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This paper adopts the measurement of mercury intrusion porosimetry and nuclear magnetic resonance (NMR) to analyze the pore system and the pore structure of coal samples, and the measurement of maceral group composition, scanning electron microscopy, and energy dispersive X-ray spectroscopy to obtain the organic/inorganic composition of coal samples. Gravimetric and NMR methods are both used to calculate irreducible water saturation of the samples, and qualitative and quantitative research studies are therefore conducted. The following knowledge is obtained. Coal samples can be classified as micro-trans-pore-dominated samples, meso-macro-pore-dominated samples, cleat-dominated samples, and even development samples. The main composition of the samples is organic, and a little kaolinite and pyrite can be observed. Irreducible water saturation obtained by the gravimetric method is almost close to that gained by the NMR method. The influencing parameters can be divided into two categories. The first category contains the maximum vitrinite reflectance, volumetric factor, fixed carbon yield, volatile yield, vitrinite percentage, and inertinite percentage, which have a strong correlation with irreducible water saturation. The second category includes the buried depth and median radius, and they have a weak correlation with irreducible water saturation. Multivariate regression shows that there is a linear quaternion equation between irreducible water saturation and independent variables such as maximum vitrinite reflectance, volumetric factor, volatile yield, and vitrinite percentage.

In this paper, the impact of future climate changes on long-term hydropower generation (LTHG) of cascade hydropower stations in the lower reaches of the Jinsha River is discussed. Global climate models (GCM) were used to estimate the impacts of future climate changes, the Xinanjiang model (XAJ) was applied to project the streamflow of the hydropower stations, and then gravitational search algorithm (GSA) was adopted to solve the LTHG problem. In case studies, the validation of the XAJ model shows that it perform well in the projection of streamflow in the Jinsha River. Moreover, the future hydropower generation is simulated based on five different GCMs under three climate change scenarios. Finally, the GSA algorithm is used to obtain a set of schemes under the influence of climate change. The results show that future climate changes are expected to have different impact on power generation of cascade reservoirs in the downstream of the Jinsha River when the climate change scenarios are different. These findings can provide decision support for future water resources management of the Jinsha River.

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