玛纳斯河流域人口、城市化、GDP及产业结构预测情景数据（V1.0）（2010-2050）

未来人口情景预测以2005年为基准年，采用人口阻滞增长模型，不仅能够较好地描述人口与许多生物数量的变化规律，而且在经济领域也有广泛的应用。城市化率的预测采用城市化Logistics模型。依据已有的城市化水平序列值，通过非线性回归求出参数式中参数，建立预测模型。城市人口数量由预测的人口数乘以城镇化率求出。数据采用非农业人口。采用logistic模型预测流域未来各县市国民生产总值，然后根据未来各县市各时段经济发展水平（用人均GDP表示）设定各时段相应的产业结构情景，预测各次产业产值。我国及研究区产业结构的变化趋势滞后于GDP增长速度，因而根据设定的研究区未来产业结构情景需要进行了适当调整。

Future population scenario forecasting takes 2005 as the baseline year, utilizing the population logistic growth model. This model not only effectively characterizes the variation laws of population and the quantities of numerous other organisms, but also enjoys wide applications in the economic domain. Urbanization rate forecasting employs the urbanization logistic model. Based on the existing time series of urbanization level data, the parameters in the model are estimated through nonlinear regression, and a forecasting model is thus constructed. The urban population size is derived by multiplying the forecasted total population by the urbanization rate, with non-agricultural population data being adopted here. The logistic model is applied to forecast the gross national product (GNP) of each county and city within the study watershed for future periods. Subsequently, corresponding industrial structure scenarios for each time interval are formulated based on the economic development levels (expressed as per capita GDP) of each county and city in each future period, and the output values of the primary, secondary and tertiary industries are forecasted accordingly. The change trend of industrial structure in China and the study area lags behind the growth rate of GDP, so appropriate adjustments are made in accordance with the preset future industrial structure scenarios of the study area.