Accurate forecasting of annual runoff is necessary for water resources management. However, a runoff series consists of complex nonlinear and non-stationary characteristics, which makes forecasting difficult. To contribute towards improved prediction accuracy, a novel hybrid model based on the empirical mode decomposition (EMD) for annual runoff forecasting is proposed and applied in this paper. Firstly, the original annual runoff series is decomposed into a limited number of intrinsic mode functions (IMFs) and one trend term based on the EMD, which makes the series stationary. Secondly, it will be forecasted by a least squares support vector machine (LSSVM) when the IMF component possesses chaotic characteristics, and simulated by a polynomial method when it does not. In addition, the reserved trend term is predicted by a Gray Model. Finally, the ensemble forecast for the original runoff series is formulated by combining the prediction results of the modeled IMFs and the trend term. Qualified rate (QR), root mean square errors (RMSE), mean absolute relative errors (MARE), and mean absolute errors (MAE) are used as the comparison criteria. The results reveal that the EMD-based chaotic LSSVM (EMD-CLSSVM) hybrid model is a superior alternative to the CLSSVM hybrid model for forecasting annual runoff at Shangjingyou station, reducing the RMSE, MARE, and MAE by 39%, 28.6%, and 25.6%, respectively. To further illustrate the stability and representativeness of the EMD-CLSSVM hybrid model, runoff data at three additional sites, Zhaishang, Fenhe reservoir, and Lancun stations, were applied to verify the model. The results show that the EMD-CLSSVM hybrid model proved its applicability with high prediction precision. This approach may be used in similar hydrological conditions.

The serious environmental pollution caused by the spontaneous combustion of coal gangue has become a problem which cannot be ignored in the world mining industry. It is urgently necessary to clarify the law of the temperature distribution of spontaneous combustion in gangue dumps and to grasp its future dynamic evolution of spontaneous combustion. In this study, the internal temperature of the second platform of the Yinying coal mine gangue dump was monitored on the basis of the self-developed wireless temperature monitoring system. Its temperature distribution was analysed, and areas of low (280 °C) were delimited. The finite element method was also used to simulate its internal temperature development of 1–5 years. The results show that: (1) The high temperature area is mainly distributed on the side close to the slope. In the area 3 m deep, the high temperature started to propagate quickly. At a depth of 4 m, medium and high temperature represented 90% of the platform’s total surface area. At 6 m deep, temperature peaked at 667 °C. (2) The conduction of the internal temperature of the spontaneous combustion of gangue discharge is a non-linear conduction, and the conduction of heat in the horizontal direction is lower than the vertical direction. (3) During the spontaneous combustion of gangue discharge over the next five years, the overall temperature increase is faster at first, then it decreases and eventually stabilises. The high-temperature zones extend 10 m from the slope to the interior in five years, and the high-temperature zones are oval-shaped. This study provides a theoretical reference for the prevention and control of spontaneous combustion of coal gangue dumps.

The impacts of temperature and precipitation changes on regional evaporation and runoff characteristics have been investigated for the Biliu River basin, which is located in Liaoning Province, northeast China. Multiple climate change scenarios from phase 3 and phase 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) (21 scenarios in total) were utilized. A calibrated hydrologic model—SWAT model—was used to simulate future discharges based on downscaled climate data through a validated morphing method. Results show that both annual temperature and precipitation increase under most of the CMIP3 and CMIP5 scenarios, and increase more in the far future (2041–2065) than in the near future (2016–2040). These changes in precipitation and temperature lead to an increase in evaporation under 19 scenarios and a decrease in runoff under two-thirds of the selected scenarios. Compared to CMIP3, CMIP5 scenarios show higher temperature and wider ranges of changes in precipitation and runoff. The results provide important information on the impacts of global climate change on water resources availability in the Biliu River basin, which is beneficial for the planning and management of water resources in this region.

Acid Mine Drainage (AMD) has become an important issue due to its significant ecological pollution. In this paper, phytoremediation technology and mechanism for AMD were investigated by hydroponic experiments, using six wetland plants (Phragmites australis, Typha orientalis, Cyperus glomeratus, Scirpus validus, Iris wilsonii, Juncus effusus) as research objects. The results showed that (1) the removal of sulfate from AMD was highest for Juncus effusus (66.78%) and Iris wilsonii (40.74%) and the removal of Mn from AMD was highest for Typha orientalis (>99%) and Phragmites australis (>99%). In addition, considering the growth condition of the plants, Juncus effusus, Iris wilsonii, and Phragmites australis were finally selected as the dominant plants for the treatment of AMD. (2) The removal pathway of pollutants in AMD included two aspects: one part was absorbed by plants, and the other part was removed through hydrolysis and precipitation processes. Our findings provide a theoretical reference for phytoremediation technology for AMD.

In order to study the economical, efficient, and environmentally friendly techniques for the treatment of acid mine drainage (AMD), this paper investigated the effects of watering with AMD on the growth condition, the resilience of four wetland plants, as well as the uptake and transport of pollutants by plants. The results showed that Typha orientalis was more resistant to AMD (irrigation with AMD increased its catalase activity and glutathione content and promoted its growth), so it was suitable for treating high concentrations of AMD (SO₄²⁻ ≈ 9400 mg/L); Cyperus glomeratus was suitable for treating medium concentrations of AMD (SO₄²⁻ ≈ 4600 mg/L); and Scirpus validus and Phragmites australis could be used to treat low concentrations of AMD (SO₄²⁻ ≈ 2300 mg/L). All four plants could be used for phytoextraction for Mn-contaminated water (TF > 1). Phragmites australis could be used for phytoextraction for Zn-contaminated water, and the other three plants could be used for phytostabilisation for Zn-contaminated water (TF < 1); the microbial biomass in the soil was affected not only by the concentration of AMD but also by plant species. This study provides a scientific basis for the phytoremediation technology of AMD.

The assessment of water resource responses to climate change is required in water resource planning and management, protecting environmental quality, and managing watersheds. This study modeled surface runoff and baseflow responses to variations in precipitation (0%, ±10%, and ±20%) and temperature (0 °C, ±1 °C, and ±2 °C) in 25 types of scenarios in the Lanhe Watershed (1140 km²), which possesses the typical hydrological and meteorological characteristics of the Loess Plateau in China. The study is based on the Soil and Water Assessment Tool (SWAT), which was calibrated and validated using the coefficient of determination (R²), Nash-Suttcliffe (Ens), and Percent bias (PBIAS), using the observed streamflow of Shangjingyou Station, a unique gauging station in the study area. The model was calibrated with daily streamflow, from 1967 to 1996, and then validated from 1997 to 2011. R², Ens, and PBIAS were 0.95 and 0.84, 0.78 and 0.72, and 0.6% and −9.1% in annual and monthly calibration periods, 0.90 and 0.78, 0.74 and 0.67, and 22.1% and 18.8% in annual and monthly validation periods, and the overall performance ratings was “satisfactory”. The assessment indicates that surface runoff is likely to be more affected than baseflow when altering temperatures and precipitation, and the noticeable changes of surface and baseflow are from June to September and October to November, respectively. Results also indicate that surface runoff and baseflow are very sensitive to the projected reduction in temperature, rather than to an increase of temperature, while precipitation is a constant. In turn, when the temperature is a constant, the surface runoff is sensitive to the projected increase in precipitation and the baseflow is sensitive to the decrease in precipitation.