The Transboundary Nature of the Allende–Piedras Negras Aquifer Using a Numerical Model Approach

The Allende–Piedras Negras (APN) aquifer is located between the states of Texas (United States [U.S.]) and Coahuila (Mexico). The Rio Grande crosses the aquifer, acting as a natural and political divide between the countries. However, it remains unclear whether the APN aquifer can be considered a truly transboundary aquifer flow system, which would potentially require joint management by two different administrative jurisdictions. The main purpose of this study was to evaluate the transboundary nature of this aquifer. This was achieved by developing a detailed hydrogeological model to analyze the direction of volumetric fluxes within the APN aquifer using Visual MODFLOW. The model simulated a spatially averaged cumulative drawdown of 0.76 m for the entire aquifer over an 18‐year modeling period (2000–2017). The flow convergence zone, previously located below the Rio Grande, has shifted to the U.S. side in most locations, driven by higher pumping rates of the wells located near the river. This shift of the convergence zone from one country to the other means that groundwater recharge from one side flows underneath the river to the other side. This qualifies the APN aquifer as a “transboundary groundwater flow system.” The procedure followed in this study may be applied to other aquifers that straddle the U.S.–Mexico border and may motivate future modeling studies on other poorly studied transboundary aquifers around the world and thereby enable bi‐national aquifer management.     

The Role of Climate and Human Influences in the Dry‐Up of the Jinci Springs,China1

Abstract: One of the largest karst springs in North China, the Jinci Springs, dried up and has remained dry since 1994. We develop a correlation analysis with time‐lag and a regression analysis with time‐lag to study the relation between spring flow and precipitation. This allows us to obtain a better understanding of karst hydrological processes by differentiating the contribution of variation in precipitation from anthropogenic impacts on the dry‐up of Jinci Springs. We divided the karstic hydrological processes into two phases: pre‐1961 and post‐1961. In the first phase (i.e., 1954‐1960) the groundwater recharge was affected by precipitation alone, and in the second phase (i.e., 1961‐1994) the groundwater recharge was influenced by both precipitation and human activities. Using precipitation and groundwater recharge data in the first phase, we set up a groundwater recharge model with time‐lags. By running the time‐lags model, we acquired the groundwater recharge likely to occur under the sole effect of precipitation in the second phase. Using a water‐balance calculation, we conclude that the groundwater recharge exhibited statistical stationarity, and the Jinci Springs dry‐up was the result of anthropogenic activities. At least three specific types of anthropogenic activities contributed to the drying‐up of Jinci Springs: (1) groundwater pumping accounts for 51%, (2) the dewatering from coal mining accounts for 33%, (3) and dam‐building 14%. The drying‐up of Jinci Springs meant that the groundwater drained from the aquifer’s fractures, and subsequently changed the structure of the karst aquifer. Although groundwater exploitation has been reduced, the flow at Jinci Springs has not reoccurred.     

Evaluating and Extending CLIGEN Precipitation Generation for the Loess Plateau of China1

Abstract: Climate generator (CLIGEN) is widely used in the United States to generate long‐term climate scenarios for use with agricultural systems models. Its applicability needs to be evaluated for use in a new region or climate. The objectives were to: (1) evaluate the reproducibility of the latest version of CLIGEN v5.22564 in generating daily, monthly, and yearly precipitation depths at 12 stations, as well as storm patterns including storm duration (D), relative peak intensity (ip), and peak intensity (rp) at 10 stations dispersed across the Loess Plateau and (2) test whether an exponential distribution for generating D and a distribution‐free approach for inducing desired rank correlation between precipitation depth and D can improve storm pattern generations. Mean absolute relative errors (MAREs) for simulating daily, monthly, annual, and annual maximum daily precipitation depth across all 12 stations were 3.5, 1.7, 1.7, and 5.0% for the mean and 5.0, 4.5, 13.0, and 13.6% for the standard deviations (SD), respectively. The model reproduced the distributions of monthly and annual precipitation depths well (p > 0.3), but the distribution of daily precipitation depth was less well produced. The first‐order, two‐state Markov chain algorithm was adequate for generating precipitation occurrence for the Loess Plateau of China; however, it underpredicted the longest dry periods. The CLIGEN‐generated storm patterns poorly. It underpredicted mean and SD of D for storms ≥10 mm by ?60.4 and ?72.6%, respectively. Compared with D, ip, and rp were slightly better reproduced. The MAREs of mean and SD were 21.0 and 52.1% for ip, and 31.2 and 55.2% for rp, respectively. When an exponential distribution was used to generate D, MAREs were reduced to 2.6% for the mean and 7.8% for the SD. However, ip estimation became much worse with MAREs being 128.9% for the mean and 241.1% for the SD. Overall, storm pattern generation needs improvement. For better storm pattern generation for the region, precipitation depth, D, and rp may be generated correlatively using Copula methods.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.     

Linking Excess Nutrients,Light, and Fine Bedded Sediments to Impacts on Faunal Assemblages in Headwater Agricultural Streams1

Griffith, Michael B., F. Bernard Daniel, Matthew A. Morrison, Michael E. Troyer, James M. Lazorchak, and Joseph P. Schubauer‐Berigan, 2009. Linking Excess Nutrients, Light, and Fine Bedded Sediments to Impacts on Faunal Assemblages in Headwater Agricultural Streams. Journal of the American Water Resources Association (JAWRA) 45(6):1475‐1492. Abstract: Biological impairments in streams are typically defined by regulatory agencies in terms of altered invertebrate or fish assemblages. While nutrients, canopy cover, and sediment fines contribute to these impairments, these stressors are often defined, at least in part, by their impacts on periphyton. Path analysis can extend these assessments to impacts on invertebrates and fish by characterizing the direct and indirect relationships among variables along defined model pathways. With data from headwater tributaries in the Little Miami River, Ohio, we tested models of the impacts of nutrients [total nitrogen (TN), total phosphorus (TP), and the nitrogen to phosphorus (N/P) ratio], the percentage of (%) open canopy, and the % sand and fines on three periphyton metrics [periphytic ash‐free dry mass (AFDM), the percent abundance of cyanobacteria (% cyanobacteria), and the percent abundance of Chlorophyta (% Chlorophyta)] and, in turn, on selected invertebrate or fish metrics. Our objective was to develop and evaluate a statistical model that assesses the direct and indirect impacts of excess nutrients on macroinvertebrate and fish in these streams and demonstrate how this approach might be applicable elsewhere. The results suggest indirect pathways for the influences of nutrients, canopy cover, and fine bedded sediments on invertebrates or fish that are mediated by their influences on periphyton. This is in addition to any direct impacts of these stressors on the invertebrate and fish metrics. In most models, all three periphyton metrics increased with % open canopy. Periphytic AFDM increased with TN, while % cyanobacteria decreased. The % cyanobacteria also decreased with % sand and fines, but % Chlorophyta increased. The metrics, percent abundance of (%) three most dominant (macroinvertebrate) taxa, % Trichoptera, and % herbivorous fish all increased with periphytic AFDM, while % climbers, % swimmers, and %Lepomis cyanellus Rafinesque decreased. Lepomis cyanellus is an indicator species, because it is generally common in these streams and relatively tolerant to various common environmental stressors. The % three most dominant macroinvertebrate taxa increased while % Hydropsychidae (Trichoptera) and %L. cyanellus decreased with % cyanobacteria. The % Trichoptera and %L. cyanellus increased with % Chlorophyta. Some macroinvertebrate metrics, such as the % burrowers and number of burrower taxa, did not have any statistically significant relationships with the periphyton metrics but did exhibit a direct pathway with % sand and fines. These analyses illustrate how path analysis can be used to estimate the relationships among the variables in a conceptual model, modify the model, assess the relative importance of different paths, and explore responses resulting from stressors with interacting and indirect impacts.     

Bringing the outside in: Can “external” workers experience insider status?

The current study examines the possibility that agency workers can experience perceived insider status despite their assumed “outsider” category. One hundred ninety‐one agency workers from Canadian financial firms completed surveys assessing agency worker perceptions regarding the level of support from both their supervisors and the client firms' permanent workers, as well as the agency workers' level of perceived insider status and affective commitment toward the client firm. Agency worker supervisors (within the client firm) assessed the agency workers' level of interpersonal facilitation. Results indicate that: (1) Agency workers can experience perceived insider status, regardless of their objective classification as outsiders; (2) perceived support from supervisors and the client firms' permanent workers contribute to agency worker perceptions of insider status; and (3) perceptions of insider status are associated with higher levels of both affective commitment and interpersonal facilitation, even in workers that are considered marginally tied to the organization. Copyright © 2009 John Wiley & Sons, Ltd.     

Emotional competence and work performance: The mediating effect of proactivity and the moderating effect of job autonomy

This paper proposes and tests a model where emotional competence influences work performance through employees' proactive behaviors toward their supervisors. Results from 196 supervisor‐employee pairs supported that emotional competence was positively associated with proactive behaviors, and proactive behaviors were positively associated with both task effectiveness and social integration. In addition, proactive behaviors significantly mediated the relationships between emotional competence and work performance, although this was mostly true of followers who had a higher degree of autonomy in their work. Copyright © 2009 John Wiley & Sons, Ltd.     

Situational Waste in Landscape Watering: Residential and Business Water Use in an Urban Utah Community1

Abstract: Landscape water conservation is an important issue for municipalities throughout the Western United States, and especially in Utah as rapid growth strains existing water supplies. We conducted interdisciplinary research in Layton, Utah, that aimed at understanding patterns of landscape water use among households and businesses. The research project involved three basic tasks. First, a landscape “water budget” was developed by producing a calibrated and classified mosaic of landscape type and area from airborne multispectral digital imagery, integrating this information with Layton City parcel boundary data to determine landscape vegetated areas per lot, and estimating irrigation needs derived from reference evapotranspiration (ETo) obtained using weather data for the Salt Lake City metropolitan region. Second, utilizing Layton water billing data, water use for each household and business was identified and categorized as “conserving,”“acceptable” or “wasteful” by determining how much the water applied varied from actual landscape plant need. Third, surveys were administered to a random stratified sample of households and businesses in the study area to investigate various factors that were hypothesized to be predictive of wasteful watering practices. This paper primarily focuses on analysis of the household and business survey data, which explores factors affecting urban landscape water use from a human behavioral perspective. We found that the most significant factors predicting actual water use were the type of irrigation system and whether the location was a household or business. Attitudinal and motivational characteristics were not consistently associated with water use. We found that wasteful watering is the result of many factors embedded in the complex context of urban landscapes. This implies that water conservation programs should identify potential wasteful users through analyses of water billing data and direct water conservation measures at these users by focusing on site‐specific evaluations and recommendations. Water audits or water checks are one such tool that some communities have employed to help people understand and assess the quantity of water needed by and applied to their landscapes. This approach provides an opportunity to evaluate situational constraints at particular locations and design appropriate strategies for reducing water waste.     

A Statistical Sediment Yield Prediction Model Incorporating the Effect of Fires and Subsequent Storm Events1

Abstract: Alluvial fans are continuously being developed for residential, industrial, commercial, and agricultural uses in southern California. Development and alteration of alluvial fans need to consider the possibility of mud and debris flows from upstream mountain watersheds affected by fires. Accurate prediction of sediment yield (or hyper‐concentrated sediment yield) is essential for the design, operation, and maintenance of debris basins to safeguard properly the general populace. This paper presents a model for the prediction of sediment yields that result from a combination of fire and subsequent storm events. The watersheds used in this analysis are located in the foothills of the San Gabriel Mountains in southern California. A multiple regression analysis is first utilized to establish a fundamental statistical relationship for sediment yield as a function of relief ratio, drainage area, maximum 1‐h rainfall intensity and fire factor using 45 years of data (1938‐1983). In addition, a method for multi‐sequence sediment yield prediction under fire conditions was developed and calibrated using 17 years of sediment yield, fire, and precipitation data for the period 1984‐2000. After calibration, this model was verified by applying it to provide a prediction of the sediment yields for the 2001‐2002 fire events in southern California. The findings indicate a strong correlation between the estimated and measured sediment yields. The proposed method for sequence sediment yield prediction following fire events can be a useful tool to schedule cleanout operations for debris basins and to develop an emergency response strategy for the southern California region where plentiful sediment supplies exist and frequent fires occur.     

Feasibility assessment of electrocoagulation towards a new sustainable wastewater treatment

BACKGROUND, AIM AND SCOPE: Electrocoagulation (EC) may be a potential answer to environmental problems dealing with water reuse and rational waste management. The aim of this research was to assess the feasibility of EC-process for industrial contaminated effluents from copper production, taking into consideration technical and economical factors. EC-technology claims to offer efficient removal rates for most types of wastewater impurities at low power consumption and without adding any precipitating agents. MATERIALS AND METHODS: Real wastewater from Saraka stream with high concentrations of heavy metals was provided by RTB-BOR, a Serbian copper mining and smelting complex. Runs were performed on a 10 l EC-reactor using aluminum plates as sacrificial electrodes and powered by a 40 A supply unit. Results concerning key factors like pH, conductivity and power consumption were measured in real time. Analysis of dissolved metal concentrations before and after treatment were carried out via ICP-OES and confirmed by an independent test via AAS. RESULTS: Several aspects were taken into account, including current density, conductivity, interfacial resistivity and reactor settings throughout the runs, in order to analyze all possible factors playing a role in neutralization and metal removal in real industrial wastewater. DISCUSSION: Electrode configurations and their effects on energy demand were discussed and exemplified based on fundamentals of colloidal and physical chemistry. CONCLUSIONS: Based on experimental data and since no precipitating agents were applied, the EC-process proved to be not only feasible and environmentally-friendly, but also a cost-effective technology RECOMMENDATIONS AND PERSPECTIVES: The EC-technology provides strategic guidelines for further research and development of sustainable water management processes. However, additional test series concerning continuous operation must be still performed in order to get this concept ready for future large-scale applications.