中国耕地变化及耕地与水资源的匹配研究
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摘要
针对我国水资源分布不均,且耕地数量和结构存在不合理分布的问题,为了探究近年来我国耕地分配模式是否与水资源耦合得当,从时空尺度对我国水土资源不匹配程度进行了分析。在时间尺度上,采用基尼系数法进行分析;在空间尺度上,选择在时间尺度上我国水土不匹配等级最高的2016年为研究年份,以MODIS年蒸散和降水量数据分析水土不匹配等级。并依据省级水土不匹配等级将全国省份划分为三种类型,分类型对耕地数量和结构进行优化讨论。结果表明:2009—2016年我国水土不匹配等级均为差(4级),且不匹配程度略有升高。从全国层面看,我国水土不匹配等级为差(4级),且短缺等级(3级)高于富余等级(2级),水土不匹配的主要原因是水资源短缺。从省级层面看,水土不匹配等级最高的是新疆维吾尔自治区,水资源不足导致其水土匹配程度很差(5级)。另有10个省份的水土不匹配等级达到差(4级),除福建省主要因水资源富余导致水土不匹配外,其余省份均因为水资源短缺。研究成果对在水资源约束条件下优化我国耕地数量和结构分配模式、降低水土不匹配程度具有参考价值。
Aiming at the uneven distribution of water resources in China and the unreasonable distribution of the quantity and structure of cultivated land, the mismatching degree of the water-land resources in China is analyzed on spatial and temporal scales, so as to explore whether the distribution mode of cultivated land in China is properly coupled with water resources in recent years. On temporal-spatial scale, the analysis is made with Gini coefficient method, while the year——2016 with the highest water-land mismatching degree is selected on spatial scale as the study year, and then the water-land mismatching grade in China is analyzed with the data of MODIS annual evapotranspiration and precipitation. Moreover, all the provinces in China are divided into three types in accordance with the relevant provincial water-soil mismatching grade, thus the discussion on optimizing the quantity and structure of cultivated land is carried out according to the types. The result shows that all the mismatching grades in China are poor(grade 4) from 2009 to 2016, while the mismatching degree is slightly increased as well.From the aspect of the national level, the mismatching grade in China is poor(grade 4), while the grade of shortage(grade 3) is higher than surplus grade(grade 2); for which the main reason of water-land mismatching is the shortage of water resources. From the aspect of the provincial level, the province with the highest water-land mismatching grade is Xinjiang Uygur Autonomous Region, of which the water-land mismatching grade is the poorest(grade 5) due to the water resources shortage therein. Additionally, the mismatching grades of the other ten provinces reach the poor grade(grade 4). Except Fujian Province with the water-land mismatching mainly caused by surplus of water resources, the water-land mismatchings of all the other provinces are caused by shortage of water resources. The study result has a referential value for optimizing the distribution mode of the quantity and structure of cultivated land in China and lowering the water-land mismatching degree concerned.
Aiming at the uneven distribution of water resources in China and the unreasonable distribution of the quantity and structure of cultivated land, the mismatching degree of the water-land resources in China is analyzed on spatial and temporal scales, so as to explore whether the distribution mode of cultivated land in China is properly coupled with water resources in recent years. On temporal-spatial scale, the analysis is made with Gini coefficient method, while the year——2016 with the highest water-land mismatching degree is selected on spatial scale as the study year, and then the water-land mismatching grade in China is analyzed with the data of MODIS annual evapotranspiration and precipitation. Moreover, all the provinces in China are divided into three types in accordance with the relevant provincial water-soil mismatching grade, thus the discussion on optimizing the quantity and structure of cultivated land is carried out according to the types. The result shows that all the mismatching grades in China are poor(grade 4) from 2009 to 2016, while the mismatching degree is slightly increased as well.From the aspect of the national level, the mismatching grade in China is poor(grade 4), while the grade of shortage(grade 3) is higher than surplus grade(grade 2); for which the main reason of water-land mismatching is the shortage of water resources. From the aspect of the provincial level, the province with the highest water-land mismatching grade is Xinjiang Uygur Autonomous Region, of which the water-land mismatching grade is the poorest(grade 5) due to the water resources shortage therein. Additionally, the mismatching grades of the other ten provinces reach the poor grade(grade 4). Except Fujian Province with the water-land mismatching mainly caused by surplus of water resources, the water-land mismatchings of all the other provinces are caused by shortage of water resources. The study result has a referential value for optimizing the distribution mode of the quantity and structure of cultivated land in China and lowering the water-land mismatching degree concerned.
引文
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[19] 黄健熙, 李荔, 张超,等. 基于遥感蒸散发数据的耕地灌溉保证能力评价方法[J]. 农业工程学报, 2015, 31(5):100- 106.
[20] 高磊, 申双和, 邵立瑛,等. 水稻蒸散特征及日尺度作物系数估算[J]. 中国农业气象, 2016, 37(2):158- 165.
[21] 刘钰, 汪林, 倪广恒,等. 中国主要作物灌溉需水量空间分布特征[J]. 农业工程学报, 2009, 25(12):6- 12.
[22] 庞艳梅, 陈超, 潘学标. 1961—2010年四川盆地玉米有效降水和需水量的变化特征[J]. 农业工程学报, 2015, 31(S1):133- 141.
[23] SMITH M. CROPWAT: A computer program for irrigation planning and management[M].Rome: Food & Agriculture Organization, 1992.
[24] D?LL P, SIEBERT S. Global modeling of irrigation water requirements[J]. Water Resources Research, 2002, 38(4):1- 10.
[25] 王静, 张晓煜, 马国飞,等. 1961—2010年宁夏灌区主要作物需水量时空分布特征[J]. 中国农学通报, 2015, 31(26):161- 169.
[26] 胡玮, 严昌荣, 李迎春,等. 气候变化对华北冬小麦生育期和灌溉需水量的影响[J]. 生态学报, 2014, 34(9):2367- 2377.
[27] 姜艳阳, 王文, 周正昊. MODIS MOD16蒸散发产品在中国流域的质量评估[J]. 自然资源学报, 2017,32(3):517- 528.
[28] DU J, SONG K. Validation of Global Evapotranspiration Product (MOD16) Using Flux Tower Data from Panjin Coastal Wetland, Northeast China[J]. Chinese Geographical Science, 2018,28(3):420- 429.
[2] 郧文聚, 高璐璐, 张超吕,等. 从生态文明视角看我国土地利用的变化及影响[J]. 环境保护, 2018, 20(46):31- 35.
[3] 边振兴, 刘琳琳, 王秋兵,等. 基于LESA的城市边缘区永久基本农田划定研究[J]. 资源科学, 2015, 37(11):2172- 2178.
[4] 岳天祥, 曲耀光, 艾南山. 河西地区水资源利用及耕地面积预测[J]. 兰州大学学报(自科版), 1991(1):118- 124.
[5] 程维明, 柴慧霞, 方月,等. 基于水资源分区和地貌特征的新疆耕地资源变化分析[J]. 自然资源学报, 2012, 27(11):1809- 1822.
[6] 蔡璐佳, 安萍莉, 刘应成,等. 水资源约束下内蒙古农牧交错带耕地适度集约利用研究——以乌兰察布市为例[J]. 干旱区资源与环境, 2017, 31(5):81- 87.
[7] 周浩, 雷国平, 张博,等. 1990—2013年挠力河流域耕地变化下水土资源平衡效应分析[J]. 农业工程学报, 2015, 31(1):272- 280.
[8] 董佩华. 甘肃省水土资源空间分布与组合评价[J]. 干旱区地理, 2009, 32(6):834- 840.
[9] 潘宜, 侣小伟, 金苗,等. 城市化进程中水土资源系统耦合配置研究[J]. 水土保持通报, 2010, 30(5):216- 220.
[10] 董雯, 杨宇, 张豫芳. 绿洲城镇发展与水土资源开发的耦合效应及其时空分异[J]. 资源科学, 2013, 35(7):1355- 1362.
[11] 姚海娇, 周宏飞, 苏风春. 从水土资源匹配关系看中亚地区水问题[J]. 干旱区研究, 2013, 30(3):391- 395.
[12] 王薇, 吕宁江, 王昕,等. 黄河三角洲水土资源空间匹配格局探析[J]. 水资源与水工程学报, 2014(2):66- 70.
[13] 韦森. 入世的政治—经济学家阿尔伯特·赫希曼的思想之旅[J]. 复旦学报(社会科学版), 2015, 57(6):117- 129.
[14] 洪思扬, 宋志松, 程涛,等. 基于基尼系数的南水北调受水区水资源空间匹配分析[J]. 北京师范大学学报(自然科学版), 2017, 53(2):175- 179.
[15] 杨齐祺, 杨悉廉, 乔传泰斗,等. 基尼系数视野下的安徽省水土资源匹配分析[J]. 中国农学通报, 2016, 32(20):72- 76.
[16] 胡登, 石丽忠. 基于基尼系数的辽宁省水资源与人口经济匹配研究[J]. 沈阳大学学报(自然科学版), 2016, 28(5):379- 383.
[17] 马海燕, 缴锡云. 作物需水量计算研究进展[J]. 水科学与工程技术, 2006, 2006(5):5- 7.
[18] ALLEN R G, PEREIRA L S, RAES D, et al. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56[R]. Rome: FAO, 1998.
[19] 黄健熙, 李荔, 张超,等. 基于遥感蒸散发数据的耕地灌溉保证能力评价方法[J]. 农业工程学报, 2015, 31(5):100- 106.
[20] 高磊, 申双和, 邵立瑛,等. 水稻蒸散特征及日尺度作物系数估算[J]. 中国农业气象, 2016, 37(2):158- 165.
[21] 刘钰, 汪林, 倪广恒,等. 中国主要作物灌溉需水量空间分布特征[J]. 农业工程学报, 2009, 25(12):6- 12.
[22] 庞艳梅, 陈超, 潘学标. 1961—2010年四川盆地玉米有效降水和需水量的变化特征[J]. 农业工程学报, 2015, 31(S1):133- 141.
[23] SMITH M. CROPWAT: A computer program for irrigation planning and management[M].Rome: Food & Agriculture Organization, 1992.
[24] D?LL P, SIEBERT S. Global modeling of irrigation water requirements[J]. Water Resources Research, 2002, 38(4):1- 10.
[25] 王静, 张晓煜, 马国飞,等. 1961—2010年宁夏灌区主要作物需水量时空分布特征[J]. 中国农学通报, 2015, 31(26):161- 169.
[26] 胡玮, 严昌荣, 李迎春,等. 气候变化对华北冬小麦生育期和灌溉需水量的影响[J]. 生态学报, 2014, 34(9):2367- 2377.
[27] 姜艳阳, 王文, 周正昊. MODIS MOD16蒸散发产品在中国流域的质量评估[J]. 自然资源学报, 2017,32(3):517- 528.
[28] DU J, SONG K. Validation of Global Evapotranspiration Product (MOD16) Using Flux Tower Data from Panjin Coastal Wetland, Northeast China[J]. Chinese Geographical Science, 2018,28(3):420- 429.