| Future climate change had important impact on agricultural production, and it was mainly negative. Climate change would increase the instability of agricultural production, and yield volatility, agricultural layout and structure changes, increasing agricultural production and investment costs, which Directly related to the national food security, was an issue of common concern to all society. Crop production level was an important standard of regional agricultural development, not only by the impact of technology, variety, but also affected by weather conditions. Climate could provide material, energy foundation and yield formation for the crops growth, and restrained effective implementation of agricultural technologies. The paper based on the main data sources of Songnen Plain, contained daily weather observations of 40 meteorological stations from 1961-2013, and field observations in 4 typical sites. With the P-M formula, Mann-Kendall mutation detection methods and DSSAT model, it was showed evolutional trends of Agricultural climate resources, spatial and temporal distribution of dry and wet conditions, and climatic characteristics of the potential production, to seek effective way to improve productivity in Maize and resource utilization. The main results are as follows:(1) In recent 53 a, the solar radiation showed a significant downward trend in spring maize growing season and whole year, and growing season was about 71.9% of the whole year. Of all four seasons, the largest amount of solar radiation was summer. Solar radiation was significantly decreased in spring, summer and winter, while the fall trends were not significant. Among the 4 Seasons, average and minimum temperature increased significantly, and the biggest was winter. The maximum temperature in summer, growing season and the whole year were significantly increased. Minimum temperature warming rate is about 2 times of the maximum. Maximum and minimum temperature performance asymmetry variation. Minimum changed greater than maximum, contributed to the average temperature rising. Spring corn growing season precipitation accounted for about 84.9 percent of the whole year. The annual precipitation declining rates were 2.82, 1.82 and 1.95 times of spring, autumn and growing season, which showed trends of warming and drying. Of 4 seasons, maximum potential evapotranspiration was in summer, while minimum in winter. Spring corn growing season evapotranspiration accounted for about 81.7% of the whole year. By Mann-Kendall nonparametric test, in spring, summer, growing season as well as full year, solar radiation occurred mutations from more to less in 1980/1981. The annual average and minimum temperature mutated earlier than the maximum. In the scale of 4 seasons, growing seasons and whole year, solar radiation, temperature and potential evapotranspiration trends showed gradually decreasing from southwest to northeast, while precipitation trends gradual increased from southwest to northeast.(2) From yearly scale, the relative humidity index(M) showed a significant decreasing trend. The arid range over mild-drought expanded. From seasonal scale, spring and autumn showed a significant decreasing trend. In drought intensified speed,autumn was greater than spring, and was to expand in the scope. However, M showed a significant increasing trend in winter, which indicated mitigation and reduction of drought. Mann-Kendall test results showed in yearly scale, M mutations occurred in 1979/1980 from high to low. After the mutation year, the degree of drought intensified. Seasonal M showed increasing trend from southwest to northeast, presented trend of drought mitigation from southwest to northeast. And Drought stations proportion yearly also showed decreasing trend from southwest to northeast. Southwestern region was the overlap region of severe and high frequency of drought. Changes of M in yearly scale were significantly related to precipitation, wind speed and air temperature. Secondly, the relative moisture showed strong correlation with the changes of precipitation, solar radiation and relative humidity seasonally. In spring corn growing season, the changes of M was significantly decreasing, and drought was in the increasing trend. And arid range was significant incremental. M negatively correlated with air temperature and solar radiation,while positive correlated with relative humidity, wind speed and precipitation. The annual variability of M was most relevant with precipitation, followed by relative humidity, temperature and solar radiation, while wind speed of less relevance. The spatial distribution of M showed increasing trend from southwest to northeast, presented trend of drought mitigation. Drought stations proportion yearly from southwest to northeast presented a decreasing trend, especially in heavy arid regions, the Drought stations proportion ran above 94%. From the growing season, special drought further exacerbated in Baicheng. The trend of mid-drought in Shuangliao and light-drought in Harbin aggravated. Mingshui didn’t change significantly on time sequence. In whole growth season and tasseling-maturity stage, M was decreasing with relative humidity in Harbin and Baicheng, showed trend of increasing drought. In Sowing-jointing stage and growth season, M had a significant negative correlation with the average temperature in Baicheng and Mingshui, and drought aggravated with increasing temperature. M was negatively correlated with solar radiation in whole growth period in Harbin and Mingshui, and the drought presented alleviated trend.(3) Photothermal potential productivity(PPP) and climatic potential productivity(CPP) of spring corn fluctuated heavily, and PPP exhibited a significant increase in the trend, linear trend is 7.03 kg·mu-1·a-1, while CPP in the time-series was not obvious. PPP decreased from southwest to northeast, which had similar spatial characteristics with average temperature of Songnen Plain. CPP was increased from northwest to southeast, with similar spatial pattern of precipitation. CPP were significantly positive correlation with longitude, while negative with latitude respectively. With the increase of longitude and latitude 1° in Songnen Plain, CPP increased 20.6 kg·mu-1 and reduced 28.9 kg·mu-1. And it was significantly positively correlated with precipitation in space. The precipitation for each additional 1mm, CPP increased 0.54 kg?mu-1 averagely. Meanwhile, the average temperature had significant positive correlation with CPP. Between the average temperature for each additional 1℃, CPP increased 21.6 kg?mu-1 averagely. It also has a significant positive correlation with M in space. Between the distribution of M increasing by 0.1, the average of CPP increased 251.9 kg·mu-1.(4) Base on the analysis of water demand and Rainfall in Songnen Plain,in the whole growth stages, Baicheng had the highest average water demand. In sowing-jointing, jointing-heading and heading-maturity stages, Mingshui, Harbin and shuangliao had highest water demand. And only sowing-jointing stage, Harbin presented a significant decreasing trend. In whole growth seasons, average rainfall in Baicheng was the highest. In sowing-jointing stage, four sites presented water deficit, the largest was Baicheng. While in heading-maturation stage, Baicheng, Mingshui, Shuangliao appeared water deficit. Water deficit tends in Harbin was to slow down in sowing-jointing stage. Water deficit intensified in Baicheng and shuangliao of heading-maturity stage. Harbin and shuangliao were the highest average yield potential, followed by the Baicheng, the lowest was Mingshui. Harbin potential yield had significantly increased trends in recent 30 a, others weren’t obvious. Potential yield of Harbin, Mingshui and Shuangliao was significantly positively correlated with average temperature in whole growth seasons. The potential yield increase with average temperature. Potential yield strong correlated with precipitation breakeven of Shuangliao in jointing-heading and heading-maturity stages.Crop yield formation was a complex process, not only related to the meteorological elements, but also to the crop varieties, human management and other factors. It ascertained background and climate resources constraints on Songnen Plain. Furthermore, based on the classical methods and model simulations, the effects of non-climatic factors affecting crop yield potential mechanisms were studied, in order to making basis and technical support for climate change, sustainable production of maize and agriculture regional development in the future of Songnen Plain. |
PDF Full Text Request