Water erosion is one of most important global environmental problems which has been widely researched but remains poorly understood because of the complexity of its underlying mechanisms driven by interacting environmental factors. Water erosion is highly sensitive to climate change and associated events such as increasing extreme rainfall events and global warming. This chapter provides a comprehensive overview of the research progress on water erosion processes, as well as how they can be influenced by the natural and anthropogenic factors. The main water erosion control practices are introduced, which need better spatial and temporal allocations under future climate risk. We also reviewed the literature that has quantified direct and indirect climate change impacts on water erosion. Future avenues of research might include: deeper investigation of the natural and anthropogenic factors associated with water erosion, high resolution predictions of water erosion at larger scale and evaluation of economic models associated with erosion control practices to help policymakers develop and implement measures to mitigate the impacts of climate change.

The Lancang-Mekong River Basin (LMRB) is Asia's most important transboundary river. The precipitation-dependent agriculture and the world's largest inland fishery in the basin feed more than 70 million people. Floods are the main natural disasters which pose a serious threat to the local agriculture and human life. In the future, climate change will affect the streamflow and lead to changes in flood events. Based on the GMDF and GCM data, the SPI and the VIC model were used to assess the impact of climate change on streamflow and flood events during the historical (1985–2016) and future periods (2020–2050) in the LMRB. The results show that the LMRB will become more humid in the future and annual precipitation will change from about -2 to 6 per cent under RCP4.5 and RCP8.5. In the future, this basin should experience a higher flood risk, with more flood events and a relative increase in the flood peak and frequency reaching up to +15 and +58 per cent, respectively. This study contributes to improve our understanding of the role of climate change on streamflow and flood events and provides a scientific reference for the development of local water resources management in the LMRB.

A better detection of landslide occurrence is critical for disaster prevention and mitigation. Over the past four decades, great achievements have been made, ranging from inventories to mapping, susceptibility analysis to triggering threshold identification. Here, we proposed a model to establish global distributed rainfall thresholds, by linking triggering rainfall with geo-environmental causes related to landslide events. The model was based on multiple linear regression method, to define rainfall thresholds as a function of diverse geo-environmental variables, fitted and validated by a combined and relatively accurate landslide dataset. Results show primarily feasible performances for training and testing datasets, with low mean absolute error (0.22 log(mm)) and a high coefficient of determination (0.67) totally. We further prepared global distributed threshold maps for sub- and multi-daily rainfall durations. They share similar spatial distributions in line with previous research. The normalized rainfall index, defined as the ratio of precipitation amount over distributed rainfall thresholds, can be an index of possible landslide occurrence, that is, regions with a normalized index over 1.0 correspond to high probability. We argue that distributed rainfall threshold models are an improvement of empirical threshold models and susceptibility assessments by considering the interaction between triggering rainfall and geo-environmental causes, and promising for better hazard assessment.

Climate change caused by the increase in regional and global air temperature significantly affects the environment, especially in cold regions. The frozen ground degradation and its environmental consequence in the Tibetan region are reviewed. Model simulations show that air temperature in the Tibetan Plateau will continue to increase by 3.8–4.8°C at the end of this century. From 1981 to 2010, the duration of seasonally frozen ground was shortened, which delayed its start by 3.4 days and ended 9.4 days earlier than normal. The warming phenomenon resulted in degradation of frozen ground and permafrost by 3.3 105 km2 and 1.11 106 km2, respectively. From 2001 to 2015, soil erosion and desert area increased by 1.14 and 1.80 per cent, respectively. This resulted in a reduction of vegetation coverage. In addition, the influence of climate change on highway on the Qinghai–Tibetan Plateau was also caused by frozen ground degradation, soil deformation and thawed settlement. With a large portion of frozen ground degradation in the Qinghai–Tibetan Plateau, long-term field monitoring, remote sensing investigations, model predictions for temperature and frozen soil, and adaptations to environmental change are needed to mitigate the effects of more intense changes expected in the future.

Lake Urmia, in the north-west of Iran, used to be the second-largest hypersaline lake around the world. Over the past few decades, unsustainable water resources planning and management as well as climate variability have led to a dramatic shrinkage of the lake. In this chapter, we describe the past and present situation of the lake through an analysis of in-situ and global datasets. Furthermore, we provide a brief review of the literature on the basin and describe the Urmia lake restoration programme (ULRP) measures taken to restore the lake. The precipitation and temperature data from 17 CORDEX models under RCP2.6, RCP4.5 and RCP8.5 scenarios are used to project the climatic condition of the basin by the end of the century. The results from CORDEX model simulations under all scenarios suggest changes in total amounts of precipitation are not likely to vary significantly. Conversely, increases in the basin temperature are expected under all scenarios. Therefore, an increase in evaporation from the lake and higher water demands are expected in the future. Consequently, the management of water demand in the basin is key to avoid a potential future deterioration of the current situation.