The human-climate-ecosystem interactions in the past were valuable for today’s human beings who face the challenge of global change. The multi-proxy reconstruction of climate change impacts and social responses and the comparative study between typical periods form an effective tool for elucidating the mechanisms of the interactions. In this paper, with a reconstruction of the proxy series of famine, migration and wars, the most typical social consequences related to climate change and disasters (flood/drought) in North China in 1470–1911 were quantitatively described, and two typical periods of human-climate interaction with similar climate change backgrounds (cold periods of the ‘Little Ice Age’), which were the late Ming dynasty (1560–1644) and late Qing dynasty (1780–1911), were selected and compared. It is determined that the climate deterioration (rapid cooling and increasing extreme disasters) in the late 16th and 18th centuries both resulted in severe social consequences characterized by more famine and popular unrest. The differences were that the climatic impacts in the late Ming were much more serious, and interregional migration, which was an effective responsive measure in the late Qing, was not important in the late Ming; they were primarily influenced by three factors based on the analytical framework of the impacts of historical climate change and social responses: (1) climate deterioration in the late Ming was more severe (more rapid cooling and more extreme disasters), (2) social system were more sensitive to climate change in the late Ming because of its mode of agricultural production (especially cropping system and crop species), and (3) the capacity of social response to climate disaster, especially disaster relief and refugee settlement, was considerably greater in the late Qing.

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The negative impact of climate change continues to escalate flood risk. Floods directly and indirectly damage highway systems and disturb the socioeconomic order. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The approach has three parts: (1) a multi-agent simulation model to represent traffic, heterogeneous user demand, and route choice in a highway network; (2) a flood simulator using future runoff scenarios generated from five global climate models, three representative concentration pathways (RCPs), and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the highway traffic simulation system, and quantifies the flood impact on a highway system based on car following model. This approach is illustrated with a case study of the Chinese highway network. The results show that (i) for different global climate models, the associated flood damage to a highway system is not linearly correlated with the forcing levels of RCPs, or with future years; (ii) floods in different years have variable impacts on regional connectivity; and (iii) extreme flood impacts can cause huge damages in highway networks; that is, in 2030, the estimated 84.5% of routes between provinces cannot be completed when the highway system is disturbed by a future major flood. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.

To improve the accuracy of historical cropland data, we reconstructed cropland cover in the northern China’s farming–pastoral zone during the Liao dynasty using historical literature and settlement relics. We first reconstructed the total cropland area using historical household data based on the cropland area per household. Next, we allocated the cropland area into 5′ grid cells weighted by settlement density to generate a cropland data. Our main findings were as follows: (1) Data on settlement relics enabled not only the identification of ancient farming areas but also the allocation of cropland cover within high resolution grids in the study area. (2) In the flourishing period of the Liao dynasty, the total cropland area was 0.39 × 104 km2. The cropland grids comprised 28.30% of the total grids, with average and maximum values of cropland fractions of 6.61% and 31.18%, respectively. (3) Compared with our result, we found that the PJ overestimate the cropland area of the study area in 1100 AD, whereas the HYDE 3.2 underestimate it. The area of anthropogenic land use in KK 10 was larger than the cropland area in this study too. None of the three global datasets revealed the mosaic spatial distribution pattern of cropland cover in this study area. (4) The orders of land suitability for cultivation during the Liao dynasty and the present period were almost the identical, even in the farming–pastoral zone of northern China, which has fragile ecological environment.