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[Display omitted] • Parallel computing framework is introduced to upscale agroecosystem model. • The new model well reproduced soil and crop variables in North China Plain. • The optimum irrigation water and fertilizer N demands were estimated. • The model shows a potential value to optimize regional water and N management. Process-based agroecosystem model is difficult to apply at the regional scale due to the complexity of model parameterization and execution efficiency. Thus, developing a regional agroecosystem model is challenging. In this study, a parallel computing framework is introduced to upscale an agroecosystem model (WHCNS model) from field to regional scale by integrating parallel computing, inversing modeling, and spatial calculation. The newly developed model was tested in the North China Plain (NCP) for modeling water consumption, N fate, and crop growth for winter wheat–summer maize rotation system under different water and N management practices. The optimum irrigation water and fertilizer N demands of winter wheat–summer maize system was estimated based on the auto-irrigation and auto-fertilization component in the model. Multisite testing showed that the model well reproduced soil water and N dynamics, crop biomass, LAI, yield, and crop N uptake, with R2 exceeding 0.886. The estimated annual average irrigation water and fertilizer N demands of winter wheat–summer maize rotation system was 395.8 mm and 529.5 kg N ha−1, respectively. Winter wheat was the major consumer of irrigation water and fertilizer N, accounting for 79.2 % and 54.4 % of annual irrigation water and chemical N fertilizer use, respectively. These results suggested that winter wheat was a crop with high water and fertilizer N demand in the NCP. The RegWHCNS model has potential value to assess and optimize regional water and N management for intensive agricultural-production systems. This study can provide as a scientific reference to upscale agroecosystem models from field to region for other agroecosystem models. [ABSTRACT FROM AUTHOR]

The middle basin of Heihe River has witnessed rapid urban growth and excessive agricultural activities during the last two decades, mainly because of its economic development and increasing population pressure. In this study, we aimed to understand the growth dynamics of the region, to forecast its future expansion, and to provide a basis for regional management. We calibrated and validated a SLEUTH model with historical data derived from different sources, which comprised remotely sensed and strategic planning data records from 1995, 2000, 2005, and 2009. Three scenarios based on local regional ecological planning were designed to simulate the spatial pattern of urban growth in different conditions. The first scenario allowed urban expansion without any additional managed growth limitations and the continuation of the actual historical trend. The second scenario was limited based on environmental considerations and managed growth was assumed with moderate protection. The third scenario simulated managed growth with strict protection on wetland reserves and productive agricultural areas in the study area. We consider that the results of these models of growth in the study area obtained under different scenarios are of great potential use to city managers and stakeholders. We also suggest that scale sensitivity and spatial accuracy are among the factors that must be considered in practical applications. We urge future researchers to build on the present study to produce models for similar regions in northwest China. [ABSTRACT FROM AUTHOR]

Abstract: Soil organic carbon (SOC) is an important carbon pool which can ameliorate the increasing concentration of atmospheric carbon dioxide as part of the carbon cycling process. Organic carbon in cropland soils is an active pool which is strongly influenced by anthropogenic activities. SOC in cropland soils accounted for 14.5% of the total organic carbon stock of 89.61Mt C in China. In this study, RothC model was used to simulate the change of SOC in upland soils at 626 original 50km×50km grids under B2 and A2 climate scenarios during the upcoming decades in China. Future climate data under B2 and A2 scenarios were predicted by Providing Regional Climates for Impacts Studies (PRECIS) regional climate model downscaled based on HadCM3. The simulation results showed that SOC will generally decrease during the next decades and the decrease rate of SOC will be higher over time if there is no addition of organic material (e.g. organic manure application or straw return) adopted in China. Simulations got the following results: (i) SOC will decrease in most areas of China, especially in northern China; the increase of SOC only occurred in a few scattered grids in Southwest China and mid-south China. The decrease rate of SOC in northern China was higher than in southern China under either B2 or A2 climate scenarios. (ii) The changing rate of SOC over time under B2 scenario was minor during the early 21st century and quite large during the late 21st century. In contrast, the changing rate of SOC over time under A2 scenario was somewhat constant over time. The percentage decrease (decrease rate divided by its basic value in 1980s) of SOC in northern China was around 5.5%, 12%, and 15% by the year 2020, 2050, and 2080 under B2 and A2 scenarios, while it was about 2.3%, 7.7%, and 10.9% under B2 scenario and 3.3%, 4.5%, and 5.5% under A2 scenario in southern China. (iii) Upland soils would lose organic carbon by 2.7tC/ha, 6.0tC/ha, and 7.8tC/ha at the 0–30cm depth by the year 2020, 2050, and 2080, respectively, under the typical conventional tillage without organic material amendment under B2 scenario in China, which accounted for about 4.2%, 9.3%, and 12.1%, respectively, of the basic SOC of 1980s in the upland soils. SOC would decrease by 2.9tC/ha, 6.8tC/ha, and 8.2tC/ha by the year 2020, 2050, and 2080, respectively, under A2 scenario in China, which accounted for about 4.5%, 10.5%, and 12.7%, respectively, of that in 1980s under the conventional tillage and management practices. (iv) Our simulations of future change in SOC suggest it is the influence of combination by temperature, precipitation, evaporation, and original soil properties together and that the predominant factors and the interaction among these factors will vary in different geographical regions. The limitations and uncertainties of the simulation are also discussed. [Copyright &y& Elsevier]