Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced.

In recent years, the amount of water and sediment in the Yellow River Basin has dropped drastically. This paper selected 125 rainfall and flood data points from 1965 to 2015, combined hydrological methods and mathematical statistics to analyze the hydrological factors and runoff generation mechanism, and combined the underlying surface conditions of the Gushanchuan Basin. The characteristics of change revealed the temporal and spatial variation characteristics and related factors of the runoff generation mechanism in the basin. The results showed that the Gushanchuan Basin is still dominated by HOF runoff, but the runoff generation mechanism has also changed with changes in the underlying surface, which are reflected in increased runoff components, the reduced proportion of HOF runoff, and the increased proportion of saturation-excess overland flow (SOF) runoff and mixed runoff. We analyzed the variation law of underlying surface in the basin, which indicated that the increase in the forest grass area was the main factor affecting changes in the watershed runoff generation mechanism. This research will enable a deeper understanding of the runoff generation mechanism of the main soil erosion areas in the Loess Plateau, and reveal variations in the runoff generation mechanism in the Yellow River.

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The choice of scheme for the optimal allocation of water resource (OAW R) is a fuzzy multiple-attribution decision that is determined using information from many figures and fuzzy language regarding several evaluated factors, such as investment, daily water supplying, fee of contaminated water disposal, water conservation, and the development of economy.In this paper, the evaluation system employed to choose an OAWR scheme is established based on the evaluation of fuzzy language and the generalized induced ordered weighted averaging (GIOWA) operator. Considering economic aspects and a sustainable water supply, the five following constituents are chosen: 1) Investment (Yuan), 2) Daily water supply (ton/day), 3) Fee of contaminated water disposal (Yuan), 4) Water conservation (fuzzy language), and 5) Development of economy (fuzzy language). The analytic hierarchy process (AHP) method is used to determine the weighting vector.A case study on the choice of OAWR in the northern area of Shenyang city, China was conducted by a multiple-attribution decision based on the GIOWA operator. The results shows that the system employed was able to choose the best scheme of OAWR in which fuzzy and multiple-attribution decision-making should be performed.