| Coal is the primary energy resource in China.The production and consumption of coal in primary energy accounts for more than 70%of the total energy consumption.High groundwater table and dense river network are one of the main characteristic of eastern plain area of China.Under the comprehensive effect of precipitation,surface runoff and groundwater,extensive underground coal mining exploitation leads to land subsidence and forms subsided water areas(subsidence pool)around the mining working face where the underground water level is shallow.Due to the surface water and soil of coal cities have been polluted in some ways.As a result,the instability of water quality of the collapse pond brings potential threats to the health of local residents and throw adverse effect upon the sustainable development of the local economy and society.In this research,we take one subsidence pool in Panji coal mining located in Huainan city,Anhui province,East China as an example.Firstly,we collected water samples five times through 2016 and performed laboratory analysis to obtain the water reflectance spectra,physical and chemical data.At the meantime,we collected remote sensing reflectance spectra simultaneously at each sampling site and build up the mathematical inversion model of water quality parameters.After that,we adopted collaborative kriging method by choosing the optimal band reflectance spectral as a covariate to derive the spatio-temporal evolution of each water quality parameter in the research area.Based on that,we analyze the pollution characteristics and main pollutants of the water body during 2016.And then,we set up a model to evaluate the level of water quality and performed early warning of the water quality in the research area based on the Weber-Fechner law.The main conclusion are as follows:(1)It can be seen from the average spectral curve of sampling for each time that the lowest water spectral curve was found in July,and the highest in March.The concentration of chlorophyll a in the subsidence pool had the greatest influence on spectral characteristics of the water.It showed very strong absorption efifect.The higher concentration of chlorophyll a,the lower relative height of the water spectrum curve.By analyzing and comparing the correlation coefficient among the measured water quality parameters and the raw spectral reflectance,normalized spectral reflectance and first order differential data,we found that the correlation between water quality parameters and spectral data is the best after the first order differential of the raw spectral reflectance.(2)Compared with ordinary kriging interpolation method of the single variable,the measured spectral data of water can effectively improve the accuracy of spatial interpolation of water quality parameters.It is a simple,fast and feasible Co-kriging method.We adopted the Co-kriging interpolation method to interpolate six conventional water quality indicators(chlorophyll a,total phosphorus,total nitrogen,suspended solids,total organic carbon,dissolved oxygen)and eight heavy metals(iron,manganese,zinc,copper,chromium,cadmium,lead,nickel).We obtained the spatio-temporal distribution maps of 14 factors affecting the quality of collapsed pond water respectively.Taking the spatial distribution map of July as an example,we analyzed the main sources of water heavy metal contaminants(3)Based on Weber-Fechner law,14 kinds of univariate water quality parameters were superposed and analyzed.Time series of spatial maps of the water quality in the study area was obtained.Ww conduct comprehensive evaluation and early warning analysis of the water quality and the trend in the study area.The results showed that the best water quality was found in March and the worst was found in May.High warning was observed in the west of the study area which indicated that the pollution in west was more serious than that in the east in the study area,and the source of the water pollution is mainly from the western part of the study area. |
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