中国灌区水分生产率及其时空差异分析

    Analysis on temporal and spatial differences of water productivity in irrigation districts in China

    • 摘要: 从粮食产出和广义水资源投入出发,计算了31个省区灌溉农田的水分生产率并分析其时空变化特征,同时建立广义水利用系数以评价水资源的有效利用率。结果显示:由于粮食单产提高和灌溉用水量的减少,1998-2010年各省区水分生产率值均呈增大趋势,全国平均值由0.67 kg/m3增大到0.81 kg/m3;空间自相关分析表明,水分生产率值相似的省区在空间上显著地聚集,全局Moran's I的检验值都大于0.01 的置信水平,高值省区以黄淮海平原为核心集中分布,长江以南和东北则密集了低值省区,局部自相关属性为高-高(HH)、低-低(LL)的省区超过了20个,13 a来总体和局部的空间分异特征随时间变化均不明显;不同地区的广义水利用系数都随时间增加,省区间水分生产率和广义水利用系数大小关系无一致性,水分生产率高的省区亦存在较大节水潜力。从自然条件、农业生产特征、经济发展程度等方面宏观分析了水分生产率和广义水利用系数在空间差异的原因。该研究为灌区水资源管理宏观政策的制定提供依据。

       

      Abstract: Based on grain output and generalized water resources input, water productivity and utilization factor of generalized water in irrigation districts of 31 provinces were counted and it's spatial and temporal differences were analyzed. The results showed that water productivity of every province presented an increasing trend, and national average water productivity increased from 0.67 kg/m3 to 0.81 kg/m3from 1998 to 2010. Spatial autocorrelation analysis results showed provinces with resemble water productivity value showed significant aggregation, and Moran's I inspection values were higher than confidence level (0.01). Distributions of provinces with high water productivity value were centered with Huang-Huai-Hai plain, and provinces with lower water productivity values were distributed in South and Northeast China. Local autocorrelation analysis revealed that more than 20 provinces showed high-high positive autocorrelation(HH) and low-low positive autocorrelation(LL), general and regional spatial differentiation characteristics in 1998-2010 was insignificant. Generalized water use coefficient of different province increased, and there were no consistency on relations between water productivity and water use coefficient in different provinces, there were still great water saving potential in provinces with high water productivity value, and reasons of spatial differences for water productivity and generalized water utilization factor were analyzed from natural conditions, agricultural production features, economic development levels, etc. This research provides references for making macro policies of water resources management in irrigation districts.

       

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