Comparative Water Environment Simulation Study of Two Typical Models with BMPs in a Karst Basin

Carbonate rocks are widely distributed in southwest China, forming a unique karst landscape. The Lijiang River Basin provides a typical example of an area with concentrated karst. Research on the laws of hydrology and water quality migration in the Lijiang River Basin is important for the management of the water resources of Guilin City and similar areas. In this study, we combined three meteorological data with the soil and water assessment tool (SWAT) model and the hydrological simulation program-Fortran (HSPF) model to simulate the hydrological and water quality processes in the Lijiang River Basin separately. We chose the Nash–Sutcliffe efficiency (NSE) coefficient, coefficient of determination (R2), root mean square error-observations standard deviation ratio (RSR), and mean absolute error (MAE) as the metrics used to evaluate the models. The results, combined with the time-series process lines, indicated that the SWAT model provides a more accurate performance than the HSPF model in streamflow, ammonia nitrogen (NH3-N), and dissolved oxygen (DO) simulations. In addition, we divided the karst and non-karst areas, and we analyzed the differences between them in water balance, sediment transport, and pollution load. We further identified the key source areas of pollution load in the Lijiang River Basin, evaluated the pollution reduction effect of best management practices (BMPs) on surface source pollution, and proposed some pollution control countermeasures. Each scenario, especially returning farmland to forest and creating vegetation buffer zones, reduces the NH3-N and DO pollution load.

Responses of water environmental indicators to climate conditions in the middle and lower reaches of Lijiang River

With global climate change and increasingly extreme weather conditions, the water environment of the Lijiang River Basin is facing huge threats. Past studies have mostly focused on large-scale areas or have regional characteristics. Therefore, this study is based on the meteorological, hydrological, and water quality data of the Lijiang River from 2012 to 2018, using the analysis method Spearman's rank correlation coefficient, sensitivity , and contribution rate to quantitative analysis of the relationship between climate conditions and water environment indicators. The results show that the oxidation and alkalinity of the water in the Lijiang River Basin gradually increase, and the intensity becomes stronger as it goes downstream. DO increase and the concentrations of COD Mn , BOD 5 , and NH 4 -N all decreased, and water quality improved year by year. The input of external pollution has led to an upward trend in TP in Yangshuo. DO is positively correlated with wind speed and negatively correlated with other climate indicators. NH 4 -N and TP are mainly affected by precipitation, streamflow, humidity, and sunshine duration, only sunshine duration is negatively correlated. Pollutants from Guilin to Yangshuo on both sides of the Lijiang River were carried by the surface runoff into the water body contain a certain amount of organic matter and acidic matter. Water environment indicators are not very sensitive to precipitation and streamflow, humidity and wind speed have higher sensitivity. Water temperature and sunshine duration have a positive effect on reducing NH 4 -N and TP. Various climate conditions can help reduce organic matter in the water body where there are few external sources and the opposite contribution with external sources. No climate condition can dominate one water environment indicator of two stations at the same time. The difference between Yangshuo and Guilin is mostly due to the input of external sources on both sides of the Lijiang River, which leads to the difference in sensitive climate conditions. Construction of non-point source pollution reduction facilities and sewage treatment measures are very necessary.

Spatial and temporal variation of dissolved heavy metals in the Lijiang River China: Implication of rainstorm on drinking water quality

Lijiang River is an essential drinking water source and natural scenery in the Guilin City. For the first time, implications of rainstorm were taken into consideration by investigating spatial and temporal variation of dissolved heavy metals (HMs) in the Lijiang River water. A total of 68 water samples were collected during low flow (normal) season and high flow (rainstorm) season from 34 sampling sites. Dissolved HMs including Cr, Mn, Co, Cu, Zn, As, Cd, Sb, and Pb were found to meet the respective drinking water standards, while higher concentration was observed after the rainstorm season, except for Cr. Multivariate statistical analysis showed Co, Cu, Cr, Zn, Sb, and Pb in normal season are mainly controlled by anthropogenic sources. Furthermore, higher concentration of Mn, Cu, Cd, Pb, Co and Zn during the high flow season is attributed to rainstorm. The water quality index (WQI) showed good grades, and comparatively lower in rainstorm season. The results of health risk assessment revealed that HMs in Lijiang River pose limited health risk, however, As poses potential health risk during rainstorm season. It is suggested to adopt preventive measures in mining activities and industrial waste-water discharge at the river’s upstream and downstream.

Investigation and Water quality Analysis of Agricultural nonpoint Source pollution in Tanxia Town

Taking the small watershed in Tanxia town as an example, the classified investigation of agricultural non-point source pollution in the tributaries of Lijiang River was carried out, the sources of local agricultural non-point source pollution were analyzed, and the surface water environmental quality standard and Nemero index method were used to evaluate the water quality of the basin. The results show that the water quality of the basin is poor and the pollution exceeds the standard all the year round, and the source of agricultural non-point source pollution mainly depends on the pollution of agricultural chemical fertilizer. Improving the use of local chemical fertilizer and rational application of chemical fertilizer are the key factors to improve local agricultural non-point source pollution.