基于APSIM模型小麦生育期需水量的模拟分析

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雷娟娟, 闫丽娟, 李广, 聂志刚, 王钧, 董莉霞. 基于APSIM模型小麦生育期需水量的模拟分析. 草业科学, 2016,33(5):871-877
Lei Juan-juan, Yan Li-juan, Li Guang, Nie Zhi-gang, Wang Jun, Dong Li-xia. Simulation on water requirement of wheat during growth period by APSIM. Pratacultural Science,2016,33(5): 871-877 复制到剪切板

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基于APSIM模型小麦生育期需水量的模拟分析

雷娟娟¹, 闫丽娟², 李广^1,³, 聂志刚⁴, 王钧⁴, 董莉霞⁴

1.甘肃农业大学资源与环境学院,甘肃兰州 730070

2.甘肃农业大学农学院,甘肃兰州 730070

3.甘肃农业大学林学院,甘肃兰州 730070

4.甘肃农业大学信息科学技术学院,甘肃兰州 730070

李广(1971-),男,内蒙古化德人,教授,博导,博士,主要从事农业系统工程等教学和科研工作。E-mail:lig@gsau.edu.cn

第一作者:雷娟娟(1989-),女,甘肃庆阳人,硕士,主要从事理论生态学等方面的研究。E-mail:1140313073@qq.com

收稿日期: 2015-03-10

基金: 国家自然科学基金(31560343、31560378); 甘肃省科技支撑计划(144NKCA038); 甘肃省高等学校基本科研业务费项; 干旱生境作物学重点实验室开放基金(GSCS-2010-11); 甘肃省高等学校科研项目(2014A-058); 甘肃省青年基金(1506RJYA005)

摘要

为探讨小麦( Triticum aestivum)生育期水资源的合理利用,本研究运用APSIM模型模拟不同生育期降水量变化条件下小麦的产量,并求得不同生育期小麦需水量的阈值。结果表明,区域降水年型基本呈旱涝交替出现;小麦生育期总需水量为325.3 mm;其中,出苗期、拔节期、抽穗期、旗叶期、开花期和灌浆期需水量分别为34.72、80.6、67.1、43.81、58.67和30.4 mm,分别占小麦生育期降水总量的10.67%、27.85%、20.63%、13.47%、18.04%和9.35%。出苗期、拔节期、抽穗期、旗叶期、开花期和灌浆期平均降水亏缺率分别为70.78%、48.83%、46.22%、40.35%、75.66%和-121.05%;春小麦需水关键期为出苗期、拔节期、开花期。

关键词: APSIM; 小麦生育期; 需水量; 小麦产量

中图分类号:S512.107 文献标志码:A 文章编号:1001-0629(2016)5-0871-07 doi: 10.11829/j.issn.1001-0629.2015-0047

Simulation on water requirement of wheat during growth period by APSIM

Lei Juan-juan¹, Yan Li-juan², Li Guang^1,³, Nie Zhi-gang⁴, Wang Jun⁴, Dong Li-xia⁴

1.College of Resources and Environmental, Gansu Agricultural University, Lanzhou 730070, China

2.College of Agronomy, Gansu Agricultural University, Lanzhou 730070, China

3.College of Forestry Science, Gansu Agricultural University, Lanzhou 730070, China

4.College of Information Science and Technology, Gansu Agricultural University, Lanzhou 730070, China

Corresponding author: Li Guang E-mail: lig@gsau.edu.cn

Abstract

To find the rational use of water resources for wheat growth periods, this study used the APSIM model to simulate wheat yield under different growth periods with changeable rainfall and estimate the threshold value for requirement of wheat for water at different growth periods. This study showed that the regional precipitation pattern generally showed an alternation from droughts to floods, and the requirement of wheat for water during whole growth periods was 325.3 mm, in which the requirements of wheat for water during emergencing, jointing, heading, flag leaf, flowering and grain filling periods were 34.72, 80.6, 67.1, 43.81, 58.67 and 30.4 mm, respectively, and accounting for 10.67%, 27.85%, 20.63%, 13.47%, 18.04% and 9.35% of total precipitation during wheat growth periods. Precipitation deficitwas 70.78%, 48.83%, 46.22%, 40.35%, 75.66%, -121.05% at, jointing, heading, flag leaf, flowering, grain filling period, respectively, which indicated that the key periods of spring wheat for requiring water were emergencing, jointing and flowering period.

Keyword: APSIM; wheat growth period; requirement for water; wheat production

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气候变化对人类生存环境以及自然生态系统都产生了显著影响, 尤其对农业及水资源利用直接而深远。农业发展受水资源的限制, 水资源的时空分布与数量变化会直接影响农业生产^{[1, 2]}。农业用水的主体是作物需水量, 对农作物需水量进行研究, 有利于提高水的生产力以及有效地进行灌溉^[3]。

杨琪等^[4]利用公式得到甘肃河东地区近50年来冬、春小麦(Triticum aestivum)全生育期的需水量与缺水量, 并分析了其变化趋势, 结果表明, 对春小麦需水量影响最大的气象因子是日平均温度、相对湿度和风速。而通过田间试验对冬小麦、春玉米(Zea mays)间作条件下作物需水规律的研究^[5]则为间作种植的水分管理提供参考; 胡志桥等^[6]采用水量平衡法, 对石羊河流域春小麦的需水量进行了研究, 结果表明春小麦全生育期需水量为480.5 mm, 需水关键期为拔节期、抽穗期和开花期。而根据田间实测资料, 采用FAO-PM公式计算昆明1972―2007年小麦各生育期的需水量和缺水率, 认为昆明小麦生育期重度水分亏缺, 严重影响了小麦的年际生长发育和产量^[7]; 同样, 利用FAO-PM公式估算了黑河中游小麦作物需水量, 发现小麦作物需水量整体分布具有由南至北递增的趋势^[8]。APSIM(Agricultural Production System Simulator)是用于模拟农业生产, 由澳大利亚农业生产系统研究所(APSRU)开发。国内学者已对该模型的适用性进行了验证与调试^{[9, 10]}。李广和黄高宝^[11]为研究耕作措施对土壤水分与作物生长发育的影响, 对APSIM模型的适应性进行了研究, 结果表明此模型可用于甘肃旱作区作物生长的模拟。甘肃省定西地区属于季风气候区与非季风气候区的过渡带, 是典型的大陆温带干旱半干旱气候^[12], 对该地区春小麦生育期水资源的合理利用的研究鲜有报道。本研究利用APSIM模型, 根据定西试验点多年实测气候及田间资料, 对小麦产量形成过程进行模拟, 并计算出定西春小麦各生育期的需水量, 分析其影响程度, 以期为甘肃旱作区的节水农业提供一定理论依据。

1 材料与方法

1.1 试验区概况及小区设置

田间试验于2002-2005年在甘肃省定西市安定区李家堡乡甘肃农业大学旱农试验站进行, 研究区属陇中黄土高原, 是典型的雨养农业区, 一年一熟制, 春小麦是当地种植面积最大的作物。多年平均降水量391.0 mm, 年蒸发量1 531 mm。海拔2 000 m, 年均太阳辐射592.9 kJ· m^-2, 日照时数2 476.6 h, 年均气温6.4 ℃, ≥ 0 ℃年积温2 933.5 ℃· d, ≥ 10 ℃年积温2 239.1 ℃· d, 无霜期140 d。供试作物为定西35号春小麦。

从1981-2010年研究区的降水量年际变化特征图可以看出(图1), 春小麦休闲期30年的年均降水量为181.75 mm, 最大降水量为310.1 mm(2003年), 最大降水量为最小降水量的2.8倍; 春小麦生育期30年的年降水量为199.77 mm, 最大降水量为289.9 mm(1999年), 最大降水量为最小降水量的3.6倍。研究区30年来降水量的年际变异很大, 变异系数为16.45%, 休闲期变异系数为25.71%, 生育期变异系数为26.70%, 年际小麦生育期最大降水量变异系数为34.94%。

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	图1 1981-2010年降水量年际变化Fig.1 The inter-annual change of precipitation from 1981 to 2010

1.2 APSIM模型

APSIM-Wheat可以动态模拟小麦地上和地下部分的生长状况, 有研究^[11]表明, APSIM 可依据小麦不同生产阶段的降水量来判断产量。该模型包括4个模块:小麦生长(NWHEAT)、土壤肥力(SOILN)、土壤水分(SOILWAT)和作物残余物(RESIDUE)。APSIM-Wheat模型运行所需数据包括气象数据、作物数据、土壤数据、栽培措施数据与试验点的经纬度、海拔等^[13]。

1.2.1 APSIM模型核心 APSIM 模型由4 部分组成: 生物物理模块, 用来模拟农业系统中生物和物理过程; 管理模块, 控制模拟及发展用户定义模拟过程的管理措施; 中心引擎, 驱动模拟过程及控制不同模拟信息的传递; 调用模块, 管理各种模拟过程数据的“ 进出” 。

1.2.2 APSIM 土壤水分模块 APSIM中的土壤水分模块是基于层叠(Cascade)水分平衡模型, 利用了CERES和PERFECT模型中水分模块。土壤的水分特征曲线由萎蔫系数(LL15)、最大田间持水(DUL)、作物利用下限(CLL)和饱和体积含水量(SAT)来表示。APSIM相比CERES和PERFECT的优越之处在于水分模块对水分动态的模拟为逐日、连续的; 可计算逐日每一土层中大于最大田间持水的饱和含水量部分, 这部分饱和水分将移向下层; 不同的土壤类型采用的土壤扩散系数不同; 邻近层次中非饱和水流可以运动, 直到达到特定的水分梯度为止。不同的土壤类型采用的径流曲线不同, 其值从0~100不等, 采用了美国农业部USLE模型的径流曲线, 土壤蒸发参照CERES模型^[14]。

1.3 数据分析

模拟试验中, APSIM平台参数均来源于李广等^[10]研究者在黄土丘陵沟壑区APSIM适用性研究中经过反复本土化修订的参数。运用本土化的APSIM模型, 对1981-2010年传统耕作措施下的小麦产量进行模拟, 并以天为单位模拟田间日降水量, 接着计算每年小麦不同生育期的降水量, 包括:出苗期(第79-95天)、拔节期(第96-139天)、抽穗期(第140-158天)、旗叶期(第159-174天)、开花期(第175-181天)、灌浆期(第182-211天)。运用Excel和DPS软件进行相关性分析和多元回归分析。春小麦各生育期需水量由回归分析方法计算。

降水亏缺率计算公式为:

β _w= $\begin{matrix} \{\begin{matrix} (E T_{m} - R) / E T_{m} \times 100 % & R < E T_{m} \\ 0 & R \geq E T_{m} \end{matrix}\} \end{matrix}$ .

式中:β _w为降水亏缺率(%), R为小麦各生育期的降水量, ET_m为小麦各生育期的需水量(mm)^{[15, 16]}。

在管理要素、作物品种、土壤类型等完全相同的情况下, 运用APSIM模型对研究区域1981-2010年的小麦产量进行模拟, 并以天为单位模拟田间日降水量, 接着计算每年小麦不同生育期的降水量。选择出苗期降水量、拔节期降水量、抽穗期降水量、旗叶期降水量、开花期降水量、灌浆期降水量、小麦休闲期降水量作为自变量因子, 以小麦产量为因变量, 对所有变量进行无量纲化处理之后, 利用DPS软件进行回归分析。无量纲化方法为“ 极差化” 处理, 令x'=(x- m)/(M-m), 式中, m和M分别为指标观测值x的最小值和最大值。

2 结果与分析

2.1 春小麦各生育期降水量特征分析

研究区1981-2010年, 30年小麦各生育期年均降水量分别为灌浆期(67.20 mm)> 拔节期(46.36 mm)> 抽穗期(36.08 mm)> 旗叶期(26.13 mm)> 开花期(14.28 mm)> 出苗期(10.15 mm)(表1), 分别占30年年均降水量(381.52 mm)的17.61%、12.15%、9.46%、6.85%、3.74%和2.66%; 不同生育期降水量的变异系数为开花期(91.00%)> 出苗期(85.83%)> 旗叶期(76.98%)> 抽穗期(66.61%)≥ 拔节期(51.87%)> 灌浆期(44.44%)。结果表明, 灌浆期年均降水量最多, 出苗期最少; 灌浆期降水量占全年降水量比例最多, 出苗期占全年降水量比例最少; 开花期降水量最不稳定, 灌浆期相比其它生育期降水量波动最小。这是因为定西是典型的旱作雨养农业区, 地形复杂多山脉屏障, 降水稀少, 且降水季节分布不均, 春冬少雨, 夏末秋初多雨^{[17, 18]}。

表1 1981-2010年小麦生育期降水量(mm)变化 Table 1 Change of precipitation(mm)in different wheat growth periods from 1981 to 2010

2.2 春小麦产量与各生育期降水量的回归分析

利用DPS软件对无量纲化处理之后的变量进行回归分析, 得出小麦产量(Y)与出苗期(X₁)、拔节期(X₂)、抽穗期(X₃)、旗叶期(X₄)、开花期(X₅)、灌浆期(X₆)、休闲期(X₇)降水量的多元回归方程为:Y=0.27-7.34X₁+3.27X₂+2.9X₃-4.01X₄+5.90X₅-2.87X₆+2.70X₇+3.28 $\begin{matrix} {X_{1}}^{2} \end{matrix}$ -2.51 $\begin{matrix} {X_{2}}^{2} \end{matrix}$ -2.37 $\begin{matrix} {X_{3}}^{2} \end{matrix}$ +4.13 $\begin{matrix} {X_{4}}^{2} \end{matrix}$ -2.48 $\begin{matrix} {X_{5}}^{2} \end{matrix}$ +3.23 $\begin{matrix} {X_{6}}^{2} \end{matrix}$ +4.32X₁X₃+2.01X₁X₄+3.81X₁X₅+4.48X₁X₆+2.15X₂X₃+1.18X₂X₅-2.34X₂X₆-2.36X₂X₇-5.91X₃X₅+0.57X₄X₆-1.67X₄X₇-3.28X₅X₆-5.76X₅X₇。

回归方程相关系数为0.999 9, 显著性水平检验, Sig.=0.000 1< 0.01, 方程回归达到极显著水平, 表明方程拟合性较好, 能够反映小麦生育期降水量与小麦产量之间的关系。

开花期多年降水量呈上升趋势, 倾向率为0.5 mm· 10 a^-1; 其它生育阶段降水年际变化都呈下降趋势, 出苗期、拔节期、抽穗期、旗叶期、灌浆期的减少倾向率分别为-1.7、-5.5、-5.5、-0.7、-1.2 mm· 10 a^-1(图2)。从多年降水变化可以看出, 研究区小麦拔节期、抽穗期降水递减率最大, 旗叶期递减率相对较小。

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	图2 1981-2010年小麦不同生育阶段降水量变化趋势Fig.2 Precipitation in different growth periods of wheat from 1981 to 2010

2.3 春小麦各生育期需水量定量分析

为进一步分析各生育期降水量对小麦产量的影响, 对上述回归模型进行降维处理, 因小麦休闲期降水量(X₇)自变量影响不显著, 已被回归方程剔除。将其它因素都固定为零水平, 可得到某因素对产量的一元二次子模型:Y₁=0.27-7.34X₁+3.28 $\begin{matrix} {X_{1}}^{2} \end{matrix}$ ; Y₂=0.27+3.27X₂-2.51 $\begin{matrix} {X_{2}}^{2} \end{matrix}$ ; Y₃=0.27+2.9X₃-2.37 $\begin{matrix} {X_{3}}^{2} \end{matrix}$ ; Y₄=0.27-4.01X₄+4.13 $\begin{matrix} {X_{4}}^{2} \end{matrix}$ ; Y₅=0.27+5.90X₅-2.48 $\begin{matrix} {X_{5}}^{2} \end{matrix}$ ; Y₆=0.27-2.87X₆+3.23 $\begin{matrix} {X_{6}}^{2} \end{matrix}$ 。

在各因素试验水平值范围内, 将值代入方程可实现各因子与产量的效应关系, 由降维方程可以得出, dY_i/dX_i=0时, 求得dY_i阈值, 出苗期需水量为34.72 mm, 拔节期需水量80.6 mm, 抽穗期需水量67.1 mm, 旗叶期需水量43.81 mm, 开花期需水量58.67 mm, 灌浆期需水量30.4 mm。

2.4 不同生育期降水量对小麦产量的制约因素分析

研究区1981-2010年小麦全生育期最大降水量289.9 mm, 最小降水量80.5 mm, 30年全生育期平均降水量199.77 mm, 变异系数为26.70%。由模拟试验得出, 小麦生长各生育期需水量满足条件下, 小麦生育期降水总量应该达到315.3 mm, 与30年降水平均值相差115.53 mm。不同生育期需水量分别占小麦生育期降水总量百分比为10.67%(出苗期)、27.85%(拔节期)、20.63%(抽穗期)、13.47%(旗叶期)、18.04%(开花期)、9.35%(灌浆期)。1981-2010年的30年间, 出苗期降水量最大值31 mm, 最小降水为0, 降水亏缺率10.71%~100.00%; 拔节期降水量最大值124 mm, 最小降水为13.3 mm, 降水亏缺率-36.87%~85.32%; 抽穗期降水量最大值110 mm, 最小降水为2.4 mm, 降水亏缺率-63.93%~96.42%; 旗叶期降水量最大值89.4 mm, 最小降水为0, 降水亏缺率-104.06%~100.00%; 开花期降水量最大值49.3 mm, 最小降水为0, 降水亏缺率15.97%~100.00%; 灌浆期降水量最大值142.2 mm, 最小降水为0, 降水亏缺率-367.76%~100.00%(图3)。

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	图3 1981-2010年降水亏缺率与小麦产量变化趋势Fig.3 Deficit precipitation rate and wheat production trends from 1981 to 2010

3 讨论和结论

本研究使用的气象资料是甘肃省定西市安定区李家堡乡定位试验站实测日照时数转换过的辐射量、日最高温、日最低温、日降水量, 运用APSIM模型在管理要素、土壤类型以及作物品种完全相同的情况下对小麦产量形成过程进行模拟研究, 相较于高阳等^[5]、李广和黄高宝^[11]利用统计资料, APSIM模型能够更加灵活, 更加全面预测小麦生长发育的动态过程。在APSIM模型小麦生产管理模块的使用上相较于沈禹颖等^[13]有待提高, 可以进一步深入探究降水格局对小麦氮素利用效率和水分利用效率的影响。但该模型较少考虑突发气候变化和病虫害等因素, 所以对于此模型的应用需进一步研究。

研究区, 春小麦30年年平均降水量为381.52 mm, 最大值564.5 mm, 最小值245.7 mm; 全生育期平均降水量为199.77 mm, 小麦全生育期需水量为315.3 mm, 与需水量两者相差115.53 mm, 全生育期降水量最大值为289.9 mm, 最小值为80.5 mm, 变异系数为26.70%, 小麦生育期降水量年际变化程度较大, 降水年基本呈旱涝交替出现。1999年, 小麦全生育期降水289.9 mm, 达到最大值, 运用APSIM模型模拟的小麦产量在1999年也达到最大值(3 012.17 kg· hm^-2), 小麦各生育期(出苗期、拔节期、抽穗期、旗叶期、开花期、灌浆期)降水分别为0、69.3、42.3、50.6、0、142.2 mm, 拔节期和抽穗期需水量稍欠, 旗叶期、灌浆期需水量满足。1982年, 小麦全生育期降水80.5 mm, 为最小值, 小麦产量890.02 kg· hm^-2, 非最小值, 小麦各生育期(出苗期、拔节期、抽穗期、旗叶期、开花期、灌浆期)降水分别为8.4、28.4、2.4、3.6、12.2、25.5 mm, 都未满足需水量。综上所述, 1999年, 小麦全生育期降水289.9 mm, 全生育期降水量达到30年来最大值, 尽管各生育期需水量没有完全达到, 但是小麦几个关键生长期降水基本满足, 其中拔节期和抽穗期需水量基本满足, 旗叶期、灌浆期需水量满足, 产量达到最大值; 1982年, 小麦全生育期降水80.5 mm, 为最小值, 各生育期需水量严重不足, 但是小麦各生育期降水均有所分配, 小麦产量890.02 kg· hm^-2, 非最小值。这与李广和黄高宝^[11]认为作物产量不仅与年降水总量有关, 还与降水量在不同季节的分配密切相关。王春泽和乔光建^[19]结合区域降水特性, 并调整农业种植结构以达到雨水资源的充分利用, 本研究还需对小麦需水与降水的耦合关系分析进一步研究。而毛婧杰和李广^[12]就降水量对小麦产量的影响进行了更加深入和具体的分析, 为提高水资源的利用和小麦产量提供理论依据。

出苗期、拔节期、抽穗期、旗叶期、开花期、灌浆期需水量分别为34.72、 80.6、 67.1、43.81、58.67、30.4 mm, 分别占全生育期需水量的10.67%、27.85%、20.63%、13.47%、8.04%和9.35%。小麦总生育期需水量为315.3 mm, 这与张旭东等^[20]研究干旱区定西、榆中、临夏春小麦生育期平均需水量324.8 mm基本一致, 与王鹏云等^[7]对昆明小麦生长需水量的研究结果小麦生育期平均需水量284.1 mm, 最大需水量为322.6 mm基本一致。

出苗期、拔节期、抽穗期、旗叶期、开花期、灌浆期平均降水亏缺率分别为70.78%、48.83%、46.22%、40.35%、75.66%和-121.05%。结果表明, 30年内出苗期降水量都未达到需水值; 拔节期在1990、1998年降水量分别为97.7、124 mm, 达到需水量; 抽穗期降水满足的是1985、1991、2010年, 降水量分别为70.9、110、69.6 mm; 旗叶期在1984、1993、1994、1999、2000、2002、2007年降水量分别为49.2、44.4、48.4、50.6、49.4、89.4 mm, 大于需水量; 开花期降水亏缺率都为正值, 因此30年内降水量都未满足; 灌浆期只有1982、1991年降水量25.5和28 mm, 小于需水量, 其它年份降水都满足。这与胡志桥等^[5]研究结果, 春小麦的需水关键期为拔节期和抽穗期和开花期一致。

本研究运用APSIM在甘肃省定西市模拟定西35号春小麦不同生育期降水量对小麦产量的影响, 为节水、高产栽培提供了理论依据。主要结论为:1)春小麦30年年均(休闲期+生育期)降水量为381.52 mm, 全生育期平均降水量为199.77 mm, 小麦全生育期需水量为315.3 mm, 不同生育期需水量分别占小麦生育期降水总量百分比为10.67%(出苗期)、27.85%(拔节期)、20.63%(抽穗期)、13.47%(旗叶期)、18.04%(开花期)和9.35%(灌浆期)。作物产量不仅与年降水总量有关, 还与降水量在不同季节的分配密切相关。2)小麦出苗期、拔节期、抽穗期、旗叶期、开花期、灌浆期需水量分别为34.72、 80.6、 67.1、43.81、58.67和30.4 mm。3)出苗期、拔节期、抽穗期、旗叶期、开花期、灌浆期平均降水亏缺率分别为70.78%、48.83%、46.22%、40.35%、75.66%、-121.05%; 春小麦需水关键期为出苗期、拔节期、开花期。

The authors have declared that no competing interests exist.

参考文献

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2013

0.0

... 农业发展受水资源的限制,水资源的时空分布与数量变化会直接影响农业生产^[1,2] ...

2015

0.0

王莺, 李耀辉, 孙旭映. 气候变化对黄河源区生态环境的影响. 草业科学, 2015, 32(4): 539-551.

Wang

, Li Y

, Sun X

Impact of climate change on the eco-environment in the Yellow River Source.

Pratacultural Science, 2015, 32(4): 539-551. (in Chinese)

Eco-environment has been disturbed severely in the Yellow River source by global climatic change and human activity. Currently, it had been gotten people’s close concern on impact of climate change on eco-environment in source region of Yellow River. Based on the analysis and systematic summary of the research results at home and abroad in recent years, authors concluded the climate change characteristics and key problem of the eco-environmental, and gave a comprehensive analysis of the main problems from runoff, soil erosion, wetlands, permafrost and vegetation in the Yellow River source, and discussed the characters of the effect of climatic change on eco-environment. Above all, authors had provided the main strategy of the eco-environment protection in the Yellow River source. The results were as follows: The precipitation was slightly increased, but the temperature was significantly increased in the Yellow River source region; It was great variation that the inter-annual variation and inter-decadal variation for runoff in the Yellow River source region. The runoff was in ample flow period from the middle of 1960s to the late of 1970s and in low water period from the early 1990s to 2008, and the good correlativity was between the annual runoff anomaly and annual precipitation anomaly, and the precipitation intensity was another important cause for runoff volume; The Yellow River source was the region with severe soil erosion, and the wetland was seriously damaged with an obvious decreasing area and dominance and increasing the number of patch, fragmentation degree and fractal dimension; The source region of permafrost had been thinned or disappeared, and there were formed inconsistently frozen ground and residual thawed layers in the vertical profile in the fringe, and raised 50~70 m in the lower limit of permafrost distribution; In general the vegetation cover was preserved previous condition or partially degraded in the Yellow River source. Therefore, we should consummate ecological compensation mechanism, strengthen the construction of a legal system and social environmental awareness, improve the quality of the law enforcement contingent, strengthen the joint of different departments, implement the ecological immigration, and advocate improving the ecotourism toprotect the ecological environment of the Yellow River source.

Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, Key Laboratory of Arid Change and Disaster Reduction of CMA, Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730020, China

在全球气候变暖和人类活动的共同作用下，黄河源区的生态环境受到严重干扰。目前，气候变化对黄河源生态环境的影响已经得到了很多学者的关注。本文在系统总结国内外已有研究成果的基础上，归纳了黄河源区的气候变化特征和已存在的生态环境问题，从径流量、土壤侵蚀、湿地、冻土和植被5个方面综合分析了黄河源区生态环境所面临的主要问题，讨论了气候变化对黄河源区生态环境的影响特点，并在此基础上提出了黄河源生态环境保护的治理对策。结果显示，黄河源区降水略有增加,气温显著升高。黄河源区径流有很大的年际和年代际变化，20世纪60年代中期至80年代后期相对偏丰，90年代初至2008年相对偏枯；源区年径流量距平的年际变化与年降水量距平的年际变化有很好的相关性；降水强度也是影响径流量的原因。黄河源区土壤侵蚀现象严重。湿地面积减少，沼泽和水域的斑块数、破碎度和分维数增加，优势度降低。源区多年冻土已经减薄或消失，多年冻土的边缘地带，垂直方向上形成不衔接冻土和融化夹层，多年冻土分布下界升高50～70 m。源区植被覆盖总体上保持原状，局部出现退化。在黄河源区生态环境保护方面应形成完善的生态补偿机制，加强法制建设，强化社会环保意识，提高执法队伍素质，加强部门联合，实施生态移民，大力发展生态旅游。

... 农业发展受水资源的限制,水资源的时空分布与数量变化会直接影响农业生产^[1,2] ...

2008

0.0

... 农业用水的主体是作物需水量,对农作物需水量进行研究,有利于提高水的生产力以及有效地进行灌溉^[3] ...

2013

0.0

杨琪, 张勃, 尹海霞, 赵一飞, 李小亚. 甘肃河东地区近50 年小麦需水量变化趋势及影响因子. 生态学杂志, 2013, 32(11): 3074-3081.

Yang

, Zhang

, Yin H

, Zhao Y

, Li X

Change trend of wheat water requirement and related affecting factors in Hedong region of Gansu Province, northwest China in recent 50 years.

Chinese Journal of Ecology, 2013, 32(11): 3074-3081. (in Chinese)

Based on the last 50 years meteorological data from 10 stations (including five stations for winter wheat and five for spring wheat) in Hedong region of Gansu Province, and by using FAO-recommended Penman-Monteith model, the water requirement and water deficiency of winter wheat and spring wheat in the study region were calculated. Meanwhile, by using MannKendall method to analyze the variation trends of the water requirement and water deficiency, the major meteorological factors affecting the variations of wheat water requirement were obtained by correlation analysis. The future trends of the wheat water requirement were forecasted by the method of rescaled range analysis. In the study region, the water requirement of winter wheat in Huanxian had a slight decrease, while that in Kongdong, Tianshui, Wudou, and Xifeng presented an increasing trend. The water requirement of spring wheat in Jingtai decreased, while that in Lintao, Linxia, Minxian, and Yuzhong exhibited an increasing trend. The water deficiency of winter wheat in the study region all showed an increasing trend, with a rate of 7.32-25.19 mm·10 a -1 . The water deficiency of spring wheat in Jingtai showed a decreasing trend, with a rate of 20.81 mm·10 a -1 , while that in Lintao, Linxia, Minxian, and Yuzhong showed an increasing trend, with a rate 0.42-20.4 mm·10 a -1 . The major meteorological factors affecting the water requirement of winter wheat were the mean daily air temperature and wind speed, while those affecting the water requirement of spring wheat were the mean daily temperature, relative humidity, and wind speed.

(College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China)

基于河东地区冬小麦、春小麦各5个站近50年气象资料，利用FAO推荐的Penman-Monteith公式，得到河东地区近50年来冬、春小麦全生育期的需水量和缺水量，并用MannKendall法分析其变化趋势，利用相关分析法得到影响小麦需水量变化的主要气象因子。结果表明：环县冬小麦需水量呈略微减少趋势，崆峒、天水、武都、西峰冬小麦需水量呈增加趋势；景泰春小麦需水量呈显著减少趋势，临洮、临夏、岷县、榆中4站春小麦需水量呈增加趋势；冬小麦缺水量均呈增加趋势，增加幅度在7.32～25.19 mm·10 a-1；景泰春小麦缺水量为下降趋势，减小幅度为20.81 mm·10 a -1 ，其他4站缺水量为增加趋势，幅度在0.42～20.4 mm·10 a -1 ；对冬小麦需水量影响最大的气象因子是日平均温度、风速；对春小麦需水量影响最大的气象因子是日平均温度、相对湿度和风速。

... 杨琪等^[4]利用公式得到甘肃河东地区近50年来冬、春小麦(Triticum aestivum)全生育期的需水量与缺水量,并分析了其变化趋势,结果表明,对春小麦需水量影响最大的气象因子是日平均温度、相对湿度和风速 ...

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... 而通过田间试验对冬小麦、春玉米(Zea mays)间作条件下作物需水规律的研究^[5]则为间作种植的水分管理提供参考 ...

... 3 讨论和结论本研究使用的气象资料是甘肃省定西市安定区李家堡乡定位试验站实测日照时数转换过的辐射量、日最高温、日最低温、日降水量,运用APSIM模型在管理要素、土壤类型以及作物品种完全相同的情况下对小麦产量形成过程进行模拟研究,相较于高阳等^[5]、李广和黄高宝^[11]利用统计资料,APSIM模型能够更加灵活,更加全面预测小麦生长发育的动态过程 ...

... 这与胡志桥等^[5]研究结果,春小麦的需水关键期为拔节期和抽穗期和开花期一致 ...

2011

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... 胡志桥等^[6]采用水量平衡法,对石羊河流域春小麦的需水量进行了研究,结果表明春小麦全生育期需水量为480 ...

2010

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王鹏云, 王辉, 李万春, 赵丽芬, 曾艳, 田燕. 昆明小麦生长期需水量和缺水状况研究. 麦类作物学报, 2010, 30(1): 111-115.

Wang P

, Wang

, Li W

, Zhao L

, Zeng

, Tian

Research on water demand and water shortage of wheat growing in Kunming.

Journal of Triticeae Crops, 2010, 30(1): 111-115. (in Chinese)

The deficiency of natural rainfall is one of the main factors influencing wheat growth and yield formation. Research on water demand and precipitation deficit can play a guiding role in irrigation water plan and increasing water use efficiency. Based on the analysis of wheat growth observational data, the wheat water requirement and precipitation deficit rates at development periods of wheat were calculated with the equation of Penman Monteith recommended by FAO. The results show that the average rainfall and average water requirement is 142.1mm and 284.1mm in growth season of wheat, respectively. The rainfall was obviously insufficient. The precipitation deficit rates at jointing, booting, heading and blooming stages was 73.0%, 72.4%, 83.5%, 78.0%, respectively. The frequency of severe and extremely severe water deficit was >0.8 from jointing to maturity stage. Especially in heading, blooming and milk stage, the frequency of severe and extremely severe water deficit was 0.86, 0.95, 0.89, respectively, which seriously affect the wheat growth and yield formation.

为了明确昆明地区小麦生育期需水量和缺水状况，根据田间实际观测的资料，采用FAO推荐的Penman Monteith公式，以小麦各生育期为单位，分析了昆明1972-2007年小麦出苗至成熟各生育期的需水量和缺水率。结果表明，在小麦生长期，平均降雨量为142.1 mm，平均需水量为284.1 mm，小麦生长期的降雨量明显不足。在小麦拔节和孕穗期，降水亏缺率为73.0%和72.4%；抽穗和开花期，降水亏缺率达到83.5%和78.0%。在拔节至成熟期，重度和特重度水分亏缺出现频率＞0.8，尤其是在抽穗、开花、乳熟期，重度和特重度水分亏缺出现的频率分别为0.86、0.95、0.89，对小麦年际生长发育和产量形成影响严重。

... 而根据田间实测资料,采用FAO-PM公式计算昆明1972―2007年小麦各生育期的需水量和缺水率,认为昆明小麦生育期重度水分亏缺,严重影响了小麦的年际生长发育和产量^[7] ...

... 8 mm基本一致,与王鹏云等^[7]对昆明小麦生长需水量的研究结果小麦生育期平均需水量284 ...

2011

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王瑶, 赵传燕, 田风霞, 王超. 黑河中游春小麦需水量空间分布. 生态学报, 2011, 31(9): 2374-2382.

Wang

, Zhao C

, Tian F

, Wang

Spatial variation of water requirement for spring wheat in the middle reaches of Heihe River basin.

Acta Ecologica Sinica, 2011, 31(9): 2374-2382. (in Chinese)

Sustainability of irrigated agriculture depends primarily on the efficient management of irrigation water. Understanding crop evapotranspiration ( ET c ) is essential in planning the most effective use of water resources in the arid northwest China. ET c is not only the important component of water balance, but also an important requirement for proper constitution of irrigation strategy. In this study, the middle reach of Heihe River was selected as the study area which has the largest agricultural oases in China. Agricultural development has over 2000 years history own to its flat land. Irrigated spring wheat is the main crop in this region. With the increase in population growth and farmland area is 2452.1 km 2 agricultural water requirement in the middle Heihe River basin is rapidly increasing. This results in the conflict between the agricultural water demand and ecological water demand. Ecological environment deteriorates due to vegetation disappearing at a rapid rate in large areas in the region. In the field, when the crop is small, water is predominately lost by soil evaporation, but once the crop is well developed and the canopy completely covers the soil, transpiration becomes the main process of water loss.. The objective of this study was to map the spatial distribution of water requirements and analyze the relationship between the spatial variation of water requirement and main meteorological parameter during 1970-2009 in the Heihe River basin. First, reference crop evapotranspiration ( ET 0 ) was calculated using Penman-Monteith equation with daily data obtained from 14 meteorological stations in and around the study area. Secondly, the crop coefficients ( K c ) of spring wheat in different growing stages were adjusted according to the data obtained from the field studies. Finally, we estimated the spatial distribution and variation trend of the water requirement of spring wheat in the middle reaches of Heihe river basin with the use of Geographical information system (GIS). The results showed that the trend of crop evapotranspiration ( ET c ) gradually increased from south to north,the ET c varies from 573 mm to 781 mm during the entire growing season. The ET c in Gaotai, Zhangye, Linze, Minle, Shandan, and Jiuquan is 731.26, 686.88, 598.24, 728.89, 719.77 and 713.59 mm, respectively. The ET c of mid-season stage is the largest percentage during the entire growing season, accounting for 51.67%, 51.11%, 50.96%, 51.24%, 50.83% and 50.77% of total ET c at six meteorological stations, respectively. Temperature, precipitation, wind speed, min relative humidity and sunshine duration were the dominant meteorological parameters influencing ET c , and the relative influences of temperature, sunshine duration, wind speed, precipitation and min relative humidity are 57.29%, 26.92%, 15.15%, 1.41% and 0.78% respectively.

合理估计春小麦的需水量( ET c )是进行干旱区水资源配置的有效方法,利用黑河中游14个气象站1970-2009年的逐日气象资料,应用Penman-Monteith公式估算各站点的参考作物蒸散量,并根据春小麦生长期的作物系数,在地理信息系统(GIS)技术支持下得出黑河中游春小麦需水量的空间分布及变化趋势。结果表明:1970-2009年黑河中游春小麦作物需水量整体分布具有从南向北递增的趋势,全生长期需水量在573-781 mm之间;高台、张掖、临泽、民乐、山丹、酒泉的春小麦需水量分别为731.26、686.88、598.24、728.89、719.77、713.59 mm,其中生长中期需水量最大,分别占全生长期的51.67%、51.11%、50.96%、51.24%、50.83%和50.77%;日平均气温、日照时数、风速、降水量、最小相对湿度和各因子的影响力由大到小分别占总影响力的57.29%、26.92%、15.15%、1.41%和0.78%。

... 同样,利用FAO-PM公式估算了黑河中游小麦作物需水量,发现小麦作物需水量整体分布具有由南至北递增的趋势^[8] ...

2012

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刘志娟, 杨晓光, 王静, 吕硕, 李克南, 荀欣, 王恩利. APSIM玉米模型在东北地区的适应性. 作物学报, 2012, 38(4): 740-746.

Liu Z

, Yang X

, Wang

, Lyu

, Li K

, Xun

, Wang E

Adaptability of APSIM maize model in northeast China.

Acta Agronomica Sinica, 2012, 38(4): 740-746. (in Chinese)

The APSIM ( Agricultural Production Systems Simulator) model was introduced to simulate maize growth, development and yields in the northeast China using the field experimental data and climate data collected from six typical agricultural meteorological stations in the studied area. APSIM was calibrated using the first part of data to determine the varietal parameters, then simulated the growing periods, leaf area index (LAI), total above-ground biomass and yields using the second part of data at each site. The results showed that there was a good agreement between the simulated and observed values in growing periods. The difference of growing periods from sowing to emergence, form sowing to flowering and form sowing to maturity between simulated and observed data was 0 – 2.0, 0.7 – 2.0, and 0.7 – 2.3 d, respectively. The Normalized Root Mean Square Error( NRMSE ) values for measured and simulated LAI and total above-ground biomass in Harbin station were 33% and 11%, respectively. NRMSE values for measured and simulated yield in Harbin, Hailun, Tailai, Huadian, Tonghua, and Benxi station were 18%, 13%, 4%, 4%, 5%, and 2%, respectively. These results indicated that APSIM model has good ability to simulate the growing periods, dynamic process of LAI, dynamic process of above-ground biomass and yield of maize in Northeast of China. This research supports the model application in Northeast of China, such as simulating maize potential yield, or prescribing yield limiting factors.

1 College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China; 2 The Commonwealth Scientific and Industrial Research Organisation Land and Water, GPO Box 1666, Black Mountain, Canberra, ACT 2601, Australia

利用东北地区6个典型农业气象试验站的玉米田间试验数据和同期逐日气象数据对APSIM模型(农业生产系统模型)在东北玉米产区的适应性进行了初步研究。先依据各站第一组玉米试验数据对模型相关参数进行调试、确定，再利用另一组试验数据检验模型模拟玉米生育期、叶面积指数、地上部总生物量和产量的可靠性。结果表明，APSIM模型模拟的播种至出苗、开花和成熟各阶段天数与实测天数有较好的一致性，其误差分别为0~2.0、0.7~2.0和0.7~2.3 d；哈尔滨地区模拟的叶面积指数和地上部总生物量相对均方根差分别为33%和11%，模拟效果较好；黑龙江哈尔滨、海伦、泰来，吉林桦甸、通化和辽宁本溪的模拟产量与实际产量的 NRMSE 分别为18%、13%、4%、4%、5%和2%。说明APSIM模型对东北地区玉米生育期、叶面积指数动态变化过程、地上部总生物量动态变化过程和最终产量具有较好的模拟结果，验证后的APSIM模型在东北地区具有较好的适应性。以上结果为今后在东北地区深入开展玉米生产潜力以及解析产量形成的限制因素等研究提供了技术平台与支撑。

... 国内学者已对该模型的适用性进行了验证与调试^[9,10] ...

2015

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雷娟娟, 闫丽娟, 李广, 董莉霞, 高珍妮. 基于APSIM模型光照与CO₂对小麦的影响机制. 草业科学, 2015, 32(8): 1310-1316.

Lei J

, Yan L

, Li

, Dong L

, Gao Z

Effects of CO₂ and illumination on wheat grain yields based on APSIM model.

Pratacultural Science, 2015, 32(8): 1310-1316. (in Chinese)

In order to explore the effects of illumination intensity and CO2 concentration on wheat (Triticum aestivum) grain yield, the grain yield under different illumination intensities and CO2 concentrations was simulated by validated Agricultural Production System Simulator Model（APSIM） and cooperation factors were analysised by multiple regressions. The results showed that the grain yield rapidly decreased with the increase of illumination intensity under the same CO2 condition which had maximum grain yield losses of 17.16% and the average grain yield losses of 9.40% with the light intensity increased by 0.5 MJ·m-2. The grain yield increased with the increase of CO2 condition under the same illumination intensity which had maximum grain yield losses of 22.08% and the average grain yield losses of 11.27% with the CO2 concentration increased by 100 μmol·mol-1. There was negative interaction between light intensity and CO2 concentration which suggested the local environment was suitable for wheat growth.

1.College of Resources and Environment Science, Gansu Agricultural University, Lanzhou 730070, China; 2.College of Agriculture, Gansu Agriculture University, Lanzhou 730070, China;3.Forest College of Gansu Agricultural University, Lanzhou 730070, China；4.College of information science and technology, Gansu agricultural university, Lanzhou, 730070, China

为了探索光照强度与CO2浓度对小麦（Triticum aestivum）产量形成的影响，运用验证后的APSIM模型模拟不同光照强度与CO2浓度下的小麦产量，并采用多元回归分析法分析其对小麦产量的影响机制。结果表明，在相同的CO2浓度条件下，小麦产量随光照强度的增加而明显下降，日光照强度每升高0.5 MJ·m-2，最大减产幅度高达17.16%，平均减产9.40%。相同光照条件下，CO2浓度每升高100 μmol·mol-1，平均增产11.27%，最大增产可达到22.08%。CO2浓度与光照强度之间存在负交互效应。表明在研究区光照已完全满足旱地春小麦产量的需求。

... 国内学者已对该模型的适用性进行了验证与调试^[9,10] ...

... 3 数据分析模拟试验中,APSIM平台参数均来源于李广等^[10]研究者在黄土丘陵沟壑区APSIM适用性研究中经过反复本土化修订的参数 ...

2010

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李广, 黄高宝. 基于APSIM模型的降水量分配对旱地小麦和豌豆产量影响的研究. 中国生态农业学报, 2010, 18(2): 342-347.

, Huang G

Determination of the effect of precipitation distribution on yield of wheat and pea in dryland using APSIM. Chinese Journal of

Eco-Agriculture, 2010, 18(2): 342-347. (in Chinese)

By using APSIM model, the effect of precipitation seasonal distribution on crop yield was determined in rain-fed agriculture area of the Loess Plateau. Next, the effect of precipitation seasonality on crop yield was explored via integral regression analysis. The study shows that APSIM model can reliably simulate wheat and pea yield. Crop yield is highly related with annual precipitation and its seasonal distributon. The seasonal distribution of participation has a positive U-shaped quadratic relation with wheat and pea yield. Precipitation in the months of June and July significantly influences wheat yield, while that in the months of May and June importantly influences pea yield. With 1 mm increase in precipitation, wheat and pea yield respectively increases at the rate of 10.4 kg・hm -2 and 10.3 kg・hm -2 . Seasonal precipitation distribution more importantly influences crop yield than annual precipitation.

为探索降水量分配对作物产量的作用机制和规律, 在对APSIM模型检验的基础上, 运用APSIM模型和多元积分回归方法研究黄土高原雨养农业区降水季节分配对作物产量的影响。结果表明: APSIM模型可用来模拟小麦和豌豆的产量; 作物产量除与年降水总量有关外, 还与降水量的季节分配有关; 降水量的季节分配对小麦和豌豆产量影响为开口向上的二次曲线, 并且都为正效应; 当年6～7月份降水对小麦产量影响最大, 5～6月份降水对豌豆产量影响最大, 最大贡献率为每增加1 mm的降水量, 小麦增产10.4 kg?hm -2 , 豌豆增产10.3 kg?hm -2 ; 降水量季节分配比年降水总量对作物产量的形成有更为深刻的影响。

... 李广和黄高宝^[11]为研究耕作措施对土壤水分与作物生长发育的影响,对APSIM模型的适应性进行了研究,结果表明此模型可用于甘肃旱作区作物生长的模拟 ...

... 2 APSIM模型APSIM-Wheat可以动态模拟小麦地上和地下部分的生长状况,有研究^[11]表明,APSIM 可依据小麦不同生产阶段的降水量来判断产量 ...

... 这与李广和黄高宝^[11]认为作物产量不仅与年降水总量有关,还与降水量在不同季节的分配密切相关 ...

2014

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毛婧杰, 李广. 陇中地区降水量对小麦产量的影响. 草业科学, 2014, 31(2): 290-295.

Mao J

, Li

Impacts of precipitation on wheat yield during growth period.

Pratacultural Science, 2014, 31(2): 290-295. (in Chinese)

In order to explore the mechanism and regular pattern of precipitation on wheat yield, the impacts of precipitation from 1971 to 2005 on wheat yield during its growth period were imitated using APSIM model and quadratic polynomial stepwise regression analyzed in Dingxi City, Gansu province. The results showed that wheat production was not only affected by total annual precipitation, but also the variations of growth period precipitation. The most effective precipitation period was seedling stage and followed by jointing stage, carry flag stage, heading stage, filling stage and flowering stage. The correlation between precipitation and wheat yield during seedling stage and jointing stage showed downward opening parabola. Effects of precipitation in seedling stage and jointing stage were 6.6 and 3.7 times of precipitation in carry flag stage, respectively. Effects of precipitation in heading stage, carry flag stage, flowering stage and filling stage on wheat yield showed secondary superposition incremental trends during the studied area. The precipitation in seedling and elongation stage was one of main limit factors of wheat yield in this studied area.

College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China

为探讨生育期降水对小麦( Triticum aestivum )产量的作用机制和规律, 以甘肃省定西市1971-2005年小麦产量和各生育期降水量为研究对象, 运用APSIM模型模拟, 并用二次多项式逐步回归法分析了生育期降水量对小麦产量的影响。结果表明, 小麦产量除与年降水总量有关外, 还与生育期降水量的变化有关。不同生育期降水量对小麦产量影响表现为苗期>拔节期>挑旗期>抽穗期>灌浆期>开花期, 其中, 苗期和拔节期的降水量与小麦产量呈开口向下抛物线型变化。且苗期和拔节期降水量效应分别是挑旗期降水量效应的6.6和3.7倍, 而抽穗期、挑旗期、开花期和灌浆期降水量对小麦产量影响在研究区降水范围内出现二次叠加递增变化。甘肃陇中地区小麦产量的主要限制因子是苗期和拔节期降水量。

... 甘肃省定西地区属于季风气候区与非季风气候区的过渡带,是典型的大陆温带干旱半干旱气候^[12],对该地区春小麦生育期水资源的合理利用的研究鲜有报道 ...

... 而毛婧杰和李广^[12]就降水量对小麦产量的影响进行了更加深入和具体的分析,为提高水资源的利用和小麦产量提供理论依据 ...

2002

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... APSIM-Wheat模型运行所需数据包括气象数据、作物数据、土壤数据、栽培措施数据与试验点的经纬度、海拔等^[13] ...

... 在APSIM模型小麦生产管理模块的使用上相较于沈禹颖等^[13]有待提高,可以进一步深入探究降水格局对小麦氮素利用效率和水分利用效率的影响 ...

2006

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... 不同的土壤类型采用的径流曲线不同,其值从0~100不等,采用了美国农业部USLE模型的径流曲线,土壤蒸发参照CERES模型^[14] ...

2011

0.0

王鹤龄, 王润元, 张强, 牛俊义, 吕晓东. 气候变暖对甘肃省不同气候类型区主要作物需水量的影响. 中国生态农业学报, 2011, 19(4): 866-871.

Wang H

, Wang R

, Zhang

, Niu J

, Lyu X

Impact of warming climate on crop water requirement in Gansu Province. Chinese Journal of

Eco-Agriculture, 2011, 19(4): 866-871. (in Chinese)

作物需水量是农田水分循环系统中最重要的因素之一。在未来温度上升1～4 ℃的情景下, 研究了气候变暖对我国甘肃省不同气候类型区主要作物需水量的影响。结果表明, 气候变暖对不同作物需水量的影响程度不同。其中对冬小麦需水量的影响最大, 对玉米和春小麦次之。当生长期内温度上升1～4 ℃时, 冬小麦需水量将增加3.05%～12.90%, 相当于13.2～81.2 mm; 玉米需水量将增加2.49%～10.80%, 相当于9.9～60.6 mm; 春小麦需水量将增加2.74%～11.69%, 相当于6.7～40.0 mm。气候变暖对作物需水量的影响存在一定地域性差异。对干旱区的作物需水量影响最大, 半干旱区次之, 其次是半湿润区, 对湿润区影响不大。根据甘肃省目前的种植结构, 据此估算, 当温度上升1～4 ℃时, 将使甘肃省冬小麦的灌溉需水量增加12.43×108 m3、13.02×108 m3、13.74×108 m3和14.65×108 m3, 玉米的灌溉需水量增加7.94×108 m3、8.32×108 m3、8.78×108 m3和9.3×108 m3, 春小麦的灌溉需水量增加4.97×108 m3、5.16×108 m3、5.42×108 m3和5.76×108 m3。

... _w为降水亏缺率(%),R为小麦各生育期的降水量,ET_m为小麦各生育期的需水量(mm)^[15,16] ...

2011

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王鹤龄, 牛俊义, 王润元, 吕晓东. 气候变暖对河西走廊绿洲灌区主要作物需水量的影响. 草业学报, 2011, 20(5): 245-251.

Wang H

, Niu J

, Wang R

, Lyu X

Impact of climate change on water requirement of main crops in irrigated oasis of Hexi Corridor.

Acta Prataculturae Sinica, 2011, 20(5): 245-251. (in Chinese)

作物需水量是农田水分循环系统中最重要的因素之一。在未来温度上升１～４℃的情景下，研究了气候变暖对我国河西绿洲灌区主要作物需水量的影响。结果表明，气候变暖对不同作物需水量的影响程度不同。其中对棉花和玉米需水量的影响最大，对小麦的影响次之。当生长期内温度上升１～４℃ 时，棉花需水量将增加２．１７％～１２．６６％，相当于１５．００～８３．００ｍｍ；玉米需水量将增加１．９０％～１１．４９％，相当于１４．６０～８２．５０ｍｍ；小麦需水量将增加１．８０％～１０．０３％，相当于９．７０～５０．７０ｍｍ。气候变化对作物需水量的影响存在一定地域性差异。当增加１℃时，对干旱区武威作物需水量的影响略大于极端干旱区敦煌。当增加２℃时，武威和敦煌的作物需水量几乎相当。当增加３和４℃时，则对敦煌作物需水量的影响大于武威。根据河西绿洲灌区目前的种植结构，当温度上升１～４℃时，估算将使整个地区棉花的灌溉需水量增加０．１１，０．２１，０．３７，０．６２亿ｍ３；玉米的灌溉需水量增加０．１６，０．３３，０．５６，０．９３亿ｍ３；小麦的灌溉需水量增加０．１４，０．２６，０．４５，０．７１亿ｍ３；总的灌溉需水量增加０．４１，０．８０，１．３８，２．２５亿ｍ３。气候变暖将使河西绿洲灌区业已紧张的水资源供需矛盾更加突出。

... _w为降水亏缺率(%),R为小麦各生育期的降水量,ET_m为小麦各生育期的需水量(mm)^[15,16] ...

2006

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... 这是因为定西是典型的旱作雨养农业区,地形复杂多山脉屏障,降水稀少,且降水季节分布不均,春冬少雨,夏末秋初多雨^[17,18] ...

2012

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... 这是因为定西是典型的旱作雨养农业区,地形复杂多山脉屏障,降水稀少,且降水季节分布不均,春冬少雨,夏末秋初多雨^[17,18] ...

2008

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... 王春泽和乔光建^[19]结合区域降水特性,并调整农业种植结构以达到雨水资源的充分利用,本研究还需对小麦需水与降水的耦合关系分析进一步研究 ...

1999

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... 3 mm,这与张旭东等^[20]研究干旱区定西、榆中、临夏春小麦生育期平均需水量324 ...