陕北小流域植被耗水过程及环境因素影响研究
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摘要
陕北地区是我国生态环境最为脆弱的地区,研究流域尺度植被耗水特征及环境因子影响,对合理规划、利用水土资源及建设可持续发展的生态系统有重要意义。本文通过监测流域内不同土地利用方式土壤水分,系统掌握了不同植被类型耗水规律,并分析了小流域土壤理化性质的空间分布特征。本研究的主要结论如下:
     (1)不同土地利用方式土壤水分垂直变化上可分为土壤水分活跃层(0~40 cm)、土壤水分利用层(40~160 cm)和土壤水分调节层(160 cm以下)。变异系数和平均含水量呈线性负相关,极差和平均含水量呈线性正相关。不同土地利用储水量季节变化规律基本一致,5、6月份土壤储水量最少,8、9月份土壤储水量最高。2009年生长期降水量相对充足为421.5 mm,裸地、农地和灌木在雨季末土壤水分略有盈余。2010年生长季降水量较少为364.7 mm,导致所有土地利用方式土壤水分在雨季末均呈现出亏缺状态。2009年耗水量依次为:林地>草地>灌木>农地>裸地,2010年耗水量依次为:草地>灌木>林地>农地>裸地。
     (2)通过累积概率、相对偏差和spearman相关系数分析可知,LA、LB和LC子区域内点LA17、LB13和LC8与平均储水量间的相关性好、差异性小,可以分别代表3个区域剖面平均土壤储水量。LA和LB子区域3~4 m土壤储水量比其它土层稳定,子区域LC土壤储水量时间稳定性特征与LA和LB存在明显差异性。土壤储水量与spearman秩相关系数存在密切关系,土壤储水量变化较大时,spearman秩相关系数较小,时间稳定性差。而储水量保持稳定时,spearman秩相关系数明显较大。
     (3)不同处理3种植被株高和茎粗在生育期内的变化呈现出“慢-快-慢”的趋势,保水剂处理植被生长状况最好,株高、茎粗比秸秆覆盖和对照处理都要好。不同处理土壤蒸发量和植被蒸散耗水量日变化过程受降水量影响明显。秸秆覆盖明显减少了土壤蒸发量和植被蒸散耗水量,但对植被生物量和土壤性质的影响不明显,保水剂处理可减少土壤和植被的耗水量,同时对植被生物量和土壤性质的改善比较明显。保水剂和对照处理日实际蒸散耗水量与气象因素有明显的相关性,而秸秆覆盖条件下日蒸散耗水量与气象因子之间的相关性较弱。
     (4)经典统计表明流域内土壤颗粒分形维数、土壤pH、总孔隙度和容重属于弱变异,粘粒、粉粒、砂粒、有机碳、全磷、全氮、铵态氮、有效钾、有效磷、有效铜、有效锌、有效铁、有效锰和毛管孔隙度均属于中等变异,硝态氮和饱和导水率为强变异。单因素方差分析的结果表明不同土地利用方式显著影响土壤理化性质在流域内的分布状况。小流域内的分形维数值在1.37~2.66之间,分形维数与粘粒、粉粒和沙粒分别呈曲线相关。地统计学研究表明,流域内不同土壤理化性质含量及其它属性的空间变异结构存在较大差异,且土壤理化性质的空间自相关距变化较大,空间自相关范围差异显著。土壤理化性质插值图可以获取准确的土壤性质空间信息及分布规律,为该地区实施精准农业提供帮助和依据。
     (5)主成分人工神经网络模型对于4站点日ET0值的模拟能力非常好,特别在训练样本阶段主成分人工神经网络模型对榆林、太原和西安日ET0值模拟效果明显好于传统BP人工神经网络模型,且与Penman-Monteith公式计算值的相关性好、差异性小(R2 > 0.95)。与传统BP人工神经网络模型比较发现,经主成分简化的人工神经网络模型具有结构简单、精度高和降低噪音的效果。
The nature ecological environment is very fragile in the northern loess plateau of china. Study on characteristics of vegetation water consumption and its influencing factors in a small watershed, will help to utilize water-soil resources and establish sustainable development ecosystem. In this study, in order to understand characteristics of different vegetations water consumption, the dynamics of soil moisture and water consumptions of vegetations on different land uses were analyzed. In addition, spatial variability of soil properties was investigated in a watershed on the Loess Plateau of China. The main conclusions of this study were as follows:
     (1) The results showed that the vertical change of soil moisture could be divided into three layers: weak absorbing layer, absorbing layer, and regulating layer. There were significant linear negative correlation between coefficient of variations and mean soil moisture, and significant linear positive correlation between extreme differences and mean soil moisture. The seasonal changes of soil water storage in different land uses were similar. In May and June the soil water storages were low, and in September and October were high. The total precipitation in the growing season was 421.5 mm in the year of 2009, which was sufficient for the growing of plants. The soil moisture was surplus for bare land, farm land, and shrub land in the end of growing season. The total precipitation was 364.7 mm in the year of 2010 which was 56.8 mm less than the year of 2009. In the end of growing season in 2010 the soil moisture was deficit. The orders of different land uses water consumptions in the year of 2009 were: wood land > grass land > shrub land > farm land > bare land. The orders of different land uses water consumptions in the year of 2010 were: grass land > shrub land > wood land > farm land > bare land.
     (2) The sites of LA17, LB13, and LC8 could represent the mean SWS of LA, LB, and LC subregions, respectively. The 3~4 m SWS had higher time stabilities than other soil depths at LA and LB subregions. The time stability of SWS in LC subregion was obviously different from LA and LB subregions. The spearman rank correlation coefficients were small when the SWS varied greatly, but increased when the SWS remained more or less stable.
     (3) The change of vegetations height and stem diameter complied with“slow-quick-slow”curve during the different growing stages. The biomasses under PAM treatment were higher than straw mulch treatment and CK. The daily water consumption variations of the three types of vegetations were significantly affected by precipitation, indicating that evapotranspiration processes were controlled by the soil water moisture in the arid region. PAM and straw mulch could reduce the water consumption for bare land and three kinds of vegetations. PAM could increase the biomasses and improve soil properties; however straw mulch had no influence on them. There were significant correlation between the water consumption and meteorological factors on PAM treatment and CK, and no correlation on straw mulch treatment.
     (4) The classical statistics indicated that fractal dimension (D), pH, total porosity, and bulk density were weak variability, and ammonium nitrogen (NH_4~`+-N), extractable soil potassium (K), phosphorus (P), copper (Cu), zinc (Zn), ferrum (Fe), and manganese (Mn) were medium variability, while nitrate nitrogen (NO_3~--N) and soil hydraulic conductivity (KS) had strong variability. Soil properties were mainly correlated to land uses within the research area. The D values in the research area ranged from 1.37 to 2.66. There was a significant sigmoidal correlation between D values and the contents of clay, silt, and sand fractions. Geostatistical analyses showed that the spatial autocorrelation of all soil properties were strong. The ordinary kriging maps could provide useful information for the development and application of precision agriculture in wind-water erosion crisscross region on the Loess Plateau of China.
     (5) The performance of the principal components BP neural network model was well in simulating daily ET0 on the Loess Plateau. The simulation ability of principal components BP neural network model was better than tradition BP neural network model during the training stage for Yulin, Taiyuan, and Xi’an stations. The ET0 values simulated by three principal components BP neural network were consistent with the Penman-Monteith method (R2>0.95). It clearly demonstrated that high precision, simple structure and minimum error for the principal components BP neural network model in estimating ET0 compared to the tradition BP neural network model.
引文
白文波,宋吉青,李茂松,汪亚峰,武永峰,刘布春,王春艳,王秀芬. 2009.保水剂对土壤水分垂直入渗特征的影响.农业工程学报,25(2):18~23.
    白一茹,邵明安. 2009.黄土高原水蚀风蚀交错带不同土地利用方式坡面土壤水分特性研究.干旱地区农业研究,27(1):122~129.
    曾群,蔡述明,杜耘. 2006.全球气候变化对水资源的潜在影响.资源环境与发展,(1):45~48.
    陈宝玉,王洪君,滕轶,孙海芹,杨建,黄选瑞. 2008.保水剂对土壤温度和水分动态的影响.中国水土保持科学,6(6):32~36.
    陈素英,张喜英,裴冬,孙宏勇. 2005.玉米秸秆覆盖对麦田土壤温度和土壤蒸发的影响.农业工程学报,21(10):171~173.
    程积民,万惠娥,王静. 2003.黄土丘陵区小叶杨林地土壤水分过耗动态.水土保持学报,17(3):70~73.
    程积民,万惠娥,王静,雍绍萍. 2005.半干旱区柠条生长与土壤水分消耗过程研究.林业科学,41(2):37~41.
    崔远来,马承新,沈细中,马吉刚. 2005.基于进化神经网络的参考作物腾发量预测.水科学进展,16(1):76~81.
    党亚爱,李世清,王国栋,赵坤. 2009.黄土高原典型土壤剖面土壤颗粒组成分形特征.农业工程学报,25(9):74~78.
    董英,郭绍辉,詹亚力. 2004.聚丙烯酰胺的土壤改良效应.高分子通报,5:83~87.
    杜社妮,白岗栓,赵世伟,侯喜录. 2007.沃特和PAM保水剂对土壤水分及马铃薯生长的影响研究.农业工程学报,23(8):72~79.
    杜社妮,白岗栓,赵世伟,侯喜录. 2008.沃特和PAM施用方式对土壤水分及玉米生长的影响.农业工程学报,24(11):30~35.
    杜太生,康绍忠,魏华. 2000.保水剂在节水农业中的应用研究现状与展望.农业现代化研究,21(5):317~320.
    冯娜娜,李廷轩,张锡洲,王永东,夏建国. 2006.不同尺度下低山茶园土壤有机质含量的空间变异.生态学报,26(2):349~356.
    傅伯杰,陈利顶,马克明. 1999.黄土丘陵区小流域土地利用变化对生态环境的影响-以延安市羊圈沟流域为例.地理学报,54(3):241~246.
    甘卓亭,刘文兆. 2006.黄土塬区麦田蒸散特征.应用生态学报,17(8):1435~1438.
    高茂盛,温晓霞,黄灵丹,廖允成,刘根全. 2010.耕作和秸秆覆盖对苹果园土壤水分及养分的.自然资源学报,25(4):547~555.
    龚元石,廖超子,李保国. 1998.土壤含水量和容重的空间变异及其分形特征.土壤学报,35(1):10~15.
    郭忠升. 2004.黄土丘陵半干旱区土壤水分植被承载力研究.[博士学位论文].西北农林科技大学:杨凌.
    郭忠升,邵明安. 2003.半干旱区人工林草地土壤旱化与土壤水分植被承载力.生态学报,23(8):1640~1647.
    郭忠升,邵明安. 2007.人工柠条林地土壤水分补给和消耗动态变化规律.水土保持学报,21(2):119~123.
    韩蕊莲,侯庆春. 1996.黄土高原人工林小老树成因分析.干旱地区农业研究,14(4):104~108.
    韩仕峰,李玉山,张孝中,史竹叶. 1989.黄土高原地区土壤水分区域动态特征.中国科学院西北水土保持研究所集刊(土壤水分与土壤肥力研究专集),10:161~167.
    和继军,蔡强国,唐泽军. 2007. PAM控制土壤风蚀的风洞实验研究.水土保持学报,21(2):12~15.
    侯景儒,尹镇南,李维明,向永生,黄竞先,胡平昭. 1998.实用地质统计学.地质出版社:北京.
    侯庆春. 1993.神木试区自然条件及环境整治综合分析.中国科学院水利部西北水土保持研究所集刊,18:136~137.
    侯庆春,韩蕊莲,韩仕峰. 1999.黄土高原人工林草地“土壤干层”问题初探.中国水土保持科学,(5):11~14.
    胡建忠,朱金兆. 2005.黄土高原退化生态系统的恢复重建方略.北京林业大学学报(社会科学版),4(1):13~19.
    胡伟,邵明安,王全九. 2005.黄土高原退耕坡地土壤水分空间变异的尺度性研究.农业工程学报,21(8):11~16.
    黄占斌,张国桢,李秧秧,郝明德. 2002.保水剂特性测定及其在农业中的应用.农业工程学报,18(1):22~26.
    霍再林,史海滨,李为萍,佟长福,徐冰. 2004.参考作物蒸发蒸腾量的人工神经网络模型研究.沈阳农业大学学报,35(Z1):436~438.
    贾恒义,雍绍萍,王富乾. 1993.神木试区的土壤资源.中国科学院水利部西北水土保持研究所集刊,18:36~46.
    姜娜,邵明安,雷廷武,田磊. 2007.水蚀风蚀交错带典型土地利用方式土壤水分变化特征.北京林业大学学报,29(6):134~137.
    李洪建,王孟本,柴宝峰. 1998.晋西北人工林土壤水分特点与降水关系研究.土壤侵蚀与水土保持学报,4(4):60~65.
    李慧星,夏自强,马广慧. 2007.含水量变化对土壤温度和水分交换的影响研究.河海大学学报(自然科学版),35(2):172~175.
    李军,陈兵,李小芳,程积民,郝明德. 2007.黄土高原不同干旱类型区苜蓿草地深层土壤干燥化效应.生态学报,27(1):75~89.
    李玲玲,黄高宝,张仁陟,晋小军. 2005.免耕秸秆覆盖对旱作农田土壤水分的影响. 水土保持学报,19(6):94~96.
    李世清,高亚军,杜建军. 1995.耕作制度和施用磷肥对土壤蓄水的影响.汪德水(编辑),旱地农田肥水关系原理与调控技术.中国农业科技出版社,北京:322~325.
    李世荣,张卫强,贺康宁. 2003.黄土半干旱区不同密度刺槐林地的土壤水分动态. 中国水土保持科学,1(2):28~32.
    李玉山. 1983.黄土区土壤水分循环特征及其对陆地水分循环的影响.生态学报,3(2):91~101.
    李玉山. 2002.苜蓿生产力动态及其水分生态环境效应.土壤学报,(3):404~411.
    李云开,杨培岭,刘洪禄. 2002.保水剂农业应用及其效应研究进展.农业工程学报,18(2):182~187.
    林文杰,马换成,周蛟,张志斌,甘云浩. 2004.干旱胁迫下保水剂对苗木生长及生理的影响.干旱区研究,21(4):353~357.
    刘沛松,贾志宽,李军,任小龙,李永平,刘世新. 2008.宁南山区紫花苜蓿(Medicago sativa)土壤干层水分动态及草粮轮作恢复效应.生态学报,28(1):183~191.
    刘世亮,寇太记,介小磊,李有田,谭金芳. 2005.保水剂对玉米生长和土壤养分转化供应的影响研究.河南农业大学学报,39(2):146~150.
    刘婷,贾志宽,张睿,郑甲成,任世春,杨宝平,聂俊峰,刘艳红,王海霞. 2010.秸秆覆盖对旱地土壤水分及冬小麦水分利用效率的影响.西北农林科技大学学报(自然科学版),38(7):69~76.
    刘孝利,李凤民,曾昭霞,陈求稳. 2007.黄土高原地区不同草地退耕模式水分利用效率的比较.生态学报,27(7):2847~2855.
    刘云鹏. 2002.土壤结构的分形特征及土壤水分运动模型研究.[博士学位论文].西北农林科技大学:陕西杨凌.
    吕军,俞劲炎. 1990.水稻土物理性质空间变异性研究.土壤学报,27(1):8~15.
    闵惜琳,刘国华. 2008.用MATLAB神经网络工具箱开发BP网络应用.计算机应用,21(8):163~164.
    欧建锋,程吉林. 2008.基于主成分BP人工神经网络的参考作物腾发量预测.灌溉排水学报,27(2):55~58.
    潘颜霞,王新平,苏延桂,李小军,高艳红. 2009.荒漠人工固沙植被区浅层土壤水分动态的时间稳定性特征.中国沙漠,29(1):81~86.
    逄焕成. 1999.秸秆覆盖对土壤环境及冬小麦产量状况的影响.土壤通报,30(4):174~175.
    彭世彰,魏征,徐俊增,丁加丽. 2008.参考作物腾发量主成分神经网络预测模型.农业工程学报,24(9):161~164.
    冉有华,李新,王维真,晋锐. 2009.黑河流域临泽盐碱化草地网格尺度多层土壤水分时空稳定性分析.地球科学进展,24(7):817~824.
    申元村. 2005.黄土高原植被生态建设的反思与对策.大自然,1:15~19.
    沈掌泉,周斌,孔繁胜,John S B. 2004.应用广义回归神经网络进行土壤空间变异研究.土壤学报,41(3):471~475.
    史海滨,陈亚新,蔡凯,张旭. 1997.西辽河平原土壤墒情的空间变异性与大面积区域预测预报研究.干旱区资源与环境,11(4):36~40.
    史竹叶. 1993.神木试区土壤水分资源状况.中科院西北水土保持研究所集刊,18:132~134.
    孙帆,施学勤. 2007.基于MATLAB的BP神经网络设计.计算机与数字工程,35(8):124~126.
    孙长忠,黄宝龙,陈海滨,刘增文,温仲明. 1998.黄土高原人工植被与其水分环境相互作用关系研究.北京林业大学学报,3:7~11.
    谭勇,王长如,梁宗锁,杜峰. 2006.黄土高原半干旱区林草植被建设措施.草业学报,15(4):4~11.
    唐克丽. 2000.黄土高原水蚀风蚀交错区治理的重要性与紧迫性.中国水土保持,1(11):11~16.
    唐克丽. 2004.中国水土保持.科学出版社:北京.
    唐克丽,侯庆春,王斌科. 1993.黄土高原水蚀风蚀交错带和神木试区的环境背景及整治方向.中国科学院水利部西北水土保持研究所集刊,18:1~15.
    万素梅,贾志宽,韩清芳,杨宝平. 2008.黄土高原半湿润区苜蓿草地土壤干层形成及水分恢复.生态学报,28(3):1045~1051.
    汪丙国,靳孟贵,王贵玲. 2010.农田秸秆覆盖的土壤水分效应.中国农村水利水电,(6):76~80,84.
    汪莹,李炳富. 2008.神经网络的应用研究探讨.电脑知识与技术,3(22):635~636.
    王改改,魏朝富,吕家恪,张卫华. 2009.四川盆地丘陵区土壤水分空间变异及其时间稳定性分析.山地学报,27(2):211~216.
    王国梁,刘国彬,党小虎. 2009.黄土丘陵区不同土地利用方式对土壤含水率的影响.农业工程学报,25(2):31~35.
    王国梁,周生路,赵其国. 2005.土壤颗粒的体积分形维数及其在土地利用中的应用.土壤学报,42(4):545~550.
    王华连. 2004.黄土高原小流域植被建设问题探讨.甘肃林业科技,29(3):44~47.
    王礼先. 2000.植被生态建设与生态用水-以西北地区为例.水土保持研究,7(3):5~7.
    王力,邵明安,侯庆春. 2000.延安试区土壤干层现象分析.水土保持通报,20(3):35~37.
    王力,卫三平,吴发启. 2009.黄土丘陵沟壑区土壤水分环境及植被生长响应-以燕沟流域为例.生态学报,29(3):1543~1553.
    王延平,邵明安,张兴昌. 2008.陕北黄土区陡坡地人工植被的土壤水分生态环境.生态学报,28(8):3769~3778.
    王延平. 2009.·陕北黄土区陡坡地土壤水分植被承载力研究.[博士学位论文].西北农林科技大学:陕西杨凌.
    王一鸣. 2000.保水剂在我国农业中的试验研究与应用.中国农业气象,21(1):49~51.
    王幼奇,樊军,邵明安. 2010.陕北黄土高原雨养区谷子棵间蒸发与田间蒸散规律.农业工程学报,26(1):6~10.
    王幼奇,樊军,邵明安,白一茹. 2008.黄土高原地区近50年参考作物蒸散量变化特征.农业工程学报,24(9):6~10.
    王宇,叶建仁. 2008.保水剂种类及含量对土壤水分蒸发的影响.南京林业大学学报(自然科学版),32(4):95~97.
    王云强,张兴昌,从伟,魏清才. 2006.黄土区不同土地利用方式坡面土壤含水率的空间变异性研究.农业工程学报,22(12):65~71.
    温耀华,罗金耀,李小平,孙俊,高金花,程国银,赵秀江. 2008.基于BP神经网络的大棚作物腾发量预测模型.中国农村水利水电,2:20~21,25.
    吴德瑜. 1991.保水剂与农业.中国农业出版社:北京.
    吴钦孝,杨文治. 1998.黄土高原植被建设与可持续发展.科学出版社:北京.
    夏永秋,邵明安. 2008.黄土高原半干旱区柠条(Caragana korsh inskii)树干液流动态及其影响因子.生态学报,28(4):1376~1382.
    徐炳成,山仑. 2004.半干旱黄土丘陵区沙棘和柠条水分利用与适应性特征比较.应用生态学报,15(11):2025~2028.
    徐俊增,彭世彰,张瑞美,李道西. 2006.基于气象预报的参考作物蒸发蒸腾量的神经网络预测模型.水利学报,30(3):376~379.
    徐自祥,周德云,罗奕然. 2006.基于主成分的模糊神经网络.计算机工程与应用,(5):34~36.
    杨宝华. 2008.基于Matlab的BP神经网络应用.电脑知识与技术,19:124~125,134.
    杨海军,孙立达,余新晓. 1993.晋西黄土区水土保持林水量平衡的研究.北京林业大学学报,15(3):42~50.
    杨连利,李仲谨,邓娟利. 2005.保水剂的研究进展及发展新动向.材料导报,19(6):42~44.
    杨培岭,罗远培,石元春. 1993.用粒径的重量分布表征的土壤分形特征.科学通报,38(20):1896~1899.
    杨勤科,郑粉莉,张竹梅. 1993.神木试区土地资源与利用.中国科学院水利部西北水土保持研究所集刊,18:47~56.
    杨维西. 1996.试论我国北方地区人工植被的土壤干化问题.林业科学,32(1):78~85.
    杨文治,韩仕峰. 1985.黄土丘陵区人工林草地的土壤水分生态环境.中国科学院西
    北水土保持研究所集刊(土壤水分与土壤肥力研究专集),2(2):18~28.
    杨文治,余存祖. 1992.黄土高原区域治理与评价.科学出版社:北京.
    杨永东,张建生,蔡国军,莫保儒,王子婷,柴春山. 2008.黄土高原丘陵沟壑区不同植被类型土壤水分动态变化.水土保持研究,15(4):149~151,156.
    杨永辉,武继承,吴普特,赵世伟,何方,史福刚. 2009.秸秆覆盖与保水剂对土壤结构、蒸发及入渗过程的作用机制.中国水土保持科学,7(5):70~75.
    杨永辉,武继承,赵世伟,曹丽花,黄占斌. 2007. PAM的土壤保水性能研究.西北农林科技大学学报(自然科学版),35(12):120~124.
    杨直毅,汪有科,赵颖娜,黎朋红,段雪松. 2010.树枝覆盖与保水剂对土壤水分的影响.灌溉排水学报,29(1):97~99.
    于健,雷廷武,I. Shainberg,张俊生,张季平. 2010.不同PAM施用方法对土壤入渗和侵蚀的影响.农业工程学报,26(7):38~44.
    于舜章,陈雨海,周勋波,李全起,罗毅,于强. 2004.冬小麦期覆盖秸秆对夏玉米土壤水分动态变化及产量的影响.水土保持学报,18(6):175~179.
    员学锋,吴普特,汪有科,徐福利. 2006.免耕条件下秸秆覆盖保墒灌溉的土壤水、热及作物效应研究.农业工程学报,22(7):22~26.
    原焕英,许喜明. 2004.黄土高原半干旱丘陵沟壑区人工林土壤水分动态研究.西北林学院学报,19(2):5~8.
    苑小勇,黄元仿,高如泰,柴旭荣,贺勇. 2008.北京市平谷区农用地土壤有机质空间变异特征.农业工程学报,24(2):70~76.
    张北赢,徐学选,白晓华. 2006.黄土丘陵区不同土地利用方式下土壤水分分析.干旱地区农业研究,24(2):96~99.
    张淑娟,何勇,方慧. 2003.基于GPS和GIS的田间土壤特性空间变异性的研究.农业工程学报,19(2):39~44.
    赵聚宝,梅旭荣,薛军红,钟兆站,张天佑. 1996.秸秆覆盖对旱地作物水分利用效率的影响.中国农业科学,29(2):59~66.
    赵姚阳,刘文兆,濮励杰. 2005.黄土丘陵沟壑区苜蓿地土壤水分环境效应.自然资源学报,20(1):85~91.
    赵永存,史学正,于东升,赵彦锋,孙维侠,王洪杰. 2005.不同方法预测河北省土壤有机碳密度空间分布特征的研究.土壤学报,42(3):379~385.
    郑纪勇,邵明安,张兴昌. 2004.黄土区坡面表层土壤容重和饱和导水率空间变异特征.水土保持学报,18(3):53~56.
    中国科学院黄土高原综合科学考察队. 1991.黄土高原地区自然环境及其演变.科学出版社:北京.
    周海光,刘广全,焦醒,王鸿喆. 2008a.黄土高原水蚀风蚀复合区几种树木蒸腾耗水特性.生态学报,28(9):4568~4574.
    周海光,刘广全,焦醒,王鸿喆,李红生. 2008b.黄土高原水蚀风蚀复合区人工植被土壤水分状况.水土保持学报,22(5):194~197,203.
    周开利,康耀红. 2005.神经网络模型及其Matlab仿真程序设计.清华大学出版社:北京.
    周启友,岛田纯. 2003.土壤水空间分布结构的时间稳定性.土壤学报,40(5):683~690.
    朱德兰,杨涛,王得祥,蔺雨阳,钱红格,周金星. 2009.黄土丘陵沟壑区三种不同
    植被土壤水分动态及蒸散耗水规律研究.水土保持研究,16(1):8~12.
    朱显谟. 1989.黄土高原土壤与农业.农业出版社:北京
    Allen R G, Jensen M E, Wright J L, Burman R D. 1989. Operational estimates of reference evapotranspiration. Agronomy Journal, 81(4): 650~662.
    Allen R G, Pereira L S, Raes D, Smith M. 1998. Crop Evapotranspiration - Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainge Paper 56. Bittelli M, Campbell G S, Flury M. 1999. Characterization of particle-size distribution in soils with a fragmentation model. Soil Science Society of America Journal, 63(4): 782~788. Cambardella C A, Moorman T B, Novak J M, Parkin T B, Karlen D L, Turco R F, Konopka A E. 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal, 58(5): 1501~1511.
    Chauhan S, Shrivastava R K. 2009. Performance evaluation of reference evapotranspiration estimation using climate based methods and artificial neural networks. Water Resources Management, 23(5): 825~837.
    Chen Y Z, Luck S H. 1989. Sediment sources and recent changes in the sediment load of Yellow River, China. In: Rindwanich S (Ed.), Land Conservation for Future Generations Ministry of Agriculture, Bangkok: pp. 313~323. 100
    Comegna V, Basile A. 1994. Temporal stability of spatial patterns of soil water storage in a cultivated vesuvian soil. Geoderma, 62(1-3): 299~310.
    Cosh M H, Jackson T J, Moran S, Bindlish R. 2008. Temporal persistence and stability of surface soil moisture in a semi-arid watershed. Remote Sensing of Environment, 112(2): 304~313.
    Duffera M, White J G, Weisz R. 2007. Spatial variability of southeastern US coastal plain soil physical properties: Implications for site-specific management. Geoderma, 137(3): 327~339.
    Evett S R, Peters F H, Jones O R, Unger P W. 1999. Soil hydraulic conductivity and retention curves from tension infiltrometer and laboratory data. In: van Genuchten M T, Leij F J, Wu L (Eds.), Proceedings of the International Workshop on Characterisation and Measurement of the Hydraulic Properties of Unsaturated Porous Media, University of California: p. 541~551.
    Falleiros M C, Portezan O, Oliveira J C M, Bacchi O O S, Reichardt K. 1998. Spatial and temporal variability of soil hydraulic conductivity in relation to soil water distribution, using an exponential model. Soil & Tillage Research, 45(3): 279~285.
    Farahani H J, Buchleiter G W. 2004. Temporal stability of soil electrical conductivity in irrigated sandy fields in Colorado. Transactions of the Asae, 47(1): 79~90.
    Florinsky I V, Eilers R G, Manning G R, Fuller L G. 2002. Prediction of soil properties by digital terrain modelling. Environmental Modelling & Software, 17(3): 295~311.
    Fu B J, Chen L D, Ma K M, Zhou H F, Wang J. 2000. The relationships between land use and soil conditions in the hilly area of the loess plateau in northern Shaanxi, China. Catena, 39(1): 69~78.
    Fu B J, Wang J, Chen L D, Qiu Y. 2003. The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China. Catena, 54(1-2): 197~213.
    Fu X L, Shao M A, Wei X R, Horton R. 2010. Soil organic carbon and total nitrogen as affected by vegetation types in Northern Loess Plateau of China. Geoderma, 155(2): 31~35.
    Goovaerts P. 1998. Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil properties. Biology and Fertility of Soils, 27(4): 315~334.
    Grant C A, Lafond G P. 1991. Effect of tillage and crop rotation on soil quality factors. Proceedings of the Saskatchewan Soils and Crops Workshop. Sask, Saskatoon.
    Grayson R B, Western A W. 1998. Towards areal estimation of soil water content from point measurements: time and space stability of mean response. Journal of Hydrology, 207(1): 68~82.
    Heathman G C, Larose M, Cosh M H, Bindlish R. 2009. Surface and profile soil moisture spatio-temporal analysis during an excessive rainfall period in the Southern Great Plains, USA. Catena, 78(2): 159~169.
    Hendrayanto, Kosugi K i, Uchida T, Matsuda S, Mizuyama T. 1999. Spatial variability of soil hydraulic properties in a forested hillslope. Journal of Forest Research, 4(2): 107~114.
    Hopfield J J. 1982. Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences of the United States of America, 79(8): 2554~2558.
    Hu W, Shao M A, Han F P, Reichardt K, Tan J. 2010. Watershed scale temporal stability of soil water content. Geoderma, 158(4): 181~198.
    Hu W, Shao M A, Wang Q J, Reichardt K. 2009a. Time stability of soil water storage measured by neutron probe and the effects of calibration procedures in a small watershed. Catena, 79(1): 72~82.
    Hu W, Shao M G, Wang Q J, Fan J, Horton R. 2009b. Temporal changes of soil hydraulic properties under different land uses. Geoderma, 149(3): 355~366.
    Iqbal J, Thomasson J A, Jenkins J N, Owens P R, Whisler F D. 2005. Spatial variability analysis of soil physical properties of alluvial soils. Soil Science Society of America Journal, 69(4): 1338~1350.
    Jacobs J M, Mohanty B P, Hsu E C, Miller D. 2004. SMEX02: Field scale variability, time stability and similarity of soil moisture. Remote Sensing of Environment, 92(4): 436~446.
    Jain S K, Nayak P C, Sudheer K P. 2008. Models for estimating evapotranspiration using artificial neural networks, and their physical interpretation. Hydrological Processes, 22(13): 2225~2234.
    Jaynes D B, Hunsaker D J. 1989. Spatial and temporal variability of water content and infiltration on a flood irrigated field. Transactions of the ASEA, 32(4): 1229~1238.
    Jia X H, Li X R, Zhang J G, Zhang Z S. 2009. Analysis of spatial variability of the fractal dimension of soil particle size in Ammopiptanthus mongolicus' desert habitat. Environmental Geology, 58(5): 953~962.
    Kisi O. 2006a. Daily pan evaporation modelling using a neuro-fuzzy computing technique. Journal of Hydrology, 329(3): 636~646.
    Kisi O. 2006b. Evapotranspiration estimation using feed-forward neural networks. Nordic Hydrology, 37(3): 247~260.
    Kisi O. 2006c. Generalized regression neural networks for evapotranspiration modelling. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 51(6): 1092~1105.
    Kisi O. 2007. Evapotranspiration modelling from climatic data using a neural computing technique. Hydrological Processes, 21(14): 1925~1934.
    Kumar M, Bandyopadhyay A, Raghuwanshi N S, Singh R. 2008. Comparative study of conventional and artificial neural network-based ETo estimation models. Irrigation Science, 26(6): 531~545.
    Li H, Reynolds J F. 1995. On definition and quantification of heterogeneity. Oikos, 73(2): 280~284.
    Liu X, Zhang G C, Heathman G C, Wang Y Q, Huang C H. 2009. Fractal features of soil particle-size distribution as affected by plant communities in the forested region of Mountain Yimeng, China. Geoderma, 154(1): 123~130.
    Lopez-Granados F, Jurado-Exposito M, Atenciano S, Garcia-Ferrer A, de la Orden M S, Garcia-Torres L. 2002. Spatial variability of agricultural soil parameters in southern Spain. Plant and Soil, 246(1): 97~105.
    Mallants D, Mohanty B P, Vervoort A, Feyen J. 1997. Spatial analysis of saturated hydraulic conductivity in a soil with macropores. Soil Technology, 10(2): 115~131.
    Mandelbrot B B. 1983. The fractal geometry of nature. W.H. Freeman: San Francisco. Martinez-Fernandez J, Ceballos A. 2003. Temporal stability of soil moisture in a large-field experiment in Spain. Soil Science Society of America Journal, 67(6): 1647~1656.
    Martinez-Fernandez J, Ceballos A. 2005. Mean soil moisture estimation using temporal stability analysis. Journal of Hydrology, 312(4): 28~38.
    Millan H, Gonzalez-Posada M, Aguilar M, Dominguez J, Cespedes L. 2003. On the fractal scaling of soil data. Particle-size distributions. Geoderma, 117(1): 117~128.
    Mohanty B P, Skaggs T H. 2001. Spatio-temporal evolution and time-stable characteristics of soil moisture within remote sensing footprints with varying soil, slope, and vegetation. Advances in Water Resources, 24(9): 1051~1067.
    Nielsen D R, Bouma J. 1985. Soil spatial variability. Proceedings of a workshop of the ISSS and the SSSA,. Pudoc, Wageningen(Netherlands), Las Vegas (USA). Osunbitan J A, Oyedele D J, Adekalu K O. 2005. Tillage effects on bulk density, hydraulic conductivity and strength of a loamy sand soil in southwestern Nigeria. Soil and Tillage Research, 82(1): 57~64.
    Qiu Y, Fu B J, Wang J, Chen L D. 2001. Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China. Journal of Hydrology, 240(3): 243~263.
    Qureshi. Salahuddin. 1989. Regional perspective on dry farming. Rawat Published: Jaipur.
    Sauer T J, Clothier B E, Daniel T C. 1990. Surface measurements of the hydraulic properties of a tilled and untilled soil. Soil and Tillage Research, 15(4): 359~369.
    Shukla M K, Slater B K, Lal R, Cepuder P. 2004. Spatial variability of soil properties and potential management classification of a chernozemic field in lower Austria. Soil Science, 169(12): 852~860.
    Sigua G C, Hudnall W H. 2008. Kriging analysis of soil properties - Implication to landscape management and productivity improvement. Journal of Soils and Sediments, 8(3): 193~202.
    Sobieraj J A, Elsenbeer H, Coelho R M, Newton B. 2002. Spatial variability of soil hydraulic conductivity along a tropical rainforest catena. Geoderma, 108(1): 79~90.
    Starks P J, Heathman G C, Jackson T J, Cosh M H. 2006. Temporal stability of soil moisture profile. Journal of Hydrology, 324(1): 400~411.
    Su Y Z, Zhao H L, Zhao W Z, Zhang T H. 2004. Fractal features of soil particle size distribution and the implication for indicating desertification. Geoderma, 122(1): 43~49.
    Sudheer K P, Gosain A K, Rangan D M, Saheb S M. 2002. Modelling evaporation using an artificial neural network algorithm. Hydrological Processes, 16(16): 3189~3202.
    Trajkovic S, Todorovic B, Stankovic M. 2003. Forecasting of reference evapotranspiration by artificial neural networks. Journal of Irrigation and Drainage Engineering-Asce, 129(6): 454~457.
    Tsegaye T, Hill R L. 1998. Intensive tillage effects on spatial variability of soil physical properties. Soil Science, 163(2): 143~154.
    Turcotte D. 1986. Fractals and fragmentation. Journal of Geophysical Research, 91(B2): 1921~1926.
    Vachaud G, Passerat De Silans A, Balabanis P, Vauclin M. 1985. Temporal stability of spatially measured soil water probability density function. Soil Science Society of America Journal, 49: 822~828.
    Vivoni E R, Gebremichael M, Watts C J, Bindlish R, Jackson T J. 2008. Comparison of ground-based and remotely-sensed surface soil moisture estimates over complex terrain during SMEX04. Remote Sensing of Environment, 112(2): 314~325.
    Wagner W, Pathe C, Doubkova M, Sabel D, Bartsch A, Hasenauer S, Bloschl G, Scipal K, Martinez-Fernandez J, Low A. 2008. Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR). Sensors, 8(2): 1174~1197.
    Wang Y Q, Shao M A, Gao L. 2010. Spatial variability of soil particle size distribution and fractal features in water-wind erosion crisscross region on the Loess Plateau of China. Soil Science, 175(12): 579~585
    Zhang R D. 2005. Applied geostatistics in environmental science. Science Press USA Inc.
    Zhang X Y, Sui Y Y, Zhang X D, Meng K, Herbert S J. 2007. Spatial variability of nutrient properties in black soil of northeast China. Pedosphere, 17(1): 19~29.
    Zhao P P, Shao M A. 2010. Soil water spatial distribution in dam farmland on the Loess Plateau, China. Acta Agriculturae Scandinavica Section B-Soil and Plant Science, 60(2): 117~125.
    Zhao P P, Shao M A, Zhuang J. 2009. Fractal features of particle size redistributions of deposited soils on the dam farmlands. Soil Science, 174(7): 403~407.
    Zhao Y, Peth S, Wang X Y, Lin H, Horn R. 2010. Controls of surface soil moisture spatial patterns and their temporal stability in a semi-arid steppe. Hydrological Processes, 24(18): 2507~2519. .

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