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江苏淮北地区主要作物需水量的初步研究
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你可能喜欢作物需水系数
water demand coefficient
作物需水系数
基于1个网页-
作物系数是计算作物需水量必不可少的参数。
Crop coefficient is the basic parameter for determining crop water requirement.
最后确定冬小麦、赤豆等农作物在南京地区的农田需水量及作物系数。
Finally, water requirement and crop coefficients for winter wheat, red bean, etc. are determined.
分析了覆膜旱作水稻需水量试验资料，得出覆膜旱作水稻各生育阶段综合作物系数。
The synthetic crop coefficients are evaluated by analyzing the experiment data on water requirement of rice in plastic film mulched dryland (RPFMD).
crop evapotranspiration coefficient 作物全生育期内的蒸发蒸腾水量与收获的干物质量或产量之比。
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感谢您的反馈，我们会尽快进行适当修改！沿海滩涂围垦区土地生产潜力模型构建与应用——以江苏省如东县为例
许艳, 濮励杰, 于雪, 朱明, 蔡芳芳.
2015.沿海滩涂围垦区土地生产潜力模型构建与应用——以江苏省如东县为例[J]. 地理科学进展, 34(7): 862-870
Yan XU, Lijie PU, Xue YU, et al.
2015.Potential land productivity of the coastal reclamation zones of Rudong County, Jiangsu Province[J]. Progress In Geography,34(7): 862-870&&10.18306/dlkxjz.
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沿海滩涂围垦区土地生产潜力模型构建与应用——以江苏省如东县为例
濮励杰1,2,*,
1. 南京大学地理与海洋科学学院,南京 210023
2. 国土资源部海岸带开发与保护重点实验室,南京 210023
通讯作者：濮励杰(1965-),男,江苏吴江人,教授,主要从事土地利用与规划等研究,E-mail:。
作者简介：许艳(1986-),女,江苏滨海人,博士研究生,主要从事土地利用与评价研究,E-mail:。
基金:国家自然科学基金项目(55); 江苏省普通高校研究生科研创新计划项目(CXLX12-0036); 南京大学优秀博士研究生创新能力提升计划项目();
沿海淤泥质滩涂是中国重要的耕地后备资源之一,滩涂围垦新增的大量耕地资源的生产潜力能反映滩涂土壤粮食安全保障能力大小。本文以江苏省如东县滩涂围垦区为例,在现有的光温水气候生产潜力模型的基础上,引进基础地力贡献率和盐分限制因子作为土壤有效性系数,构建沿海地区土地生产潜力模型,并通过水稻和小麦产量对模型结果进行初步验证。研究表明：该模型具有一定可行性。滩涂围垦区水稻产量土壤基础地力贡献率为55%~59%;小麦基础地力贡献率为50%~80%。未脱盐的1982年滩涂围垦区水稻和小麦产量受到盐分阻碍的系数分别为0.73和1.00。2007年垦区由于盐分太高不能种植水稻,小麦产量受到盐分阻碍系数为0.35。未脱盐的1982年滩涂垦区土壤基础地力修正后的水稻和小麦土地生产潜力分别为02.23 kg/hm2;土壤盐分修正后的土地生产潜力分别为329.39 kg/hm2;土壤基础地力和盐分共同修正后的土地水稻和小麦生产潜力分别为02.23 kg/hm2。与实地调查的水稻产量(9750 kg/hm2)和小麦生产潜力(6000 kg/hm2)相比,目前土地生产力远小于盐分限制下的土地生产潜力,与基础地力和盐分双重限制下的土地生产潜力接近,改善土壤施肥技术可以进一步提高土地生产力。
土地生产潜力;
基础地力贡献率;
盐分限制因子;
土壤有效性系数;
江苏沿海地区
Potential land productivity of the coastal reclamation zones of Rudong County, Jiangsu Province
Lijie PU1,2,*,
Ming ZHU1,
Fangfang CAI1
1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
2. Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resources, Nanjing 210023, China
The Jiangsu muddy coastal zone is one of the key bases of cropland complementary resources in China. In 2009, the Chinese government approved the development plan of the Jiangsu coastal zone, wherein the tidal flat will be reclaimed and developed into new farmland. Potential land productivity in the coastal area can reflect its capacity to supply food for the country, and is the basis for maintaining the sustainability of the regional agricultural production. There exist various potential land productivity models in China and worldwide. Models based on the process of crop physiology and ecology were used at the field scale, such as the Crop-Environment Resource Synthesis System (CERES) and World Food Studies (WOFOST). Land productivity models based on light, temperature, precipitation, and soil properties—the Classification and Evaluation Techniques of Farmland and Evaluation System of Land Productivity (ESLP)—have been used in China. However, the soil validation coefficients in these two models are based on the evaluation of soil quality and did not consider the relationship between crop yields and soil properties. This article takes the reclamation zones in Rudong County, Jiangsu Province as a case study and attempts to improve the soil validation coefficient in potential land productivity models. It incorporates the percentage of soil fertility contribution (PSFC) and soil salinity factor as soil validation coefficients into the model of potential land productivity to reflect the quality of land. We used the field survey data on rice and wheat yields to verify the feasibility of the potential land productivity model in the coastal area of China. The results show that the PSFC of rice production in the Jiangsu coastal area was about 55%~59%. The PSFC of wheat production in the study area was 50%~80%. The rice and wheat production in the reclamation zones in 1951 and 1974 was not affected by soil salinity because the soils in these reclamation zones were not saline. The rice and wheat production in the reclamation zones in 1982 and 2007 were influenced by soil salinity. The salinity factors of rice and wheat production in the reclamation zones in 1982 were 0.73 and 1.00, respectively. The salinity factors of rice and wheat production in the reclamation zones in 2007 were 0 and 0.35. In 2007 the soil in the reclamation zone was no longer suitable for growing rice paddy. The rice and wheat potential productivity corrected by PSFC in the un-desalinized reclamation zones in 1982 were 12235.84 and 6502.23 kg/hm2. The rice and wheat potential productivity corrected by soil salinity in the un-desalinized reclamation zones in 1982 were 15677.42 and 10329.39 kg/hm2. The rice and wheat potential productivity corrected by PSFC and soil salinity in the un-desalinized reclamation zones in 1982 were 8934.97 and 6502.23 kg/hm2. The actual field yields of rice and wheat (9750 and 6000 kg/hm2) are consistent with the potential productivity corrected by PSFC and soil salinity, and is far less than the potential productivity corrected by soil salinity. Improved fertilization can increase land production. The result of this research can be useful for evaluating newly reclaimed farmland resources and for calculating crop production in the coastal reclamation zones.
potential land productivity;
percentage of soil fertility contribution;
salinity factor;
soil validation coefficient;
Jiangsu coastal area
1 引言土地生产力的概念因土地税征收需要而起源于20世纪20年代的德国。中国学者50年代开始研究农作物生产与气候的关系(;),考虑光、温、水、土等自然因子以及人类耕作、施肥、灌溉等农业管理技术,根据作物能量转化过程来逐步估算农业生产潜力大小。在一定的自然地理背景下,即光、温度、水分大致一定的情况下,土地生产潜力存在阈值,改变客观不利因素,力争发挥最大生产潜力,是生产力研究的重要目标()。国内外与土地生产力相关的作物生长模型很多,比如美国作物—环境资源综合系统(Crop-Environment Resource Synthesis System, CERES),荷兰的作物生长模型WOFOST(World Food Studies),国内水稻生长日历模拟模型(Rice Growth Calendar Simulation Model, RICAM)等,多侧重于从作物生理生态过程模拟。国内从资源利用角度出发的宏观土地生产力模型主要包括农用地分等定级和产能核算()与ESLP模型()等,这些模型在区域尺度上系统性地光、温、水、土以及管理因子多层次开展参数本地化的应用研究,但不同地区农业生产潜力的主要限制因素不尽相同,包括无霜期()、旱涝盐碱灾害()等,确定与农业生产过程相适应的各类有效系数无论在指标设定还是研究尺度方面均较粗略()。目前测算土壤有效系数依据的土壤基本理化性质是根据全国土壤因子评价标准进行打分加权平均而得到的,并未考虑土壤基本理化属性与农作物产量之间的关系,没有真正反映出作物实际生长过程中潜力变化过程。沿海滩涂土壤是中国重要的耕地后备资源基地之一(;),构建沿海滩涂围垦区土地生产潜力模型,了解该地区土地生产潜力大小是沿海开发的重要基础性工作,同时也关系到沿海地区的农业可持续发展,对新增资源评价利用等相关研究具有一定参考价值。目前,在沿海滩涂地区滩涂湿地的初级生产力已受到学术界的广泛关注(;),但对滩涂围垦区的土地生产力潜力估算研究还比较薄弱。本文引入土壤基础地力贡献率和土壤盐分限制因子两个系数来表征土壤有效系数,构建沿海滩涂围垦区土地生产潜力模型,并对江苏省如东县沿海滩涂围垦区开展实证研究。2 研究方法土地生产潜力模型是在光合生产潜力模型的基础上,开展温度订正(),水分订正(;),以及土壤有效系数修正,其模型为： Y=Q×f1×f2×f3×f4=Y1×f2×f3×f4=Y2×f3×f4=Y3×f4(1)式中： Y为土地生产潜力/(kg/hm2); Q为太阳总辐射/(MJ/m2); f1为光合有效系数; Y1为光合生产潜力/(kg/hm2); f2为温度有效系数; Y2为光温生产潜力/(kg/hm2); f3为水分有效系数; Y3为气候生产潜力/(kg/hm2); f4为土壤有效系数,系土壤基础地力贡献率与土壤盐分限制因子修正系数的乘积。按照作物生长期的土地生产潜力模型如下： Y=∑Q×f1×f2i×f3i×f4(2)式中： Y为土地生产潜力/(kg/hm2); Qi为第 i生长阶段的太阳总辐射/(MJ/m2); f1为光合有效系数; f2 i为第 i个生长阶段的温度有效系数; f3 i为第 i个生长阶段的水分有效系数; f4为土壤有效系数。2.1 农作物生长期的划分不同时期农作物生长状况与农作物产量密切相关。联合国粮农组织(FAO)将作物生育期分为4个阶段分别为初始生长期、生长发育期、中期和末期()。本文将作物生长期分为5个阶段,分别为苗期、营养生长期、营养生殖生长期、营养灌浆期和灌浆成熟期。在江苏省沿海地区,水稻生长期为5月15日-10月23日,水稻的生育期约150~155天,包括秧苗期、有效分蘖期、无效分蘖期、拔节孕穗期、抽穗期、扬花期、灌浆期和成熟期。因此,水稻的苗期为5月下旬-6月上旬,营养生长期为6月下旬-7月上旬,营养生殖生长期为7月下旬-8月上旬,营养灌浆期为8月下旬-9月上旬,灌浆成熟期为9月下旬-10月下旬。冬小麦生长期为10月23日-次年6月上旬,生长期220~270天,包括出苗、三叶、分蘖、越冬、返青、起身、拔节、孕穗、抽穗、开花、灌浆和成熟期。因此,冬小麦的苗期为10月下旬,营养生长期为11月上旬-次年2月下旬,营养生殖生长期为3月上旬-4月上旬,营养灌浆期为4月下旬-5月上旬,灌浆成熟期为5月下旬-6月上旬。2.2 光合有效系数光合有效辐射的观测仪器甚少,通常需要通过计算方法取值,主要方法如式(3)-(4)表示。 Qg=ε×Q(3) Qg=ε1×Q1+ε2×Q2(4)式中： Qg表示光合作用有效辐射/(MJ/m2);ε、ε1、ε2分别表示不同的系数; Q表示总辐射/(MJ/m2), Q1和 Q2分别表示直接辐射/(MJ/m2)和间接辐射/(MJ/m2)。本文采用式(3)计算光合作用有效辐射。光合有效系数计算如式(5)所示： f1=Ωεφ(1-α)1-β1-ρ1-γ1-ωf(L)1-η-11-δ-1q-1S(5)式中： f1表示光合有效系数;Ω表示作物光照强度利用效率;ε表示光合有效辐射占总辐射的比例;φ为光量子转化的效率;α表示植物群体反照率;β表示植物繁茂群体透射率;ρ是作物非光合器官截获辐射比例;γ是超过光饱和点的光的比例;ω表示呼吸消耗占光合产物的比例; f(L)是作物叶面积动态变化的订正值;η是成熟作物的含水率;δ表示作物灰分率; q表示单位干物质的含热量/(MJ/kg); S表示作物收获指数,即干物质(籽粒、糖、油)所占总生物量的比例。本文采用的光合有效系数参数见(;;)。表1Tab.1表1(Tab.1)
表1 光合有效系数参数取值
Tab.1 The values of photosynthetic parameters参数Ωεφαβργω f(L)ηδ q S水稻0.90.490.220.060.080.10.050.330.560.140.0816.90.45小麦0.850.490.220.10.070.10.050.330.50.140.0817.580.45
表1 光合有效系数参数取值
Tab.1 The values of photosynthetic parameters2.3 温度有效系数作物不同生长阶段中温度环境存在很大的差异,其决定着作物体内各种酶的活性。很多学者分别对C3和C4作物(;),以及喜凉作物和喜温作物(;)采用不同的线性函数进行温度有效系数修正,也有学者采用非线性函数进行修正()。由于作物生长对温度环境的变化的适应能力的复杂性,本文采用非线性温度修正方法(;),如式(6)-(7)所示。 f2=(T-T1)(T2-T)B(T0-T1)(T2-T0)B(6) B=T2-T0T0-T1(7)式中： f2为温度有效系数; T为某一段时间的平均气温/℃; T0、 T1、 T2分别为该段时间作物产量形成的最适温度/℃、生长发育的下限温度/℃、上限温度/℃; B为中间变量。采用的作物不同时期三基点温度见。表2Tab.2表2(Tab.2)
表2 作物各生长阶段三基点温度
Tab.2 Temperature of three key points at different growth stages of crops生长阶段水稻小麦 T0 T1 T2 T0 T1 T2苗期2192818527营养生长期2512.53224730营养生殖生长期27.81533271433营养灌浆期26.31533251433灌浆成熟期19.310.530181030注：水稻和小麦温度参数参考文侯光良等(1985);村田吉男研究表明,小麦表观光合作用在0~40℃,最适温度为18℃()。
表2 作物各生长阶段三基点温度
Tab.2 Temperature of three key points at different growth stages of crops2.4 水分有效系数作物不同生长阶段其降雨量和蒸散量等差异较大,同时作物自身对水分的需求量和缺水产生的影响也不同。水分有效系数计算公式如公式(8)。本文采用温度、相对湿度以及风速与蒸散量的函数关系进行估算蒸散量()。作物需水系数和作物缺水敏感系数与作物生育期有关()。各参数如所示()。表3Tab.3表3(Tab.3)
表3 作物各生长阶段需水系数和缺水敏感系数
Tab.3 Parameters of crop water requirement and sensitivity to water scarcity at different growth stages生长阶段作物需水系数 Kc作物缺水敏感系数 Ky水稻小麦水稻小麦苗期1.10~1.150.30~0.400.220.20营养生长期1.10~1.500.70~0.800.320.60营养生殖生长期1.10~1.301.05~1.200.270.60营养灌浆期0.95~1.050.65~0.750.190.50灌浆成熟期0.95~1.050.20~0.250.150.00注：水稻作物缺水敏感系数参考文献()；作物需水系数采用最高值。
表3 作物各生长阶段需水系数和缺水敏感系数
Tab.3 Parameters of crop water requirement and sensitivity to water scarcity at different growth stages f3=1-Ky×1-PETm，P<ETm1，P≥ETm (8)式中： f3为水分有效系数; P为作物生育期降水量/ ETm为作物需水量/ Ky为作物缺水敏感系数。作物需水量可根据参考作物蒸散量计算得到： ETm=Kc×ET0(9)式中： ETm为作物需水量/ Kc为作物系数; ET0为参考作物蒸散量。作物蒸散量( ET0)计算公式()如下： ET0=0.0003×(25+T)2×(100-f)×(3+μ)(10)式中： T、 f、 u分别为月平均气温/℃、相对湿度/%、风速/(m/s)。2.5 土壤有效系数作物生长发育离不开土壤养分供给。衡量土壤施肥对作物产量的贡献一般用基础地力贡献率表示,其值为不施肥时的作物产量与适宜肥料施用下的产量之比,与作物类型、气候和土壤特性等因素密切相关,变幅在20%~75%(,;)。汤勇华等(2009)将土壤粘粒含量、有机质、全氮、速效磷和速效钾含量,以及氮磷钾的交互作用(TN×AP,TN×AK, AP×AK,TN×AP×AK)等土壤参数和气候因子加总,得到不同作物和不同种植区域的作物基础地力贡献率模型,其中南方单季稻的统计模型为： PSFC=52.4+0.22x4+0.48x6(11)式中： PSFC表示基础地力贡献率, x4表示粘粒含量(Clay)/%; x6表示速效磷(AP)/(mg/kg)。南方冬小麦的统计模型()如下： PSFC=-95.7+3.37x2+1.34x3+2.21x5x6+
25.21×10-3x6x7-29.39×10-3x5x6x7(12)式中： x2为纬度; x3表示土壤有机质(SOM)/(g/kg); x5表示土壤全N含量(TN)/(g/kg); x6表示速效磷(AP)/(mg/kg); x7表示土壤速效钾(AK)/(mg/kg)。由于沿海地区土壤盐分对作物产量产生很大的影响,根据联合国粮农组织(FAO)有关土壤盐分与作物减产的数量关系和Maas-Hoffman模型(;)得到土壤盐分和水稻和小麦作物产量的数学关系,如式(13)和(14)所示。土壤盐分含量与土壤饱和电导率数学关系如式(15)所示。 y=100，x≤3y=100-12×(x-3)，3<x<11.33y=0，x≥11.33(13)式中： y表示水稻相对产量/%; x表示土壤饱和电导率/(ds/m)。小麦相对产量与土壤盐分的关系如下： y=100 x≤6y=100-7.1×(x-6)，6<x<20.08y=0 x≥20.08(14)式中： y表示小麦相对产量/%; x表示土壤饱和电导率/(ds/m)。 ECe=19SS-0.46(15)式中： ECe表示土壤饱和电导率/(ds/m); SS表示土壤盐分含量/%。3 研究区域与数据3.1 研究区概况如东县位于江苏沿海地区(120°42′~121°22′E, 32°12′~32°36′N),海岸线长106 km,主要受亚热带和海洋性季风气候影响,光照与降水量充足,年平均气温为15℃。潮滩是如东县最宝贵的自然资源之一,总面积为6.93万hm2。近代以来如东县一直开展滩涂围垦工作,用于农业生产、水产养殖以及国营盐场()。年,如东县沿海滩涂共围垦了20个垦区,匡围面积约3.46万hm2。与其他沿海县市相似,1990年前滩涂围垦靠人工作用;年靠人机结合;2000年以来靠机械化作业,随着围垦技术的提高,如东县起围高程不断降低。如东县是江苏沿海滩涂围垦的典型县市之一,其老北坎垦区、洋东垦区、新北坎垦区、东凌垦区、凌洋垦区、豫东垦区等主要用于农业生产和水产养殖。本文研究区包括老北坎垦区、新北坎垦区、东凌垦区和豫东垦区,如和所示。图1Fig.1 图1 研究区和采样点示意图Fig.1 Location of the study area and soil sampling sites表4Tab.4表4(Tab.4)
表4 如东县滩涂围垦区情况表
Tab.4 Basic information of reclamation zones in Rudong County, Jiangsu Province垦区名称围垦年限匡围面积/hm2起围高程/m围堤长度/km豫东200720672.513.35东凌198234003.0~4.016.58新北坎197421333.0~3.513.60老北坎195112003.0~3.57.00
表4 如东县滩涂围垦区情况表
Tab.4 Basic information of reclamation zones in Rudong County, Jiangsu Province3.2 研究数据本文所用气象数据来自江苏省气象中心如东气象站和吕泗气象站,主要包括辐射、温度、降水、湿度、风等。本文通过2012年在如东县不同年限滩涂围垦区（包括老北坎垦区、新北坎垦区、东凌垦区和豫东垦区）采集0~10 cm土壤表层样品(),并带回实验室进行风干,测定土壤粒度、土壤全氮、土壤有机质、土壤速效磷、土壤速效钾等项目。土壤粒度采用激光粒度分析方法;土壤全氮采用凯氏定氮法;土壤有机质采用重铬酸钾氧化—外加热法测定;土壤速效磷采用H2SO4—高氯酸消煮—铝蓝比色法测定;土壤速效钾(AK)采用乙酸铵浸提—火焰光度法测定。2014年5月底(小麦即将收割时期)对不同年限滩涂围垦区水稻和小麦产量进行实地调研。4 结果与分析4.1 光温水生产潜力水稻—小麦轮作是江苏沿海地区农业最主要的轮作方式之一。江苏沿海地区水稻和小麦粮食作物不同生育期光照辐射、降水和气温如。水稻生育期内苗期、营养生殖生长期和灌浆成熟期光照辐射最强,而这3个时期降雨量最小,平均气温差异较小,结合水稻不同生长期对温度和水分的敏感系数,得到水稻产量在这3个生育期间受到水分因子影响很大,通过式(8)-(10)计算得到江苏省沿海地区水稻水分修正系数在苗期、营养生殖生长期以及成熟期分别为0.83、0.77和0.91()。而在小麦生育期内,虽然营养生长期和营养生殖生长期光照辐射较强,降雨量充足,但平均气温相对较低,此阶段小麦干物质积累受到温度影响较大,结合小麦不同生长期对温度和水分的敏感系数,通过公式(6)-(7)得到小麦在营养生长期、营养生殖生长期以及营养灌浆期的温度修正系数分别为0.19、0.55和0.65()。表5Tab.5表5(Tab.5)
表5 江苏沿海地区如东县气候因子情况表
Tab.5 Climatic e factors of Rudong County in the coastal zone of Jiangsu Province水稻小麦光照辐射/(MJ/m2)降水量/mm平均气温/℃光照辐射/(MJ/m2)降水量/mm平均气温/℃苗期558.8527.221.81172.0240.417.18营养生长期382.52316.625.42980.17272.65.08营养生殖生 长期601.6822.728.97647.45128.210.14营养灌浆期459.20176.025.40476.0149.518.67灌浆成熟期676.6540.819.22558.8527.221.81
表5 江苏沿海地区如东县气候因子情况表
Tab.5 Climatic e factors of Rudong County in the coastal zone of Jiangsu Province表6Tab.6表6(Tab.6)
表6 沿海地区气候因子修正系数
Tab.6 Climate correction coefficient in the Jiangsu coastal zone水稻小麦温度修正系数水分修正系数温度修正系数水分修正系数苗期0.990.831.001.00营养生长期1.001.000.191.00营养生殖生长期0.980.770.551.00营养灌浆期0.991.000.650.90灌浆成熟期1.000.910.831.00
表6 沿海地区气候因子修正系数
Tab.6 Climate correction coefficient in the Jiangsu coastal zone通过式(1)计算得到：江苏省沿海地区水稻和小麦光合生产潜力分别为144.56 kg/hm2;光温生产潜力分别为549.15 kg/hm2;光温水生产潜力分别为329.39 kg/hm2。4.2 土壤有效系数江苏沿海地区土壤肥力贫瘠、盐分高、物理性质较差(),1949年以来滩涂围垦区的土壤有机质约为1.57%,新围垦的2007年豫东垦区土壤盐分高达0.82%,对作物生长有明显的胁迫作用。本文用基础地力贡献度和盐分阻碍因子来表达土壤有效性系数,与以往的土壤质量综合评价值作为土壤有效系数相比,更能定量化反映土壤属性与作物产量之间的关系。通过计算得到随着沿海滩涂围垦区基础地力贡献率仅为50%左右,土地生产潜力受到土壤肥力等因素的限制较大。从不同作物种类来看,如东县滩涂围垦区水稻的基础地力贡献率约为55%~59%();随着滩涂围垦年限的增加,耕地质量不断改良,土壤基础地力贡献率总体呈现上升趋势;冬小麦基础地力贡献率约为50%~80%。随着滩涂围垦年限增加,由于土壤速效钾含量减少,土壤基础地力贡献率不断降低。表7Tab.7表7(Tab.7)
表7 如东县不同年限滩涂围垦区土壤理化性质
Tab.7 Soil physical and chemical properties in the reclamation zones of Rudong County年限纬度/°有机质/(g/kg)全氮/(g/kg)速效磷/(mg/kg)速效钾/(mg/kg)粘粒/%盐分/%195132.37180.0611.5641.664.680.04197432.3917.20.037.2084.564.320.09198232.3314.60.056.06204.597.660.30200732.3415.70.034.98367.122.750.82
表7 如东县不同年限滩涂围垦区土壤理化性质
Tab.7 Soil physical and chemical properties in the reclamation zones of Rudong County表8Tab.8表8(Tab.8)
表8 沿海地区不同年限滩涂围垦区土壤基础地力贡献和盐分阻碍因子系数
Tab.8 Percentage of soil fertility contribution (PSFC) and salinity factor coefficients in the reclamation zones of Rudong County围垦年限基础地力修正系数/%盐分限制因子系数水稻小麦水稻小麦195158.9850.351.001.00197456.8151.791.001.00198256.9962.950.731.00200755.4079.110.000.35
表8 沿海地区不同年限滩涂围垦区土壤基础地力贡献和盐分阻碍因子系数
Tab.8 Percentage of soil fertility contribution (PSFC) and salinity factor coefficients in the reclamation zones of Rudong County土壤盐分是沿海地区作物生产主要的限制因子,通过影响作物根部渗透压以及离子毒害两方面来影响作物产量,因此需要盐分阻碍系数综合反映土壤盐分对作物产量的影响。江苏沿海滩涂土壤属于典型的滨海盐土,经人类围垦农业耕作后,土壤盐分不断降低。1951年围垦的老北坎垦区和1974年围垦的新北坎垦区已经基本处于脱盐状态,因此作物生长不受土壤盐分限制;而年滩涂围垦区土壤盐分分别为0.3%和0.8%。通过计算得到水稻盐分修正系数分别为0.73和0;小麦盐分修正系数分别为1和0.35。在2007年垦区盐分很高部分区域,基本不能种植水稻和小麦等粮食作物。4.3 土地生产潜力及验证比较通过式(1)对气候生产潜力进行土壤有效系数修正计算得到水稻、小麦的生产潜力()：江苏省沿海地区、1982滩涂围垦区土地水稻生产潜力分别为195.89、8934.97 kg/hm2,2007年滩涂围垦区由于盐分较高尚不能种植水稻;小麦生产潜力分别为49.26、80.24 kg/hm2。对、年滩涂围垦区水稻和小麦气候生产潜力仅进行盐分修正得到：、1982年滩涂围垦区水稻生产潜力分别为469.18、15677.42 kg/hm2;、年滩涂围垦区小麦生产潜力分别为329.39、40.90 kg/hm2。表9Tab.9表9(Tab.9)
表9 沿海滩涂围垦区土地生产潜力模型
Tab.9 Land productivity in the Jiangsu coastal reclamation zones围垦年限土地生产潜力/(kg/hm2)基础地力修正盐分修正基础地力和盐分修正水稻小麦水稻小麦水稻小麦195112661.775200.4021469.1810329.3912661.775200.40197412195.895349.2721469.1810329.3912195.895349.27198212235.846502.2315677.4210329.398934.976502.23200711893.608171.36—3640.90—2880.24注："—"表示垦区内不能种植水稻作物。
表9 沿海滩涂围垦区土地生产潜力模型
Tab.9 Land productivity in the Jiangsu coastal reclamation zones通过对、年滩涂围垦区进行水稻和小麦产量调研,得到和1982年水稻产量大约在 kg/hm2,小麦的产量约在 kg/hm2;2007年滩涂垦区不种植水稻,小麦产量为4875 kg/hm2。与实地调查的水稻产量(9750 kg/hm2)和小麦生产潜力(6000 kg/hm2)相比,1982年垦区现实土地生产力远小于盐分限制下的土地生产潜力,与基础地力和盐分双重限制下的土地生产潜力接近。5 结论与讨论江苏沿海滩涂围垦区水稻和小麦光温水生产潜力为329.39 kg/hm2,由于不同年限滩涂围垦区土壤质量差异较大,、1982年滩涂围垦区土地水稻生产潜力分别为195.89、8934.97 kg/hm2,2007年滩涂围垦区由于盐分较高尚不能种植水稻;、年滩涂围垦区小麦生产潜力分别为49.26、80.24 kg/hm2。通过实地产量调查与本文土地生产潜力模型结果对比,在江苏沿海滩涂围垦区引进基础地力贡献率和盐分限制因子系数作为土壤有效系数的土地生产潜力模型具有一定的可行性。基于统计学和实验数据以及Maas-Hoffman模型得到的土壤基础地力以及土壤盐分与作物产量关系来确定土壤有效性系数(,),相对于主观地对土壤因子进行评价打分更具有可行性。基础地力贡献率计算结果一般在20%~75%,与气候因子、作物类型和土壤特性相关,能够真实地反映土壤质量对土地农业生产潜力的影响,要优于以往的土壤有效系数只考虑土壤特性评价分级。因此,基础地力贡献率更能体现出不同地域土壤养分对农业生产潜力的贡献程度。同时,土壤盐分是沿海滩涂围垦区农业生产的主要限制性因子,考虑土壤盐分更能显示研究区的特殊性和典型性。沿海滩涂围垦区土地生产潜力模型能为江苏沿海开发中不断新增的耕地资源开展评价,并为估算出粮食生产潜力提供手段与方法。需要说明的是,本文基础地力贡献率和盐分限制因子是采用国内外已有的研究成果(含联合国有关标准),为保证测算更具精确性,今后有必要在当地设计实验方案,测算出本地土壤基础地力和盐分对光温水生产潜力实现的限制程度。
The authors have declared that no competing interests exist.
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... 曹卫星, 2006 ...
... 梁佳勇等, 2004),以及喜凉作物和喜温作物(曹卫星, 2006 ...
... 本文采用温度、相对湿度以及风速与蒸散量的函数关系进行估算蒸散量(曹卫星, 2006) ...
Van Velthuizen H, Fischer G, 等. 2007. 基于AEZ模型的我国农区小麦生产潜力分析[J]. [Cai C Z, Van Velthuizen H, Fischer G, et al. 2007. Analyses of wheat yield potential by AEZ model on the basis of Chinese farming system zonation[J].
Wheat yield potentials in 41 Chinese farming system sub-zones were calculated on the bases of AEZ model developed by FAO and IIASA in accordance with verified statistical data (1961 to 1997)on China.The distribution of maximum wheat yield potential was extrapolated on Chinese GIS map.Results show that maximum yield potential of wheat can be 2～3 folds its present levels,an invaluable discovery for high wheat yield breeding and cultivation in China.
根据联合国粮农组织(FAO)和国际应用系统分析研究所(IIASA)基于中国年的统计资料(经多方校正)共同开发的AEZ模型，运用GIS平台计算了中国41个农作制亚区的小麦生产潜力，并指出了单产最高潜力分布区域。研究结果表明，我国小麦的最高产量潜力约为目前产量的2～3倍。这对我国小麦高产育种及栽培具有重要意义。
... 蔡承智等, 2007)采用不同的线性函数进行温度有效系数修正,也有学者采用非线性函数进行修正(陈建文等, 1999) ...
陈超, 于强, 王恩利, 等. 2009. 华北平原作物水分生产力区域分异规律模拟[J]. [Chen C, Yu Q, Wang E L, et al. 2009. Modeling the spatial distribution of crop water productivity in the North China Plain[J].
The North China Plain (NCP) is the largest agricultural production area in China with a dominant wheat-maize double cropping system. Excessive use of ground and surface water for irrigation has caused rapid decline in groundwater tables and surface water resources. Crop water productivity (WP) is the amount of water required per unit of yield, the increase of which is the ultimate objective of water-saving agriculture. In order to use water resources more efficiently, a better understanding of how WP responds to climate variations and irrigation strategies is required. This paper uses a modeling approach to investigate the responses in the NCP. The Agricultural Systems Model software APSIM is validated by using 14 years of experimental data at three sites. The validated model, together with long-term climate data from 32 weather stations are then used to simulate WP of wheat-maize double cropping system as it responds to climate variations and irrigation scenarios. The simulation results show that considerable spatial variations in WP values exit for both wheat and maize, which correspond to the average conditions in the NCP. WPET (the ratio of gain yield to evapotranspiration during crop growing season) for wheat rang from 1.38 to 1.69 kg/m3 with an average of 1.53 kg/m3 under full irrigation, decreasing from south to north of the NCP due to the increasing vapor press deficit (VPD). Under this irrigation scenario, WPET for maize rang from 1.69 to 2.05 kg/m3 with an average of 1.83 kg/m3. Due to the relatively concentrated rainfall during the maize season, there are no significant differences in VPD and WP for maize has no great differences bet however, it decreases from east to west as a result of the increasing VPD. WPET for wheat and maize under the irrigation scenario can partially meet crop water demand and is slightly higher than that under full irrigation. WPET for wheat under rain irrigation decreases from south to north, ranging from 0.29 to 1.57 kg/m3 with an average of 0.77 kg/m3, as a result of decreasing rainfall in the growing season from south to north in this area. The range of WPET for rain irrigated maize is from 0.86 to 2.03 kg/m3 with an average of 1.47 kg/m3. Improving irrigation water management can increase crop WP. Reducing the loss of water through evaporation can also increase crop WP.
提高作物水分生产力（Water Poduetivity）是节水农业研究的最终目标，定量分析作物WP对干旱和半干旱地区水资源管理和决策制定具有重要意义。华北平原是我国重要的粮食生产基地，但水资源问题已成为制约该区可持续发展的瓶颈，明确该区作物WP时空变化特征及其与气候的关系，对指导该区农业生产和水资源高效利用具有重要作用。本文首先利用华北平原3个代表性试验站各连续3～4年的小麦-玉米轮作田间试验资料，校准验证澳大利亚开发的APSIM模型，然后利用校准后的APSIM模型和研究区域32个气象站1961年～2005年逐日气象数据，结合GIS技术，对华北平原不同供水情景下冬小麦、夏玉米WP空间分布特征进行了模拟研究。模拟结果表明：①当不考虑作物品种变化时，华北平原小麦、玉米WPET（产量与蒸散量比值）分布响应于该区平均气候状况，具有明显的空间分布特征；②充分供水情景下全区小麦WPET为（1.38～1.69）kg/m3，平均值为1.53kg/m3，玉米WPET为（1.69～2.05）kg/m3，平均值为1.83kg/m3；非充分供水情景（仅满足作物水分需求一半）下两作物WPET分布与充分供水情景下相似；雨养情景下小麦WPET为（0.29～1.57）kg/m3，平均值为 0.77kg/m3，玉米WPET为（0.86～2.13）kg/m3，平均值为1.47kg/m3；③饱和水汽压差（VPD）是影响作物水分生产力的主要气象因子，研究区域小麦生长季VPD北高南低的趋势使得小麦WPET呈北低南高分布特征；而玉米生长季VPD西高东低，玉米WPET呈西低东高的趋势。改善灌溉管理可提高作物WP，减少由土壤蒸发损失的非生产性耗水对提高作物WP也具有重要意义。
... 国内从资源利用角度出发的宏观土地生产力模型主要包括农用地分等定级和产能核算(郧文聚等, 2007)与ESLP模型(邓祥征等, 2009)等,这些模型在区域尺度上系统性地光、温、水、土以及管理因子多层次开展参数本地化的应用研究,但不同地区农业生产潜力的主要限制因素不尽相同,包括无霜期(王志强等, 2009)、旱涝盐碱灾害(陈超等, 2009)等,确定与农业生产过程相适应的各类有效系数无论在指标设定还是研究尺度方面均较粗略(郑海霞等, 2003) ...
陈建文, 贺安乾, 杨碧轩, 等. 1999. 陕北、渭北及关中气候生产潜力的估算与分布特征分析[J]. [Chen J W, He A Q, Yang B X, et al. 1999. Estimation and analysis of climatic potential productivity in arid and semiarid areas of Shaanxi Province[J].
利用陕西各气象台站1961年至1990年气象观测资料和1992年陕西省农业生产状况调查报表的资料,应用布达哥夫斯基连乘原理,引用了灌溉因子对陕西省陕北黄土高原沟壑区、渭北旱塬区和关中平原区三个气候区的光合生产潜力、光温生产潜力、气候生产潜力和综合气候生产潜力进行了估算,并将综合生产潜力计算结果通过小网格方法绘制成小网格分布图,分析了各气候区综合气候生产潜力的分布特征,以为上述地区的农业及多种经营的潜力开发提供气候依据.
... 蔡承智等, 2007)采用不同的线性函数进行温度有效系数修正,也有学者采用非线性函数进行修正(陈建文等, 1999) ...
邓祥征, 姜群欧, 战金艳. 2009. 中国土地生产力变化的情景分析[J]. 生态环境学报, 18(5): 1835-1843. [Deng X Z, Jiang Q O, Zhan J Y.
2009. Scenario analyses of land productivity in China[J]. Ecology and Environmental Sciences, 18(5): 1835-1843. ]
... 国内从资源利用角度出发的宏观土地生产力模型主要包括农用地分等定级和产能核算(郧文聚等, 2007)与ESLP模型(邓祥征等, 2009)等,这些模型在区域尺度上系统性地光、温、水、土以及管理因子多层次开展参数本地化的应用研究,但不同地区农业生产潜力的主要限制因素不尽相同,包括无霜期(王志强等, 2009)、旱涝盐碱灾害(陈超等, 2009)等,确定与农业生产过程相适应的各类有效系数无论在指标设定还是研究尺度方面均较粗略(郑海霞等, 2003) ...
韩士群, 严少华, 张建秋, 等. 2009. 滩涂池塘生态系统的光合能量利用及其影响因子[J]. [Han S Q, Yan S H, Zhang J Q, et al. 2009. Impact factors of photosynthesis energy utilization in the coastal fish ponds of Jiangsu Province[J].
The characteristics of primary productivity, utilization of solar energy efficiency and their impact factors under the different culture models were studied in the coastal fish ponds of Jiangsu. The results showed that there existed dynamic changes of the primary productivity (such as vertical distribution, daily variation and seasonal changes) in the water of fish ponds, and thus changes were directly related to the solar radiation intensity. The average net primary productivity (Pn) was (7.58±2.52) gO2/(m2·d), which was only about 55.41% of gross primary productivity (Pg). The ecological efficiency of transforming solar radiation energy to carp products was from 0.020% to 0.029%, the ecological indexes were lower in the coast fish ponds than the high-yield ponds, indicating that the ecosystem structure needs to be further optimized. The primary productivity of the water was significantly affected by the phytoplankton chlorophyll, solar radiation intensity, phytoplankton biomass, transparency, N/P ratio, Mg2+ concentration, but not significantly influenced by the contents of total salts and concentrations of Na+ and Cl- in the water.
研究了江苏沿海滩涂不同养殖模式下初级生产力特征、能量利用率及其影响因子。结果表明，滩涂养殖水体浮游植物的初级生产力存在垂直分布、日变化和季节的动态变化，这种变化与太阳辐射强度有直接的关系。滩涂养殖水体净初级生产量平均值为(7.58±2.52) gO2/(m2·d)，只占毛产量的55.41%，太阳能转化为鲢、鳙鱼产量的生态效率为0.020%~0.029%，这些指标低于我国高产养殖塘，鱼塘生态系统结构有待进一步优化。浮游植物生物量、透明度、N/P值、Mg2+浓度等因素显著影响水体初级生产力的大小，多元逐步回归表明浮游植物叶绿素含量和到达水体表面的太阳辐射强度是初级生产力的最主要因子，其回归方程为：Pg =0.0785Cha+0.0577 Iλ0+1.346；n=22， FCha>F Iλ0>F0.1，而盐度、Na+、Cl-浓度影响不显著。
... 目前,在沿海滩涂地区滩涂湿地的初级生产力已受到学术界的广泛关注(韩士群等, 2009 ...
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粮食是我国人民的主要食物,也是畜牧业、渔业、林业、农副产品加工业及工业得以顺利发展的重要物质基础。随着社会人口的增加及人们物质生活水平的提高,粮食的需要量将日趋增加,需求标准将越来越高。我国人口众多,耕地较少,自然灾害频繁,必须有一定数量的储备粮。粮食问题处理是否得当,关系整个国民经济的发展和人民生活水平的提高。
蒋蕊竹, 李秀启, 朱永安, 等. 2011. 基于MODIS黄河三角洲湿地NPP与NDVI相关性的时空变化特征[J]. [Jiang R Z, Li X Q, Zhu Y A, et al. 2011. Spatial-temporal variation of NPP and NDVI correlation in wetland of Yellow River Delta based on MODIS data[J].
Study of vegetation productivity and carbon sequestration of wetland ecosystem is a main research topic of global carbon cycle and global change. The ecosystem productivity study of Yellow River Delta, a wetland delta with fastest reclamation speed in China and in the world, is therefore extremely important. Due to human activities have affected all of ecological systems, to find an expeditious way to assess the ecosystem health becomes the major topic of current study. Net primary productivity (NPP) is a key component of terrestrial carbon cycle, and it is defined as the accumulative organic matters by green plants per unit of time and space. NPP, the direct reflection of plant community productivity for a certain natural environment, is the basis of matter and energy cycles of terrestrial ecosystem. The Normalized Difference Vegetation Index has been used for many years to measure and monitor plant growth, vegetation cover, and biomass production from multispectral satellite data. It is an indicator of vegetation growth and its spatial distribution has a close relationship with climate conditions. We use MODIS NPP and NDVI data to analyze the characteristics of spatial-temporal variation of NPP and NDVI in Yellow River Delta between 2001 and 2006. Distribution of NDVI shows that soil water-salt distribution is the main controlling factor of plant growth in the delta. The distribution of primary productivity has been obviously affected by human activities. We further built a new coastal regression model. As the changeable different regions which have different distances from the coastline and which have different lengths, we discuss the correlation between annual NPP (aNPP) and average annual NDVI (ANDVI). Results suggest that distribution of wetland ecosystems in the Yellow River Delta has obvious spatial heterogeneity from sea to land, along with the ecosystem succession. Mud flat along the coastline is a place for developing ecosystem with a large amount of pioneer plants, which has high productivity and their aNPP is positively related to ANDVI. Saline-alkali land has a low lever of aNPP because of higher co Agricultural land is a developed mature ecosystem in which the nutrition circulates only inside the ecosystem and affected mostly by human activities. Thus there is no directly relationship between aNPP and ANDVI in saline-alkali land and agriculture land, Consequently, we preliminarily discussed the feasible regions in the Yellow River Delta that can use MODIS NDVI to monitor their productivity. In the region where the distance to coastline is less than 6km, all of six simple regression models for each year passed the significant F-test (α=0.01, R2 0.86 - 0.97). Finally, to understand the time differentiation characteristics of correlation coefficient between ANDVI and aNPP, we calculated the percentage size and the average aNPP with different ANDVI value range. We figured out that resource competition may be one of the fact making the correlation coefficient difference. Therefore, we can use NDVI to effectively monitor and manage the ecosystems and to increase their productivity. Based on the research of the ecosystem productivity of Yellow River Delta, we can effectively understand the regularity for change of productivity during the rapid economic development period, which can further guide the administration of local ecosystems.
应用EOS/MODIS卫星遥感资料,分析年黄河三角洲地区植被净初级生产NPP及NDVI时空变化特征,在到海岸线不同距离的区域内,讨论了年植被净初级生产力(aNPP)与年均归一化植被指数(ANDVI)的相关性,并建立一元回归分析模型。可以看出,黄河三角洲湿地生态系统分布自海向陆具有明显的空间异质性,滩涂湿地分布于沿海地区,生产力高,该地区aNPP值高且与ANDVI呈显著正相关;其他区域由于是盐碱荒地或农业生态系统,因土壤盐分含量高而系统生产力低,或农耕地受人类干扰严重,一年总的生产力下降,而导致这些区域ANDVI与aNPP呈负相关。利用NDVI进行黄河三角洲生产力监测的可行区域,在距离海岸线小于6_km的范围内,所研究的6a回归模型均通过α=0.01的显著水平的F检验,模型的R2值为0.86-0.97。同时在生产力无法估测的区域,可以使用NDVI有效管理黄河三角洲生态系统,提高其生产力水平。
... 蒋蕊竹等, 2011),但对滩涂围垦区的土地生产力潜力估算研究还比较薄弱 ...
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1992. Research on the potential agricultural productivity of China with the help of GIS[J].
This paper makes a study of the distribution of the potential agricultural productivity of China with the help of geographical information system (GIS).On the basis of the researches of others, the writer chooses appropriate mathematical model and parameters, collects meteorological data of 30 years () and distribution data of physical and chemical characterastics and nutritions conditions of zonal soils (or large-area soils) of China, creates a data base, calculates the potential agricultural productivity of China, and draws a series of maps. The work is with the help of ARC/INFO system, a software of GIS.This paper analyses all the factors influencing potential agricultural productivity. They are sunlight, temperature, water condition and soil condition. The soil condition is analysed by a new method that uses eight factors, namely, soil texture, pH value, nitrogen content, phosphorus content, potassium content, organic matter content, soil erosion status and soil alkalinity status, classifying each of them and giving every class a mark so as to know the soil condition of a region and to calculate its soil availability coefficient.This paper also devides the potential agricultural productivity of China into 9 classes and describes their distribution.
本文在地理信息系统的支持下,分析了全国671个气象台站的30年地面气象资料及地带性或大面积土壤的物化性质及养分状况资料,对影响生产潜力的光、温度、水分、土壤诸要素分别进行了分析、计算,尤其对土壤要素的处理进行了新的尝试,计算了我国的农业生产潜力。
... 在一定的自然地理背景下,即光、温度、水分大致一定的情况下,土地生产潜力存在阈值,改变客观不利因素,力争发挥最大生产潜力,是生产力研究的重要目标(冷疏影, 1992) ...
李春云, 戴玉杰, 宋玉红, 等. 2001. 蒸发势的一种计算方法[J]. [Li C Y, Dai Y J, Song Y H, et al. 2001. A method for calculating the evaporation potentia[J].
A empirical method for calculating the evaporation potential is discussed. It is the function of three factors: average air temperature, relative humidity and wind speed. The correlation analysis is made between the obtained values and Penman evaporation potential values, as well as evaporation capacity observed with a E601 Evaporimeter and a small-sized evaporimeter. The correlation coefficients are above the remarked level and very stable. It can be concluded preliminarily that the method is applicable to the local area, easy to understand, easy to use and can be used along with concerned indexes very well, for example Xerothermic winds. It obtained success in estimating the moisture profit and loss, and has significance in analyzing Xerothermic winds and droughts.
讨论蒸发势的一种经验计算方法，考虑了平均气温、相对湿度、风速3种要素.其数值与彭曼蒸发势值，与用E601蒸发器、小型蒸发器观测的蒸发量(以下分别简称E601蒸发量，小型蒸发量)作相关分析，相关系数都在极显著水平以上，而且很稳定.因此，初步认为这种计算法适合于本地.本计算方法通俗易懂，便于掌握和使用，与有关指标(例如干热风指标)可以较好地衔接.利用本计算方法所得结果在评估水分盈亏时取得了明显的成效，在干旱和干热风分析中有重要的实际意义.
... 作物蒸散量(ET0)计算公式(李春云等, 2001)如下： ...
... 梁佳勇等, 2004),以及土壤有效系数修正,其模型为： ...
... 梁佳勇等, 2004),以及喜凉作物和喜温作物(曹卫星, 2006 ...
... 本文采用的光合有效系数参数见表1(林文鹏等, 2000 ...
... 很多学者分别对C3和C4作物(林文鹏等, 2000 ...
... 中国学者50年代开始研究农作物生产与气候的关系(任美锷, 1950 ...
... 近代以来如东县一直开展滩涂围垦工作,用于农业生产、水产养殖以及国营盐场(任美锷, 1996) ...
汤勇华, 黄耀. 2008. 中国大陆主要粮食作物基础地力贡献率及其影响因素的统计分析[J].
通过对国内大量文献数据的调研和整理,采用数理统计方法,研究了中国大陆3种主要粮食作物(水稻、小麦和玉米)地力贡献率的统计特征及其与地理位置和土壤理化性质的定量关系.统计分析表明,水稻、小麦和玉米地力贡献率的空间变异总体呈正态分布,3种作物地力贡献率的均值和标准差依次为60.2%±12.5%(n=121)、45.7%±15.7%(n=91)、51.0%±19.7%(n54).单因子相关分析表明,各类作物在不同种植区的地力贡献率与土壤基本特性及地理位置间存在显著的相关关系.基于相关分析结果,采用逐步回归分析方法,分别建立了北方和南方单季稻、冬小麦;双季早稻、双季晚稻、春小麦、春玉米和夏玉米地力贡献率的统计模型.残差分析结果表明,所建立的统计模型具有较好的解释性,可用于估算不同作物的地力贡献率,为制定区域尺度农田施肥策略和控制农业面源污染提供依据.
... 衡量土壤施肥对作物产量的贡献一般用基础地力贡献率表示,其值为不施肥时的作物产量与适宜肥料施用下的产量之比,与作物类型、气候和土壤特性等因素密切相关,变幅在20%~75%(汤勇华等, 2008, 2009 ...
... 基于统计学和实验数据以及Maas-Hoffman模型得到的土壤基础地力以及土壤盐分与作物产量关系来确定土壤有效性系数(汤勇华等, 2008, 2009),相对于主观地对土壤因子进行评价打分更具有可行性 ...
汤勇华, 黄耀. 2009. 中国大陆主要粮食作物基础地力贡献率和基础产量的空间分布特征[J]. [Tang Y H, Huang Y.
2009. Spatial distribution characteristics of the percentage of soil fertility contribution and its associated basic crop yield in mainland China[J].
利用农业统计数据和土壤属性数据,将业已建立的地力贡献率统计模型与GIS技术耦合,研究了中国大陆3种主要粮食作物(水稻、小麦和玉米)的地力贡献率和基础产量的空间分布特征.结果表明,地力贡献率和基础产量空间分布差异较大.其中,玉米的生长受钾素的影响较大,高值区分布在华北平原和东北春玉米区,基础产量和地力贡献率分别为3.43 t·hm-2和51%;低值区分布在华中华南一带,为1.90t·hm-2和33%.其余作物的高产区分布在东部沿海以及长江黄淮流域,特别是华东华中和四川盆地,低产区主要分布在华北以北以及西南丘陵地带.统计分析表明,地力贡献率和基础产量对水稻生产的贡献最大,且空间变异小.冬小麦地力贡献率和基础产量的变异系数均大于其他各作物.该研究能较好地模拟我国3种作物的基础产量,可为区域尺度农田指导施肥和控制农业生态环境胁迫提供依据.
... 衡量土壤施肥对作物产量的贡献一般用基础地力贡献率表示,其值为不施肥时的作物产量与适宜肥料施用下的产量之比,与作物类型、气候和土壤特性等因素密切相关,变幅在20%~75%(汤勇华等, 2008, 2009 ...
... 南方冬小麦的统计模型(汤勇华等, 2009)如下： ...
... 基于统计学和实验数据以及Maas-Hoffman模型得到的土壤基础地力以及土壤盐分与作物产量关系来确定土壤有效性系数(汤勇华等, 2008, 2009),相对于主观地对土壤因子进行评价打分更具有可行性 ...
... 杨重一等, 2010) ...
... 杨重一等, 2010),如式(6)-(7)所示 ...
杨恒山, 王芳, 张冬梅, 等. 1999. 哲里木盟4种主要农作物气候生产潜力变化及对比分析[J]. [Yang H S, Wang F, Zhang D M, et al. 1999. A compariative analysis on the potential productivities of the main crops in Zhelimu League impacted by climatic variation[J].
分析了哲里木盟玉米、水稻、高 梁、大豆４ 种主要作物近４５ 年光能、光温、气候生产潜力的变化，结果表明：生长季内（５ ～９ 月） 光能生产潜力在波动中有减小的趋势；温度升高，对４ 种作物光温生产潜力有不同程度的提高，其中对玉米、水稻、高粱的影响明显大于对大豆的影响；降水变化对生产潜力的影响远大于温度变化的影响，其中降水对玉 米气候生产潜力的影响高于对高粱、大豆的影响。从生产潜力的大小及其变化来看，玉米和水稻是适应当地气候变化的优势作物，降水量不足是影响生产潜力发挥的 主要限制因子
... 2 研究方法土地生产潜力模型是在光合生产潜力模型的基础上,开展温度订正(杨恒山等, 1999),水分订正(张强等, 1995 ...
... 由于作物生长对温度环境的变化的适应能力的复杂性,本文采用非线性温度修正方法(杨恒山等, 1999 ...
... 联合国粮农组织(FAO)将作物生育期分为4个阶段分别为初始生长期、生长发育期、中期和末期(尹海霞等, 2012) ...
... 作物需水系数和作物缺水敏感系数与作物生育期有关(尹海霞, 2012) ...
尹钧, 苗果园. 1992. 山西省小麦气候生产潜力的评价[J]. [Yin J, Miao G Y.
1992. Evaluation of the meteorological potentiality of wheat production in Shanxi[J].
生产潜力的评价是农业生产区域化和因地制宜发展生产的基础,也是确定高效农业投资方向和商品粮基地建设的依据。山西省小麦光合生产潜力为800—1500公斤/亩,光能利用率3%左右;光温生产潜力为700—1100公斤/亩,光能利用率2.4%左右;气候生产潜力为400—600公斤/亩,光能利用率1.1—1.4%;现实生产水平不足200公斤/亩,光能利用率仅0.54%左右,小麦生产具有很大的潜力。目前应采取以培肥地力为中心中综合技术。把东西部丘陵山区作为重点,通过提高水分利用率,开发小麦气候生产潜力。
... 国内从资源利用角度出发的宏观土地生产力模型主要包括农用地分等定级和产能核算(郧文聚等, 2007)与ESLP模型(邓祥征等, 2009)等,这些模型在区域尺度上系统性地光、温、水、土以及管理因子多层次开展参数本地化的应用研究,但不同地区农业生产潜力的主要限制因素不尽相同,包括无霜期(王志强等, 2009)、旱涝盐碱灾害(陈超等, 2009)等,确定与农业生产过程相适应的各类有效系数无论在指标设定还是研究尺度方面均较粗略(郑海霞等, 2003) ...
王千, 金晓斌, 周寅康. 2011. 江苏沿海地区耕地景观生态安全格局变化与驱动机制[J]. [Wang Q, Jin X B, Zhou Y K.
2011. Dynamic analysis of coastal region cultivated land landscape ecological security and its driving factors in Jiangsu[J].
Jiangsu coastal district are dramatic and fragile ecosystem sensitive areas. which located in north of the subtropical and warm temperate zone in the transition zone, and beach land resources are very rich, density of water network. Coastal areas is an important grain, cotton, oil origin of of Jiangsu Province. Under the "coastal development strategy", the implementation, resulting in dramatic changes in land use pattern, over increasing competition between classes, of cultivated land as the essence of the land, its security is more and more attention. In this paper, as the study area along the coast of Jiangsu Province, based on landscape ecological security theory, remote sensing and spatial analysis, landscape ecology from a safety point of land estimated 20 counties of the coastal landscape ecological security index, on this basis, focusing on the
arable land in Jiangsu coastal ecological security structure change and driving. The results showed: in 19 coastal counties and cities in Jiangsu Province, the safety of farmland landscape, combined with Nature Break method, can be divided into three levels, Ⅰ-class district, ES ≤ 0.45, Ⅱ grade zone, 0.45
0.75. Coastal Region farmland landscape security pattern was significantly different characteristics, ecological security landscape in 1995, cultivated land, Ⅰ level mainly distributed in the northern entrance for the study area, Lianyungang City, Guanyun, such as 5 Guannan and Xiangshui counties, Ⅱ grade mainly distributed in the study area, north-central region Funing, coastal counties, Jianhu, Donghai County, Yancheng, and the 5 counties, Ⅲ grade mainly distributed in central and southern study area 10 compared to , Landscape ecological security grade Ⅰ cultivated area increased by Donghai County, the coastal counties and Funing, mainly in the northern study area, Ⅱ grade distribution more dispersed areas include Jianhu, Yancheng, Rugao City, County and MSC, Ⅲ grade zone in 1995 based on the reduction of the coastline and R to 2005 in Jiangsu Province-level ecological security of coastal farmland landscape area on the basis of 2000 continued to expand, mainly In the northern study area, Ⅱ grade areas mainly concentrated in the southern region, Ⅲ grade areas concentrated in the central study area, including Sheyang County, a large County, eastern Taiwan counties and Rudong., Jiangsu Province, ecological security of coastal farmland landscape pattern change of the main features, Ⅰ-class areas are more significant pattern changes, mainly grade Ⅰ area north to the south-central region by the expansion of its scope be changed by the District Level Ⅱ The main proof from the man-land relationship began to change tension in the region, such as the sound of water, Funi Ⅱ-class areas are more dispersed pattern changes, mainly to grade Ⅱ Ⅲ lev farmland landscape-level ecological security zone Ⅲ narrowing the scope, mainly on the grounds in the southern region to reduce the central region, from inland to coastal areas to promote, such as the Yancheng City, Rugao City,
MSC County Farmland landscape ecological security changes are a manifestation of this feature. Regression model for the landscape ecological security index and the driving factor analysis, regression model showed that in
the county level in Jiangsu coastal farmland landscape pattern change and ecological security were the main drivers of the national economy the size of GDP> Population density> road density> the number of land consolidation projects> regional construction land ratio.
沿海地区是土地利用变化剧烈区,同时也是生态系统敏感脆弱区。以江苏省沿海为研究区,基于景观生态安全理论,结合遥感技术与空间分析技术,从景观生态安全角度测算沿海19个县耕地景观生态安全指数,在此基础上,重点讨论年江苏沿海地区耕地景观生态安全格局变化特征与驱动机制。研究结果显示:江苏沿海地区15a来耕地景观安全格局变化显著,Ⅰ级区范围呈扩大趋势,Ⅱ级区格局变化较为分散,Ⅲ级区的范围逐渐缩小,呈现由南部地区向中部地区减少,由内陆向沿海推进的格局变化特征;回归模型显示,县级层次耕地景观生态安全主要驱动力为土地整理项目数量、国民经济总产值和人口密度,其回归系数分别为0.253、-0.224和-0.176。
... 王千等, 2011),构建沿海滩涂围垦区土地生产潜力模型,了解该地区土地生产潜力大小是沿海开发的重要基础性工作,同时也关系到沿海地区的农业可持续发展,对新增资源评价利用等相关研究具有一定参考价值 ...
... 国内从资源利用角度出发的宏观土地生产力模型主要包括农用地分等定级和产能核算(郧文聚等, 2007)与ESLP模型(邓祥征等, 2009)等,这些模型在区域尺度上系统性地光、温、水、土以及管理因子多层次开展参数本地化的应用研究,但不同地区农业生产潜力的主要限制因素不尽相同,包括无霜期(王志强等, 2009)、旱涝盐碱灾害(陈超等, 2009)等,确定与农业生产过程相适应的各类有效系数无论在指标设定还是研究尺度方面均较粗略(郑海霞等, 2003) ...
曾祥明, 韩宝吉, 徐芳森, 等. 2012. 不同基础地力土壤优化施肥对水稻产量和氮肥利用率的影响[J]. [Zeng X M, Han B J, Xu F S, et al. 2012. Effect of optimized fertilization on grain yield of rice and nitrogen use efficiency in paddy fields with different basic soil fertilities[J].
【Objective】 The effects of optimized fertilization on grain yield of rice and nitrogen use efficiency in paddy fields with different basic soil fertilities in Jianghan plain of China were studied. 【Method】 Three-year field trials were carried out to investigate the differences in grain yield, soil N dependent rate (SNDR), N fertilization contribution rate (NCR) and the N fertilization efficiency of the popular middle rice variety Fengliangyouxiang1 in three treatments, including modified farmers& fertilizer practice (MFP), farmers& fertilizer practice (FFP) and the control, in Jianghan plain, China. 【Result】 The results showed that the grain yield of MFP was the highest among all the three different nitrogen fertilizer treatments in all the field spots with different basic soil fertilities. The grain yield of MFP increased by about 6.9% and 5.0% in the high soil fertility field (HSF) and low soil fertility field (LSF) compared with the treatment of FFP, and about 17.3% and 30.3% in HSF and LSF compared with the control, respectively. Moreover, the N recovery efficiency (NRE), N agronomic efficiency (NAE) and partial factor productivity of applied N (PEPN) of MFP increased more greatly compared with that of FFP. The contribution of N fertilization to the grain yield in the LSF was significantly more than that in the HSF; however, low soil N dependent rate and good grain yield potential were observed in the LSF. 【Conclusion】 Optimized fertilization reduced the relative contribution of basic soil fertilities to the grain yield of rice and increased N fertilization efficiency.
1.华中农业大学农业部长江中下游耕地保育重点实验室，武汉 430070&br /&2.华中农业大学作物生理生态与栽培研究中心，武汉 430070
【目的】研究江汉平原地区不同基础地力土壤和优化施肥对水稻产量和氮肥利用率的影响。【方法】以江汉平原水稻主推品种丰两优香一号为试验材料，通过3年田间小区试验，考察分析土壤基础地力不同的稻田优化施肥、农民习惯施肥和不施肥处理的产量、氮肥贡献率、土壤氮素依存率和氮肥利用率等的差异。【结果】土壤基础地力不同的稻田均是优化施肥处理的产量最高，与农民习惯施肥处理比较，高地力和低地力稻田优化施肥处理的产量分别平均提高6.9%和5.0%；与不施肥处理比较，产量分别平均提高17.3%和30.3%。与农民习惯施肥处理比较，优化施肥处理的氮肥吸收利用率、农学利用率和偏生产力均大幅度提高。高地力稻田土壤氮素依存率高、氮肥贡献率小、施肥增产的潜力小；低地力稻田土壤氮素依存率低、氮肥贡献率大、施肥增产的潜力大。【结论】优化施肥可以降低水稻产量对土壤基础地力的依赖，提高氮肥利用率。
... 曾祥明等, 2012) ...
郑海霞, 封志明, 游松财. 2003. 基于GIS的甘肃省农业生产潜力研究[J]. [Zhen H X, Feng Z M, You S C.
2003. A study on potential land productivity based on GIS technology in Gansu province[J].
Based on previous researches on potential agricultural productivity and supported by geographical information system (GIS) technology and agricultural databases which include spatial databases and attribute databases, potential land productivity in Gansu province was studied? By using the mechanism methodology, the model of potential agriculture productivity was established? Effective coefficients for factors such as radiation, temperature, water a then potential photosynthesis productivity, potential temperature productivity, potential precipitation productivity, potential agricultural water resources productivity and potential land productivity in Gansu province were calculated? The results show the spatial distribution inconsistency between agricultural production and agricultural resources in Gansu province, and this reveals the different limitation of radiation, temperature, water and land effective coefficient to agricultural production.
Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101
在气象数据库、属性数据库和GIS支持下,采用机制法对作物生产潜力模型进行了光、温、水、土逐级订正,得到了甘肃省的光合、光温、降水、水资源及土地的生产潜力,其结果很好的反映了甘肃省农业生产和农业资源分布的空间格局,各级订正的有效系数进一步揭示了各种资源因子对农业生产的限制程度。
... 国内从资源利用角度出发的宏观土地生产力模型主要包括农用地分等定级和产能核算(郧文聚等, 2007)与ESLP模型(邓祥征等, 2009)等,这些模型在区域尺度上系统性地光、温、水、土以及管理因子多层次开展参数本地化的应用研究,但不同地区农业生产潜力的主要限制因素不尽相同,包括无霜期(王志强等, 2009)、旱涝盐碱灾害(陈超等, 2009)等,确定与农业生产过程相适应的各类有效系数无论在指标设定还是研究尺度方面均较粗略(郑海霞等, 2003) ...
郑剑非, 卢志光. 1982. 北京市冬小麦气候生产潜力及干旱期间最佳灌水方案[J]. [Zhen J F, Lu Z G.
1982. The climate potential productivity of wheat in Beijing and the optimal irrigation scheme during the drought[J].
本文目的是探讨在当前北京市水资源紧张前提下小麦生产栽培管理中的最佳灌溉方案。为达此目的,第一步首先估算出北京市冬小麦光温生产潜力,即满足其他条件情况下可能达到的最高产量,进而再论述不同生育时期水份供应条件对产量的影响。
... 各参数如表3所示(郑剑非, 1982) ...
张强, 杨贤为, 黄朝迎. 1995. 近30年气候变化对黄土高原地区玉米生产潜力的影响[J]. [Zhang Q, Yang X W, Huang C Y.
1995. Impact of climatic variation in maize productive capacity in the Loess Plateau area in recent 30 years[J].
摘　要： 应用黄土高原地区７２站６０－８０年代的气象条件，分析了气候变化对玉米生产潜力的影响。结果表明，虽然整个黄土高原８０年代年平均气温有变暖趋热，但影响玉米生产期内的温度并没有增高，反面有所降低，以至８０年代玉米的光渐生产潜力均较６０、７０年代减少。由于降水变化的影响，除陕西省外，其它省区８０年代气候生产潜力均高于６０、７０年代。
... 2 研究方法土地生产潜力模型是在光合生产潜力模型的基础上,开展温度订正(杨恒山等, 1999),水分订正(张强等, 1995 ...
周生路, 吕蕾. 2006. 江苏沿海耕地资源量空间分布态势与评价[J]. [Zhou S L, Lv L.
2006. Spatial distribution of farmland resources in the coastal region of Jiangsu[J].
首先采用农用地分等中自然质量分值的计算方法对江苏沿海耕地自然质量进行测算,然后在此基础上结合各乡镇耕地面积和人口数量计算人均耕地量,对江苏沿海地区耕地资源量的空间分布态势进行评价.结果表明:研究区北部、中西部和南部除少数地区外耕地质量总体较好,中东部耕地质量较差;耕地质量优良的地区人均耕地量水平较低,耕地质量较差的地区人均耕地量水平反而较高.根据评价结果,从提高土地整体利用效率、合理占用耕地、合理开发土地后备资源、污染排放源头控制与生产过程中治理相结合等几个方面提出了沿海地区耕地资源可持续利用的有效途径.
... 沿海滩涂土壤是中国重要的耕地后备资源基地之一(周生路等, 2006 ...
竺可桢. 1964. 论我国气候的几个特点及其与粮食作物生产的关系[J]. 地理学报, 30(1): 189-199.
... 竺可桢, 1964),考虑光、温、水、土等自然因子以及人类耕作、施肥、灌溉等农业管理技术,根据作物能量转化过程来逐步估算农业生产潜力大小 ...
... Ayers et al, 1985)得到土壤盐分和水稻和小麦作物产量的数学关系,如式(13)和(14)所示 ...