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• This paper constructed a framework for green water assessment in the Loess Plateau gully region using MIKE SHE model. • A new concept and extraction method for green water components was defined based on existing research. • A new concept of the potential of green water was defined in relation to the dried soil layers' classification indicators. • We assessed the dependence on green water components and potential for environmental changes. Exponentially increasing water demand and increasingly uncertain hydrological conditions due to climate change (CC) and land use/cover change (LUCC) undoubtedly pose significant challenges to the sustainability of water systems in arid and semi-arid regions worldwide, and even more so in the rain-fed agricultural area of the Loess Plateau (LP) in China, where green water supports all ecological landscapes and most agriculture. Therefore, an accurate assessment of green water resources is crucial for regional development. This paper constructed a comprehensive framework for assessing green water resources based on the MIKE SHE model, defined a new concept of green water components (GWCs) that can be extracted based on existing studies, proposes the potential of green water (GW P), and present a research methodology. To validate this research framework, we applied it to a typical basin in the LP gully area of the Nanxiaohegou (NXHG) basin. The model was calibrated using runoff data from basin outlet stations to extract four GWCs: high-efficiency green water (GW H), low-efficiency green water (GW L), unused green water (GW U), ineffective green water (GW I). We then assessed the GW P of the basin and analyzed its trends, consistency, and dependence on changing environments. The assessment framework is simple and easy to use, providing valuable information for regional revegetation and basin water management, and is highly recommended for replication in other regions. [ABSTRACT FROM AUTHOR]

• A method was proposed by coupling the ERI and the CLUE-S model. • Three different scenarios designed to explore ERI of LUCC in 2027. • Spatiotemporal characteristics of ERI were predicted under different scenarios. The Jinghe County of the Ebinur Lake Basin was chosen as the study area. Based on Landsat TM / OLI images obtained in 2007 and 2017, this paper attempts to use CLUE-S model to predict LUCC under three different scenarios (Natural Development scenario, Farmland Protection scenario, Water Resources Protection scenarios) in 2027. Landscape indices and ecological risk index were calculated and spatially interpolated for the whole region, and the results of ecological risk could be divided into five different zones: extremely low, low, moderate, high and extremely high. They were carried out for assessing the spatial–temporal changes in ecological risk for each landscape pattern. The results show that: (1) Among the three scenarios designed in this paper, the spatial distribution of LUCC in the Water Resource Protection scenario has the most obvious changes, followed by the Farmland Protection scenario and the Natural Development scenario becomes the third. In the water resources protection scenario, the scale of the desert decreases, but the forest and grass part increases, which is conducive to ecological improvement. (2) the distribution area of high ecological risk areas was the largest of three different scenarios, especially the farmland protection scenario. The area of low-risk level is the largest under the water conservation scenario. The ecological risk of LUCC under the water resources protection scenario is lower, which is better for ecological environment. (3) Water bodies mainly concentrate upon low ecological risk degree, accounting for approximately 62.8%, 82.2%, and 73.1% of low ecological risk; Farmland mainly lies in the low-risk areas, accounting for 59.1%, 63.5% and 68.8% of the lower ecological risk levels; In 2027, the unused land and other land types are the main land types of the higher ecological risk areas under three different scenarios, whose proportions are 67.40%, 68.24% and 65.90%, respectively. [ABSTRACT FROM AUTHOR]

• The rainfall-runoff relationship has changed under climate change and human activities in the TRH region. • The impacts climate indicators of rainfall-runoff ratio in the sub-basins of TRH region were different. • The contribution rates of human activity in the YRB were a little higher than that in the YARB. Identifying the impact of climate change and human activities on rainfall-runoff relationship in the Three-River Headwaters (TRH) region is essential for water source conservation, ecological security, and biodiversity maintenance of China and East Asia. In this paper, the runoff-rainfall ratio was used as the index of rainfall-runoff relationship. Different methods were employed to identify the impact indicators and quantitative assessment of rainfall-runoff relationship from 1957 to 2016. The results are the following: (1) the rainfall-runoff relationship has changed in the source regions of Yangtze River basin (YARB) and Yellow River (YRB), and runoff-rainfall ratio has increased by 2.9% and decreased by 3.2%, respectively; (2) the main climate indicators of runoff-rainfall ratio were rainfall, potential evaporation and sunshine hours in the YARB, and rainfall, potential evaporation and temperature in the YRB; (3) the contribution rates of human activity in the YRB were a little higher than that in the YARB, and the contribution rates of climate change and human activity were 90.9% and 9.1% in the YARB and 42.9% and 57.1% in the YRB. The results can provide invaluable information for managing water resources and taking ecological protection measures. [ABSTRACT FROM AUTHOR]