Abstract

Accurately evaluating surface water quality grade (WQG) is of great significance in improving the efficiency of regional water quality management. Based on seven main surface water quality indicators (including dissolved oxygen (DO), chemical oxygen demand (COD), permanganate index (CODMn), ammonia nitrogen (NH4+-N), fluoride (FL), total phosphorus (TP) and total nitrogen (TN)) data from 910 measuring points in Heilongjiang Province from May to August 2017, an improved Nemerow index method (IN method) based on combined weighting was constructed, and the WQG was evaluated. On this basis, the multiple linear or non-linear regression models (MLR or MNR) under different quantities of water quality indicators were established, and the prediction results were evaluated. Results show that: 1) WQG in Heilongjiang Province above grade III accounts for more than 92.6%, evaluated by the IN method; 2) The accuracy of WQG evaluated by MLR based on different quantities of water quality indicators are maintained at 77%-90% and decreases with the increase of the number of water quality indicators (N), which may be related to the selected combination of water quality indicators and key water pollutants. The accuracy is improved by 3.9%-17.4% for MNR as compared to MLR, and especially the accuracy can reach as high as 95.6% when N is 5; 3) Compare to the MLR, the MNR is less affected by the data fluctuation characteristics, and performs best when N is 5 under both the great and small data fluctuations, with an accuracy of 85% and 90%, respectively. 4) TN (0.72), NH4+-N (0.41), and CODMn (0.33) are significantly related to the WQG. COD is a key parameter affecting the stability and uncertainty of MLR and MNR. These results provide a simple and reliable method for accurately evaluating the surface WQG, which have important guiding significance for decision-makers and researchers in water environment protection and agricultural water fertilizer management in Heilongjiang Province.

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