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.     

Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston1

Teague, Aarin, Philip B. Bedient, and Birnur Guven, 2011. Targeted Application of Seasonal Load Duration Curves Using Multivariate Analysis in Two Watersheds Flowing Into Lake Houston. Journal of the American Water Resources Association (JAWRA) 47(3):620‐634. DOI: 10.1111/j.1752‐1688.2011.00529.x Abstract: Water quality is a problem in Lake Houston, the primary source of drinking water for the City of Houston, Texas, due to pollutant loads coming from the influent watersheds, including Spring Creek and Cypress Creek. Statistical analysis of the historic water quality data was developed to understand the source characterization and seasonality of the watershed. Multivariate analysis including principal component, cluster, and discriminant analysis provided a custom seasonal assessment of the watersheds so that loading curves may be targeted for season specific pollutant source characterization. The load duration curves have been analyzed using data collected by the U.S. Geologic Survey with corresponding City of Houston water quality data at the sites to characterize the behavior of the pollutant sources and watersheds. Custom seasons were determined for Spring Creek and Cypress Creek watersheds and pollutant source characterization compared between the seasons and watersheds.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

坡岸截留强化处理设施在不同运行条件下对农业面源污染物去除效果

对坡岸截留强化处理设施在不同温度、不同雨强、不同降雨间隔条件下处理农业面源污染进行中试试验研究.结果表明,水温从20℃下降至4.3℃,COD、TN、NH+4-N、TP去除率下降了15.58%、48.93%、42.26%、57.75%;降雨强度由0.65mm·min-1增加1倍至1.30 mm·min-1,COD的平均去除率低了15.19%,TN、NH+4-N的去除效率相当,TP的去除效率提高了11.21%,但COD、TN、NH+4-N、TP单位面积去除的总量却提高了26.27%、68.3%、32.6%、104.2%;降雨间隔从2 d增加到4 d时对COD去除的影响不大,但使NH+4-N、TN的处理效率提高19.31%、13.95%,对TP的单位面积去除量提高71.43%,但去除总量有限.     

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。     

罕见冬季降雨中人工增雨微物理过程分析研究

用Micaps实时资料、CPAS卫星反演分析资料、NCEP再分析资料、ECMWF再分析资料,多普勒雷达PUP产品资料,对2015年12月1日夜间至2日凌晨沈阳地区罕见冬季降雨过程,进行了天气学分析、及大气微物理人工增雨作业条件分析,并结合沈阳地区人工增雨作业指标,得出本次降雨过程在厄尔尼诺正在发生的背景下,为常见的高空槽转东北冷涡型,水汽、动力等微物理作业条件也适合于开展人工增雨作业,并给出了相应的作业指导参数,为沈阳地区今后在冬季降雨天气过程中开展人工增雨作业积累了宝贵经验.     

酸雨区不同用地类型土壤有效态Cd含量季节变化及关键影响因子

探明污染土壤重金属有效态含量的季节变化特征及其敏感影响因子,对农业生产过程中减低重金属生态风险具有重要的参考价值.研究于湘江中下游典型Cd超标农业小流域中选取稻田、旱作蔬菜地、丘陵林地这3类主要用地类型,分析不同用地类型Cd活性的季节变化特征及其与土壤基本理化参数的关联.为期1 a的原位监测结果显示,研究区为典型酸雨区,雨水p H值呈现冬、春季节低于夏、秋季.稻田土壤总Cd含量显著高于旱作蔬菜地,菜地显著高于林地,3种用地类型土壤总Cd含量季节特征相似,均为夏秋季节略低于冬春两季.3种用地类型Cd有效态季节变化与总Cd含量无明显的相关性,稻田土壤有效态Cd含量在5~9月的作物生长季明显低于其他月份,而菜地和林地则恰好相反.稻田土壤Cd有效性的最关键影响因子为Eh,呈显著正相关,与土壤p H负相关,菜地土壤与土壤TOC明显负相关,而林地土壤Cd有效性与水溶性有机碳、TOC呈现明显的正相关关系.研究可为Cd超标土壤污染阻控与农业安全生产提供一定的数据参考.