研究论文 正式出版 版本 4 Vol 9 (4) : 372-382 2018
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毛乌素沙地地下水浅埋区田间水分动态研究
Study on Field Water Dynamics in Mu Us Sand Land with Shallow Groundwater Table
: 2018 - 07 - 23
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摘要&关键词
摘要:毛乌素沙地种植区地下水埋深较浅,地下水与土壤水分之间联系紧密,为揭示春玉米生长过程中水分运移关键过程,本文基于原位监测,利用Hydrus-1D建立模型研究毛乌素沙地的田间水分动态。结果发现:在包气带中,40 cm深以上土层受根系吸水和气象条件影响水分变化剧烈,50 cm深以下土层水分变化受地下水影响显著;在玉米整个生长期内,蒸发量占蒸散量的比例为31%,地下水对玉米生长的水分贡献总量为220.09 mm,占玉米耗水总量的37.9%;为了减少深层入渗,满足节水灌溉,在当前地下水埋深条件下,可将每次的灌溉量减少为原水量的72%;地下水位的下降会减少玉米对地下水的利用,并增大灌溉量,模拟发现,当平均地下水埋深下降至147 cm深时,玉米生长将不再利用地下水。研究成果可为毛乌素沙地的农田水分利用及生态环境保护提供重要的理论依据和参考信息。
关键词:Hydrus-1D;水分动态;蒸散发;地下水利用
Abstract & Keywords
Abstract: Background, aim, and scope The vegetation water consumption is one critical part composing the transport processes of water and heat in the Soil-Plant-Atmosphere Continuum (SPAC), especially for the arid areas. For the arid areas, water is not only the main factor restricting plant growth, but also vital for the maintenance of the local ecological environment. The Mu Us Sandy Land (MUSL) in the northwest of China is dominated by arid climate with relatively shallow groundwater table, and the MUSL groundwater variation is closely related to that of soil moisture. Considering the critical role of water in the development of agriculture in MUSL region, it will be of great importance to study the field water dynamics in the Mu Us Sandy Land. Since spring maize is the primary crop in the MUSL region, here we examined the key water transport processes during the growing season of spring maize by combining model simulations with field measurements. Materials and methods In order to quantify field water dynamics in the MUSL region, one typical field at the Hailiutu catchment was selected to conduct this study. We collected in-situ measurements of hydrologic factors including soil water content, soil water potential and groundwater table during the whole growing season of spring maize from May to October (a total of 155 days). Soil water content was measured at the depth of 10-90cm with10-cm-spacing every 5 days using Time Domain Reflectometer (TDR). Three TDRs were set with the distance of 3m in this study. Soil water potential was measured with Watermark (with seven sensors) every 10 minutes at six depths. The MiniDiver was applied to monitor groundwater table every 10 minutes. A Bowen-ratio meteorological station was used to observe meteorological variables including wind speed/direction, net radiation, air temperature/humidity and rainfall. On this basis, we parameterized and validated the Hydrus-1D model, and used it to evaluate the field water dynamics during the growing season of spring maize. Results The soil water content above the depth of 40 cm strongly varied with influences of irrigation and rainfall events, while the soil water content below the depth of 50 cm varied similarly with the groundwater dynamics. The simulation results from Hydrus-1D model indicated that, evapotranspiration (ET) of spring maize during the whole growing period reached 580.32mm, in which 31% were contributed by evaporation, and the ET amount during the jointing, earing and filling periods accounted for 71.8% of the whole ET amount. The dynamics of evaporation and transpiration were found to be significantly related with the variation of leaf area index (LAI), with correlation coefficients of -0.599 and 0.712, respectively. The contribution of groundwater for maize growing was 220.09 mm, which accounted for 37.9% of the total ET amount. The model outputs showed that there were about about 8.5 mm of infiltration under the present irrigation amount (~30 mm). Meanwhile, simulation results also indicated that spring maize would not utilize the groundwater when the average depth of groundwater table fell to 147 cm, and the irrigation amount thus turned to be maximum (432.45 mm). Discussion The field soil water content varied dramatically during our study period. However, the main factors influencing the dynamics of soil water content at different depths were different. The soil water content at shallow depths was mainly affected plant growth and meteorological conditions, while the variation of soil moisture at the deep depths was dominant by groundwater dynamics. The evaporation and transpiration and their relative magnitudes varied along the growing season of spring maize due to influences of LAI, which resulted in that the transpiration peaked during earing period and evaporation peaked during sowing period. Conclusions The field water dynamics of spring maize in the MUSL region were closely related with plant growth, meteorological conditions and groundwater table, and the main factors influencing the dynamics of soil water content at different depths were different. The ET mainly occurred during the jointing, earing and filling periods. In order to reduce the deep infiltration and meet the need of water-saving irrigation, the irrigation amount could be reduced to 72% of the original standard at the present groundwater table. For the shallow ground water table, obvious water transport process existed between ground water and soil water, and ground water contributed to the water consumption of spring maize. However, spring maize would not utilize the groundwater when the average depth of groundwater table fell to 147 cm. Recommendations and perspectives Understanding the field water dynamics of spring maize in the MUSL region is not only essential in providing reference basis to the local farmers to improve irrigation use efficiency, but also informative for the water-saving agriculture and ecological environmental protection in Mu Us Sandy Land.
Keywords: Hydrus-1D; water dynamics; evapotranspiration; groundwater utilization
水分动态是土壤-植物-大气连续体(SPAC)水热传输过程研究的关键(Philip,1966),反映了植物的耗水特征和水分通量各组分间的相互关系。特别是在干旱地区,水分作为制约植物生长的主要因子,与生态环境的维系与水资源的合理利用也密切相关(徐小玲和延军平,2003;高浩等,2016)。
毛乌素沙地处于干旱、半干旱地区,生态环境脆弱,降雨量少,是中国四大沙地之一。在毛乌素沙地,地下水资源相对丰富,特别是农业种植区,地下水埋深一般较浅。研究表明,浅埋的地下水与土壤水之间存在着水分交换(雷志栋等,1992),并且其动态过程受到了如降水、蒸发、地下水埋深、土壤质地、前期土壤含水量和植被类型等的影响(宋献方等,2011;王云强等,2012;贺美娜等,2017)。因此,针对浅埋地下水环境,开展毛乌素沙地植被水分利用一直是一个研究的热点(钱多等,2017),特别是在油蒿、麻黄、沙柳等沙生植被的耗水规律、土壤水分动态特征以及影响因素方面开展了大量的研究工作,认识到了地下水在沙生植被生长、荒漠化治理、水资源保护方面的重要作用(王鹤松等,2010;于晓娜等,2015;高浩等,2016;傅子洹等,2015)。虽然对毛乌素沙地不同植被的水分动态已经有了比较深入的研究,但是主要集中于特征分析等定性描述,在量化研究方面尚有不足之处。并且,春玉米作为当地最主要农作物,关系到农业生产、经济发展和水资源利用等多个方面,其田间土壤水分与浅埋地下水之间也存在着紧密的关系(包含等,2014)。因此,针对春玉米的田间水分动态开展量化研究工作,具有重要的科学和现实意义。
目前,对田间水分动态的研究主要是通过估算田间水分通量来实现,农田水分通量是研究农田生态系统内部及其与大气之间水热交换和分配的主要指标,体现了农田内部和表面水分输送到大气中的总过程。对此,前人已经做了充分的工作,研究方法也相对成熟,包括试验观测法 (Duan et al,2016;Cubera et al,2007;孙宏勇等,2004)、模型模拟法(Zhu et al,2009;袁成福等,2014)、遥感图像反演法(Albert et al,1999;彭致功等,2008)等。其中,基于原位测试,结合数值模型开展研究工作是一种常用手段。在众多数值软件中,Hydrus-1D因为便于模拟一维变饱和度地下水流、根系吸水、溶质运移和热运移、气运移而得到广泛应用(Simunek et al,1998)。
本文以毛乌素沙地田间水分作为研究对象,开展原位实验与观测,在获取田间气象因子、降水与灌溉量、土壤含水量、土壤水势、地下水位变动以及玉米生长状况的基础上,分析土壤水分变化特征,并利用Hydrus-1D软件建立模型,量化作物生长过程中的田间水分动态变化,分析浅埋地下水对田间水分通量的影响。从而掌握整个春玉米生长期的田间水分动态过程,揭示田间耗水特征,为保护毛乌素沙地水资源,改善生态环境,提高用水效率提供理论基础。
1   研究区概况与研究方法
1.1   研究区概况和试验介绍
研究区位于毛乌素沙地海流兔河流域,位置(N:38°23.502′,E:109°11.942′,H:1152 m)。区域多年平均降水量约为349.37 mm,多年平均水面蒸发量(200 mm蒸发皿)为2035.19 mm。试验区地下水埋藏深度浅,研究时段地下水埋深波动范围为90-130 cm。研究区农作物以春玉米为主,研究时间段为春玉米整个生长期,自4月30日至10月1日,共计155天。试验年为典型枯水年,整个玉米生长期降水量为214.1 mm,灌溉量为177 mm。
本项研究对田间的地下水埋深、土壤水势、土壤含水率、降雨灌溉和气象进行了监测,相关观测项目、观测时间及方法如表1所示。
表1   毛乌素沙地田间观测项目、方法及日期
监测项目
Monitoring item
仪器
Instrument
测量高度
Measuring height /cm
测量频率
Measuring
frequency
监测时间(月-日)
Monitoring time (month-day)
地下水埋深
Groundwater depth
MiniDiver/MiniBaro−150/−1010 min一次
Once per 10 minutes
04-30—10-01
土水势
Soil water potential
Watermark−10、−20、−30、−50、−70、−9010 min一次
Once per 10 minutes
06-01—10-01
土壤含水率
Soil water content
时域反射仪(Trime-IPH)
Time Domain Reflectometer
−10、−20、−30、−40、−50、−60、−70、−80、−905 d一次, 降雨灌溉前后加密
Once per 5 days, and once before and after rainfall and irrigation, respectively
06-01—10-01
雨量
Rainfall
自动雨量计
Automatic rain gauge
10004-30—10-01
灌溉量
Irrigation
量水堰
Measuring weir
06-1—10-01
其中,MiniDiver用来监测地下水位,并使用MiniBaro进行气压校正。土水势仪(Watermark)共7个探头,布置间距为30 cm。时域反射仪(Trime-IPH)设置3个测管,间距为300 cm,因试验需要或者降雨灌溉后加密测量。此外自动雨量计与波文比气象站系统连通,采集风速风向、净辐射、温度湿度、降水等气象数据。监测设备相对安装位置如图1。


图1   毛乌素沙地试验现场仪器安装位置示意图
Fig.1 Schematic diagram of instruments installation locations in the test site of Mu Us Sandy Land
1.2   Hydrus-1D 模型介绍
本项研究以气象观测和原位试验为基础,利用Hydrus-1D建立模型,对玉米种植区内田间水分通量进行量化分析。
Hydrus-1D模型用于模拟计算一维垂直非饱和流和溶质运移,不仅考虑了植物根系吸水和土壤持水能力的滞后效应,还加入了气象模块,适用于各种恒定或非恒定的边界条件(Simunek et al,1998)。
以地表为基准面,垂直一维土壤水分运动模型可由Darcy-Richards方程确定(坐标轴向下为正),方程如式(1)。
\(\frac{\partial \theta }{\partial t}=\frac{\partial }{\partial z}\left[\left({K}_{\left(\theta \right)}\frac{\partial h}{\partial z}\right)-{K}_{\left(\theta \right)}\right]-S\) (1)
式1中:\(\theta \)为土壤体积含水率(cm3·cm-3);\({K}_{\left(\theta \right)}\)为非饱和渗透系数(cm·d-1);S为单位时间单位体积土壤中根系吸水率(d-1);t为时间变量(d);Z为空间变量(cm),地表为原点,向下为正。其中,非饱和渗透系数由Van Genuchten模型计算(Genuchten,1980)。
Van Genuchten 模型的表示方式为:
\({\theta }_{\left(h\right)}={\theta }_{r}+\frac{{\theta }_{s}-{\theta }_{r}}{{\left[1+{\left|\alpha h\right|}^{n}\right]}^{m}}\)h<0 (2)
\({K}_{\left(h\right)}={K}_{s}{S}_{e}^{1/2}{\left[1-{\left(1-{S}_{e}^{1/m}\right)}^{m}\right]}^{2}\)h<0 (3)
\({S}_{e}=\frac{\theta -{\theta }_{r}}{{\theta }_{s}-{\theta }_{r}}\) (4)
式中,\({\mathrm{S}}_{\mathrm{e}}\)为无量纲的有效水分含量;\(\mathrm{\theta }\)为土壤体积含水率(cm3·cm-3);\({\mathrm{\theta }}_{\mathrm{r}}\)\({\mathrm{\theta }}_{\mathrm{s}}\)分别为残留和饱和土壤含水率(cm3·cm-3);nm
别为Van Genuchten模型参数,m=1-1/n\({K}_{\mathrm{s}}\)为饱和导水率(cm·d-1)。
根系吸水模型采用以水势差为基础的Feddes模型(Feddes et al,1978),如式(5)。
\(S\left(z,t\right)=\alpha \left(h,z\right)\beta \left(z\right){T}_{p}\) (5)
式5中,\(\alpha \left(h,z\right)\)表示水分胁迫反应方程;\(\beta \left(z\right)\)为根系吸水分布函数(mm-1),\(S\left(z,t\right)\)用来描述根系吸水的空间变异;\({T}_{p}\)为作物的潜在蒸腾速率(mm·d-1)。而\({T}_{p}\)可通过Beer定律(Ritchie,1972)计算,如式(6)。
\({T}_{p}=E{T}_{0}\left(1-{\mathrm{e}}^{-kLAI}\right)\) (6)
其中ET0 是参考作物蒸散量(cm),可由FAO推荐的Penman-Monteith公式计算(Allen,1998),LAI是叶面积指数,指单位土地面积上植物叶片总面积占土地面积的倍数,其中叶面积=长×宽×0.75(李向岭等,2011),k是植物灌层辐射衰减系数,本文中k值采用式(7)的Rosenthal方法计算(祁红彦等,2011),取玉米整个生长期的平均值0.478。
k =-0.055LAI+0.622 (7)
1.3   模型建立与参数反演
模型选取水分运移、根系吸水、根系生长3个子程序,以天为单位模拟田间一维垂向的土壤水分运动过程。模拟土壤层的厚度为150 cm,根据土壤性质的差异(包含等,2014),共分为5个土层,各层土壤的划分范围见表2。模拟时间为玉米的整个生长期,以气象条件作为模型的非稳定边界条件,选择Penman-Monteith公式运算,通过输入气象因子(气温、风速、相对湿度、净辐射、降水等)和玉米的LAI、株高,由模型自动计算蒸散量。研究区农田土壤类型为壤质砂土,降雨过程中很难产生地表径流,将模型上边界选为大气边界。研究区地下水埋深浅,不超过150 cm,因此水分运移的下边界为变压力水头边界。根系吸水模型采用无水分胁迫的Fedds模型,吸水参数采用Wesseling 1991年推荐的参数。玉米根系生长状况采用经验公式(8)进行估算(张蔚榛,1996)。
\({L}_{r}\left(\stackrel{-}{t}\right)=150\left(1-{e}^{-2.1886\stackrel{-}{t}}\right)\) (8)
其中\({L}_{r}\left(\stackrel{-}{t}\right)\)为根系层厚度,\(\stackrel{-}{t}\)为相对时间,是实际时间与整个生长期之比。
模型中的土壤水分特征参数包括残余含水率\({\theta }_{r}\)(cm3·cm-3),饱和含水率\({\theta }_{s}\)(cm3·cm-3),渗透系数K(cm·d-1),曲线形状参数n,经验参数\(\partial \) (cm-1)。特征参数通过Hydrus-1D软件依据Van Genuchten模型分层反演,并且将反演所得土壤水分特征曲线与实测值进行对比,则最小差异所对应的特征值作为最优反演结果,见表2和图2。
表2   土壤水分特征参数
土壤层深度
Soil depth /cm
\({\theta }_{r}\) /(cm3·cm-3)\({\theta }_{r}\) /(cm3·cm-3)\(\partial \) /cm-1nK /(cm·d-1)
0-100.0540.3920.08381.35939
10-200.0640.370.07931.38834.2
20-300.0560.3650.07861.44875.2
30-500.0440.380.05361.65351.4
50-1500.0460.440.03612.54869.7


图2   各深度土层拟合土壤水分特征曲线与实测值关系
Fig.2 The relationship between soil-water characteristic curves and measured values at different depth
图2显示,在浅部,拟合出的土壤水分特征曲线与实测值吻合度较高,而深部拟合结果与实测结果相差较大。可见,不同土壤水分吸力条件下模拟结果不同,在低土壤吸力的情况下模拟结果与实测误差较大,这与李峰等(2009)的研究相吻合。
1.4   模型检验
为了检验模拟效果,采用均方根误差、相对误差和Nash效率系数(Nash and Sutcliffe,1970)3个评价指标对模型进行定量评价,各评价指标的计算公式如下。
均方根误差(root mean square error,RMSE
\(RMSE=\sqrt{\frac{1}{N}\sum _{i=1}^{N}{\left({s}_{i}-{o}_{i}\right)}^{2}}\) (9)
相对误差(relative error,RE
\(RE=\frac{{\sum }_{i=1}^{N}{s}_{i}}{\sum _{i=1}^{N}{o}_{i}}-1\) (10)
Nash效率系数(Nash-sutcliffe efficiency coefficient,NSE
\(NSE=1-\frac{\sum _{i=1}^{N}{\left({s}_{i}-{o}_{i}\right)}^{2}}{\sum _{i=1}^{N}{\left({o}_{i}-\stackrel{-}{o}\right)}^{2}}\) (11)
以上公式中,\({s}_{i}\)\({o}_{i}\)分别为第i个样本的模拟值和实测值,\(o\)为实测值的平均值,N为样本数。3个指标中,RMSE反映模拟值与实测值的绝对误差的平均程度,RE反映模拟值与实测值总量之间的相对误差,NSE反映模拟值与实测值随时间变化过程的符合程度,当NSE>0.5时,认为模拟值为可接受值。
模型输出结果包括蒸散发、土壤含水率和底部交换量等。前人研究结果表明,Hydrus-1D模拟非饱和带水盐运移方面具有较高的精度(李亮等,2010),为了验证本模型运行结果的精度,将模拟含水率值与实测含水率值进行比较,利用RMSE、RE和NSE三个指标评价,结果如图3。


图3   春玉米试验田模拟值与实测值
Fig.3 Simulation and experimental values of spring corn field
图3结果显示,模型对浅部土壤的模拟比较精确,受地下水影响,在深部模拟精度有所下降。整体来看,各层土壤含水率的模拟值均能满足精度要求。
2   结果与讨论
2.1   土壤水分变化特征
土壤含水率的变化同灌溉降水、作物生长、蒸散发有密切的联系,在地下水浅埋区,地下水对土壤水分也有着重要的影响(Yang and Yanful,2002;乔冬梅等,2005)。
毛乌素沙地地下水浅埋区田间土壤含水率、地下水埋深、灌溉降水之间的关系如图4所示。


图4   不同深度土壤含水率、灌溉、降水、地下水埋深动态变化曲线
Fig.4 Dynamic curves of soil water content, irrigation, precipitation and groundwater depth
图中表明,深层含水率受地下水影响明显,变化规律同地下水埋深的变化规律较浅层更相似,而浅层土壤(40 cm深以上)含水率受到了根系吸水和气象因素的影响,对灌溉和降水的响应强烈,并且波动性比较大。在实际情况中,灌溉为缓解水分胁迫现象,图4中可见,当出现水分胁迫时,位于10 cm、20 cm、30 cm深度处土壤的含水率约为0.17、0.18、0.18 (cm3·cm-3)。
土壤含水率与地下水埋深的关系说明地下水影响土壤含水率。在田间排水沟中可发现,毛细水所形成的湿润面距离水面的高度可以达到70-80 cm,而研究时段的地下水埋深范围在90-130 cm,可见耕作层中的水分有一部分来自于地下水,这部分水分将参与到农田的蒸散作用中。
2.2   水分通量计算
利用Hydrus-1D模型输出田间蒸散量、土壤水储存量和底部交换量,田间水文变化过程见图5。


图5   水文变化过程及模型输出结果
Fig.5 Hydrological process and model output
结果表明,玉米的蒸散发与LAI之间关系密切。玉米生长初期LAI值小,田间蒸发强烈,随着LAI值的增大,蒸发量呈减小趋势,而蒸腾量逐渐变大。研究时段内平均地下水埋深为112.1 cm,毛细水上升高度则可以达到70-80 cm,模拟土层土壤水分储存量的变化与地下水埋深变化趋势相关性达0.96,而在图5中蒸散量与地下水埋深则呈反相关关系,由此可定性的判断地下水参与了农田的蒸散作用。
模型所输出的底部通量反映了模拟土层底部的水分交换信息,可定量化计算地下水对玉米生长的水分贡献。输出结果显示,模拟土层底部水分交换剧烈,在整个模拟期内,底部水分上移量为389.83 mm,深层入渗量为169.74 mm。由此可见,地下水对玉米生长的水分贡献量为220.09 mm,其中水分上移主要在蒸散作用强烈和地下水位抬升的情况下发生,深层入渗则主要发生在灌溉降水之后的较短时段内。灌溉作为补充土壤水分的方式,最佳的灌水量是既能满足对土壤水分的补充,又不发生多余的水量浪费,灌溉所引起的深层入渗是灌水的多余量,应尽量避免。研究时段内共发生6次灌溉,每次灌溉水量约为30 mm,根据模型输出结果,每次灌溉后深层入渗量平均值约为8.5mm,因此可将灌溉量减少为原水量的72%,以实现对水资源的有效利用和保护。
为了研究田间水分通量的变化规律,将水分通量按照玉米生长期进行分阶段定量研究,如表3。
表3   春玉米不同生长阶段田间水分通量变化
生长阶段/日期
Growth stage /Date
播种
Sowing
4.30-5.12
出苗
Seeding
5.13-6.11
拔节
Jointing
6.12-7.17
抽穗
Earing
7.18-8.7
灌浆
Filling
8.8-9.8
蜡熟
Dough
9.9-10.1
全期
Whole stage
4.30-10.1
天数
Days /d
133036213223155
灌溉降水入渗
Infiltration of irrigation and rainfall /mm
-95.77-6.81-143.15-62.47-26.59-3.21-338
蒸散
Evapotranspiration /mm
35.4258.13143.1131.53142.0570.1580.32
日蒸散
Daily evapotranspiration /(mm·d-)
2.721.943.976.264.443.053.74
日蒸发
Daily evaporation /mm
2.721.541.280.750.590.851.17
日蒸腾
Daily transpiration /mm
00.42.75.513.852.22.57
蒸发量占蒸散量比例
Proportion of evaporation in evapotranspiration /%
100793212132831
底面均衡
Bottom balanced /mm
-45.3-9.2417.8741.77144.9170.08220.09
日底面均衡
Daily balanced at bottom /(mm·d-)
-3.48-0.310.51.994.533.051.42
注:负号表示方向为垂直地面向下。
表3表明,玉米全生育期蒸散总量为580.32 mm,其中,蒸散主要发生在拔节、抽穗、灌浆三个生育阶段,占整个生育期的71.8%。蒸散最强烈发生在抽穗期,蒸腾最强烈发生在抽穗期,蒸发最强烈发生在播种期,而在灌浆期最弱。在玉米整个生育期内蒸发量占蒸散量的比例为31%。根据玉米生长过程和图5(a)所示信息,说明蒸发、蒸腾与叶面积指数具有显著的相关性,其相关系数分别为-0.599和0.712。
底部水分通量与降水灌溉和蒸散密切相关。在蒸散量较少的播种期,灌溉降水补给量大,在土壤层底部发生深层渗漏;而在蒸散量比较大的抽穗和灌浆期,底部水分上移,补充土壤水分,满足作物生长的蒸散;蜡熟期虽然蒸散减弱,但地表水分补给非常少,底部水分依然是田间蒸散水量的主要来源。在整个生长期中,地下水对蒸散的贡献量为220.09 mm,占总蒸散量比例的37.9%
2.3   地下水利用量与埋深关系
玉米的蒸散水分主要来自于降水灌溉、地下水、土壤水储存减少三部分。研究表明,地下水埋深直接影响植物根区土壤水分状况,地下水埋深越大,对植物耗水的补给作用越弱(亢连强等,2007)。
近几十年来,毛乌素沙地生态环境逐渐恶化,地下水位逐渐下降(徐小玲和延军平,2003)。地下水位的下降,减少了作物对地下水的利用,在同样气象条件下,所需灌溉量增多。为了推算不同地下水埋深下玉米对地下水的利用量,在Hydrus-1D模型的基础上,将模拟土层改为200 cm深,利用研究年气象条件,在地下水平均埋深112.1 cm的基础上降低地下水位,推测在不同地下水位埋深条件下玉米对地下水的利用量。其中假定作物生长状态不变,为了满足水分需求,需相应增加灌溉量。结果如图6所示。


图6   不同地下水埋深条件下春玉米水分利用情况
Fig.6 Groundwater uptake of spring coin under different depth
结果显示,随着地下水位的不断下降,玉米对地下水的利用量逐渐减小,所需灌溉量相应增加。当地下水位下降到埋深为147 cm的时候,玉米生长将不再利用地下水,而此时的灌溉量需要432.45 mm。所以,在毛乌素沙地,随着生态环境的不断恶化,地下水位的不断下降,当地的农业生产将会面临更大的压力。
3   结论
基于原位监测和Hydrus-1D模拟,对毛乌素沙地地下水浅埋区春玉米田间水分动态进行研究,结论如下:
(1)毛乌素沙地地下水埋深较浅,地下水与土壤水之间联系紧密。受根系吸水和气象因素的影响,10-40 cm深土层水分变化剧烈,而50 cm深以下土层水分变化受地下水的影响更显著。
(2)玉米全生育期的蒸散总量为580.32 mm,其中蒸发占比为31%。玉米的生长与地下水有密切的联系,地下水对玉米生长的水分贡献量为220.09 mm,占耗水总量的37.9%。
(3)现有的灌水量造成了水分的深层渗漏,为合理利用和保护水资源,在不改变灌溉方式的情况下,可将灌溉量减少为原水量的72%。
(4)地下水位的下降会减少作物对地下水的利用量,并且引起灌溉量的增加,当地下水位下降到埋深为147 cm的时候,玉米生长将不再利用地下水,而此时灌溉量也达到最大为432.45 mm。
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稿件与作者信息
包含1*,张国彪1,侯立柱2,沈建根3
BAO Han1*, ZHAN Guobiao1, HOU Lizhu2, SHEN Jiangen3
基金项目: 国家自然科学基金项目(41790443, 31700414);中央高校基本科研业务费项目(310821171007, 310821173701)
Foundation Item: National Natural Science Foundation of China (41790443, 31700414); Fundamental Research Fund for the Central University(310821171007, 310821173701)
出版历史
出版时间: 2018年7月23日 (版本4
参考文献列表中查看
地球环境学报
Journal of Earth Environment