The Agricultural Policy/Environmental eXtender (APEX) model has five different interfaces used to process and build simulation projects. These interfaces utilize different input databases that lead to different model ...The Agricultural Policy/Environmental eXtender (APEX) model has five different interfaces used to process and build simulation projects. These interfaces utilize different input databases that lead to different model default values. These values can result in different hydrologic, crop growth, and nutrient flow model outputs. This study compared structural and input value differences of the ArcAPEX and Nutrient Tracking Tool (NTT) interfaces. Long-term, water quality data from the Rock Creek watershed, located in Ohio were used to determine the impact of the differences on computation time, parameter sensitivity, and streamflow, total nitrogen (TN), and total phosphorus (TP) simulation performance. The input structures were the same for both interfaces for all files except soils, where NTT assigns three soil files per field, rather than a single one in ArcAPEX. As a result, computation times were three times as long for NTT as for ArcAPEX. There were twelve sensitive parameters in both cases, but the order of sensitivity was different. Both interfaces simulated streamflow well, but ARCAPEX simulated evapotranspiration, TN, and TP better than NTT, while NTT simulated crop yields better than ArcAPEX. However, none of the models met all of the performance criteria for either interface. Therefore, more work is needed to ensure models are properly calibrated before being used for scenario analysis. While it is acceptable for the values to be different from the SSURGO database, there is no documentation explaining the rationale for the modifications from the original source. This is one of the examples that highlights lack of detailed documentation that would be useful to model users. Overall, the results indicate that different interfaces lead to different model simulation results and, therefore, the authors recommend users specify the interface used and any modifications made to the associated databases when reporting model results.展开更多
论文以内蒙古沙漠化地区为例,运用Bioe-conom ic M odel,比较自由放牧与耕垦、禁牧与禁垦、控制放牧规模与禁垦的土地利用政策情景下,引进舍饲养牛技术与信贷服务和增加非农就业机会对农户土地利用决策及其家庭收入的影响,据此探讨中国...论文以内蒙古沙漠化地区为例,运用Bioe-conom ic M odel,比较自由放牧与耕垦、禁牧与禁垦、控制放牧规模与禁垦的土地利用政策情景下,引进舍饲养牛技术与信贷服务和增加非农就业机会对农户土地利用决策及其家庭收入的影响,据此探讨中国北方地区沙漠化发展的人文驱动机制以及生态重建的环境政策。结果表明:实施控制放牧规模与禁垦的环境政策,同时引进舍饲养牛技术能够有效地促进生态重建并提高农户收入;引进舍饲养牛技术需要启动基金,提供信贷服务和增加非农就业机会是贫困农户引进该技术的前提。因此,迫切需要调整宏观环境政策,提高农业集约化经营水平和城乡联系力度,从而提高农户家庭收入、减轻农民对环境的依赖性和促进农村的可持续发展。展开更多
文摘The Agricultural Policy/Environmental eXtender (APEX) model has five different interfaces used to process and build simulation projects. These interfaces utilize different input databases that lead to different model default values. These values can result in different hydrologic, crop growth, and nutrient flow model outputs. This study compared structural and input value differences of the ArcAPEX and Nutrient Tracking Tool (NTT) interfaces. Long-term, water quality data from the Rock Creek watershed, located in Ohio were used to determine the impact of the differences on computation time, parameter sensitivity, and streamflow, total nitrogen (TN), and total phosphorus (TP) simulation performance. The input structures were the same for both interfaces for all files except soils, where NTT assigns three soil files per field, rather than a single one in ArcAPEX. As a result, computation times were three times as long for NTT as for ArcAPEX. There were twelve sensitive parameters in both cases, but the order of sensitivity was different. Both interfaces simulated streamflow well, but ARCAPEX simulated evapotranspiration, TN, and TP better than NTT, while NTT simulated crop yields better than ArcAPEX. However, none of the models met all of the performance criteria for either interface. Therefore, more work is needed to ensure models are properly calibrated before being used for scenario analysis. While it is acceptable for the values to be different from the SSURGO database, there is no documentation explaining the rationale for the modifications from the original source. This is one of the examples that highlights lack of detailed documentation that would be useful to model users. Overall, the results indicate that different interfaces lead to different model simulation results and, therefore, the authors recommend users specify the interface used and any modifications made to the associated databases when reporting model results.
文摘论文以内蒙古沙漠化地区为例,运用Bioe-conom ic M odel,比较自由放牧与耕垦、禁牧与禁垦、控制放牧规模与禁垦的土地利用政策情景下,引进舍饲养牛技术与信贷服务和增加非农就业机会对农户土地利用决策及其家庭收入的影响,据此探讨中国北方地区沙漠化发展的人文驱动机制以及生态重建的环境政策。结果表明:实施控制放牧规模与禁垦的环境政策,同时引进舍饲养牛技术能够有效地促进生态重建并提高农户收入;引进舍饲养牛技术需要启动基金,提供信贷服务和增加非农就业机会是贫困农户引进该技术的前提。因此,迫切需要调整宏观环境政策,提高农业集约化经营水平和城乡联系力度,从而提高农户家庭收入、减轻农民对环境的依赖性和促进农村的可持续发展。
