Poyang Lake is the largest freshwater lake connecting the Yangtze River in China. It undergoes dramatic dynamics from the wet to the dry seasons. A comparison of the hydrological changes between the wet and dry seasons may be useful for understanding the water flows between Poyang Lake and Yangtze River or the river system in the watershed. Gauged measurements and remote sensing datasets were combined to reveal lake area, level and volume changes during 2000–2020, and water exchanges between Poyang Lake and Yangtze River were presented based on the water balance equation. The results showed that in the wet seasons, the lake was usually around 1301.85–3840.24 km², with an average value of 2800.79 km². In the dry seasons, the area was around 618.82–2498.70 km², with an average value of 1242.03 km². The inundations in the wet seasons were approximately quadruple those in the dry seasons. In summer months, the lake surface tended to be flat, while in winter months, it was inclined, with the angles at around 10′′–16′′. The mean water levels of the wet and dry seasons were separately 13.51 m and 9.06 m, with respective deviations of around 0–2.38 m and 0.38–2.15 m. Monthly lake volume changes were about 7.5–22.64 km³ and 1–5.80 km³ in the wet and dry seasons, respectively. In the wet seasons, the overall contributions of ground runoff, precipitation on the lake surface and lake evaporation were less than the volume flowing into Yangtze River. In the dry seasons, the three contributions decreased by 50%, 50% and 65.75%, respectively. Therefore, lake storages presented a decrease (−7.42 km³/yr) in the wet seasons and an increase (9.39 km³/yr) in the dry seasons. The monthly exchanges between Poyang Lake and Yangtze River were at around −14.22–32.86 km³. Water all flowed from the lake to the river in the wet seasons, and the chance of water flowing from Yangtze River in the dry seasons was only 5.26%.

As Arctic warming continues, its impact on vegetation greenness is complex, variable and inherently scale-dependent. Studies with multiple spatial resolution satellite observations, with 30 m resolution included, on tundra greenness have been implemented all over the North American tundra. However, finer resolution studies on the greenness trends in the Russian tundra have only been carried out at a limited local or regional scale and the spatial heterogeneity of the trend remains unclear. Here, we analyzed the fine spatial resolution dataset Landsat archive from 1984 to 2018 over the entire Russian tundra and produced pixel-by-pixel greenness trend maps with the support of Google Earth Engine (GEE). The entire Russian tundra was divided into six geographical regions based on World Wildlife Fund (WWF) ecoregions. A Theil–Sen regression (TSR) was used for the trend identification and the changed pixels with a significance level p < 0.05 were retained in the final results for a subsequent greening/browning trend analysis. Our results indicated that: (1) the number of valid Landsat observations was spatially varied. The Western and Eastern European Tundras (WET and EET) had denser observations than other regions, which enabled a trend analysis during the whole study period from 1984 to 2018; (2) the most significant greening occurred in the Yamal-Gydan tundra (WET), Bering tundra and Chukchi Peninsula tundra (CT) during 1984–2018. The EET had a greening trend of 2.3% and 6.6% and the WET of 3.4% and 18% during 1984–1999 and 2000–2018, respectively. The area of browning trend was relatively low when we first masked the surface water bodies out before the trend analysis; and (3) the Landsat-based greenness trend was broadly similar to the AVHRR-based trend over the entire region but AVHRR retrieved more browning areas due to spectral mixing adjacent effects. Higher resolution images and field measurement studies are strongly needed to understand the vegetation trend over the Russian tundra ecosystem.

More than 1100 lakes covering an area greater than 4500 km² are located on the Tibetan Plateau, and these lakes are important regulators of several large and famous rivers in Asia. The determination of hydrological changes that have occurred in these lakes can reflect climate change and supply scientific data to plateau environmental research. Data from high frequency (moderate-resolution imaging spectro-radiometer) MODIS images, altimetry, and the Hydroweb database collected during 2000–2015 were integrated in this study to delineate the detailed hydrological changes of 15 lakes in three basins—Inner Basin, Indus Basin, and Brahmaputra Basin—on the southern Tibetan Plateau. Seven of the 10 lakes in the Inner Basin presented increasing trends with various intensities, and the increasing rates in the area of four lakes (Nam Co, Selin Co, Zhari-namco, and Ngangze) were 1.62, 28.81, 2.27, and 3.70 km²/yr, respectively. The yearly increases in volume of the four lakes were 3.6, 9.44, 6, and 2.36 km³, respectively. A water balance equation was established for the four lakes based on lake volume changes to illustrate the contributions of precipitation, ground runoff, evaporation, and other factors. The results revealed that surface runoff was the major contributor to expansion, and lake surface evaporation was almost 2.76–3.86 times that of lake surface precipitation. The two lakes in Indus Basin, Rakshastal and Mapam Yumco, presented a slight retreat. As a representative of Brahmaputra Basin, Yamzho Yumco underwent a retreat of –3.49 km²/yr in area, –0.39 m/yr in level, and –0.19 km³/yr in volume. Decreasing precipitation, increasing evaporation, and the operation of a hydrological project were the main causes of its constant retreat.

The energy efficiency of the enhanced geothermal system (EGS) measures the economic value of the heat production and electricity generation, and it is a key indicator of system production performance. Presently there is no systematic study on the influence of well layout on the system energy efficiency. In this work we numerically analyzed the main factors affecting the energy efficiency of EGS using the TOUGH2-EOS1 codes at Gonghe Basin geothermal field, Qinghai province. The results show that for the reservoirs of the same size, the electric power of the three horizontal well system is higher than that of the five vertical well system, and the electric power of the five vertical well system is higher than that of the three vertical well system. The energy efficiency of the three horizontal well system is higher than that of the five vertical well system and the three vertical well system. The reservoir impedance of the three horizontal well system is lower than that of the three vertical well system, and the reservoir impedance of the three vertical well system is lower than that of the five vertical system. The sensitivity analysis shows that well spacing has an obvious impact on the electricity production performance; decreasing well spacing will reduce the electric power, reduce the energy efficiency and only have very slight influence on the reservoir impedance. Fracture spacing has an obvious impact on the electricity production performance; increasing fracture spacing will reduce the electric power and reduce the energy efficiency. Fracture permeability has an obvious impact on the electricity production performance; increasing fracture permeability will improve the energy efficiency and reduce the reservoir impedance.

Lakes on the Tibetan Plateau have experienced variations over the last several decades, and the delineation of lake dynamics is favorable for the regional water cycle and can serve as important information for plateau environmental research. This study focused on 57 lakes near the Tanggula Mountains on the southeastern Tibetan Plateau. Yearly inundations of the lakes in 1989–2019 and altimeter data available for 2003–2020 were integrated to illustrate the changing patterns of glacier-fed and non-glacier-fed lakes. These two groups of lakes presented very similar evolution stages. They both increased in 1989–1992, decreased in 1992–1996, increased rapidly in 1998–2005, and had batch-wise fluctuations since 2005, with respective areas of around 5305.28 and 1636.79 km² in the last decade. The non-glacier-fed lakes were more sensitive to precipitation variation, and glacier-fed lakes were more sensitive to temperature changes. Based on lakes with obvious changes in water level, the whole water storage variations of the studied lakes were 1.90 Gt/y in 2003–2009, including 1.80 Gt/y for glacier-fed lakes and 0.10 Gt/y for non-glacier-fed lakes. The contribution from glacier melting in 2003–2009 amounted to 16.11% of the whole lake volume increase. In 2010–2020, water mass changes were 0.42 Gt/y for glacier-fed lakes and −0.14 Gt/y for non-glacier-fed lakes, respectively. The volume increase of glacier-fed lakes in 2010–2020 was mainly due to the expansion of Selin Co. Selin Co experienced a water increase of about 0.46 Gt/y, and the other glacier-fed lakes experienced a decreasing volume of −0.04 Gt/y. In 2010–2020, 99.43% of the glacier contribution supplied Selin Co.

The equivalent continuum method an effective approach for modeling heat transfer in fractured geothermal reservoirs. However, presently there is a lack of systematical and profound study on application conditions of the equivalent porous media (EPM) method. In this study, we numerically investigated the application conditions of the EPM method based on geological data of Yangbajing geothermal field. The results indicate that when fracture spacing is within 3–25 m, the results of the EPM method are basically in the same levels as those of the MINC method. However, when the fracture spacing is within 25–300 m, differences of the EPM method from the MINC method increase with the fracture spacing, so when the fracture spacing is within 25–300 m, it is unreasonable to adopt the EPM method to simulate the fractured reservoirs. With the fracture spacing increasing within 25–300 m, the system production temperature and electric power will gradually decrease; the injection pressure, reservoir impedance and pump power will gradually increase; and the energy efficiency will gradually decrease.