Effects of Meteorological Parameters on Air Pollutant Concentrations in Elazig,Turkey

In the present study, air pollutant concentrations have been analyzed statistically with meteorological factors in the city of Elazig, which is located in the east Anatolia region of Turkey, for the months of September, October, November, December, January, February, March, and April during the years 2003 and 2004. SPSS code was used for statistical analyses. The relationship between monitored air pollutant concentrations, such as SO₂ and the total suspended particles (TSP) data, and meteorological factors such as wind speed, temperature, relative humidity and pressure was investigated. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elazig. The correlation between the previous day's SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and the coefficient of determination R was found to be 0.80 and 0.76, respectively. The statistical models of SO₂ and TSP, including all of the meteorological parameters, gave an R of 0.50 and 0.40, respectively. Further, in order to develop this model, the previous day's SO₂ and TSP concentrations were added to the equations. The new model for SO₂ and TSP was improved considerably with R = 0.85 and 0.80, respectively.     

Instream sensor results suggest soil–plant processes produce three distinct seasonal patterns of nitrate concentrations in the Ohio River Basin

The Ohio River Basin (ORB) is responsible for 35% of total nitrate loading to the Gulf of Mexico yet controls on nitrate timing require investigation. We used a set of submersible ultraviolet nitrate analyzers located at 13 stations across the ORB to examine nitrate loading and seasonality. Observed nitrate concentrations ranged from 0.3 to 2.8 mg L⁻¹ N in the Ohio River's mainstem. The Ohio River experiences a greater than fivefold increase in annual nitrate load from the upper basin to the river's junction with the Mississippi River (74–415 Gg year⁻¹). The nitrate load increase corresponds with the greater drainage area, a 50% increase in average annual nitrate concentration, and a shift in land cover across the drainage area from 5% cropland in the upper basin to 19% cropland at the Ohio River's junction with the Mississippi River. Time-series decomposition of nitrate concentration and nitrate load showed peaks centered in January and June for 85% of subbasin-year combinations and nitrate lows in summer and fall. Seasonal patterns of the terrestrial system, including winter dormancy, spring planting, and summer and fall growing-harvest seasons, are suggested to control nitrate timing in the Ohio River as opposed to controls by river discharge and internal cycling. The dormant season from December to March carries 51% of the ORB's nitrate load, and nitrate delivery is high across all subbasins analyzed, regardless of land cover. This season is characterized by soil nitrate leaching likely from mineralization of soil organic matter and release of legacy nitrogen. Nitrate experiences fast transit to the river owing to the ORB's mature karst geology in the south and tile drainage in the northwest. The planting season from April to June carries 26% of the ORB's nitrate and is a period of fertilizer delivery from upland corn and soybean agriculture to streams. The harvest season from July to November carries 22% of the ORB's nitrate and is a time of nitrate retention on the landscape. We discuss nutrient management in the ORB including fertilizer efficiency, cover crops, and nitrate retention using constructed measures.     

Iowa Statewide Stream Nitrate Load Calculated Using In Situ Sensor Network

Various techniques exist to estimate stream nitrate loads when measured concentration data are sparse. The inherent uncertainty associated with load estimation, however, makes tracking progress toward water quality goals more difficult. We used high‐frequency, in situ nitrate sensors strategically deployed across the agricultural state of Iowa to evaluate 2016 stream concentrations at 60 sites and loads at 35 sites. The generated data, collected at an average of 225 days per site, show daily average nitrate‐N yields ranging from 12 to 198 g/ha, with annual yields as high as 53 kg/ha from the intensely drained Des Moines Lobe. Thirteen of the sites that capture water from 82.5% of Iowa's area show statewide nitrate‐N loading in 2016 totaled 477 million kg, or 41% of the load delivered to the Mississippi–Atchafalaya River Basin (MARB). Considering the substantial private and public investment being made to reduce nitrate loading in many states within the MARB, networks of continuous, in situ measurement devices as described here can inform efforts to track year‐to‐year changes in nitrate load related to weather and conservation implementation. Nitrate and other data from the sensor network described in this study are made publicly available in real time through the Iowa Water Quality Information System.     

Nitrogen input to the Gulf of Mexico

Historical streamflow and concentration data were used in regression models to estimate the annual flux of nitrogen (N) to the Gulf of Mexico and to determine where the nitrogen originates within the Mississippi Basin. Results show that for 1980-1996 the mean annual total N flux to the Gulf of Mexico was 1,568,000 t yr-1. The flux was about 61% nitrate N, 37% organic N, and 2% ammonium N. The flux of nitrate N to the Gulf has approximately tripled in the last 30 years with most of the increase occurring between 1970 and 1983. The mean annual N flux has changed little since the early 1980s, but large year-to-year variations in N flux occur because of variations in precipitation. During wet years the N flux can increase by 50% or more due to flushing of nitrate N that has accumulated in the soils and unsaturated zones in the basin. The principal source areas of N are basins in southern Minnesota, Iowa, Illinois, Indiana, and Ohio that drain agricultural land. Basins in this region yield 1500 to more than 3100 kg N km-2 yr-1 to streams, several times the N yield of basins outside this region.     

MODELING NORTH CASCADES ANNUAL RUNOFF DISTRIBUTION USING DRAINAGE BASIN ELEVATION DISTRIBUTION1

ABSTRACT: The annual distribution of flow in a drainage basin within a given region is a function of many factors. These may include annual distribution of rainfall, basin orientation, ground cover, or presence of glaciers. Since the North Cascades region of northern Washington State has little variation in precipitation distribution by month, and the region has significant snowpack, one would predict that in an unregulated basin, basin elevation would be one of the most important factors impacting an annual hydrograph distribution. Such a prediction can be made since the higher a drainage basin is, the larger the portion of runoff that would occur as late spring snowmelt. Given that there is a relationship between elevation distribution and annual hydrograph, the problem becomes one of how to use this relationship to model an ungaged basin's hydrograph. This study concludes that, within the North Cascades region and perhaps within other regions, an effective method of determining annual flow distribution is to model ungaged flows in the same manner as flows from a gaged basin with an elevation distribution similar to that of the subject basin.     

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.     

Cropland Riparian Buffers throughout Chesapeake Bay Watershed: Spatial Patterns and Effects on Nitrate Loads Delivered to Streams

We used statistical models to provide the first empirical estimates of riparian buffer effects on the cropland nitrate load to streams throughout the Chesapeake Bay watershed. For each of 1,964 subbasins, we quantified the 1990 prevalence of cropland and riparian buffers. Cropland was considered buffered if the topographic flow path connecting it to a stream traversed a streamside forest or wetland. We applied a model that predicts stream nitrate concentration based on physiographic province and the watershed proportions of unbuffered and buffered cropland. We used another model to predict annual streamflow based on precipitation and temperature, and then multiplied the predicted flows and concentrations to estimate 1990 annual nitrate loads. Across the entire Chesapeake watershed, croplands released 92.3 Gg of nitrate nitrogen, but 19.8 Gg of that was removed by riparian buffers. At most, 29.4 Gg more might have been removed if buffer gaps were restored so that all cropland was buffered. The other 43.1 Gg of cropland load cannot be addressed with riparian buffers. The Coastal Plain physiographic province provided 52% of the existing buffer reduction of Bay‐wide nitrate loads and 36% of potential additional removal from buffer restoration in cropland buffer gaps. Existing and restorable nitrate removal in buffers were lower in the other three major provinces because of less cropland, lower buffer prevalence, and lower average buffer nitrate removal efficiency.     

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.     

CONSTRUCTING A PROBLEM SOLVING ENVIRONMENT TOOL FOR HYDROLOGIC ASSESSMENT OF LAND USE CHANGE1

ABSTRACT: This paper describes the integration of a comprehensive hydrological model known as the Hydrological Simulation Program Fortran (HSPF) into a problem solving environment (PSE) for watershed management. The original PSE concept was a structure providing web‐based access to a suite of models, including HSPF and other models of in‐stream hydrodynamics, biological impacts and economic effects, for the watershed‐wide assessment of alternative land use scenarios. The present paper describes only the HSPF integration into the PSE program. Example applications to the 148 square kilometer (57 square mile) Back Creek subwatershed in the upper Roanoke River system (1,479 square kilometers or 571 square miles) in southwest Virginia are used to illustrate important concepts and linkages between land development and hydrological change using hypothetical' what if'scenarios. The features of HSPF and its limitations in this context are discussed. The paper as such is a proof‐of‐concept paper and not a completion report. It is intended to describe the PSE tool building process rather than analysis of the many possible simulation outcomes. However, the dominance of raw imperviousness as a contributor to hydrograph response is apparent in all the PSE simulations described in this paper.     

Urbanization and Its Effect On Runoff in the Whiteoak Bayou Watershed,Texas1

Abstract: The capacity of a watershed to urbanize without changing its hydrologic response and the relationship between that response and the spatial configuration of the developed areas was studied. The study was conducted in the Whiteoak Bayou watershed (223 km²), located northwest of Houston, Texas, over an analysis period from 1949 to 2000. Annual development data were derived from parcel data collected by the Harris County Appraisal District. Using these data, measures of the spatial configuration of the watershed urban areas were calculated for each year. Based on regression models, it was determined that the annual runoff depths and annual peak flows depended on the annual precipitation depth, the developed area and the maximum 12‐h precipitation depth on the day and day before the peak flow took place. It was found that, since the early 1970s, when the watershed reached a 10% impervious area, annual runoff depths and peak flows have increased by 146% and 159%, respectively. However, urbanization is responsible for only 77% and 32% of the increase, respectively, while precipitation changes are responsible for the remaining 39% and 96%, respectively. Likewise, an analysis of the development data showed that, starting in the early 1970s, urbanization in the watershed consisted more of connecting already developed areas than of creating new ones, which increases the watershed’s conveyance capacity and explains the change in its response. Before generalizing conclusions, though, further research on other urban watersheds with different urbanization models appears to be necessary.     

MODEL ACCURACY IN SNOWMELT-RUNOFF FORECASTS EXTENDING FROM 1 TO 20 DAYS1

ABSTRACT: This paper examines the performance of snowmelt-runoff models in conditions approximating real-time forecast situations. These tests are one part of an intercomparison of models recently conducted by the World Meteorological Organization (WMO). Daily runoff from the Canadian snowmelt basin Illecille. waet (1155 km², 509–3150 m a.s.l.) was forecast for 1 to 20 days ahead. The performance of models was better than in a previous WMO project, which dealt with runoff simulations from historical data, for the following reasons: (1) conditions for models were more favorable than a real-time forecast situation because measured input data and not meteorological forecast inputs were distributed to the modelers; (2) the selected test basin was relatively easy to handle and familiar from the previous WMO project; and (3) all kinds of updating were allowed so that some models even improved their accuracy towards longer forecast times. Based on this experience, a more realistic follow-up project can be imagined which would include temperature forecasts and quantitative precipitation forecasts instead of measured data.     

Pollution source analyses using 1-dimensional time series

Lake Holiday, a human-made recreational lake in northern Illinois, was threatened with closure due to high bacterial levels. A factorially designed experiment with multivatiate responses was developed to study and identify the main sources of pollution. Data on total coliform, fecal coliform, fecal streptococci, dissolved oxygen, pH, ammonia-N, total phosphorus, nitrate/nitrite-N were analyzed using regression models describing dam spillway loads as a function of source loads and time. The results suggest that the relationships among source, time, and load are complex, even though only two sources account for most of the lake's loading Stevens Brook, which receives the discharge from the Somonauk Sewage Treatment Plant, and Somonauk Creek, which is the major drainage, contribute high loads of bacteria and nutrients to the lake. The influent loads contributed to the lake are discharged at the dam over about 4 weeks     

Nitrate Removal in a Restored Spring‐Fed Wetland,Pennsylvania, USA1

ABSTRACT:  In 2001, the 1.04‐ha Hornbaker wetland in south‐central Pennsylvania was restored by blocking an artificial drainage ditch to increase water storage and hydraulic retention time (HRT). A primary goal was to diminish downstream delivery of nitrate that enters the wetland from a limestone spring, its main source of inflow. Wetland inflow and outflow were monitored weekly for two years to assess nitrate flux, water temperature, pH, and specific conductivity. In Year 2, spring discharge was measured weekly to allow calculation of nitrate loads and hydraulic retention time. Surface runoff was confirmed to be a small fraction of wetland inflows via rainfall‐runoff modeling with TR‐55. The full dataset (n = 102) was screened to remove 13 weeks in which spring discharge constituted < 85% of total inflows because of high precipitation and surface runoff. Over two years (n = 89), mean nitrate‐nitrogen concentrations were 7.89 mg/l in inflow and 3.68 mg/l in outflow, with a mean nitrate removal of 4.19 mg/l. During Year 2 (n = 47), for which nitrate load data were available, the wetland removed an average of 2.32 kg N/day, 65% of the load. Nitrate removal was significantly correlated with HRT, water temperature, and the concentration of nitrate in inflow and was significantly greater during the growing season (5.36 mg/l, 64%) than during the non‐growing season (3.23 mg/l, 43%). This study indicates that hydrologic restoration of formerly drained wetlands can provide substantial water quality benefits and that the hydrologic characteristics of spring‐fed wetlands, in particular, support effective nitrogen removal.     

A MONTHLY TIME SERIES MODEL OF MUNICIPAL WATER DEMAND1

A multivariate time series model is formulated to study monthly variations in municipal water demand. The left hand side variable in the multivariate regression model is municipal water demand (gallons per connection per day) and the right hand side contains (explanatory) variables which include price (constant dollars), average temperature, total precipitation, and percentage of daylight hours. The application of the regression model to Salt Lake City Water Department data produced a high multiple correlation coefficient and F-statistic. The regression coefficients for the right hand side variables all have the appropriate sign. In an ex post forecast, the model accurately predicts monthly variations in municipal water demand. The proposed monthly multivariate model is not only found useful for forecasting water demand, but also useful for predicting and studying the impact of nonstructural management decisions such as the effect of price changes, peak load pricing methods, and other water conservation programs.     

Detection and visualization of storm hydrograph changes under urbanization: an impulse response approach

Urbanization often alters catchment storm responses, with a broad range of potentially significant environmental and engineering consequences. At a practical, site-specific management level, efficient and effective assessment and control of such downstream impacts requires a technical capability to rapidly identify development-induced storm hydrograph changes. The method should also speak specifically to alteration of internal watershed dynamics, require few resources to implement, and provide results that are intuitively accessible to all watershed stakeholders. In this short paper, we propose a potential method which might satisfy these criteria. Our emphasis lies upon the integration of existing concepts to provide tools for pragmatic, relatively low-cost environmental monitoring and management. The procedure involves calibration of rainfall-runoff time-series models in each of several successive time windows, which sample varying degrees of watershed urbanization. As implemented here, only precipitation and stream discharge or stage data are required. The readily generated unit impulse response functions of these time-series models might then provide a mathematically formal, yet visually based and intuitive, representation of changes in watershed storm response. Nominally, the empirical response functions capture such changes as soon as they occur, and the assessments of storm hydrograph alteration are independent of variability in meteorological forcing. We provide a preliminary example of how the technique may be applied using a low-order linear ARX model. The technique may offer a fresh perspective on such watershed management issues, and potentially also several advantages over existing approaches. Substantial further testing is required before attempting to apply the concept as a practical environmental management technique; some possible directions for additional work are suggested.     

Modeling Nitrate-Nitrogen Load Reduction Strategies for the Des Moines River,Iowa Using SWAT

The Des Moines River that drains a watershed of 16,175 km² in portions of Iowa and Minnesota is impaired for nitrate-nitrogen (nitrate) due to concentrations that exceed regulatory limits for public water supplies. The Soil Water Assessment Tool (SWAT) model was used to model streamflow and nitrate loads and evaluate a suite of basin-wide changes and targeting configurations to potentially reduce nitrate loads in the river. The SWAT model comprised 173 subbasins and 2,516 hydrologic response units and included point and nonpoint nitrogen sources. The model was calibrated for an 11-year period and three basin-wide and four targeting strategies were evaluated. Results indicated that nonpoint sources accounted for 95% of the total nitrate export. Reduction in fertilizer applications from 170 to 50 kg/ha achieved the 38% reduction in nitrate loads, exceeding the 34% reduction required. In terms of targeting, the most efficient load reductions occurred when fertilizer applications were reduced in subbasins nearest the watershed outlet. The greatest load reduction for the area of land treated was associated with reducing loads from 55 subbasins with the highest nitrate loads, achieving a 14% reduction in nitrate loads achieved by reducing applications on 30% of the land area. SWAT model results provide much needed guidance on how to begin implementing load reduction strategies most efficiently in the Des Moines River watershed.     

ESTIMATION OF SOIL MOISTURE WITH API ALGORITHMS AND MICROWAVE EMISSION1

Large area soil moisture estimations are required to describe input to cloud prediction models, rainfall distribution models, and global crop yield models. Satellite mounted microwave sensor systems that as yet can only detect moisture at the surface have been suggested as a means of acquiring large area estimates. Relations previously discovered between microwave emission at the 1.55 cm wavelength and surface moisture as represented by an antecedent precipitation index were used to provide a pseudo infiltration estimation. Infiltration estimates based on surface wetness on a daily basis were then used to calculate the soil moisture in the surface 0–23 cm of the soil by use of a modified antecedent precipitation index. Reasonably good results were obtained (R²= 0.7162) when predicted soil moisture for the surface 23 cm was compared to measured moisture. Where the technique was modified to use only an estimate of surface moisture each three days an R² value of 0.7116 resulted for the same data set. Correlations between predicted and actual soil moisture fall off rapidly for repeat observations more than three days apart. The algorithms developed in this study may be used over relatively flat agricultural lands to provide improved estimates of soil moisture to a depth greater than the depth of penetration for the sensor.     

Precipitation as the Primary Driver of Variability in River Nitrogen Loads in the Midwest United States

Nitrogen (N) losses from agricultural lands in the Midwest United States are contributing to the expansion of the hypoxic zone in the Gulf of Mexico. This study evaluated the importance of inter‐annual variability in precipitation, land cover, and N fertilizer use on NO₃ + NO₂‐N loads in seven United States Midwestern Rivers using the backward stepwise regression analysis. At the annual scale, fluctuations in the current and previous years’ precipitations explained much of the variation in streamflow, baseflow, and N‐load. Previous years precipitation effects were associated with fillable soil porosity. In some years, higher residual soil N from previous dry years also contributed to an increase in N‐load. Area under soybean production (SOY), a surrogate for replacement of prairies and small grains was generally not a significant explanatory variable. Fertilizer use from 1987 to 2012 was also not a significant explanatory variable in the annual analysis. Precipitation in both the current and previous months and previous year were important in explaining variation in monthly streamflow, baseflow, and N‐load. SOY was significant in one or two months from June to August, but had a higher p‐value than precipitation. We conclude recent increases in river N‐loads are primarily due to wet climate and minimally due to the changes in land cover or N fertilizer use. Under current cropping systems and agronomic N application rates, tile water remediation will be necessary to reduce river N‐loads.     

Nitrate nitrogen in surface waters as influenced by climatic conditions and agricultural practices

Subsurface tile drainage from row-crop agricultural production systems has been identified as a major source of nitrate entering surface waters in the Mississippi River basin. Noncontrollable factors such as precipitation and mineralization of soil organic matter have a tremendous effect on drainage losses, nitrate concentrations, and nitrate loadings in subsurface drainage water. Cropping system and nutrient management inputs are controllable factors that have a varying influence on nitrate losses. Row crops leak substantially greater amounts of nitrate compared with perennial crops; however, satisfactory economic return with many perennials is an obstacle at present. Improving N management by applying the correct rate of N at the optimum time and giving proper credits to previous legume crops and animal manure applications will also lead to reduced nitrate losses. Nitrate losses have been shown to be minimally affected by tillage systems compared with N management practices. Scientists and policymakers must understand these factors as they develop educational materials and environmental guidelines for reducing nitrate losses to surface waters.     

Hydrologic Controls on Nitrogen and Phosphorous Dynamics in Relict Oxbow Wetlands Adjacent to an Urban Restored Stream

Although wetlands are known to be sinks for nitrogen (N) and phosphorus (P), their function in urban watersheds remains unclear. We analyzed water and nitrate (NO₃^?) and phosphate (PO₄^3?) dynamics during precipitation events in two oxbow wetlands that were created during geomorphic stream restoration in Baltimore County, Maryland that varied in the nature and extent of connectivity to the adjacent stream. Oxbow 1 (Ox1) received 1.6‐4.2% and Oxbow 2 (Ox2) received 4.2‐7.4% of cumulative streamflow during storm events from subsurface seepage (Ox1) and surface flow (Ox2). The retention time of incoming stormwater ranged from 0.2 to 6.7 days in Ox1 and 1.8 to 4.3 days in Ox2. Retention rates in the wetlands ranged from 0.25 to 2.74 g N/m²/day in Ox1 and 0.29 to 1.94 g N/m²/day in Ox2. Percent retention of the NO₃^?‐N load that entered the wetlands during the storm events ranged from 64 to 87% and 23 to 26%, in Ox1 and Ox2, respectively. During all four storm events, Ox1 and Ox2 were a small net source of dissolved PO₄^3? to the adjacent stream (i.e., more P exited than entered the wetland), releasing P at a rate of 0.23‐20.83 mg P/m²/day and 3.43‐24.84 mg P/m²/day, respectively. N and P removal efficiency of the oxbows were regulated by hydrologic connectivity, hydraulic loading, and retention time. Incidental oxbow wetlands have potential to receive urban stream and storm flow and to be significant N sinks, but they may be sources of P in urban watersheds.