地形对漫川漫岗黑土区大豆产量的影响

为研究黑土区田块尺度地形对大豆产量造成的影响,在海伦东兴合作社具有明显地形起伏的地块,采集大豆田间试验数据,考虑温度、太阳辐射、坡度、土壤养分等因素,运用作物生长模型DSSAT(Decision Support Systemfor Agrotechnology Transfer)模型对各样点进行参数率定及验证,得出以下结论:1)DSSAT模型的模拟产量与实际产量的相对均方根误差为7.9%,模拟结果表现为优,表明运用作物模型模拟不同地形上的产量变异具有可行性;2)地形通过影响作物生长环境因子的时空差异决定产量差异,田块尺度温度、水分和坡度是影响产量差异的主要因素;3)坡顶和坡底的产量相对较高,且产量变异性较小,阳坡虽然接收到更多的光照,却由于水分胁迫造成减产,坡底和平缓坡顶水肥保持较好,易获得高产。研究成果为田间精细管理与田块尺度耕地高效利用提供科学依据。

Effects of terrain on soybean yields in rolling hilly black soil areas

Soybean is widely cultivated in farmlands with irregular terrain in the northeast China. In this study, the influence of terrain on crop yield was investigated. Dongxing Cooperative of Hailun city in Heilongjiang Province was selected as the area of research. The study area was 10.20 hm2. The iRTK data were measured and utilized to produce the Digital Elevation Model (DEM) used for division of the sampling points'' slope position. The soil data and daily meteorological data were obtained. The soybean yield data along with the field management data at every sampling point during the growing season of soybean were also determined. The decision support system for agrotechnology transfer (DSSAT) model was used to simulate the soybean growth and development process. Seven sampling points with distinct terrain features were randomly selected from sixteen sampling points, and the data from the other sampling points were used for verification of the DSSAT model. Then the adjusted DSSAT model was used to simulate the development of soybean at each sampling point and its yield. In regards to temperature, slope, solar radiation, soil nutrients, etc., DSSAT model was put into use for yield results simulation under the condition of single factor discrepancy, and then the contribution degree of individual factor to the yield difference was examined. Data such as biomass, soil water content and soil alkali-hydrolyzed nitrogen content of each sampling point were collected during the soybean growth period, and the total solar radiation data of the study area was generated by DEM combined with the Angstrom equation. The results showed that the normalized root mean square error(nRMSE) for the simulated yield of the DSSAT model and the measured yield was 7.9%, indicating an excellent simulation. The nRMSE for leaf area index (LAI) and above-ground biomass simulation were 16.2% and 18.7%, respectively. It indicated that the DSSAT model was reliable for simulation of soybean yield, biomass and growth. The growing environment of soybean was affected by the terrain, which determined the spatial change of soybean yield. In comparison with the initial soil condition, the difference of soybean yield was more affected by temperature and slope. Compared with the other positions of slope, the soybean yield at the top and bottom of slope was higher and the yield variability was smaller. The water requirement for soybean increased during the pod-filling period of soybean and the soil water content was low in the sunny slope, which resulted in the decrease of yield. The high amount of alkali-hydrolyzed nitrogen content and soil water content were found at the bottom of the slope that could meet the needs of crop growth. Therefore, the appropriate irrigation measures should be taken to improve the soybean yield during this period. The analysis for crop yield gap could reveal the factors that restrict crop production. The outcomes of the research are conducive to the farmland''s fine operation during the precise management and can provide valuable information for field management.