Influence of irrigated paddy fields on the fluorescence properties of fluvial dissolved organic matter

This study investigated seasonal and geographical variation in the fluorescence properties of dissolved organic matter (DOM) in a river system that includes rice paddy fields in its watershed. The river system covers a northern area of the main island of Japan, and between 6 and 45% the watershed area of the tributaries is paddy fields. Water samples were collected monthly from eight tributaries for 1 yr, and the fluorescence properties of DOM were monitored by combined excitation-emission matrix (EEM) and parallel factor analysis. The EEM was statistically decomposed into six fluorescence components with different environmental dynamics. The relative proportion of these components varied with season and geographic location, the former having a greater effect than the latter. Seasonal variation is largely attributed to changes in the source of DOM associated with irrigated rice cultivation practice. The fluorescence component composition showed a stronger autochthonous signature, which varied over a wider range during off-cropping period (October-April) than cropping period (May-September). During the cropping period, a large amount of allochthonous DOM with relatively similar quality was transported into river water from flooded paddy fields and masked the variability in the quality of DOM among tributaries. Therefore, irrigated rice cropping practices are considered to be one of major factors that influence seasonal and geographical variation of fluvial DOM composition.     

TEMPORAL VARIABILITY OF WATER QUALITY IN THE ST. LUCIE ESTUARY,SOUTH FLORIDA1

ABSTRACT: Four years of monthly freshwater discharge and constituent concentration data from three tributaries were related to a concurrent series of data for three segments of the St. Lucie Estuary in South Florida using multiple regression and time-series analysis techniques. Water quality parameters examined were dissolved inorganic and total nitrogen and phosphorus, chlorophyll a, total suspended solids, turbidity, and color. On monthly time scales, a multiple regression, which included freshwater discharge, freshwater constituent concentration, and dilution with ocean water (salinity) as independent variables, explained 50 percent or less of the variability in estuarine constituents. No single independent variable explained more variation than another. By contrast, on seasonal (wet, dry) time scales, freshwater discharge explained the bulk of variation in estuarine water quality (up to 93 percent). On monthly time scales, variability in concentrations of nutrients and other constituents may be largely controlled by processes internal to the system. At seasonal time scales, freshwater discharge appears to drive variability in most estuarine water quality parameters examined. Results indicate that management of tributary input on a seasonal basis, with the expectation of achieving seasonal concentration goals in the estuary, would have a higher probability of success than managing on a monthly basis.     

Modeling Variability and Trends in Pesticide Concentrations in Streams1

Abstract: A parametric regression model was developed for assessing the variability and long‐term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long‐term (inter‐annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p‐values were accurate for as few as 10 uncensored concentrations during a three‐year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean‐squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean‐squared error and decreases in power.     

AN ELEVATIONAL CONTROL OF PEAK SNOWPACK VARIABILITY1

ABSTRACT: The records of the seasonal peaks in snow accumulation on 24 snow courses show that the relative variability (measured by the coefficient of variation) is inversely related to elevation in the San Juan Mountains, southwestern Colorado. Analysis on an annual basis shows that this is due to a tendency for the peak snowpack at high elevations to be closer to the long-term mean while that at low levels is further from the normal. This is true in both above-normal and below-normal accumulation seasons. Extrapolation of 20 annual elevation-accumulation trends suggests that mean accumulation is reached at 4107 ± 186 m elevation. This is approximately the height of the topographic harrier of the San Juan Mountains suggesting that the pattern of variability is a partial function of an atmospheric-topographic interaction.     

Comparison of Two Parametric Methods to Estimate Pesticide Mass Loads in California’s Central Valley1

Saleh, Dina K., David L. Lorenz, and Joseph L. Domagalski, 2010. Comparison of Two Parametric Methods to Estimate Pesticide Mass Loads in California’s Central Valley. Journal of the American Water Resources Association (JAWRA) 00(0):1‐11. DOI: 10.1111/j.1752‐1688.2010.00506.x Abstract: Mass loadings were calculated for four pesticides in two watersheds with different land uses in the Central Valley, California, by using two parametric models: (1) the Seasonal Wave model (SeaWave), in which a pulse signal is used to describe the annual cycle of pesticide occurrence in a stream, and (2) the Sine Wave model, in which first‐order Fourier series sine and cosine terms are used to simulate seasonal mass loading patterns. The models were applied to data collected during water years 1997 through 2005. The pesticides modeled were carbaryl, diazinon, metolachlor, and molinate. Results from the two models show that the ability to capture seasonal variations in pesticide concentrations was affected by pesticide use patterns and the methods by which pesticides are transported to streams. Estimated seasonal loads compared well with results from previous studies for both models. Loads estimated by the two models did not differ significantly from each other, with the exceptions of carbaryl and molinate during the precipitation season, where loads were affected by application patterns and rainfall. However, in watersheds with variable and intermittent pesticide applications, the SeaWave model is more suitable for use on the basis of its robust capability of describing seasonal variation of pesticide concentrations.     

承德市环境空气质量现状及对策

2003承德市空气主要污染物与2002的相比,只有SO2年均值有所增大.运用Spearman-rs秩相关系数法预测该市空气质量有好转趋势,并从城市的地理位置、卫生、交通等几方面分析其污染特征及原因,建议以行政力量为指导,提高公民环保意识,实施合理的环境规划,利用最佳实用的环保技术改善该市环境空气质量.     

A Daily Time Series Analysis of StreamWater Phosphorus Concentrations Along an Urban to Forest Gradient

During a 1-year period, we sampled stream water total phosphorus (TP) concentrations daily and soluble reactive phosphorus (SRP) concentrations weekly in four Seattle area streams spanning a gradient of forested to urban-dominated land cover. The objective of this study was to develop time series models describing stream water phosphorus concentration dependence on seasonal variation in stream base flows, short-term flow fluctuations, antecedent flow conditions, and rainfall. Stream water SRP concentrations varied on average by ±18% or ±5.7 μg/L from one week to another, whereas TP varied ±48% or ±32.5 μg/L from one week to another. On average, SRP constituted about 47% of TP. Stream water SRP concentrations followed a simple sine-wave annual cycle with high concentrations during the low-flow summer period and low concentrations during the high-flow winter period in three of the four study sites. These trends are probably due to seasonal variation in the relative contributions of groundwater and subsurface flows to stream flow. In forested Issaquah Creek, SRP concentrations were relatively constant throughout the year except during the fall, when a major salmon spawning run occurred in the stream and SRP concentrations increased markedly. Stream water SRP concentrations were statistically unrelated to short-term flow fluctuations, antecedent flow conditions, or rainfall in each of the study streams. Stream water TP concentrations are highly variable and strongly influenced by short-term flow fluctuations. Each of the processes assessed had statistically significant correlations with TP concentrations, with seasonal base flow being the strongest, followed by antecedent flow conditions, short-term flow fluctuations, and rainfall. Times series models for each individual stream were able to predict ∼70% of the variability in the SRP annual cycle in three of the four streams (r² = 0.57–0.81), whereas individual TP models explained ∼50% of the annual cycle in all streams (r² = 0.39–0.59). Overall, time series models for SRP and TP dynamics explained 82% and 76% of the variability for these variables, respectively. Our results indicate that SRP, the most biologically available and therefore most important phosphorus fraction, has simpler and easier-to-predict seasonal and weekly dynamics.     

Temporal Changes in Streamflow and Attribution of Changes to Climate and Landuse in Wisconsin Watersheds

Previous historic trends analyses on 21st Century hydrologic data in the United States generally focus on annual flow statistics and have continued to use USGS hydro‐climatic data network (HCDN) stations, although post‐1988 diversions and runoff regulations are not reflected in the HCDN. Using a more recent dataset, Geospatial Attributes of Gages for Evaluating Streamflow, version II (GAGES II), compiled by Falcone (2012), which includes more watersheds with reference conditions, a comprehensive analysis of changes in seasonal, and annual streamflow in Wisconsin watersheds is demonstrated. Given the pronounced influence of seasonal hydrology in Wisconsin watersheds, the objective of this study is to elucidate the nature of temporal (annual, seasonal, and monthly) changes in runoff. Considerable temporal and regional variability was found in annual and seasonal streamflow changes between the two historic periods 1951‐1980 and 1981‐2010 considered in the study. For example, the northern watersheds show relatively small changes in streamflow discharge ranging from ?6.0 to 4.2%, while the southern watersheds show relatively large increases in streamflow discharge ranging from 13.1 to 18.2%. To apportion streamflow changes to climate and nonclimatic factors, a method based on potential evapotranspiration changes is demonstrated. Results show that nonclimatic factors account for more than 60% of changes in annual runoff in Wisconsin watersheds considered in the study.     

SAMPLING FREQUENCY SELECTION FOR REGULATORY WATER QUALITY MONITORING1

ABSTRACT: The selection of sampling frequencies in order to achieve reasonably small and uniform confidence interval widths about annual sample means or sample geometric means of water quality constituents is suggested as a rational approach to regulatory monitoring network design. Methods are presented for predicting confidence interval widths at specified sampling frequencies while considering both seasonal variation and serial correlation of the quality time series. Deterministic annual cycles are isolated and serial dependence structures of the autoregressive, moving average type are identified through time series analysis of historic water quality records. The methods are applied to records for five quality constituents from a nine-station network in Illinois. Confidence interval widths about annual geometric means are computed over a range of sampling frequencies appropriate in regulatory monitoring. Results are compared with those obtained when a less rigorous approach, ignoring seasonal variation and serial correlation, is used. For a monthly sampling frequency the error created by ignoring both seasonal variation and serial correlation is approximately 8 percent. Finally, a simpler technique for evaluating serial correlation effects based on the assumption of AR(1) type dependence is examined. It is suggested that values of the parameter p₁, in the AR(1) model should range from 0.75 to 0.90 for the constituents and region studied.     

PRECIPITATION DISTRIBUTION IN COASTAL BRITISH COLUMBIA1

ABSTRACT: The spatial distribution and the temporal and spatial variation of the annual, seasonal, and monthly precipitation in two mountainous watersheds in southwestern British Columbia, Canada, have been analyzed using a detailed database for 1971–1990 in the Capilano and Seymour watersheds. The analysis showed that the precipitation increases up to the mid-position of the watersheds, and then either levels off or decreases. Precipitation on mountain slopes and in the valley at the same distance from the beginning of the slope is similar, and the barrier height is identified as the dominant parameter which influences the precipitation distribution. The temporal variation of the precipitation is the smallest at the mid-position of the watersheds. This variability is the least in the fall and winter and largest in the summer. Correlation between the precipitation accumulations at various stations is large, ranging from 0.80 for the wet period of October-March to 0.65 for the dry period of April-September for distances less than 32 km. Comparison with other studies and the analyses of precipitation and runoff data from coastal British Columbia showed that the results of this study are perhaps general and thus transferable to similar areas in the coastal Pacific Northwest.     

RESERVOIR SEDIMENTATION AS A FUNCTION OF PRECIPITATION VARIABILITY1

ABSTRACT: This research examines what is hypothesized as a critical factor in reservoir sedimentation - precipitation variability. The coefficient of variation for annual precipitation, computed for the period relating to sedimentation, is regressed against sediment yields for several reservoirs over a wide range of environmental settings. A significant linear relationship results, and when precipitation variability is combined with several additional variables available from reservoir summary sheets, almost 83% of the total variation in sediment yield is accounted for. It is suggested that the coefficient of variation for annual precipitation fulfills a direct process role when modeling reservoir sedimentation much more effectively than annual precipitation or runoff.     

Seasonal variation in microbial communities and organic malodor indicator compound concentrations in various types of swine manure storage systems

Anaerobic manure storage systems are one of the major contributors to the odor and environmental pollution associated with swine (Sus scrofa) production systems. The microbial ecology of manure storage systems and the relationships between microbial communities and odor production are largely unknown. In this study, we used community fatty acid methyl ester (FAME) analysis to generate lipid profiles to assess seasonal differences among microbial communities inhabiting various types of outdoor swine manure storage systems. Concurrently, we measured manure concentrations of several malodor indicator compounds as well as pH, temperature, and solids content. Principal components analysis (PCA) showed that there are differences in FAME profiles among the swine manure storage systems examined and most of the variation was in the relative abundance of 18:0, 18:1omega7t, 18:1omega7c/omega9t/omega12t, and 16:1omega7t/i15:0 2OH FAMEs. The PCA of the FAME profiles revealed that the phototrophic systems were more similar to each other and that the nonphototrophic systems were more similar to each other than they were to phototrophic lagoons. There were seasonal changes in the FAME profiles in the phototrophic systems and the concrete nonphototrophic basin (CNPB), and in one phototrophic system, the FAME profiles more closely resembled a CNPB FAME profile during the winter than the other phototrophic lagoons. In the phototrophic lagoon systems, there was a direct correlation between the abundance of the FAMEs identified in the PCA and manure concentrations of phenol, p-cresol, and 4-ethyl phenol. In the CNPB, there was a negative correlation between the total phenolics concentration and the 18:1omega7t FAME. Our results indicate that community FAME profiles could be used as a diagnostic tool for obtaining preliminary evidence that management practices are altering the system's microbial community to one that favors less air pollution potential.     

Water and economic development: The role of variability and a framework for resilience

The article advances the hypothesis that the seasonal and inter‐annual variability of rainfall is a significant and measurable factor in the economic development of nations. An analysis of global datasets reveals a statistically significant relationship between greater rainfall variability and lower per capita GDP. Having established this correlation, we construct a water resources development index that highlights areas that have the greatest need for storage infrastructure to mitigate the impacts of rainfall variability on water availability for food and basic livelihood. The countries with the most critical infrastructure needs according to this metric are among the poorest in the world, and the majority of them are located in Africa. The importance of securing water availability in these nations increases every day in light of current population growth, economic development, and climate change projections.     

Assemblage stability in stream fishes: A review

We quantified the stability of nine stream fish assemblages by calculating coefficients of variation of population size for assemblage members. Coefficients of variation were high and averaged over 96%; indicating that most assemblages were quite variable. Coefficient of variation (CV) estimates were not significantly affected by: (1) years of study, (2) mean abundance, (3) familial classification, or (4) mean interval between collections. We also detected minor regional differences in CVs. The high variability exhibited by many stream fish assemblages suggests that it may be difficult to detect the effects of anthropogenic disturbances using population data alone. Consequently, we urge managers to exercise caution in the evaluation of the effects of these disturbances. More long-term studies of the ecological characteristics of undisturbed stream fish assemblages are needed to provide a benchmark against which disturbed systems can be compared. We suggest that CVs are a better estimator of population/assemblage stability, than either Kendall's W or the standard deviation of the logarithms of numerical censuses. This conclusion is based on the following reasons. First, CVs scale population variation by the mean and, hence, more accurately measure population variability. Second, this scaling permits the comparison of populations with different mean abundances. Finally, the interpretation of CV values is less ambiguous than either of the aforementioned metrics.     

四川省游客流时间分布特征及成因分析

将四川省作为旅游目的地，以旅游人数为指标，运用季节性强度指数、季节指数以及数理统计方法比较分析了四川省入境游客流与国内游客流的时间分布特征，主要从年际变化特征与月变化特征两个方面进行研究。依据四川省主要旅游景点季节性强度指数的时间变化特征，从旅游主体、旅游客体和旅游媒体三方面分别探讨了游客流时间变化的成因，重点研究了旅游客体类型、知名度、区位等因素对游客流时间分布特征的影响。     

El Niño‐Southern Oscillation,rainfall variability and sustainable agricultural development in the Ho Municipality,Ghana

El Niño‐Southern Oscillation (ENSO), which occurs in the Equatorial Pacific Ocean, has been identified to have significant influence on rainfall variability throughout the world, especially in the tropics. Such variability in rainfall has implications for agrarian economies, such as that in Ghana. This study therefore sought to demonstrate the effect of ENSO‐induced variability in annual and seasonal rainfall on the development of sustainable agriculture in the Ho Municipality of Ghana. Using 61 years of monthly rainfall data (1955–2015) for the Ho Municipality and ENSO indices, this study showed that 15% of the variability in total annual rainfall is explained by the ENSO phenomena. Mean annual rainfall and rainfall in the major rainy season decreased for El Niño years, in addition to a more variable rainfall compared to that received in La Niña years. The major growing season was observed to be longer in La Niña years and shorter in El Niño years. This means that the potential for crop cultivation will be severely hampered in an El Niño year. Farmers within the municipality are therefore encouraged to harness other complementary water sources for farming activities and also employ water management strategies during El Niño years.     

Probabilistic Streamflow Generation Model for Data Sparse Arid Watersheds1

Abstract: The authors present a model that generates streamflow for ephemeral arid streams. The model consists of a stochastic hourly precipitation point process model and a conceptual model that transforms precipitation into flow. It was applied to the Santa Cruz River at the border crossing from Mexico into Southern Arizona. The model was constructed for four different seasons and three categories of inter‐annual variability for the wet seasons of summer and winter. The drainage area is ungauged and precipitation information was inferred from a precipitation gauge downstream. The precipitation gauge record was evaluated against simulated precipitation from a mesoscale numerical weather prediction model, and was found to be the representative of the regional precipitation variability. The flow generation was found to reproduce the variability in the observed record at the daily, seasonal and annual time scales, and it is suitable for use in planning studies for the study site.     

ASSESSMENT OF NUTRIENT EFFECTS AND NUTRIENT LIMITATION IN LAKE OKEECHOBEE1

ABSTRACT: Lake Okeechobee, the third largest lake in the United States, is a shallow, mixing basin with annual total phosphorus concentrations ranging from 50–100 μg P/L. Data, mainly from unpublished agency reports, are analyzed to determine if nutrients limit phytoplankton, to describe spatial and temporal variability in trophic state parameters, and to evaluate conclusions obtained from empirical trophic state models. Algal bioassay experiments that have been used to assess nutrient limitation have produced equivocal results. However, seasonal minima in orthophosphorus and inorganic nitrogen indicate that both nutrients may be limiting seasonally. Strong, but reverse north-south gradients and large seasonal changes in phosphorus and nitrogen concentrations, show that empirical models based on annual phosphorus loadings or concentrations are not adequate to predict chlorophyll concentrations or other trophic state variables. Spatially-segmented, multi-class phytoplankton-nutrient models of seasonal phytoplankton responses that are coupled with hydrodynamic models may provide predictability in assessing effects of changing nutrient loads on phytoplankton composition and standing crop. Successful modeling efforts of responses to nutrients also must deal with resuspended and benthic algae, periphyton, and emergent and submergent aquatic plants that must play important trophic roles in some of the lake basin.     

Time activity modelling of domestic exposures to radon

Radon gas occurs naturally in the environment with a variable distribution. In some areas radon concentrates sufficiently within the built environment that it is considered as a public health risk. It is possible, successfully, to reduce radon levels in the built environment, and it has been shown that such remediation programmes can be justified in terms of the costs and benefits accruing. However, the estimated dose received by people in their homes depends on the time spent indoors. The research presented here uses data derived from time activity surveys in Northamptonshire, together with radon data from a representative home, to model potential exposures for different population sub-groups. Average home occupancy ranged from 14.8h (probable error 2.5h) for students to 17.7 (3.1) h for adults; schoolchildren spent an average of 14.9 (1.2) h at home. Over a quarter of adults, however, were in the home for 22 h on more. These differences in occupancy patterns lead to substantial differences in radon exposure. In a home with an average hourly ground floor radon concentration of 467 Bqm(-3), modelled hourly average exposures ranged from ca. 250 Bqm(-3) for students and school children, to over 340 Bqm(-3), for women based at home. Modelled exposures show a non-linear association with total time spent at home, suggesting that exposure estimates based on linear models may provide misleading estimates of health risks from radon and the potential benefits of radon remediation. Highest hourly exposures are likely to be experienced by people with highly occupancy, living in single-storey, ground floor accommodation (for example, the elderly the infirm and non-working young mothers). Since these may be least aware of radon risks, and least able to take up remediation measures, they should be specifically targeted for radon monitoring and for assistance in remediation schemes.     

居室放射性

本文介绍了放射性的来源,讨论了室内γ射线和氡及其子体,计算了相关的年剂量当量