Elwan Ahmed, Singh Ranvir, Patterson Maree, Roygard Jon, Horne Dave, Clothier Brent, Jones Geoffrey
Institute of Agriculture and Environment (IAE), Massey University, Private Bag, Palmerston North, 11 222, New Zealand.
Horizons Regional Council, Palmerston North, New Zealand.
Environ Monit Assess. 2018 Jan 11;190(2):78. doi: 10.1007/s10661-017-6444-y.
Better management of water quality in streams, rivers and lakes requires precise and accurate estimates of different contaminant loads. We assessed four sampling frequencies (2 days, weekly, fortnightly and monthly) and five load calculation methods (global mean (GM), rating curve (RC), ratio estimator (RE), flow-stratified (FS) and flow-weighted (FW)) to quantify loads of nitrate-nitrogen (NO-N), soluble inorganic nitrogen (SIN), total nitrogen (TN), dissolved reactive phosphorus (DRP), total phosphorus (TP) and total suspended solids (TSS), in the Manawatu River, New Zealand. The estimated annual river loads were compared to the reference 'true' loads, calculated using daily measurements of flow and water quality from May 2010 to April 2011, to quantify bias (i.e. accuracy) and root mean square error 'RMSE' (i.e. accuracy and precision). The GM method resulted into relatively higher RMSE values and a consistent negative bias (i.e. underestimation) in estimates of annual river loads across all sampling frequencies. The RC method resulted in the lowest RMSE for TN, TP and TSS at monthly sampling frequency. Yet, RC highly overestimated the loads for parameters that showed dilution effect such as NO-N and SIN. The FW and RE methods gave similar results, and there was no essential improvement in using RE over FW. In general, FW and RE performed better than FS in terms of bias, but FS performed slightly better than FW and RE in terms of RMSE for most of the water quality parameters (DRP, TP, TN and TSS) using a monthly sampling frequency. We found no significant decrease in RMSE values for estimates of NON, SIN, TN and DRP loads when the sampling frequency was increased from monthly to fortnightly. The bias and RMSE values in estimates of TP and TSS loads (estimated by FW, RE and FS), however, showed a significant decrease in the case of weekly or 2-day sampling. This suggests potential for a higher sampling frequency during flow peaks for more precise and accurate estimates of annual river loads for TP and TSS, in the study river and other similar conditions.
要更好地管理溪流、河流和湖泊的水质，需要精确且准确地估算不同污染物负荷。我们评估了四种采样频率（两天一次、每周一次、每两周一次和每月一次）以及五种负荷计算方法（全球均值（GM）、率定曲线（RC）、比率估计器（RE）、流量分层（FS）和流量加权（FW）），以量化新西兰马纳瓦图河中的硝酸盐氮（NO-N）、可溶性无机氮（SIN）、总氮（TN）、溶解性活性磷（DRP）、总磷（TP）和总悬浮固体（TSS）的负荷。将估算的年河流负荷与参考“真实”负荷进行比较，该参考负荷是使用2010年5月至2011年4月的流量和水质日测量值计算得出的，以量化偏差（即准确性）和均方根误差“RMSE”（即准确性和精密度）。GM方法导致相对较高的RMSE值，并且在所有采样频率下，年河流负荷估算中存在一致的负偏差（即低估）。RC方法在每月采样频率下，对TN、TP和TSS产生的RMSE最低。然而，RC对表现出稀释效应的参数（如NO-N和SIN）的负荷高估严重。FW和RE方法给出了相似的结果，并且使用RE相对于FW并没有实质性改进。总体而言，就偏差而言，FW和RE比FS表现更好，但对于大多数水质参数（DRP、TP、TN和TSS），使用每月采样频率时，FS在RMSE方面比FW和RE略好。我们发现，当采样频率从每月增加到每两周一次时，NON、SIN、TN和DRP负荷估算的RMSE值没有显著下降。然而，TP和TSS负荷估算（由FW、RE和FS估算）中的偏差和RMSE值在每周或两天采样的情况下显著下降。这表明在流量峰值期间采用更高的采样频率，对于在研究河流及其他类似条件下更精确准确地估算TP和TSS的年河流负荷具有潜力。
