首页> 美国政府科技报告 >Comparison of Load Estimation Techniques and Trend Analysis for Nitrogen, Phosphorus, and Suspended Sediment in the Eucha-Spavinaw Basin, Northwestern Arkansas and Northeastern Oklahoma, 2002-2010.
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Comparison of Load Estimation Techniques and Trend Analysis for Nitrogen, Phosphorus, and Suspended Sediment in the Eucha-Spavinaw Basin, Northwestern Arkansas and Northeastern Oklahoma, 2002-2010.

机译:2002 - 2010年,阿肯色州西北部和俄克拉荷马州东北部Eucha-spavinaw盆地的氮,磷和悬浮泥沙负荷估算技术和趋势分析比较。

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The City of Tulsa, Oklahoma, uses water from Lake Eucha and Spavinaw Lake in the Eucha-Spavinaw basin of northwestern Arkansas and northeastern Oklahoma for public water supply. Increases in algal biomass, which cause taste and odor problems in drinking water produced from the lakes, may be attributable to increases in nitrogen and phosphorus concentrations in the lakes and in streams discharging to the lakes. To evaluate transport of nitrogen, phosphorus, and suspended sediment in this basin, loads and temporal trends were evaluated for five streamflow-gaging stations in the Spavinaw and Beaty Creek basins. Two approaches were used to develop regression equations for estimation of loads and yields of nitrogen, phosphorus, and sediment. The first approach used regression equations referred to as daily mean load (DML) regressions, developed from water-quality samples and daily mean streamflow data collected from 2002 through 2010 at five streamflow-gaging stations in the basin. This approach was updated to compare loading results with those used in previous investigations. The second approach used regression equations, referred to as instantaneous continuous (INSTC) regressions, developed from continuous measurements of physical water-quality constituents (specific conductance, temperature, and turbidity, and streamflow data) obtained from 2004 through 2010 to estimate loads of nitrogen, phosphorus, and sediment at two of the streamflow-gaging stations, Spavinaw Creek near Colcord, Okla., and Beaty Creek near Jay, Okla. Daily, annual, and mean annual loads estimated from these two regression methods were compared for the period 2005-10.

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