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The Beijing-Tianjin-Hebei region (BTH region) is a major crop-producing region of China suffering from environment deterioration. Land fallowing policy is widely used as the solution of agriculture-related environment pollution, while it is difficult to derive a quantitative basis for policy-making. An indicator system was established to quantitatively analyse economic and environmental benefits of land fallow policies in the BTH region. The system consisted of 8 indicators to describe the water, air and economic influences caused by land fallowing policy such as the amount of nutrient discharged, the emission of PM 2.5 -related and greenhouse gas, and the input and output of agriculture production. SWAT (Soil and Water Assessment Tool) and IAP-N (Improving Anthropogenic Practices of managing reactive Nitrogen) models were used to quantify environmental indicators. Five scenarios with different planting patterns and fallow intensities were simulated for five years with different hydrological conditions. It is found that the influence of policy on water environment is highly sensitive to hydrological conditions, while the influence on air environment and economy are more affected by different policy settings in scenarios. The marginal utilities of the fallowed area are indicator-dependent. Planting alternative crops can decrease production costs and keep crop yields, while may also cause atmospheric environmental pollution if the crops have nitrogen fixing ability. Indicators also have spatial and temporal heterogeneity under different planting patterns and fallow intensities. A policy evaluation and associated uncertainty analysis is essential for effective implementation. The analysis framework established could support decision-making in regions facing agri-environmental problems., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The upper catchment of the Miyun reservoir is an important drinking water source in Beijing. In recent years, researchers have used the soil conservation service curve number (SCS-CN) model to calculate surface runoff for the district. Although the runoff forecasting accuracy was unsatisfactory, the lack of understanding of rainfall processes and their influence on runoff may explain the observed deviations. Our study sought to optimize and assess the SCS-CN model simulation accuracy for the district by proposing an SCS-CN calculation method for each runoff event (CN t ) based on observation data for 253 rainfall and runoff events from 7 plots in the Miyun Shixia watershed. This study elucidated a significant positive correlation between the ratio of CN t and the average SCS-CN (CN 1 ), as well as the ratio of the maximum X-minute rainfall amount (P X ) to the total rainfall amount for each rainfall event (P). Furthermore, a calculation method involving power function equations between CN t /CN 1 and P X /P was proposed for CN t . When X = 5 min and the initial abstraction ratio (λ) = 0.01, the simulation performance of the optimized model was the highest, with a Nash-Sutcliffe efficiency coefficient of 0.791, which was significantly higher than that of the non-optimized SCS-CN model. The simulation performance for bare and cultivated land was higher than that of other land uses, with E f values of 0.831 and 0.828, respectively. Future research should focus on improving the prediction accuracy of runoff events resulting from high-intensity and short-duration rainfall events.