CLIMATE,SNOW COVER,GLACIERS, AND RUNOFF IN THE TIEN SHAN,CENTRAL ASIA1

ABSTRACT: The Pica Shan, a mountainous region located on the northern periphery of central Asia, has a wide range of climatic and hydrological conditions. On the basis of long term data from 348 meteorological and glaciological stations, the annual distribution of precipitation in different regions and elevational zones of the Tien Shan was calculated. Major climatic features are the entrance of moisture during spring-summer, small winter precipitation, decrease of precipitation towards the east and the center of the mountains or with distance up valleys, and increase of precipitation with altitude up to crest-lines of ranges. Annual total evaporation from snow can be 50–60 mm per year, reaching 30 percent of snow accumulation. Four main groups of rivers were identified: rivers with mainly snow nourishment, rivers with mainly glacial nourishment, rivers with mainly rain nourishment, and rivers with mainly ground water nourishment. Coefficient of runoff variation in Tien Shan's rivers is about 0.20, and coefficient of glacial runoff variation is about 0.15. Glacial runoff is 15–20 percent of the total volume of river runoff.     

A SIMULATION OF RIVER-BASIN RESPONSE TO MESOSCALE METEOROLOGICAL FORCING: THE SUSQUEHANNA RIVER BASIN EXPERIMENT (SRBEX)1

ABSTRACT: A mesoscale meteorological model, a surface hydrology model, and a ground-water hydrology model are linked to simulate the hydrographic response of a large river basin to a single storm. Synoptic climatology is employed to choose a representative hydro-climatic event. The mesoscale meteorological model uses three nested domains to simulate relatively high-resolution precipitation over a sub-basin of the Susquehanna River Basin. The hydrology models simulate surface runoff and ground-water baseflow using both analyzed and simulated precipitation. The hydrologic abstractions are handled using both Curve Number and Green-Ampt routines. To support the linkage of the numerical models, special attention is given to data resampling and reprojection. The mesoscale meteorological model simulation captures the spatial and temporal structure of the storm event, while the hydrology models represent the timing of the event well. The Curve Number method generates a realistic hydrograph with both analyzed and simulated precipitation. In contrast, the hydrographic response generated by the Green-Ampt routine is inferior. Several interrelated factors contribute to these results, including: the nature of the precipitation event chosen for the experiment; the tendency of the mesoscale meteorological model to underpredict low intensity, widespread precipitation in this case; and the influence of the surface soil-texture characteristics on infiltration rates.     

LIMITATIONS OF CONCEPTS USED TO DETERMINE INSTREAM FLOW REQUIREMENTS FOR HABITAT MAINTENANCE1

ABSTRACT: Today most rivers are not freely flowing but are highly regulated to meet both human and wildlife needs. Several models allow the determination of instream flows that are needed to meet wildlife demands. However, these models are based on assumptions that limit their applicability to certain types of rivers. While these limitations do not preclude the use of the models on other types of rivers, like the Platte River in Nebraska, their limitations should be considered and accommodated by those making instream flow planning and management decisions. Other factors affecting channel morphology and its associated wildlife habitat, such as threshold values and vegetation are not adequately considered by current concepts. If rivers are to be managed to provide wildlife habitat, these factors will have to be addressed.     

The Vegetation Coverage Dynamic Coupling with Climatic Factors in Northeast China Transect

Based on SPOT-VGT images and meteorological data, this paper applied an integrated method to investigate the vegetation dynamic and its response to climate factors during 1998-2008 in Northeast China Transect, one of 15 ecological transects listed in the International Geosphere-Biosphere Programme. The main findings are as follows: (1) The NDVI time series presented nonlinear patterns that vary with timescales. The series fluctuated greatly at the smallest timescale (20?days), showing no salient trend, whereas a trend manifested itself more and more with the increase of time scale and finally stabilized at the 320-day scale. Little difference was found between vegetation types about the NDVI periodicity, as they occurred on either a 280-day or a 290-day cycle. (2) NDVI exhibited a significant correlation with temperature, precipitation, and sunshine hours. Overall, the correlation between NDVI and temperature was the highest, followed by precipitation, sunshine hours, and relative humidity. For different vegetation types, the correlations between NDVI and climate variables diversified, increasing from desert steppe to typical steppe, meadow steppe, and forest. (3) The periodicity of temperature and precipitation occurred in either a 280-day or 290-day cycle, which was approximately coincident with that of NDVI. This further supported the significant relationship between NDVI and these two climate factors. (4) At all the time scales under examination, NDVI and temperature and precipitation are significantly, positively correlated, especially at the 160-day scale, which can be regarded as the most suitable time scale for investigating the responses of vegetation dynamics to climate factors at most stations.     

Stream Temperature Modeling Using Functional Regression Models

Stream temperature is one of the most important environmental variables in lotic habitats as it has important and direct impacts on the ecosystem. Given the continuous nature of this variable, the aim of this paper was to introduce functional regression for the air‐stream temperature relation, being capable to model an entire seasonal or annual curve of temperatures as one entity, rather than multiple daily or weekly values in classical models. Three types of functional models were explored in the study and compared to two classical models (Generalized Additive Model and Logistic Model) for six rivers from the United States The results show the functional models have the best performance for all the considered rivers. When comparing functional models between them, one variant of the historical functional model performs better than the two other models and is the most parsimonious. Functional regression leads to encouraging results to model the complete annual stream temperature curve as one entity compared to other classical approaches.     

Impact of informal regulation of pollution on water quality in rivers in India

In this paper an attempt is made to assess the impact of informal regulation of water pollution on water quality in Indian rivers. For this purpose, an econometric analysis of determinants of water quality in Indian rivers is carried out using water quality (water class) data for 106 monitoring points on 10 important rivers for five years, 1995-1999. To explain variations in water quality, an Ordered Probit model is estimated, in which poll percentage in parliamentary elections, a proxy for the intensity of informal regulation, is taken as one of the main explanatory variables. Rainfall, industrialization, irrigation intensity and fertilizer use are some of the other explanatory variables used in the model to control for the influence of these factors. As expected, river water quality is found to be positively related with rainfall, and negatively related with industrialization, irrigation intensity and fertilizer use. A significant positive relationship is found between poll percentage and water quality, and also between the rate of increase in literacy level in a district and the water quality in rivers flowing through the district. These results point to a significant favorable effect of informal regulation of pollution on water quality in rivers in India.     

STORM CHARACTERISTICS OF CONVECTIVE-SCALE PRECIPITATION1

A classification scheme for convective precipitation, having applications in both analysis and modeling of meteorological and hydrological events, is presented. The method is based upon observations of rainfall at the ground, radar scans of storm events, and visible and infrared satellite imagery of larger storm systems. Empirical and theoretical frequency distributions are derived for total storm rainfall, rainfall duration and time between storms for each of the convective categories. This stratification is directly applicable to the experimental design and evaluation of weather modification projects and may be useful for the development and interpretation of meteorological and hydrological models. When atmospheric conditions limit storm development to cells, rainfall was seldom observed. Small clusters also produce small amounts of rainfall but have a longer lifetime than cells and are likely candidates for cloud seeding attempts to encourage their growth to large clusters. Large and nested clusters usually produce large amounts of natural precipitation. A few large storms account for most of a season's rainfall.     

气象因素对大连空气中PM_(2.5)的去除效应分析

根据2013年1月1日至2月15日大连市环境监测中心PM2.5监测数据和大连市气象局风向、风速、降水量等资料,研究了降雪、降雨、风等气象因素对大气中PM2.5的去除效应。结果表明,大连市冬季采暖期PM2.5污染较重,PM2.5浓度受气象因素影响较明显。降雪、降雨、风三种气象因素对大气中PM2.5均有明显的去除效果,因去除机理不同,各气象因素对PM2.5的去除能力大小依次为风、降雨、降雪,去除效率分别为61.6%、46.0%、34.5%。     

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.     

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.     

Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers1

Angradi, Ted R., David W. Bolgrien, Matt A. Starry, and Brian H. Hill, 2012. Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers. Journal of the American Water Resources Association (JAWRA) 48(5): 1054‐1070. DOI: 10.1111/j.1752‐1688.2012.00669.x Abstract: We used regression models to predict summer background concentration of total nitrogen (N), total phosphorus (P), and total suspended solids (TSS), in the mid‐continent great rivers: the Upper Mississippi, the Lower Missouri, and the Ohio. From multiple linear regressions of water quality indicators with land use and other stressor variables, we determined the concentration of the indicators when the predictor variables were all set to zero — the y‐intercept. Except for total P on the Upper Mississippi River, we could predict background concentration using regression models. Predicted background concentration of total N was about the same on the Upper Mississippi and Lower Missouri Rivers (430 μg l^?1), which was lower than percentile‐based values, but was similar to concentrations derived from the response of sestonic chlorophyll a to great river total N concentration. Background concentration of total P on the Lower Missouri (65 μg l^?1) was also lower than published and percentile‐based concentrations. Background TSS concentration was higher on the Lower Missouri (40 mg l^?1) than the other rivers. Background TSS concentration on the Upper Mississippi (16 mg l^?1) was below a threshold (30 mg l^?1) designed to protect aquatic vegetation. Our model‐predicted concentrations for the great rivers are an attempt to estimate background concentrations for water quality indicators independent from thresholds based on percentiles or derived from stressor‐response relationships.     

OPTICAL CHARACTERISTICS OF NEW ZEALAND RIVERS IN RELATION TO FLOW1

ABSTRACT: Six years (1989–1994) of data from New Zealand's National Rivers Water Quality Network were used to characterize the optical water quality regime of river waters as regards: visual clarity (black disc visibility), turbidity, and light-absorbing aquatic humic material (referred to as ‘yellow substance,’ measured as light absorption at 440 nm). Quantitative relationships between optical water quality variables and flow in rivers are well-described by power law expressions. Visual clarity usually decreases strongly with increasing flow in individual rivers. There is a strong, inverse relationship between turbidity and visibility, but, because of differences between sites, turbidity is not a good general predictor of visual clarity (the attribute of real interest) in rivers. Yellow substance tends to increase with increasing flow, probably because during rainstorms, soil water high in yellow-colored humic material, rather than rain water or ground water, dominates discharge. Therefore, rivers are typically clear and low in humic matter at low flow, and turbid and yellow-colored at high flow.     

SUMMER LOW FLOWS IN NEW ENGLAND DURING THE 20TH CENTURY1

ABSTRACT: High springtime river flows came earlier by one to two weeks in large parts of northern New England during the 20th Century. In this study it was hypothesized that late spring/early summer recessional flows and late summer/early fall low flows could also be occurring earlier. This could result in a longer period of low flow recession and a decrease in the magnitude of low flows. To test this hypothesis, variations over time in the magnitude and timing of low flows were analyzed. To help understand the relation between low flows and climatic variables in New England, low flows were correlated with air temperatures and precipitation. Analysis of data from 23 rural, unregulated rivers across New England indicated little evidence of consistent changes in the timing or magnitude of late summer/early fall low flows during the 20th Century. The interannual variability in the timing and magnitude of the low flows in northern New England was explained much more by the interannual variability in precipitation than by the interannual variability of air temperatures. The highest correlation between the magnitude of the low flows and air temperatures was with May through November temperatures (r =?0.37, p= 0.0017), while the highest correlation with precipitation was with July through August precipitation (r = 0.67, p > 0.0001).     

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.     

Habitat Assessment of Non-Wadeable Rivers in Michigan

Habitat evaluation of wadeable streams based on accepted protocols provides a rapid and widely used adjunct to biological assessment. However, little effort has been devoted to habitat evaluation in non-wadeable rivers, where it is likely that protocols will differ and field logistics will be more challenging. We developed and tested a non-wadeable habitat index (NWHI) for rivers of Michigan, where non-wadeable rivers were defined as those of order ≥5, drainage area ≥1600 km², mainstem lengths ≥100 km, and mean annual discharge ≥15 m³/s. This identified 22 candidate rivers that ranged in length from 103 to 825 km and in drainage area from 1620 to 16,860 km². We measured 171 individual habitat variables over 2-km reaches at 35 locations on 14 rivers during 2000–2002, where mean wetted width was found to range from 32 to 185 m and mean thalweg depth from 0.8 to 8.3 m. We used correlation and principal components analysis to reduce the number of variables, and examined the spatial pattern of retained variables to exclude any that appeared to reflect spatial location rather than reach condition, resulting in 12 variables to be considered in the habitat index. The proposed NWHI included seven variables: riparian width, large woody debris, aquatic vegetation, bottom deposition, bank stability, thalweg substrate, and off-channel habitat. These variables were included because of their statistical association with independently derived measures of human disturbance in the riparian zone and the catchment, and because they are considered important in other habitat protocols or to the ecology of large rivers. Five variables were excluded because they were primarily related to river size rather than anthropogenic disturbance. This index correlated strongly with indices of disturbance based on the riparian (adjusted R² = 0.62) and the catchment (adjusted R² = 0.50), and distinguished the 35 river reaches into the categories of poor (2), fair (19), good (13), and excellent (1). Habitat variables retained in the NWHI differ from several used in wadeable streams, and place greater emphasis on known characteristic features of larger rivers.     

Spatiotemporal evolution of soil pH and zinc after the Aznalcollar mine spill

The residual pollution after the Aznalcóllar (southwestern Spain) pyrite mine spill is still a threat due to the continuing oxidation of sulfuric minerals. The objective of this paper was to analyze the combined effect of pyrite oxidation, sugar beet foam applications, and meteorological conditions on the spatiotemporal evolution of the pH and EDTA-extractable Zn concentration, using non co-located data from 11 sampling dates between June 1999 and March 2002. Median pH values ranged from 4.4 at the beginning of the monitoring period to 7.6 at the end, although values near 2.5 were observed throughout the entire period, despite of two sugar beet foam (SBF) applications. Zinc distributions were positively skewed and median concentrations ranged from 17 to 94 mg kg(-1). The inverse relationship between pH and Zn became weaker toward the end of the monitoring period as a consequence of the precipitation and posterior dissolution of newly formed minerals from the reaction products of the pyrite oxidation. Normal score maps showed that after the SBF applications only 0.5% of the monitored area was below the pH = 4 threshold, while on other dates up to one-third of the area remained below this value. The better performance of the second SBF application could be explained in terms of pyrite oxidation pathways and environmental conditions. From this analysis, with data obtained under uncontrolled field conditions, it is concluded that SBF should be applied before or during the wet and cold season to alleviate acidification, caused by the oxidation of pyrite or other sulfuric minerals.     

A Multi‐Scale Analysis of Single‐Family Residential Water Use in the Phoenix Metropolitan Area

Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management.     

ROLE OF BASEFLOW IN RAINFALL-RUNOFF RELATIONS1

ABSTRACT. The role of initial baseflow, or the baseflow at the beginning of storm precipitation, in modifying mathematical rainfall-runoff relations is analyzed by using data from 95 storms over a drainage basin in Illinois. A regression model is set up with total runoff, surface runoff, baseflow runoff, and peak flow as dependent variables, and storm precipitation, initial baseflow, effective and total storm durations, and highest and lowest temperatures during the storm as independent variables. Stepwise regression analyses show that storm precipitation and initial baseflow are the most important variables for making dependent variable estimates. The standard error estimates using only storm precipitation and initial baseflow as predictors show a seasonal trend with a peak in July, August, or September. An understanding of the role of baseflow as an indicator of average soil moisture condition over the basin can be of great help in short-term reservoir regulation and flood warning.     

THE DEVELOPMENT OF THE NILE HYDROMETEOROLOGICAL FORECAST SYSTEM1

ABSTRACT: The National Oceanic and Atmospheric Administration is developing a river forecast system for the Nile River in Egypt. The river forecast system operates on scientific work stations using hydrometeorological models and software to predict inflows into the high Aswan Dam and forecast flow hydrographs at selected gaging locations above the dam The Nile Forecasting System (NFS) utilizes satellite imagery from the METEOSAT satellite as the input to the forecast system. Satellite imagery is used to estimate precipitation over the Blue Nile Basin using five different techniques. Observed precipitation data and climatic statistics are used to improve precipitation estimation. Precipitation data for grid locations are input to a distributed water balance model, a hill slope routing model, and a channel routing model. A customized Geographic Information System (GIS) was developed to show political boundaries, rivers, terrain elevation, and gaging network. The GIS was used to develop hydrologic parameters for the basin and is used for multiple display features.     

CUMULATIVE EFFECTIVE STREAM POWER AND BANK EROSION ON THE SACRAMENTO RIVER,CALIFORNIA, USA1

ABSTRACT: Bank erosion along a river channel determines the pattern of channel migration. Lateral channel migration in large alluvial rivers creates new floodplain land that is essential for riparian vegetation to get established. Migration also erodes existing riparian, agricultural, and urban lands, sometimes damaging human infrastructure (e.g., scouring bridge foundations and endangering pumping facilities) in the process. Understanding what controls the rate of bank erosion and associated point bar deposition is necessary to manage large alluvial rivers effectively. In this study, bank erosion was proportionally related to the magnitude of stream power. Linear regressions were used to correlate the cumulative stream power, above a lower flow threshold, with rates of bank erosion at 13 sites on the middle Sacramento River in California. Two forms of data were used: aerial photography and field data. Each analysis showed that bank erosion and cumulative effective stream power were significantly correlated and that a lower flow threshold improves the statistical relationship in this system. These correlations demonstrate that land managers and others can relate rates of bank erosion to the daily flow rates of a river. Such relationships can provide information concerning ecological restoration of floodplains related to channel migration rates as well as planning that requires knowledge of the relationship between flow rates and bank erosion rates.