The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

Based on the Lancang River Basin (LRB) hydro–meteorological data from 1961 to 2015, this study uses the Mann–Kendall trend test and mutation test to analyze the trend of hydro–meteorological variables, as well as which year the runoff series changes, respectively. We applied the Choudhury–Yang equation to calculate the climate and catchment landscape elasticity of runoff. Then we quantified the impact of climate change and human activities on runoff change. The results show that: (1) the mean annual precipitation (P) in LRB showed an insignificant decline, the annual potential evapotranspiration (E₀) showed a significant increase, and the runoff depth (R) showed a significant decrease; (2) the abrupt change of the R occurred in 2005. Both the climate and catchment landscape elasticity of runoff increased, which means that the hydrological process of LRB became more sensitive to climate changes and human activities; (3) compared with the base period (1961–2004), the reduction of P was the leading cause of runoff reduction, with a contribution of 45.64%. The contribution of E₀ and human activities to runoff changes are 13.91% and 40.45%, respectively.

Purpose: The purpose of this study is to assess the spatiotemporal patterns of future meteorological drought in the Yellow River Basin under different representative concentration pathway (RCP) scenarios. Design/methodology/approach: Delta method is used to process the future climate data of the global climate models, then analyzed the spatiotemporal variation trend of drought in the Yellow River Basin based on standardized precipitation evaporation index (SPEI) under four RCP scenarios. Findings: This research was funded by the National Natural Science Foundation of China (41901239), Soft Science Research Project of Henan Province (212400410077, 192400410085), the National Key Research and Development Program of China (2016YFA0602703), China Postdoctoral Science Foundation (2018M640670) and the special fund of top talents in Henan Agricultural University (30501031). Originality/value: This study can provide support for future meteorological drought management and prevention in the Yellow River Basin and provide a theoretical basis for water resources management.

The economic damage function of the integrated assessment model (IAM) is used to quantify the economic loss caused by climate change, and it is quite important for coupling the economic system and natural system in a model. However, there are many shortcomings of the damage function in the current IAM. The most important shortcoming is that the only climatic factor in the damage function is the global annual mean temperature rise, which would result in the estimation deviating from reality. We improved the damage function by introducing extreme climate change events. Additionally, the improved damage function is applicable to the regional characteristics by using regional climate change data. The extreme climate event information is extracted with the categories of the disasters. The damage function is set up by using the Ordinary Least Square (OLS) method based on the climate data and economic loss data. The results show that the improved IAM damage function can better reflect the actual climate change economic loss in China, making it more reasonable. This paper provides an important method and technical solution for the realization of an effective connection between the disaster damage function of the integrated assessment model and the climate elements of the Earth system model.