Qingchun Yang

Identification of the hydrogeochemical processes and assessment of groundwater quality using classic integrated geochemical methods in the Southeastern part of Ordos basin, China

Insufficient understanding of the hydrogeochemistry of aquifers makes it necessary to conduct a preliminary water quality assessment in the southern region of Ordos Basin, an arid area in the world. In this paper, the major ions of groundwater have been studied aiming at evaluating the hydrogeochemical processes that probably affect the groundwater quality using 150 samples collected in 2015. The two prevalent hydrochemical facies, HCO3Mg·Na·Ca and HCO3Mg·Ca·Na type water, have been identified based on the hydrochemical analysis from Piper trilinear diagram. Compositional relations have been used to assess the origin of solutes and confirm the predominant hydrogeochemical processes responsible for the various ions in the groundwater. The results show that the ions are derived from leaching effect, evaporation and condensation, cation exchange, mixing effect and human activities. Finally groundwater quality was assessed with single factor and set pair methods, the results indicate that groundwater quality in the study region is generally poor in terms of standard of national groundwater quality. The results obtained in this study will be useful to understand the groundwater quality status for effective management and utilization of the groundwater resource.

Hydrochemical characterization and pollution sources identification of groundwater in Salawusu aquifer system of Ordos Basin, China ☆

Ordos Basin is located in an arid and semi-arid region of northwestern China, which is the most important energy source bases in China. Salawusu Formation (Q3 s) is one of the most important aquifer systems of Ordos Basin, which is adjacent to Jurassic coalfield areas. A large-scale exploitation of Jurassic coal resources over ten years results in series of influences to the coal minerals, such as exposed to the oxidation process and dissolution into the groundwater due to the precipitation infiltration. Therefore, how these processes impact groundwater quality is of great concerns. In this paper, the descriptive statistical method, Piper trilinear diagram, ratios of major ions and canonical correspondence analysis are employed to investigate the hydrochemical evolution, determine the possible sources of pollution processes, and assess the controls on groundwater compositions using the monitored data in 2004 and 2014 (before and after large-scale coal mining). Results showed that long-term exploration of coal resources do not result in serious groundwater pollution. The hydrochemical types changed from HCO3(-)-CO3(2-) facies to SO4(2-)-Cl facies during 10 years. Groundwater hardness, nitrate and sulfate pollution were identified in 2014, which was most likely caused by agricultural activities.

Ecological Compensation Estimation of Soil and Water Conservation Based on Cost-Benefit Analysis

Soil and water conservation ecological compensation can be simply defined as a monetary payment to offset the environmental loss. An illustration is given in this study describing the payment compensation to water resource conservation and soil losses in Erlongshan reservoir catchment, China. A semi-distributed hydrological SWAT model was applied to establish compensation standard considering six scenarios of land use changes by combined application of remote sensing and geographic information systems. Cost-benefit analysis (CBA) method is applied to evaluate the function of soil and water conservation, of which marginal opportunity cost and market value methods have been explored calculate the cost and benefit of water and soil conservation ecological function from provider and beneficiaries. Finally the ecological compensation of soil and water conservation for different land-use scenarios is calculated incorporating benefit apportion coefficient. The results provide an economically evaluated and market-oriented standard for the study of eco-compensation of environmental services and will be of great benefit to the implementation of soil and water conservation at a mesoscale catchment scale.

Hydrological impacts of climate change on streamflow of Dongliao River watershed in Jilin Province, China

The impacts of future climate change on streamflow of the Dongliao River Watershed located in Jilin Province, China have been evaluated quantitatively by using a general circulation model (HadCM3) coupled with the Soil and Water Assessment Tool (SWAT) hydrological model. The model was calibrated and validated against the historical monitored data from 2005 to 2009. The streamflow was estimated by downscaling HadCM3 outputs to the daily mean temperature and precipitation series, derived for three 30-year time slices, 2020s, 2050s and 2080s. Results suggest that daily mean temperature increases with a changing rate of 0.435°C per decade, and precipitation decreases with a changing rate of 0.761 mm per decade. Compared with other seasons, the precipitation in summer shows significant downward trend, while a significant upward trend in autumn. The annual streamflow demonstrates a general downward trend with a decreasing rate of 0.405 m3/s per decade. The streamflow shows significant downward and upward trends in summer and in autumn, respectively. The decreasing rate of streamflow in summer reaches 1.97 m3/s per decade, which contributes primarily to the decrease of streamflow. The results of this work would be of great benifit to the design of economic and social development planning in the study area.

Application of RBFN network and GM (1, 1) for groundwater level simulation

Groundwater is a prominent resource of drinking and domestic water in the world. In this context, a feasible water resources management plan necessitates acceptable predictions of groundwater table depth fluctuations, which can help ensure the sustainable use of a watershed’s aquifers for urban and rural water supply. Due to the difficulties of identifying non-linear model structure and estimating the associated parameters, in this study radial basis function neural network (RBFNN) and GM (1, 1) models are used for the prediction of monthly groundwater level fluctuations in the city of Longyan, Fujian Province (South China). The monthly groundwater level data monitored from January 2003 to December 2011 are used in both models. The error criteria are estimated using the coefficient of determination (R2), mean absolute error (E) and root mean squared error (RMSE). The results show that both the models can forecast the groundwater level with fairly high accuracy, but the RBFN network model can be a promising tool to simulate and forecast groundwater level since it has a relatively smaller RMSE and MAE.

A comparative study of shallow groundwater level simulation with three time series models in a coastal aquifer of South China

Accurate and reliable groundwater level forecasting models can help ensure the sustainable use of a watershed’s aquifers for urban and rural water supply. In this paper, three time series analysis methods, Holt–Winters (HW), integrated time series (ITS), and seasonal autoregressive integrated moving average (SARIMA), are explored to simulate the groundwater level in a coastal aquifer, China. The monthly groundwater table depth data collected in a long time series from 2000 to 2011 are simulated and compared with those three time series models. The error criteria are estimated using coefficient of determination (R2), Nash–Sutcliffe model efficiency coefficient (E), and root-mean-squared error. The results indicate that three models are all accurate in reproducing the historical time series of groundwater levels. The comparisons of three models show that HW model is more accurate in predicting the groundwater levels than SARIMA and ITS models. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies.