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Formulating suitable policies is essential for resources and environmental management. In this study, an agricultural pollutants emission trading management model driven by water resources and pollutants control is developed to search reasonable policies for agricultural water resources allocation under multiple uncertainties. Random-fuzzy and interval information in water resources system that have directly impact on the effectiveness of management schemes is reflected through interval two-stage stochastic fuzzy-probability programming. The model was root from regional agricultural water resources system in Jining City, China under considering the relationship among effective precipitation, crop water demand, and pollutants emission. Two types policies (water consumption-control and pollutants emission-control) are designed for searching the related interaction on water resources management and water quality improvement. The results indicated that water resources policies would be of water and environmental double benefits, and a large rainfall would reduce irrigation amount from water sources and lead to a larger pollutants emission trading. The results will help for defining scientific and effective water resources protection and management policies and analyzing the related interacted effects on water consumption, pollutants control and system benefit., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

With rapid economic growth and urbanization, self-sufficiency in crop production has become central to China's agriculture policy. Accurate crop production statistics are essential for research, monitoring, and planning. Although researchers agree that China's statistical authority has considerably modernized over time, China's economic statistics have still been viewed as unreliable and often overstated to meet growth targets at different administrative levels. Recent increases in crop production reported by national statistics have also come under increasing scrutiny. This paper investigates crop production data quality from a planetary boundary perspective-comparing net primary production (NPP) harvested obtained from national statistics with satellite-driven NPP estimates that are supported by detailed observation of land cover, combined with observations on physical factors that limit plant growth. This approach provides a powerful means to check the plausibility of China's grain production statistics at different administrative levels that can generate insights about their discrepancies and can contribute to improved crop production measurements. We find some evidence of potential misreporting problems from the lower administration level where the risk of manipulation of statistics is higher. We also find problems from provincial-level major grain producers. These values can also affect the national totals. Although the numbers are affected by large uncertainties, we find that improving the spatial resolution of key agricultural parameters can greatly improve the reliability of the indicator that in turn can help improve data quality. More reliable production data will be vital for relevant research and provide better insights into food security problems, the carbon cycle, and sustainable development., Competing Interests: The authors declare no competing interest.

• Probability of slight drought was higher than moderate drought. • Range of single probability of slight drought was 26.15 to 41.06% • Range of joint probability of droughts in moderately was 3.76 to 31.32% Documenting the joint probability of meteorological-hydrological, meteorological-agricultural, and hydrological-agricultural drought can be invaluable for understanding drought evolution under climate change in a high-diversity watershed of south China. Through constructing the edge and joint distribution functions of multi drought indices (SPEI, SPI, SSI, and SWI) based on SWAT and copula methods, we explored the evolution of multi droughts under climate change in the East River basin. During 1997–2017 and 2023–2099, we used logistic, generalized pareto, and normal distributions to construct edge distribution functions of SPEI, SPI, SWI, and SSI. For the four indices, the probability of slight drought increased with rcp2.6, 4.5, 6.0, and 8.5, and it was higher than moderate drought. Also, Clayton, Frank, Gumbel, and Gaussian copula functions were used to construct joint distribution functions of SPEI and SSI, SPEI and SWI, SSI and SWI to quantify their interactions. During 1997–2017, the probability of slight drought was 26.15 to 41.06 %, and the return period changed from 3.8 to 2.4 years. The joint probability of meteorological-hydrological, meteorological-agricultural, and hydrological-agricultural drought in slightly was 24.4 to 31.32 %, 14.95 to 22.63 %, and 6.18 to 22.05 %, respectively. During 2023–2099, the joint probability of droughts in moderately was 3.76 to 14.19 %, and the return period was 7 to 26.6 years. Our results provide a quantitative assessment of single and joint probability of meteorological, hydrological and agricultural drought, which could be used to support watershed water resource management. [ABSTRACT FROM AUTHOR]

An enhanced radial interval programming approach was developed for supporting the identification of sound agricultural production plans. It was designed to tackle dual uncertainties in both the economic and environmental subsystems as well as reflect differential aspiration levels for 'immunity' against such uncertainty. By adding protection functions to both the objective functions and constraints susceptible to dual uncertainties without any distributions, it improved upon previous methods through simultaneously measuring and manipulating expected return risk and resource-environmental compliance risk. Moreover, this study made novel attempts to explore system-wide optimal levels of robustness based on proposed performance evaluation criteria and investigations over the interactive effects of varied robustness aspirations for different model components. Based on analyzed tradeoffs among system optimality, robustness and uncertainty degree of solutions pertaining to the study case, a unified protection level of 13 (or 10) was recommended for risk-averse (or risk-neutral) decision making. The model outputs were compared to those from three alternatives, revealing that it could achieve a high level of system reliability at a minor price of economic return. This approach could be generalized for wide-scale applications. [ABSTRACT FROM AUTHOR]

In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation. [ABSTRACT FROM AUTHOR]

Multiple correlated risks caused by uncertain information pose great challenges to the coordinated regulation of water-energy-food nexus (WEFN). In this study, a Copula-based radial interval chance-constrained programming (CRICP) was developed. CRICP can not only quantify composite risk induced by multiple risks with nonlinear correlations, but also tackle dual uncertainty expressed as redial intervals with adjustable protection levels. CRICP was applied to an irrigated agricultural management problem constrained by water, energy, and land resource in Bayan Nur City in northern China. Results indicate that system benefit would increase with the incline of composite risk or the decline of protection level. Monte Carlo simulation verified that the different definitions of composite risk could lead to significant differences in the combination of subsystem risks. The composite risk induced by the simultaneous shortage of multiple resources would have greater impacts on system benefits compared against composite risk caused by shortage of at least one resources, with an increase of [24.65%, 25.95%] in the minimum value of system benefits. Comparisons against two alternative models further verified that CRICP outweighs previous methods by modeling the correlation structure of multiple risks and tackling dual uncertainties without distribution information. • The complex interactions and inherent uncertainty affect the security of Water-Energy-Food Nexus. • A Copula-based radial interval chance-constrained programming method was developed. • It can tackle composite risk induced by random variables with unknown correlations. • It can also address dual uncertainties without detailed distributions. • The bias in decision making process triggered different composite risks were clarified. [ABSTRACT FROM AUTHOR]