| In this paper,the characteristics and migration process of dissolved organic matter(DOM)in the water and soil system of the basin are studied by means of three-dimensional fluorescence spectroscopy and Fourier transform mid infrared spectroscopy,combined with parallel factor,fluorescence regional integration and correlation analysis.The results show that:(1)The DOM content of water system in P river basin is higher than that of soil system.The DOM concentration of sewage biochemical treatment outlet and rainwater runoff is the highest,which is a potential land-based pollution source in the basin.Fluorescence parameters show that the dom of surface water and rainwater runoff of P river is mainly land-based input,with strong characteristics of authigenic source and weak characteristics of humification;DOM in effluent from biochemical wastewater treatment is produced by both internal and external sources,with the strongest characteristics of autogenous source and the weakest characteristics of humification;DOM in sediments and soil of P river is mainly terrigenous input,with the weakest characteristics of authigenic source and strong characteristics of humification;The humification degree,molecular weight and the proportion of hydrophobic components in soil system were higher than those in water system;The dom of natural water and soil is mainly humic acid,while the dom of domestic and production water is mainly humic acid.(2)There are 5 kinds of fluorescence peaks(A,C,M,B,T)in P river water body,3 kinds of fluorescence peaks(A,C,M)in soil,and some T peaks.There are regional differences in fluorescence components and intensity of P river water body.There are two fluorescence components C1(fulvic acid like)and C2(lysine like)in mountainous grass area,and three components including C3(tryptophan like)in agricultural and rural areas and urban concentrated areas.The total fluorescence intensity and protein like proportion are urban concentrated area>Agricultural and rural area>mountainous grass area;There is no regional difference in soil fluorescence components in P River Basin.There are two fluorescence components C1(humus like)and C2(fulvic acid like)in the three regions.The total fluorescence intensity shows the regional difference of agricultural and rural areas>mountainous grass areas>urban concentration areas;The regional differences of functional groups in water and soil of P River are not obvious.They are mainly functional groups such as-OH,-CH3,C-N,N-H,C-H and benzene ring,and chemical bonds such as C≡C and C=C;The soil in the basin has little impact on the water body of P river.(3)From the fluorescence peak and content carried by rainwater runoff,it is found that the production and life of animal husbandry in mountainous grassland area is a serious land-based pollution source,which will lead to non-point source pollution in a certain range and affect the environment of water and soil system;The content of protein like substances carried by runoff will decrease after being diluted by river water and affected by microorganisms;The rainwater runoff of residential and factory areas in urban concentration areas is very easy to carry protein like substances,which is one of the pollution sources of urban surface water;Functional groups are not affected by land use types,and are mainly-OH,-CH3,C-N,N-H,C-H,C≡C and C=C.(4)After biochemical treatment measures,the content of DOM in the effluent of the sewage related water body is significantly reduced.When the effluent is discharged into the Y River,the recent characteristics of autogenous source are more obvious,the content of protein and humus are significantly increased within 50m from the sewage outlet to the downstream.After 1km,the river DOM gradually presents its original state.Correlation analysis found that the prediction of organic matter concentration by protein like content is only applicable to single type of water body,not to mixed water body.The inflow of sewage will lead to more complex DOM components of the river and increase the difficulty of river water environment prediction and monitoring. |