title: Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula.
abstract: Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH3-N) and permanganate index (CODMn) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH3-N and CODMnseries at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class Vw, Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH3-N and CODMnsimultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH3-N and CODMnis inferior to class V and class IV water quality standards, respectively.
authors.affiliation: State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China E-mail: weishi1208@163.com.
authors.forename: Wei
authors.initials: W
authors.lastname: Shi
authors.affiliation: State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China E-mail: weishi1208@163.com; Hubei Provincial Collaborative Innovation center for Water Resources Security, Wuhan 430072, China and The Research Institute for Water Security, Wuhan University, Wuhan 430072, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Xia
mesh_terms: D000641:Ammonia / Q000032:analysis; D003247:Conservation of Natural Resources; D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D008390:Markov Chains; D008962:Models, Theoretical; D009584:Nitrogen / Q000032:analysis; D018570:Risk Assessment; D045483:Rivers / Q000737:chemistry*; D014874:Water Pollutants, Chemical / Q000032:analysis*; D060753:Water Quality
chemical_list: D014874:Water Pollutants, Chemical; D000641:Ammonia; D009584:Nitrogen