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As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei (BTH) region is the most prominent area in China where the imbalance between the supply and demand of water resources restricts the sustainable and healthy development of the regional social economy. In the context of global warming, research into water demand prediction that takes climate change into consideration would be more in line with the strategic goal of the low-carbon sustainable development of future cities. At the same time, the prediction of agricultural water demands against a background of climate change is urgently needed, while industrial water consumption is weakly correlated with climate change, an investigation of the statistical relationship between the two is needed. Thus, in this paper, future climate data from the BTH region under the scenarios RCP2.6, RCP4.5 and RCP8.5 were generated using a statistical downscaling model, and then coupled with agricultural and industrial water demand prediction models to simulate and analyze the impact of climate change on the agricultural and industrial water demands, respectively. The results show that during the forecast period (2020–2035), the reference crop evapotranspiration (ET0) growth rates in the Beijing, Tianjin and Hebei areas under the RCP2.6 scenario are 1.438 mm·a−1, 1.393 mm·a−1 and 2.059 mm·a−1, respectively. Under the RCP4.5 scenario, they are 2.252 mm·a−1, 2.310 mm·a−1 and 2.827 mm·a−1, respectively. Under the RCP8.5 scenario, they are 3.123 mm·a−1, 2.310 mm·a−1 and 2.141 mm·a−1, respectively. Furthermore, under each climate scenario, the increase in evapotranspiration in the Hebei area is the largest, followed by that in the Tianjin area, and that in the Beijing area is the smallest. For water consumption per CNY 10,000 of industrial added value during the forecast period, under the three different climate scenarios, a downward trend is seen in the Beijing area, with rates of 0.158, 0.153 and 0.110, respectively, but in the Tianjin area, there is an upward trend, with an upward tendency in rates of 0.170, 0.087 and 0.071, and an upward trend in the Hebei area, with an upward tendency in rates of 0.254, 0.071 and 0.036, respectively. This study will help the BTH region to rationally allocate agricultural and industrial water against the background of future climate change, and strengthen the coordination and cooperation between the different regions to promote the healthy and sustainable development of the cities. [ABSTRACT FROM AUTHOR]

The agricultural sector is extremely vulnerable to climate change and also plays a very important role in the operation of the entire economic system, leading many studies to evaluate the possible agricultural direct economic damage (ADED) of climate change. However, this damage may have an amplification impact through the intricate industrial linkages that exist among sectors, and this impact may be even greater than the original damage. Therefore, to elucidate the economic cascading effect (ECE) in China caused by ADED and industrial linkage, this paper used the ARIO model to evaluate the total ECE and analyse the differences in the 19 sectors by taking the ADED under future annual mean temperature (AMT) increases of 1–5 °C as the input condition and adjusting the exogenous parameters to enhance the adaptability of the model; the goal was to assess the economic impact of climate change in China. The results show that (i) there is a significant amplifying impact of ECE due to industrial linkage under the influence of warming, ECE will be 4.24–5.25 times that of ADED, and the total economic impact (ADED + ECE) will exceed the GDP of the Chinese capital of Beijing in 2012 when the AMT increases by 1.5 °C, while it will exceed one tenth of China's GDP when it increases by 4 °C. (ii) Manufacturing will be the sector most affected by the industrial linkage under ADED, which accounts for 26.58% of total ECE, followed by agriculture (10.39%) and construction (8.5%). (iii) The decrease in cultivated land area will have a significant impact on the economy; when it is reduced to the minimum demand (1.41% less than 2012), ADED increases by 1.65 times and ECE increases by 2.35 times. This paper aims to provide a new perspective from which to evaluate the economic impact of climate change by studying ECEs behind sectoral interactions. [ABSTRACT FROM AUTHOR]