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Controlling non-point source pollution is often difficult and costly. Therefore, focusing on areas that contribute the most, so-called critical source areas (CSAs), can have economic and ecological benefits. CSAs are often determined using a modelling approach, yet it has proved difficult to calibrate the models in regions with limited data availability. Since identifying CSAs is based on the relative contributions of sub-basins to the total load, it has been suggested that uncalibrated models could be used to identify CSAs to overcome data scarcity issues. Here, we use the SWAT model to study the extent to which an uncalibrated model can be applied to determine CSAs. We classify and rank sub-basins to identify CSAs for sediment, total nitrogen (TN), and total phosphorus (TP) in the Fengyu River Watershed (China) with and without model calibration. The results show high similarity (81%–93%) between the identified sediment and TP CSA number and locations before and after calibration both on the yearly and seasonal scale. For TN alone, the results show moderate similarity on the yearly scale (73%). This may be because, in our study area, TN is determined more by groundwater flow after calibration than by surface water flow. We conclude that CSA identification with the uncalibrated model for TP is always good because its CSA number and locations changed least, and for sediment, it is generally satisfactory. The use of the uncalibrated model for TN is acceptable, as its CSA locations did not change after calibration; however, the TN CSA number changed by over 60% compared to the figures before calibration on both yearly and seasonal scales. Therefore, we advise using an uncalibrated model to identify CSAs for TN only if water yield composition changes are expected to be limited. This study shows that CSAs can be identified based on relative loading estimates with uncalibrated models in data-deficient regions.

This study conducted the global sensitivity analysis of the APSIM-Oryza rice growth model under eight climate conditions and two CO2 levels using the extended Fourier Amplitude Sensitivity Test method. Two output variables (i.e. total aboveground dry matter WAGT and dry weight of storage organs WSO) and twenty parameters were analyzed. The ±30% and ±50% perturbations of base values were used as the ranges of parameter variation, and local fertilization and irrigation managements were considered. Results showed that the influential parameters were the same under different environmental conditions, but their orders were often different. Climate conditions had obvious influence on the sensitivity index of several parameters (e.g. RGRLMX, WGRMX and SPGF). In particular, the sensitivity index of RGRLMX was larger under cold climate than under warm climate. Differences also exist for parameter sensitivity of early and late rice in the same site. The CO2 concentration did not have much influence on the results of sensitivity analysis. The range of parameter variation affected the stability of sensitivity analysis results, but the main conclusions were consistent between the results obtained from the ±30% perturbation and those obtained the ±50% perturbation in this study. Compared with existing studies, our study performed the sensitivity analysis of APSIM-Oryza under more environmental conditions, thereby providing more comprehensive insights into the model and its parameters.

This study conducted the global sensitivity analysis of the APSIM-Oryza rice growth model under eight climate conditions and two CO2 levels using the extended Fourier Amplitude Sensitivity Test method. Two output variables (i.e. total aboveground dry matter WAGT and dry weight of storage organs WSO) and twenty parameters were analyzed. The ±30% and ±50% perturbations of base values were used as the ranges of parameter variation, and local fertilization and irrigation managements were considered. Results showed that the influential parameters were the same under different environmental conditions, but their orders were often different. Climate conditions had obvious influence on the sensitivity index of several parameters (e.g. RGRLMX, WGRMX and SPGF). In particular, the sensitivity index of RGRLMX was larger under cold climate than under warm climate. Differences also exist for parameter sensitivity of early and late rice in the same site. The CO2 concentration did not have much influence on the results of sensitivity analysis. The range of parameter variation affected the stability of sensitivity analysis results, but the main conclusions were consistent between the results obtained from the ±30% perturbation and those obtained the ±50% perturbation in this study. Compared with existing studies, our study performed the sensitivity analysis of APSIM-Oryza under more environmental conditions, thereby providing more comprehensive insights into the model and its parameters.

Quantifying temporal and spatial variation of soil phosphorus (P) input, output and balance across Chinese arable land is necessary for better P management strategies. Here, we address this challenge using a soil P budget to analyse the soil P balance in arable land across the whole of China, for the period 1980–2012. Results indicated that the total P input to soil increased from 22.5 kg P/ha in 1980 to 79.1 kg P/ha in 2012. However, the total P output from soil only increased from 17.9 kg P/ha in 1980 to 36.9 kg P/ha in 2012. Therefore, the average net soil P surplus in China increased from 4.6 kg P/ha in 1980 to 42.1 kg P/ha in 2012. Our research found great variation in soil P balances across different regions. Soil P balance varied between regions with the order of southeast (SE) > north central (NC) and the middle and lower reaches of Yangtze River (MLYR) > southwest (SW) > northwest (NW) > northeast (NE). Phosphorus that has accumulated in agricultural soil across China could theoretically meet crop P demands for approximately 4.8–12.0 yrs, depending on the bioavailability of P stored in soils. Increasing the return rates of manure and straw could substantially reduce the demand for fertilizer-P. This paper represents a basis for more targeted, regionally informed P fertiliser recommendations in Chinese soils.

Intercropping is regarded as an important agricultural practice to improve crop production and environmental quality in the regions with intensive agricultural production, e.g., northern China. To optimize agronomic advantage of maize (Zea mays L.) and soybean (Glycine max L.) intercropping system compared to monoculture of maize, two sequential experiments were conducted. Experiment 1 was to screening the optimal cropping system in summer that had the highest yields and economic benefits, and Experiment 2 was to identify the optimum row ratio of the intercrops selected from Experiment 1. Results of Experiment 1 showed that maize intercropping with soybean (maize ∥ soybean) was the optimal cropping system in summer. Compared to conventional monoculture of maize, maize ∥ soybean had significant advantage in yield, economy, land utilization ratio and reducing soil nitrate nitrogen (N) accumulation, as well as better residual effect on the subsequent wheat (Triticum aestivum L.) crop. Experiment 2 showed that intercropping systems reduced use of N fertilizer per unit land area and increased relative biomass of intercropped maize, due to promoted photosynthetic efficiency of border rows and N utilization during symbiotic period. Intercropping advantage began to emerge at tasseling stage after N topdressing for maize. Among all treatments with different row ratios, alternating four maize rows with six soybean rows (4M:6S) had the largest land equivalent ratio (1.30), total N accumulation in crops (258 kg ha-1), and economic benefit (3,408 USD ha-1). Compared to maize monoculture, 4M:6S had significantly lower nitrate-N accumulation in soil both after harvest of maize and after harvest of the subsequent wheat, but it did not decrease yield of wheat. The most important advantage of 4M:6S was to increase biomass of intercropped maize and soybean, which further led to the increase of total N accumulation by crops as well as economic benefit. In conclusion, alternating four m

Intercropping is regarded as an important agricultural practice to improve crop production and environmental quality in the regions with intensive agricultural production, e.g., northern China. To optimize agronomic advantage of maize (Zea mays L.) and soybean (Glycine max L.) intercropping system compared to monoculture of maize, two sequential experiments were conducted. Experiment 1 was to screening the optimal cropping system in summer that had the highest yields and economic benefits, and Experiment 2 was to identify the optimum row ratio of the intercrops selected from Experiment 1. Results of Experiment 1 showed that maize intercropping with soybean (maize ∥ soybean) was the optimal cropping system in summer. Compared to conventional monoculture of maize, maize ∥ soybean had significant advantage in yield, economy, land utilization ratio and reducing soil nitrate nitrogen (N) accumulation, as well as better residual effect on the subsequent wheat (Triticum aestivum L.) crop. Experiment 2 showed that intercropping systems reduced use of N fertilizer per unit land area and increased relative biomass of intercropped maize, due to promoted photosynthetic efficiency of border rows and N utilization during symbiotic period. Intercropping advantage began to emerge at tasseling stage after N topdressing for maize. Among all treatments with different row ratios, alternating four maize rows with six soybean rows (4M:6S) had the largest land equivalent ratio (1.30), total N accumulation in crops (258 kg ha-1), and economic benefit (3,408 USD ha-1). Compared to maize monoculture, 4M:6S had significantly lower nitrate-N accumulation in soil both after harvest of maize and after harvest of the subsequent wheat, but it did not decrease yield of wheat. The most important advantage of 4M:6S was to increase biomass of intercropped maize and soybean, which further led to the increase of total N accumulation by crops as well as economic benefit. In conclusion, alternating four m

Intercropping is regarded as an important agricultural practice to improve crop production and environmental quality in the regions with intensive agricultural production, e.g., northern China. To optimize agronomic advantage of maize (Zea mays L.) and soybean (Glycine max L.) intercropping system compared to monoculture of maize, two sequential experiments were conducted. Experiment 1 was to screening the optimal cropping system in summer that had the highest yields and economic benefits, and Experiment 2 was to identify the optimum row ratio of the intercrops selected from Experiment 1. Results of Experiment 1 showed that maize intercropping with soybean (maize ∥ soybean) was the optimal cropping system in summer. Compared to conventional monoculture of maize, maize ∥ soybean had significant advantage in yield, economy, land utilization ratio and reducing soil nitrate nitrogen (N) accumulation, as well as better residual effect on the subsequent wheat (Triticum aestivum L.) crop. Experiment 2 showed that intercropping systems reduced use of N fertilizer per unit land area and increased relative biomass of intercropped maize, due to promoted photosynthetic efficiency of border rows and N utilization during symbiotic period. Intercropping advantage began to emerge at tasseling stage after N topdressing for maize. Among all treatments with different row ratios, alternating four maize rows with six soybean rows (4M:6S) had the largest land equivalent ratio (1.30), total N accumulation in crops (258 kg ha-1), and economic benefit (3,408 USD ha-1). Compared to maize monoculture, 4M:6S had significantly lower nitrate-N accumulation in soil both after harvest of maize and after harvest of the subsequent wheat, but it did not decrease yield of wheat. The most important advantage of 4M:6S was to increase biomass of intercropped maize and soybean, which further led to the increase of total N accumulation by crops as well as economic benefit. In conclusion, alternating four m