AN EXPANDING ROLE FOR SUBARCTIC WATERSHED RESEARCH1

ABSTRACT: It is increasingly recognized that natural resources research should in many cases be broadened in scope and oriented toward more general “environmental” problems. Locales with a history of “watershed” research can be eminently suited for development of comprehensive, environmental research programs. This is recognized in many research efforts of the International Biological Program (IBP), where watershed research sites have been successfully utilized for intensive investigations of process and function of selected ecosystems or ecosystem components. In the North American Subarctic there is almost no history of “watershed” studies. Basic data on hydrometeorologic parameters such as precipitation amounts and areal and seasonal distribution of runoff are scarce; the data framework within which environmental understanding can be structured is exceedingly sketchy. Opportunity exists in the discontinuous-permafrost settings of central Alaska to begin rectifying this situation. A basic program of multi-agency, multi-discipline research and data acquisition for the most significant hydrologic subregions is being developed, based around several existing environmental research areas (chiefly the Bonanza Creek Experimental Forest, the Caribou-Poker Creeks Research Watershed, the Wickersham Dome Fire Study Area, and a series of outlying sites).     

Platinum emission rate of automobiles with catalytic converters

Inconsistent data presently available on the platinum emission rate of cars in Germany equipped with catalytic converters are evaluated. Automobile sources of Pt other than autocatalysts are quantified and found to be 1–6 orders of magnitudes lower than the Pt emissions attributed to catalytic converters. A transfer of emission rates derived from test stand experiments to more realistic street conditions reaches 0.8 μg Pt/km. In this manner, data from test stand experiments and from environmental investigations meet in the range of 0.5–0.8 μg Pt/km.     

Comparison of palladium and platinum in environmental matrices: Palladium pollution by automobile emissions?

A new type of automobile catalyst based on an active Pd/Rh-layer is presently being introduced into the European market. Accordingly, in order to establish baseline information, this work attempts to assess the magnitude of Pd emissions by automobile catalysts to date. Thus, a survey is presented on Pd and Pt levels detected in polluted environmental matrices (grass, soil, dust, sludges) as available from the literature. Additionally, Pd data measured by selective preconcentration/GF-AAS-detection in polluted grass, in a time series of sewage sludge ashes back to 1972, in dust, as well as in urban rain are presented. Since the data basis from the literature is partly inconsistent, the possible impact of different analytical attempts on the data is discussed. The relationship between Pt and Pd concentration from most of the results is between 5 and 10 (Pt/Pd). However, relations down to 0.04 are also reported, thus implying anthropogenic Pd input from additional sources.     

Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values

The curve number (CN) method is used to calculate runoff in many hydrologic models, including the Soil and Water Assessment Tool (SWAT). The CN method does not account for the spatial distribution of land cover types, an important factor controlling runoff patterns. The objective of this study was to empirically derive CN values that reflect the strategic placement of native prairie vegetation (NPV) within row crop agricultural landscapes. CNs were derived using precipitation and runoff data from a seven‐year period for 14 small watersheds in Iowa. The watersheds were planted with varying amounts of NPV located in different watershed positions. The least squares and asymptotic least squares methods (LSM) were used to derive CNs using an initial abstraction coefficient (λ) of 0.2 and 0.05. The CNs were verified using leave‐one‐out cross‐validation and adjustment for antecedent moisture conditions (AMC) was tested. The asymptotic method produced CN values for watersheds with NPV treatment that were 8.9 and 14.7% lower than watersheds with 100% row crop at λ = 0.2 and λ = 0.05, respectively. The derived CNs produced Nash‐Sutcliffe efficiency values ranging from 0.4 to 0.7 during validation. Our analyses show the CNs verified best for the asymptotic LSM, when using λ of 0.05 and adjusting for AMC. Further, comparison of derived CNs against an area weighted CN indicated that the placement of vegetation does impact the CN value. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Simulating nitrate-nitrogen concentration from a subsurface drainage system in response to nitrogen application rates using RZWQM2

Computer models have been widely used to evaluate the impact of agronomic management on nitrogen (N) dynamics in subsurface drained fields. However, they have not been evaluated as to their ability to capture the variability of nitrate-nitrogen (NO(3)-N) concentration in subsurface drainage at a wide range of N application rates due to possible errors in the simulation of other system components. The objective of this study was to evaluate the performance of Root Zone Water Quality Model2 (RZWQM2) in simulating the response of NO(3)-N concentration in subsurface drainage to N application rate. A 16-yr field study conducted in Iowa at nine N rates (0-252 kg N ha(-1)) from 1989 to 2004 was used to evaluate the model, based on a previous calibration with data from 2005 to 2009 at this site. The results showed that the RZWQM2 model performed "satisfactorily" in simulating the response of NO(3)-N concentration in subsurface drainage to N fertilizer rate with 0.76, 0.49, and -3% for the Nash-Sutcliffe efficiency, the ratio of the root mean square error to the standard deviation, and percent bias, respectively. The simulation also identified that the N application rate required to achieve the maximum contaminant level for the annual average NO(3)-N concentration was similar to field-observed data. This study supports the use of RZWQM2 to predict NO(3)-N concentration in subsurface drainage at various N application rates once it is calibrated for the local condition.