Brett Michael T, Mueller Sara E, Arhonditsis George B
Department of Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, Washington 98195, USA.
Environ Manage. 2005 Jan;35(1):56-71. doi: 10.1007/s00267-003-0310-0.
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 microg/L from one week to another, whereas TP varied +/- 48% or +/- 32.5 microg/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 approximately 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 approximately 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.
在为期1年的时间里，我们每天对西雅图地区四条溪流的河水总磷（TP）浓度进行采样，并每周对可溶性活性磷（SRP）浓度进行采样。这四条溪流涵盖了从森林覆盖到城市主导的土地覆盖梯度。本研究的目的是建立时间序列模型，描述河流水磷浓度对溪流基流季节变化、短期流量波动、前期流量条件和降雨的依赖性。河流水SRP浓度在一周到另一周之间平均变化±18%或±5.7微克/升，而TP则在一周到另一周之间变化±48%或±32.5微克/升。平均而言，SRP约占TP的47%。在四个研究地点中的三个地点，河流水SRP浓度遵循简单的正弦波年周期，在低流量的夏季浓度较高，在高流量的冬季浓度较低。这些趋势可能是由于地下水和地下水流对溪流流量的相对贡献的季节性变化。在森林覆盖的伊萨夸溪，除了秋季外，SRP浓度全年相对稳定，秋季溪流中有大量鲑鱼产卵，SRP浓度显著增加。在每条研究溪流中，河流水SRP浓度与短期流量波动、前期流量条件或降雨在统计上无关。河流水TP浓度变化很大，并受到短期流量波动的强烈影响。评估的每个过程与TP浓度都有统计学上的显著相关性，其中季节性基流影响最强，其次是前期流量条件、短期流量波动和降雨。四个溪流中有三个溪流的单个时间序列模型能够预测SRP年周期中约70%的变异性（r2 = 0.57 - 0.81），而单个TP模型在所有溪流中解释了约50%的年周期（r2 = 0.39 - 0.59）。总体而言，SRP和TP动态的时间序列模型分别解释了这些变量82%和76%的变异性。我们的结果表明，SRP是生物可利用性最高、因此也是最重要的磷组分，其季节性和每周动态更简单且更易于预测。
