Backwater Confluences of the Ohio River: Organic and Inorganic Fingerprints Explain Sediment Dynamics in Wetlands and Marinas

In the Ohio River (OR), backwater confluence sedimentation dynamics are understudied, however, these river features are expected to be influential on the system’s ecological and economic function when integrated along the river’s length. In the following paper, we test the efficacy of organic and inorganic tracers for sediment fingerprinting in backwater confluences; we use fingerprinting results to evidence sediment dynamics controlling deposition patterns in confluences used for wetland and marina functions; and we quantify the spatial extent of tributary drainages with wetland and marina features in OR confluences. Both organic and inorganic tracers statistically differentiate sediment from stream and river end‐members. Carbon and nitrogen stable isotopes produce greater uncertainty in fingerprinting results than inorganic elemental tracers. Uncertainty analysis of the nonconservative tracer term in the organic matter fingerprinting application estimates an apparent enrichment of the carbon stable isotopes during instream residence, and the nonconservativeness is quantified with a statistical approach unique to the fingerprinting literature. Wetland and marina features in OR confluences impact 42% and 11% of tributary drainage areas, respectively. Sediment dynamics show wetland and marina confluences experience deposition from river backwaters with longitudinally linear and nonlinear patterns, respectively, from sediment sources.     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Time perspective balance and team adaptation in dynamic task contexts

The concept of time perspective balance has attracted increased attention from scholars in the past decade, reflected in published evidence suggesting positive outcomes ranging from enhanced mood to life satisfaction for those individuals possessing balance among their past, present, and future time perspectives, and assumedly able to shift their time perspective to match situational demands. In this paper, we consider the notion of time perspective balance in an organizational setting within which much consequential adaptation often occurs—the team environment—and explore different configurations of time perspective balance in teams facing dynamic task contexts. Drawing from work on situational awareness, we first consider the mechanism by which time perspective balance likely influences individual adaptation in dynamic task-focused situations. Next, we postulate what types of team configurations—ones with more balanced time perspective uniformity or ones with more time perspective variety—might be more appropriate in dynamic contexts given key team conditions. We illustrate our analysis with examples from healthcare team settings and offer ideas for future research.     

分散式污水处理设施集约化管理创新探索

随着近年来大量农村污水处理设施的新建,项目污水处理设施面广、点多、单体规模小、污染物浓度变化大、经营困难等问题凸显,如何突破困境找到一条相对适合分散式污水处理设施的运营管理十分必要。本文提出了集约化管理创新探索,在生产标准化管理、人力资源管理、安全管理、设备设施管理及物资管理等方面全方位的总结了运营管理经验,为分散式污水处理设施管理提供了参考和借鉴。     

生物柴油产业链分析

生物柴油是指由植物油、动物油脂等制备得到的单烷烃酯类。它是一种环境友好、清洁排放的燃料,因此是非常理想的石油柴油替代燃料。本文从生物柴油产业链中的原料来源、生产工艺、产品应用以及其效益等方面对这种新型的清洁燃料进行了简单介绍。总之,生物柴油是一种很有发展前景的生物质燃料。     

Mapping Adolescents’ Sense of Place and Perceptions of Change in an Urban–Rural Transition Area

Environmental Management - Landscapes are changing, with rural areas becoming increasingly urbanized. Children and adolescents are underrepresented in the sense-of-place literature. Our study aimed...     

Conspecific brood parasitism in an upland-nesting bird: cues parasites use to select a nest

Behavioral Ecology and Sociobiology - In the animal kingdom, conspicuous colors are often used for inter- and intra-sexual communication. Even though primates are the most colorful mammalian taxon,...