foraminiferal biotopes and sediments.     

Performance of methods for estimating the time of concentration in a watershed of a tropical region

The time of concentration (T_c) is a fundamental parameter in the design of hydrological projects for watersheds. In this study a graphical methodology is described for estimating T_c in a watershed, and this is applied to 17 rainfall–runoff events from a rural watershed located near the capital city of Mato Grosso do Sul State, in the Brazilian Cerrado. The T_c values obtained through the graphical method were compared to T_c values estimated using 20 equations from various references. The equations were selected by considering those that were not developed using data for urban watersheds, and the results of the graphical method were compared to those derived by applying the equations to sub-basin data. The graphical method was reliable in determining T_c, and Ventura’s equation was found to present the best performance for a rural watershed in a tropical climate region.     

Seasonality of Coliform Bacteria Detection Rates in New Jersey Domestic Wells

It is important that indicators of fecal pollution are reliable. Coliform bacteria are a commonly used indicator of fecal pollution. As other investigators have reported elsewhere, we observed a seasonal pattern of coliform bacteria detections in domestic wells in New Jersey. Examination of a statewide database of 10 years of water quality data from 93,447 samples, from 78,207 wells, generated during real estate transactions, revealed that coliform bacteria were detected in a higher proportion of wells during warm weather months. Further examination of the seasonal pattern of other data, including well water pH, precipitation, ground and surface water temperatures, surface water coliform bacteria concentrations, and vegetation, resulted in the hypothesis that these bacteria may be derived from nonfecal (or environmentally adapted) as well as fecal sources. We provide evidence that the coliform seasonality may be the result of seasonal changes in groundwater extraction volumes (and to a lesser extent precipitation), and temperature‐driven changes in the concentration of surface or near‐surface coliform sources. Nonfecal coliform sources may not indicate the presence of fecal wastes and hence the potential presence of pathogens, or do so in an inconsistent fashion. Additional research is needed to identify the sources of the coliforms detected in groundwater.     

The Likelihood of Coliform Bacteria in NJ Domestic Wells Based on Precipitation and Other Factors

The influence of precipitation on coliform bacteria detection rates in domestic wells was investigated using data collected through the New Jersey Private Well Testing Act. Measured precipitation data from the National Weather Service (NWS) monitoring stations was compared to estimated data from the Multisensor Precipitation Estimate (MPE) in order to determine which source of data to include in the analyses. A strong concordance existed between these two precipitations datasets; therefore, MPE data was utilized as it is geographically more specific to individual wells. Statewide, 10 days of cumulative precipitation prior to testing was found to be an optimal period influencing the likelihood of coliform detections in wells. A logistic regression model was developed to predict the likelihood of coliform occurrence in wells from 10 days of cumulative precipitation data and other predictive variables including geology, season, coliform bacteria analysis method, pH, and nitrate concentration. Total coliform (TC) and fecal coliform or Escherichia coli (FC/EC) were detected more frequently when the preceding 10 days of cumulative precipitation exceeded 34.5 and 54 mm, respectively. Furthermore, the likelihood of coliform detection was highest in wells located in the bedrock region, during summer and autumn, analyzed with the enzyme substrate method, with pH between 5 and 6.99, and (for FC/EC but not TC) nitrate greater than 10 mg/L. Thus, the likelihood of coliform presence in domestic wells can be predicted from readily available environmental factors including timing and magnitude of precipitation, offering outreach opportunities and potential changes to coliform testing recommendations.     

Sustainable livelihoods approaches to inform government‐local partnerships and decision‐making in vulnerable environments

Sustainable livelihoods approaches used in international development are applied to a vulnerable New Zealand catchment. The Waiapu Catchment has a high proportion of indigenous residents, and is one of the most remote and deprived areas in the country. Linear and centralised approaches to indigenous development have failed to bring about desired changes. We identify “capitals” (social, human/political, physical, natural, financial and cultural) present in the catchment. From this assessment, we propose capital‐based holistic approaches to bring about community‐led change. The assessment and resulting approaches can be used in other vulnerable environments around the world.     

Land Cover Changes on Ambergris Caye,Belize: A Case Study of Unregulated Tourism Development

Measuring land-use, land-cover change in biodiverse, tropical countries is critical for conservation management and sustainable planning because it provides quantifiable data regarding broad environmental changes. This project uses Landsat satellite imagery to document vegetation cover change on Ambergris Caye, Belize, from 2000 to 2017. The close proximity of the Belize Barrier Reef Reserve System has made Ambergris Caye the most popular tourist destination and economic hub in Belize. As a result, the region has undergone intense commercial and residential development coupled with rapid population growth over the past two decades. Understanding general trends in landscape dynamics is critical for the natural resource–based tourism industry of Belize to continue to thrive. Unsupervised classification methods and a per pixel postclassification comparison were used with Landsat imagery to estimate loss in vegetation cover and increases in urban and barren land. The results indicate a 10.85 percent decrease in vegetation and a 39 percent increase in urban and barren land during the seventeen-year study period with an annual forest loss rate of 0.67 percent per year using a compound interest rate formula. The results of this analysis represent a baseline study of vegetation change on Ambergris Caye to inform management and conservation efforts.