Compared with the conventional fossil fuel, bioenergy has obvious advantages due to its renewability and large quantity, and thus plays a crucial role in helping defend the energy security. However, the bioenergy development may potentially cause serious environmental alterations, which remain unclear. The study summarizes the environmental impacts of bioenergy production based on the compilation and published data. Our analysis shows that more and more attention is being paid to the environmental protection as the development of bioenergy, and among the influencing terms of bioenergy production, water issues (i.e., water quantity and quality) gain the greatest concern, whereas the least attention has been given to soil erosion. Although we recognize that the bioenergy production can indeed exert negative effects on the environment in terms of water quantity and quality, greenhouse gas emissions, biodiversity and soil organic carbon, and soil erosion, the adverse impacts varied greatly depending on biomass types, land locations, and management practices. Identifying the reasonable cultivation locations, appropriate bioenergy crop types, and optimal management practices can be beneficial to environment and sustainable development of bioenergy. In this field, Chinese bioenergy production has lagged behind and does not match its rising energy consumption, but it has a great potential of and demand for biomass-based energy especially under its urbanization, in spite of the negative environmental impacts. Therefore, this article is expected to serve as a reference and guideline on what has been done in the bioenergy-oriented countries that might stimulate development of more effective and environmentally sound guidelines for promoting bioenergy production in China and other developing countries as well.

Hydrological models play an important role in water resource management, but they always suffer from various sources of uncertainties. Therefore, it is necessary to implement uncertainty analysis to gain more confidence in numerical modeling. The study employed three methods (i.e., Parameter Solution (ParaSol), Sequential Uncertainty Fitting (SUFI2), and Generalized Likelihood Uncertainty Estimation (GLUE)) to quantify the parameter sensitivity and uncertainty of the SWAT (Soil and Water Assessment Tool) model in a mountain-loess transitional watershed—Jingchuan River Basin (JCRB) on the Loess Plateau, China. The model was calibrated and validated using monthly observed streamflow at the Jingchuan gaging station and the modeling results showed that SWAT performed well in the study period in the JCRB. The parameter sensitivity results demonstrated that any of the three methods were capable for the parameter sensitivity analysis in this area. Among the parameters, CN2, SOL_K, and ALPHA_BF were more sensitive to the simulation of peak flow, average flow, and low flow, respectively, compared to others (e.g., ESCO, CH_K2, and SOL_AWC) in this basin. Although the ParaSol method was more efficient in capturing the most optimal parameter set, it showed limited ability in uncertainty analysis due to the narrower 95CI and poor P-factor and R-factor in this area. In contrast, the 95CIs in SUFI2 and GLUE were wider than ParaSol, indicating that these two methods can be promising in analyzing the model parameter uncertainty. However, for the model prediction uncertainty within the same parameter range, SUFI2 was proven to be slightly more superior to GLUE. Overall, through the comparisons of the proposed evaluation criteria for uncertainty analysis (e.g., P-factor, R-factor, NSE, and R²) and the computational efficiencies, SUFI2 can be a potentially efficient tool for the parameter optimization and uncertainty analysis. This study provides an insight into selecting uncertainty analysis method in the modeling field, especially for the hydrological modeling community.

A long‐term transient simulation is conducted using the Community Climate System Model version 3 and the orbital acceleration technique to analyze the impact of insolation change caused by the Earth's orbital forcing on precipitation in the monsoonal East Asia (EA) and arid central Asia (CA) over the past 150 ka. Our results show that annual precipitation in both EA and CA has strong signals of the 20 ka precessional cycles and varies in phase with the Northern Hemisphere (NH) summer insolation. Similar characteristics can also be observed from previously published oxygen isotope records of stalagmites near EA and CA. Composite analyses based on seven precessional cycles suggest that the increase (decrease) in the NH summer (winter) insolation enhances EA (CA) summer (winter) precipitation by modulation of the Asian monsoon (westerly) circulation in summer (winter). When the precession‐induced NH summer insolation increases, the Asian summer monsoon circulation is enhanced and EA precipitation increases significantly. Meanwhile, the increase in the summer insolation at the precessional scale is accompanied by a decrease in the winter insolation, which causes dramatic cooling of the troposphere in the lower latitudes. Consequently, the CA winter precipitation increases due to the changes in the temperature gradient and the westerly circulation. Therefore, the responses of the Asian monsoon and westerly circulation to summer and winter insolation variations induced by the precessional cycles determine precipitation in the respective rainy seasons and are the primary cause leading to the synchronous variation patterns of annual precipitation in EA and CA at the orbital scale.