非充分灌溉条件下作物需水量预测

按照晴、云、阴、雨等几种天气类型并利用历史资料来分类统计计算ET0,以实时的天气信息数据和土壤水分监测数据为基础,采用模糊聚类的方法对实时的ET0进行修正,再充分利用预报的日降水量,根据作物非充分实时灌溉预报模型和计划湿润层深,对土壤水分修正参数、作物系数进行修正。以冬小麦为例,进行作物需水量预测,结果表明,预测的作物需水量的相对误差平均值为5.29%,该方法用于作物需水量预报有效、可行,为实时优化配水提供依据。     

内蒙古农田潜在蒸散量敏感系数时空分布规律研究

为了得出对潜在蒸散量(ET0)影响最大的气象因子,选择内蒙古自治区8个气象站点1961~2013年长时间逐日气象数据,利用Penman-Monteith(P-M)公式计算8个站点逐日ET0,并基于无维偏导数法计算了不同气象因子的敏感系数,对其年际、年内和空间变化趋势进行了分析,结果表明:内蒙古区平均温度的变化趋势最大,且不同站点正负取值不同,风速敏感系数呈自西南到东北逐渐降低趋势,日照敏感系数呈中部最高,两侧逐渐减小趋势,而相对湿度敏感系数呈自西南到东北逐渐升高趋势,对内蒙古ET0影响最大的气象因子为相对湿度,风速次之,日照和平均温度的影响较小。     

石羊河流域参考作物蒸发蒸腾量对气候变化的响应模拟及预测

模拟和预测气候变化对石羊河流域参考作物蒸发蒸腾量(ET0)时空分布的影响,为发展节水农业和科学利用水资源提供参考依据。根据石羊河流域及周边11个气象站点1951—2012年的逐日气象资料,使用PenmanMonteith公式计算现状ET0,利用大气环流模型HadCM3的输出和SDSM统计降尺度模型,预测A2、B2两种排放情景下未来石羊河流域2020s,2050s和2080s的ET0,使用反距离加权插值法(IDW)和Mann-Kendall检验分别研究ET0的空间分布特征和随时间的变化趋势。结果表明,石羊河流域多年平均ET0值为1 061mm,高值区位于东北地区,低值区位于西南地区,预计未来2020s、2050s和2080s,在HadCM3模式的A2情景下ET0将分别增加6%、14%和23%,B2情景下将分别增加7%、12%和17%,增幅较大的地区位于流域东南,2050s和2080s在B2情景下增幅低于A2情景。石羊河流域ET0在未来将持续增加,2050s之后增加趋势更为显著。     

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

参考作物蒸发蒸腾量(ET0)是进行实时灌溉预报和农田水分管理的主要参数，BP神经网络能够较好地反映ET0与诸影响因素间复杂的非线性关系。本文将ET0看作时间序列，选取前3日ET0作为影响因子，以天气预报可测因子包括最高、最低和日平均温度、反映天气类型的阴晴指数、日序数和风力等级进行修正，建立了三层BP神经网络模型。选取江苏射阳站2003与2004年气象资料，应用Matlab神经网络工具箱，采用trainer算法进行模型训练与预测。结果证明，所建模型能够很好地反映诸多影响因子与ET0之间的关系，具有较高的模拟精度和较好的泛化能力。     

基于ELM模型的孔雀河流域参考作物蒸散量研究

为实现气象资料缺乏情况下ET0高精度预测,以气象因子的不同组合为输入参数,利用P-M公式计算的ET0作为预测标准值建立基于极限学习机的ET0预测模型。选取新疆孔雀河流域2011年与2012年逐日气象资料进行模型测试,并将模拟结果同其它常用模型进行对比。结果表明ELM模型能很好地反映气象因子同ET0间复杂的非线性关系,且模拟精度较高,可以作为气象资料缺乏情况下研究区ET0计算的推荐模型。     

新疆旱区草地参考作物腾发量随机模拟及其应用

本文根据新疆地区乌鲁木齐、吐鲁番、伊宁3个气象站40年逐日观测资料,应用FAO 1998 Penman-Monteith公式,计算乌鲁木齐站(1959~2000年)、吐鲁番站(1961~2000年)和伊宁站(1961~2000年)的历年逐日ET0。在此基础上,对各站多年平均ET0序列进行了随机模拟。结果表明:3个站ET0年内变化趋势大体一致,都具有很强的季节性,总体上吐鲁番站的ET0最高,伊宁站最低;年际变化呈现递减的趋势。通过预测值和Penman-Monteith法计算值对比,说明随机模型的预测结果良好,相对误差范围在实用范围之内,可为计算灌区作物需水量和优化灌溉制度提供一定的依据。     

基于天气预报改进模型ET0实时预报应用

建立了以Penman Monteith(PM)方程计算参考作物需水量(ET0)为因变量,天气预报可测因子(日最高、最低气温、反映天气类型的阴晴指数、风力等级)为自变量的多元回归线性模型,应用自适应神经模糊推理系统(ANFIS)进行修正残差的改进模型.通过与PM计算ET0结果分析,改进模型预测结果相对于多元线性回归模型具有精度高、整体拟合度好,具有较好的预测效果.改进模型的输入项完全可以从当前短期天气预报中获得,且将两种基础方法结合,操作运行简单等优点,在实时灌溉预报中有一定的推广意义,具有实用价值.     

基于小波消噪的参考作物腾发量RBF网络预测方法

介绍小波消噪的原理和步骤。以北方某流域甲站2001—2005年逐日气象数据为基本资料,进行10阶Dmey小波消噪,然后构建预测ET0的前馈网络模型(RBF-ET0),用2001—2004年的资料作为训练样本,对2005年的ET0进行预测,并与Penman-Montieth公式计算值进行比较。结果为:预测值与目标值的相关系数为0.991 2,相对误差的平均值为6.56%,相对误差小于20%,15%,10%的合格率分别为93.88%,85.66%,73.51%,与未经小波消噪处理的RBF-ET0模型预测结果相比,预测精度有明显提高。     

南昌参考作物蒸散量时间变化及成因分析

为了深入认识南昌参考作物蒸散量(ET0)的时间变化特征,采用FAO推荐的Penman-Monteith公式计算南昌1961—2015年逐日ET0,并用Mann-Kendall趋势检验和突变检验法分析南昌ET0时间变化特征和突变时间,在此基础上使用通径分析法研究ET0变化成因。结果表明,南昌ET0年内呈现单峰曲线,7-8月最高,约占全年30%。从年际变化看,ET0和日照时数(n)无明显趋势,仅在8月呈现显著下降趋势,而相对湿度(RH)和风速(u2)显著下降,最高气温(Tmax)和最低气温(T_(min))显著上升。n和ET0多年累积距平曲线和月值曲线形状最接近,突变时间也最接近,分别在1990和1992年。n、u2、RH和T_(min)通径系数分别为0.513、0.466、-0.425和0.196,表明n最敏感,其后依次是u2、RH和T_(min)。n通过RH对ET0影响也较强(间接通径系数0.236),高于T_(min)的直接作用。     

辽宁省近55年参考作物蒸散量时空变化特征及成因分析

以辽宁省10个气象站点1961~2015年近55年的气象数据,利用FAO-56分册推荐的计算ET0标准Penman-Monteith公式计算了55年的逐日ET0。通过分析辽宁省ET0年际变化、年内变化及空间变化趋势,掌握辽宁省ET0的时空变化规律,并用敏感性分析、相关性分析、贡献率分析等方法,定性并定量地分析了影响辽宁省ET0变化的主要气候要素。结果表明,辽宁省各站点ET0呈逐年降低的趋势,同时风速、平均温度、日照时数与正相关,相对湿度与负相关,各气象因素对ET0的贡献率分别为-1.111%、0.137%、-0.511%、-0.124%,风速的降低是影响辽宁省各站点ET0降低的主要原因。     

Spatial variation of reference crop evapotranspiration on Tibetan Plateau

This study is based on meteorological observation data collected at 38 weather stations on the Tibetan Plateau over several decades. Daily reference crop evapotranspiration (ET0) was calculated with the FAO-56 standard Penman-Monteith formula. A test of normality was performed with Statistica 6.0 software, isotropic and anisotropic semi-variogram analysis was conducted with the GS+ (geostatistics for the environmental sciences) system for Windows 7.0, and the characteristics of spatial variation of daily ET0 were obtained. The following results can be obtained: Daily ETo for different periods on the Tibetan Plateau are distributed normally; Except for daily ETo in the E-W (east-west) direction in the summer, which showed a slight negative correlation with distance change, the Moran's indexes of daily ET0 for different periods in all directions on the Tibetan Plateau within a 100-km distance were positive, demonstrating a positive correlation with distance change; Variograms of daily ET0 in June, the dry season, the wet season, as well as annual average daily ET0 fit well with the Gaussian model; A variogram of daily ET0 in December fit well with the exponential model; Variograms of daily ET0 for the four seasons fit well with the linear with sill model.     

Gene-Expression Programming for Short-Term Forecasting of Daily Reference Evapotranspiration Using Public Weather Forecast Information

This study aimed to forecast the daily reference evapotranspiration (ETo) using a gene-expression programming (GEP) algorithm with limited public weather forecast information over Gaoyou station, located in Jiangsu province, China. To calibrate and validate the gene-expression code, important meteorological data and weather forecast information were collected from the local meteorological station and public weather media, respectively. The GEP algebraic formulation was successfully constructed based only on daily minimum and maximum air temperature using the true FAO56 Penman-Monteith (PM) set as reference values. The performance of the models was then assessed using the correlation coefficient (R), root mean squared error (RMSE), root relative squared error (RRSE) and mean absolute error (MAE). The study demonstrated that GEP is able to calibrate ETo (all errors ≤0.990 mm/day, R = 0.832–0.866) and forecast the daily ETo with good accuracy (RMSE = 1.207 mm/day, MAE = 0.902 mm/day, RRSE = 0.629 mm/day, R = 0.777). The model accuracies slightly decreased over a 7-day forecast lead-time. These results suggest that the GEP algorithm can be considered as a deployable tool for ETo forecast to anticipate decision on short-term irrigation schedule in the study zone.     

Variable fuzzy assessment of water use efficiency and benefits in irrigation district

In order to scientifically and reasonably evaluate water use efficiency and benefits in irrigation districts, a variable fuzzy assessment model was established. The model can reasonably determine the relative membership degree and relative membership function of the sample indices in each index's standard interval, and obtain the evaluation level of the sample through the change of model parameters. According to the actual situation of the Beitun Irrigation District, which is located in Fuhai County, in Altay City, Xinjiang Uyghur Autonomous Region, five indices were selected as evaluation factors, including the canal water utilization coefficient, field water utilization coefficient, crop water productivity,effective irrigation rate in farmland, and water-saving irrigation area ratio. The water use efficiency and benefits in the Beitun Irrigation District in different years were evaluated with the model. The results showed that the comprehensive evaluation indices from 2006 to 2008 were all at the third level(medium efficiency), while the index in 2009 increased slightly, falling between the second level(relatively high efficiency) and third level, indicating an improvement in the water use efficiency and benefits in the Beitun Irrigation District, which in turn showed that the model was reliable and easy to use. This model can be used to assess the water use efficiency and benefits in similar irrigation districts.     

黄河下游生态型引黄灌区水资源承载力研究

黄河流域生态型灌区建设是当下生态文明建设的重要组成部分,以生态型灌区水资源承载力理论为研究基础,采用模糊集对分析法对黄河下游典型引黄灌区进行水资源承载力综合评价。评价结果表明,2010—2013年大功灌区水资源承载力形势不容乐观,2014—2016年大功灌区近三分之二的区域水资源承载力形势有较大好转,直至2017年大功灌区整体水资源承载力达到承载状态。     

重庆市典型下垫面 ＳＣＳ-ＣＮ模型基于坡度修正的径流曲线数优化

以重庆市渝北区和巴南区的典型下垫面为研究对象,基于ＳＣＳ-ＣＮ模型原理和坡度修正公式,通过开展人工模拟降雨实验,优化了不同植被覆盖程度的紫色土和黄壤下垫面在不同坡度（5°、10°、15°和20°）下的ＣＮ值,同时采用模型评价参数对优化前后的模型预测精度进行对比。结果表明:地形坡度变化对径流深有显著影响,地表径流深随坡度的增大大体呈现增加的趋势。同一类型下垫面的ＣＮ值随坡度的增大而增大,同一坡度下的ＣＮ值存在黄壤＞紫色土,自然草地（稀疏）＞自然草地（浓稠）。从模型评价参数来看,由Ｈｕａｎｇ坡度修正公式修正后的模型效率系数最高且平均相对误差最小。因此,在山地城市应用ＳＣＳ-ＣＮ模型时,建议使用Ｈｕａｎｇ坡度修正公式对ＣＮ值进行优化,以便更精准地预测径流。     

Optimized Neural Network Prediction Model for Potential Evapotranspiration Utilizing Ensemble Procedure

Potential evapotranspiration (ET_o) is an essential hydrologic parameter for having better understanding for hydrologic cycle in certain catchment area. In addition, ET_o is vital for calculating the agricultural demand. In fact, Penman-Monteith (PM) method is considered as reference method for estimating (ET_o), however, this method required a lot of data to be used which is not usually available in many catchment areas. Furthermore, there are several efforts that have been performed as competitor to reach accurate estimation of (ET_o) when there is lack of data to utilize (PM) method, but still required numerous research. Recently, methods based on Artificial Intelligence (AI) have been suggested to provide reliable prediction model for several application in engineering and especially for hydrological process. However, time series prediction based on Artificial Neural Network (ANN) learning algorithms is fundamentally difficult and faces problem. One of the major shortcomings is that the ANN model experiences over-fitting problem during training session and also occurs when a neural network loses its generalization. In this research a modification for the classical Multi Layer Preceptron- Artificial Neural Network (MLP-ANN) modeling namely; Ensemble Neural Network (ENN) is proposed and applied for predicting daily ET_o. The proposed model applied at two different region with two different climatic conditions, Rasht city located north part of Iran and Johor Bahru City, Johor, Malaysia using maximum and minimum daily temperature collected from 1975 to 2005. The result showed that the ENN outperformed the classical MLP-ANN method and successfully predict daily ETo utilizing maximum and minimum temperature only with satisfactory level of accuracy. In addition, the proposed model could achieve accuracy level better than the traditional competitor methods for ET_o.     

参考作物腾发量的混沌性识别及预测

本文应用饱和关联维数法对海河流域张北站从1966~2005年50年的参考作物腾发量序列进行混沌性识别,结果表明该序列存在一定的混沌特性。同时,运用自相关函数法和饱和关联维数法确定了该序列重构相空间的嵌入维数和延迟时间,并在此基础上进行了相空间的重构。建立了混沌局域法预测模型对相空间的演化进行了计算,实现了参考作物腾发量的预测,并与时间序列自回归(AR)模型和基于气象资料的BP神经网络模型预测结果进行了比较。结果表明,预测效果比BP网络模型稍差,但明显优于AR模型。这为解决缺乏气象资料地区参考作物腾发量预测问题提供了新的思路。     

长江上游坡耕地降雨径流蓄集利用效果评价

通过建立反映坡面降雨径流调控工程技术措施、拦截季节性降水、补充作物需水高峰期用水效果的综合评价指标体系,利用模糊多因素层次评价数学模型,对坡面降雨径流调控技术及其降雨径流蓄集和利用状况进行评价分析。计算结果表明,在具有季节性干旱缺水的坡耕地灌溉区域,在不同设计代表年份的降雨情况下均表现出良好的降雨径流蓄集利用效果。因此,通过修建雨水蓄集工程,实施坡面径流调控和水系的合理配置是很有必要的,同时也能为长江上游坡耕地整治与坡地高效生态农业的可持续发展提供科学依据和决策支持。     

膜下滴灌技术在吉林省的应用研究

膜下滴灌技术是近年来在干旱和半干旱地区广泛应用的一项技术,从吉林省西部近年来的应用推广情况来看,其在节水、改善生态环境和粮食增产等方面效果显著,并显现出对不同区域、不同作物品种的效益机制的反应各有所不同。因此,本文仅基于玉米在膜下滴灌条件下的不同给水条件的生长变化机制研究成果,对原有灌溉制度的相关参数,如灌水次数、灌水强度、灌水时间等进行适应性修正。提出了基于在膜下滴灌条件下,通过调亏灌溉密植补偿效应提高单位产能的灌水机制。结果表明,结合调亏灌溉技术可改变作物的生殖生长特征,提高作物品质和土地容量,实现增产增收。     

引黄灌区泥沙远距离输送研究

采用山东省簸箕李灌区实际资料对建立的引黄渠道泥沙远距离输送数学模型进行了验证,结果表明模型能够较好地模拟簸箕李灌区干渠水流输沙规律.进而利用该模型对影响泥沙远距离输送的主要因素进行研究,成果显示渠道衬砌、复式断面利于减少渠道淤积,引水时避免小流量长时间引水、减少沿程分水和提水灌溉,是实现泥沙远距离输送的有效措施.