PREDICTIVE MODEL FOR NITRATE LOAD IN THE BULL RUN WATERSHED,OREGON1

ABSTRACT: Predictive models for nitrate in four streams in the Bull Run Watershed in the Cascade Mountains of Oregon were developed from a record of 17 years of nitrate samples. The models are time series regression models written in terms of Log(nitrate load). The independent variables are logarithm of 14-day mean daily stream discharge, current day's precipitation, logarithm of the previous day's precipitation, total precipitation for the previous seven days, a hydrograph position variable that indicates rising or falling limb, and average maximum air temperature for the preceding 14 days. The models describe annual cycle and seasonable trends and variations in nitrate load, but are unable to describe large day to day variations like those associated with hydrograph peaks.     

NATURAL EROSION RATES AND THEIR PREDICTION IN THE IDAHO BATHOLITH1

ABSTRACT: Natural rates of surface erosion on forested granitic soils in central Idaho were measured in 40 m² bordered erosion plots over a period of four years. In addition, we measured a variety of site variables, soil properties, and summer rainstorm intensities in order to relate erosion rates to site attributes. Median winter erosion rates are approximately twice summer period rates, however mean summer rates are nearly twice winter rates because of infrequent high erosion caused by summer rainstorms. Regression equation models and regression tree models were constructed to explore relationships between erosion and factors that control erosion rates. Ground cover is the single factor that has the greatest influence on erosion rates during both summer and winter periods. Rainstorm intensity (erosivity index) strongly influences summer erosion rates, even on soils with high ground cover percentages. Few summer storms were of sufficient duration and intensity to cause rilling on the plots, and the data set was too small to elucidate differences in rill vs. interrill erosion. The regression tree models are relatively less biased than the regression equations developed, and explained 70 and 84 percent of the variability in summer and winter erosion rates, respectively.     

THE ARMA MODELS APPLIED TO THE FLOW OF KARSTIC SPRINGS1

ABSTRACT: Autoregressive moving average (ABMA) models have been applied to study the flow series of the karstic springs of La Villa, Fuente Mayor (Spain), and Aliou (France). The theoretical meaning of the parameters involved in the model upon applying it to a simplified scheme of the emptying of a karstic aquifer is first analyzed. The types of transformations necessary to apply these models to the flow series that lack normality and have strong periodic components are also indicated, as are the advantages of this type of model and the physical significance of the parameters obtained, with respect to the standpoint of hydraulics, ranging from rather homogeneous aquifers (La Villa) to extremely karstic (Aliou), including aquifers with intermediate characteristics (Fuente Mayor).     

黄河三角洲风暴潮灾害及其对滨海湿地的影响

黄河三角洲是中国重要的滨海湿地分布区，也是中国风暴潮易发区。该区的风暴潮有温带气旋型与热带台风型两种，以温带风暴潮为主。近年来，重大风暴潮的发生有频率增加、危害加重的趋势。风暴潮对滨海湿地的影响是广泛而深远的，主要表现为淹没滨海低地、加速海岸蚀退、破坏地表结构、毁坏湿地植被、加剧海水入侵等，使滨海湿地不断损失退化，生态环境恶化。     

EFFECTS OF WATERSHED REPRESENTATION ON RUNOFF AND SEDIMENT YIELD MODELING1

ABSTRACT: This paper evaluates the effects of watershed geometric representation (i.e., plane and channel representation) on runoff and sediment yield simulations in a semiarid rangeland watershed. A process based, spatially distributed runoff erosion model (KINEROS2) was used to explore four spatial representations of a 4.4 ha experimental watershed. The most complex representation included all 96 channel elements identifiable in the field. The least complex representation contained only five channel elements. It was concluded that oversimplified watershed representations greatly influence runoff and sediment yield simulations by inducing excessive infiltration on hillslopes and distorting runoff patterns and sediment fluxes. Runoff and sediment yield decrease systematically with decreasing complexity in watershed representation. However, less complex representations had less impact on runoff and sediment‐yield simulations for small rainfall events. This study concludes that the selection of the appropriate level of watershed representation can have important theoretical and practical implications on runoff and sediment yield modeling in semiarid environments.     

Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).     

Analysis of Roadside Inhalable Particulate Matter (PM10) in Major Korean Cities

A data analysis of three major Korean cities was conducted to assess roadside inhalable particulate matter 10 μm or smaller in aerodynamic diameter (PM₁₀), including temporal and meteorological variations, over a recent period of 4 to 6 years. The yearly roadside PM₁₀ concentrations presented a well-defined increasing trend or no trend depending on the roadside monitoring station. Most mean values exceeded or approximated the Korean standard of 70 μg/m³ per year for PM₁₀. A representative roadside diurnal trend was characterized by a distinct morning maximum. In most cases, the Sunday roadside concentrations were similar to or somewhat lower than the weekday concentrations, and the PM₁₀ concentrations presented a well-defined seasonal variation, with the maximum concentration in March. The monthly maximum concentrations observed in March were most likely attributable to Asian dust storms. In two metropolitan cities (Seoul and Busan), the frequency of days with roadside PM₁₀ concentrations exceeding the standard of 150μg/m³ per 24 h was much lower for the roadside monitoring stations than for the residential monitoring station, whereas in the third city (Daegu), this result was reversed. Interestingly, the average maximum concentrations observed for the roadside sites in Seoul and Busan during March were higher than those for the residential sites, suggesting that the roadside concentrations responded more to the dust storms than the residential areas. The relationship between the pollutant concentrations and five important meteorological parameters (solar radiation, wind speed, air temperature, relative humidity, and precipitation) showed that the number and type of meteorological variables included in the equations varied according to the monitoring station or season. Finally, the current results confirmed that attention should be given to the PM₁₀ exposure of residents living near roadways.     

DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

Tracking a half century of media reporting on gray wolves

Natural resource and wildlife managers must balance the disparate priorities of a diversity of stakeholders. To manage these priorities, a firm understanding of topics salient to the public is needed. The media often report on issues of importance to the public; therefore, these reports may be a useful measure of public interest. However, efficient methods for distinguishing diverse topics related to a wildlife management issue reported in the media and changes in the salience of those topics have been lacking. We used latent Dirichlet allocation, a Bayesian mixture model, to quantitatively assess the salience of topics surrounding the gray wolf (Canis lupus), which was reintroduced to Idaho (U.S.A.) in 1995. We analyzed articles published from 1960 to 2015 in an Idaho newspaper. We identified 6 distinct topics associated with gray wolves: policy, hunting, biological status, implementation of management, recovery, and human-wolf conflict. The salience of topics pre- and postreintroduction of wolves (1995) and pre- and postdelisting of wolves from the U.S. Endangered Species Act (2009) differed significantly, underscoring that these events were turning points in how issues were being publicly discussed and framed. Articles written by the local reporters were more likely to report on topics regarding conflict between humans and wolves, whereas articles sourced from a national outlet reported more on topics pertaining to wolf policy and biological status. In the context of managing a contentious, far-ranging, and long-lived wildlife species, our methods can help guide the location and timing of a suite of management strategies (e.g., media relation plans and stakeholder engagement) that promote human-wildlife coexistence across different landscapes.     

太阳风暴对短波电子装备性能的影响及应对措施

目的掌握太阳风暴对短波电子装备性能的影响及应对措施,为系统设计提供参考。方法分析太阳风暴的表现形式,并从作用距离、目标检测、定位精度等方面给出太阳风暴对短波超视距雷达、短波通信等装备的影响。结果电离层SID、电离层暴可造成短波通信中断,短波通信可用频段变窄。电离层强吸收可降低天波超视距雷达作用距离和目标定位精度,电子浓度、电离层虚高快速变化影响超视距雷达检测性能和定位精度,负相电离层暴使天波超视距雷达可用频段严重变窄。地球磁暴期间,电磁场突变产生的强电压和电流有可能烧毁用于天、地波超视距雷达的电子设备。电离层非规则现象对超视距雷达有严重影响。结论太阳风暴对电子装备性能有利有弊,要分别对待。系统设计时应充分考虑太阳风暴的影响,在出现太阳风暴时,采取针对性措施降低其影响。