基于模糊神经网络的参考作物蒸腾量预测研究

为准确估算灌区作物需水量,建立了基于模糊神经网络的参考作物腾发量时间序列预测模型。采用宝鸡地区1954—2004年逐月气象资料,利用主成分分析法提取影响参考作物蒸发蒸腾量的主要影响因子,获得4个综合变量作为输入向量,用彭曼-蒙蒂斯公式计算的参考作物蒸发蒸腾量作为目标向量。运用matlab进行编程,应用模糊神经网络模型预测参考作物腾发量。结果表明:12组测试集样本的平均相对误差绝对值为5%,最大相对误差为11.4%,最小相对误差为0.4%;模糊神经网络模型与用彭曼-蒙蒂斯公式计算值有很高的一致性。     

青铜峡灌区参考作物蒸发蒸腾量与气象因子的灰色关联度分析

在收集了青铜峡引黄灌区5个气象站最近5年气象资料的基础上，应用1998年FAO修正彭曼-蒙特斯公式，计算出各站逐年的参考作物蒸发蒸腾量ET0；在阐述灰关联分析理论与计算方法的基础上，利用灰关联分析理论计算出各站各气象因子与ET0的灰色关联度并进行排序。分析结果表明：各气象因子对参考作物蒸发蒸腾量的影响都比较大，尤其是日照时数、平均最高气温和年平均风速对各站的影响相对较大，而最低气温、相对湿度和降雨对各站的参考作物蒸发蒸腾量的影响相对比较小。     

田间土壤墒情预报模型关键参数确定方法研究

为了构建黄河下游引黄灌区墒情预报水量平衡模型,分析了气象、作物蒸腾蒸发、地下水埋深、土壤特性等因子与大田土壤墒情之间的关系。确定构建模型需要率定的参数有作物蒸发蒸腾量、深层渗漏量、降雨量、灌溉量和地下水补给量等,并提出了各参数的计算方法。     

马铃薯块茎增长期短历时蒸发蒸腾量研究

为明确马铃薯块茎增长期短历时土壤水分蒸发规律,本文采用土壤水分动态观测法观测气象因子对马铃薯蒸发蒸腾量的影响。研究结果表明,在不同的土壤含水率情况下测筒的蒸发蒸腾量也不同。相对湿度、日照和风速是影响蒸发蒸腾量的直接因素。相对湿度日变化与气温日变化相反,相对湿度降低时蒸发蒸腾量增加,风速与相对湿度呈相反关系。蒸发蒸腾量与蒸发皿水面蒸发变化趋势基本一致。     

ET0计算中ngstrm-Prescott系数的取值

利用乌鲁木齐、银川等全国103个气象台站点55 a的气象资料,研究了ngstrm-Prescott系数在不同时间尺度的取值方法及其误差对参考作物蒸发蒸腾量计算结果的影响,并与国际粮农组织推荐值估算的结果进行了对比。结果表明:可以用当地拟合ngstrm-Prescott系数的全年均值来计算参考作物蒸发蒸腾量;利用国际粮农组织推荐值估算的选取站点的太阳辐射和参考作物蒸发蒸腾量的全年最大相对误差分别为11%和13%,推荐值估算的太阳辐射和参考作物蒸发蒸腾量的误差与ngstrm-Prescott系数的误差不成比例。     

半干旱区大豆腾发量的测试

由于气候的变化,干旱已经成为限制农业生产的主要因子。大豆是黑龙江省的主要作物之一,为了推动农业生产,同时能为发展节水灌溉提供基本数据,文章利用称重式蒸渗仪对大豆的叶面蒸腾量、蒸发蒸腾量及土壤表面蒸发量进行了测试。     

基于GRNN神经网络的参考作物腾发量预测

参考作物腾发量是估算作物蒸发蒸腾量的关键参数,它的准确预测对提高作物需水预报精度具有十分重要的意义。由于参考作物腾发量与各气象因子呈非线性关系,将GRNN神经网络引用于参考作物腾发量预测中,并以铁岭市为例,对比分析了GRNN模型与BP模型的预测结果。分析表明：GRNN模型不仅训练速度快,还具有比BP模型更高的预测精度、逼近性和稳定性。     

基于BP神经网络的参照腾发量预测模型

本文在分析影响作物蒸发蒸腾量的气象因子的基础上，以不同的气象因子组合为输入向量，以参照腾发量为输出向量，构建了气象资料不足情况下三种计算参数腾发量的BP神经网络模型BPET1、BPET2和BPET3。利用宁夏引黄灌区2000～2003年的逐日气象资料对所建模型进行反复训练和预测，并把预测结果与传统的Penman-Monteith公式计算而得的同期作物ETO值相比较。其中，BPET1的预测值与ETO值的相关系数平方为0．9914；BPET2的预测值与ETO值的相关系数平方为0．9917；BPET3的预测值与ETO值的相关系数平方为0．9854。研究结果表明，本文构建的模型计算精度较高，方法简便可行，能满足实际生产需要。     

利用蒸发计估测参考作物蒸发蒸腾量的试验研究

根据联合国粮农组织推荐的方法估算参考作物蒸发蒸腾量(ET0)需要具备一定的气象资料,而使用另一种方法,即蒸发计估测ET0,可以减少基于作物蒸发蒸腾量制定灌溉制度的工作量,并且降低其复杂度。在叙述蒸发计构造及使用方法的基础上,介绍了一些研究者在不同气候条件下对蒸发计估测ET0准确度的试验研究。试验表明,在缺乏标准气象资料时,可以利用蒸发计来可靠地估测农场或更广阔领域的ET0。     

基于JF-1型蒸发自动测试仪的水稻作物需水量分析研究

本文将江西省水利科学研究院研发的JF-1型蒸发自动测试仪首次成功应用于水稻田间蒸发蒸腾量测量.研究了水稻作物在不同气象条件下,水稻作物的日蒸发蒸腾量变化过程,为制定合理的灌溉制度,节约水资源,提高水稻作物产量有着重要的指导意义.     

A Water Budget Model for the Yun-Lin Plain,Taiwan

A water budget model is proposed to estimate the infiltration, runoff, evapotranspiration and recharge in vadose zone and apply to a case study. The instantaneous redistribution of infiltrated water is assumed to be uniform and a linear relationship between evapotranspiration and effective saturation is imposed. Infiltration is described by Philip's solution in conjunction with the time compression approximation method during rainfall. Runoff occurred when rainfall rate exceeds soil-infiltrating rate. The soil profile drainage was determined by evapotranspiration and recharge. Cumulative infiltration, runoff, evapotranspiration and recharge are estimated with different climate conditions and different soil hydraulic properties during simulating period. Analysis shows that initial effective saturation affects the estimated results in this water budget model in the short or mid-term simulations while not in long-term simulations. The climatic conditions of Yun-Lin plain area, Taiwan from 1991 to 1997 are used by referring to hydrological and hydrogeological parameters to provide the computational procedures of this study for estimating recharge. Results showed that the amount of annual recharge was affected by the amount of annual rainfall and soil properties.     

基于水能分配空间坐标系的流域蒸散变异归因研究

气候和下垫面变化对流域蒸散发产生显著影响,然而,如何定量分解两者对蒸散发变异的贡献程度,一直以来是流域水文学研究的重点和难点。本研究基于水量与能量平衡基本原理,建立水量-能量分配空间坐标系统,分离并量化气候及下垫面变化对流域蒸散发的影响。基于优化的水量-能量分配框架,对全球83个典型流域的实际蒸散发变化（1900—2008年）进行归因研究,对比该方法与基于Budyko-Fu公式的分解法的计算成果,检验该框架在全球范围大尺度流域的科学性和适用性。结果发现,实际蒸散发的变化,在持水能力低的湿润流域主要受下垫面因素的驱动,而在持水能力强的湿润流域中主要受气候因素的影响;对于持水能力低的半湿润流域以及干旱与半干旱流域,其水热状态的变化轨迹主要沿干燥指数线移动,流域内实际蒸散发的变化主要受下垫面因素驱动。与已有基于Budyko-Fu公式的分解法计算结果的比较表明,本研究建立的基于水能分配框架的蒸散发归因方法具有较好的可靠度。此外,相对于传统的Budyko分解法,基于水量-能量分配法的水能空间坐标系能直观地分析气候及下垫面变化分别对流域实际蒸散发的贡献大小、方向及不同时段下流域水能状态的变化轨迹,具有较强的实用性。     

Factors Influencing Markov Chains Predictability Characteristics, Utilizing SPI, RDI, EDI and SPEI Drought Indices in Different Climatic Zones

Comparability analyses were carried out to investigate behavioural aspects of effective drought index (EDI), standardized precipitation index (SPI), reconnaissance drought index (RDI) and standardized precipitation evapotranspiration index (SPEI), considering 3-month, 6-month and annual time periods. Investigations included parametric/non-parametric correlation analysis among indices, climatic zone influence, record length impacts and evapotranspiration role (RDI and SPEI) on Markov chains predictability characteristics. Except for the EDI, all indices/cases (all climatic zones) showed significant correlation. In arid/semi-arid climates, the 3-month and 6-month maximum drought severities were detected by the RDI and annual maximum drought severities were detected by the SPEI, emphasizing the evapotranspiration influence. In all climatic zones, the EDI values for wet (dry) periods were higher (lower), compared to other indices. First order dependency was detected for the EDI (all cases) and the SPI (most cases), over entire period (1951–2011) and sub-periods [(1951–1981), (1982–2011)]. The largest number of second order dependency was detected by the SPEI, followed by a relatively large number of such cases by the RDI (3-month time period), for the 61-year data period. This research showed that several factors influence Markov chains predictability characteristics in drought studies, particularly the impact of record length and evapotranspiration (RDI and SPEI) were confirmed.     

基于Budyko假设的潦河流域上游径流变化归因识别

近50年来,气候变化和人类活动在不同程度上对澡河流域水文过程产生了影响,为了识别径流变化的主要原因,以深河流域上游地区为研究区,利用Mann-Kendall检验法等分析研究区1966-2015年气象及水文要素变化趋势,同时建立基于Budyko假设的水热耦合平衡方程。运用弹性系数法对研究区径流变化的影响因素进行敏感性分析,并对各要素对径流变化的贡献进行定量评估。结果表明,1966-2015年间谍河流域上游地区年径流深呈显著减少趋势,年降水与年潜在蒸散发均元显著变化趋势。 同基准期(1966-1979年）相比,下垫面变化是径流减少的主要影响因素,1980-1997年（影响I期）与1998-2015年（影响E期〉下垫面变化对径流变化的贡献率分别为 52. 68%、88. 12%。 在气候要素中,降水对径流变化的影响大于潜在蒸散发的影响。     

长武塬区实际蒸散发变化及驱动因素分析

以大型称重式蒸渗仪系统的实测农田蒸散量数据为基础,分别从年、月、日和生长季4个尺度分析长武塬区农田蒸散量的变化特征,采用相关分析和主成分分析法探究其影响因素,建立实测蒸散与影响因素之间的定量关系。结果表明:农田蒸散的变化特征与作物生长进程一致,高蒸散期均出现于作物生育旺期,且受到降水、气温、风速、太阳辐射、日照时数、空气相对湿度和土壤含水量的共同作用,其中,气温和太阳辐射是蒸散的主要驱动因素。     

Performance Evaluation of Reference Evapotranspiration Estimation Using Climate Based Methods and Artificial Neural Networks

This study is an attempt to find best alternative method to estimate reference evapotranspiration (ET_o) for the Mahanadi reservoir project (MRP) command area located at Raipur (Chhattisgarh) in India, when input climatic parameters are insufficient to apply standard Food and Agriculture Organization (FAO) of the United Nations Penman–Monteith (P–M) method. To identify the best alternative climatic based method that yield results closest to the P–M method, performances of four climate based methods namely Blaney–Criddle, Radiation, Modified Penman and Pan evaporation were compared with the FAO-56 Penman–Monteith method. Performances were evaluated using the statistical indices. The statistical indices used in the analysis were the standard error of estimate (SEE), raw standard error of estimate (RSEE) and the model efficiency. Study was extended to identify the ability of Artificial Neural Networks (ANNs) for estimation of ET_o in comparison to climatic based methods. The networks, using varied input combinations of climatic variables have been trained using the backpropagation with variable learning rate training algorithm. ANN models were performed better than the climatic based methods in all performance indices. The analyses of results of ANN model suggest that the ET_o can be estimated from maximum and minimum temperature using ANN approach in MPR area.     

Streamflow Trends and Climate Variability Impacts in Poyang Lake Basin, China

Under the background of global warming, does the effect of the rising global surface temperature accelerate the hydrological cycle? To address this issue, we use the hydro-climatic data from five sub-basins in Poyang Lake basin in the southeast China over the past 50 years, to investigate the annual and seasonal trends of streamflow and the correlations between streamflow and climatic variables. The Theil–Sen Approach and the non-parametric Mann–Kendall test are applied to identify the trends in the annual and seasonal streamflow, precipitation and evapotranspiration series. It was found that annual and seasonal streamflow of all the stations had increasing trends except Lijiadu station in wet season. Only 37.5% hydro-stations in annual streamflow increased significantly, while most stations increased at 95% significance level in dry season. Trends in annual and seasonal precipitation during the whole period were generally not as significant as those in evapotranspiration. The correlations between streamflow and climate variables (precipitation and evapotranspiration) were detected by the Pearson’s test. The results showed that streamflow in the Poyang Lake basin are more sensitive to changes in precipitation than potential evapotranspiration.     

植被覆盖的土质边坡土壤水分平衡模型及应用

土壤水分平衡模型在洪水预测、土壤湿度计算、灌溉设计管理以及全球气候变化影响的仿真分析上十分重要.以英格兰南部Newbury一个高速公路旁的边坡为例,介绍了土壤水分平衡模型的建立及应用.潜在蒸散量根据每日的气象观测资料,用FAO Penman-Monteith公式进行计算.在此基础上,建立了水分平衡模型并进行了校核,计算出的土壤湿度变化与时域反射仪(TDR)探头测量的数据一致.还利用建立的模型,模拟了2080年的气候条件变化对潜在蒸散量和土壤水分含量的影响.结果表明,该地区的日平均潜在蒸散量将增加10.7%,土壤水分消耗量将增加16.8 mm.     

Methods to estimate irrigated reference crop evapotranspiration - a review

Efficient water management of crops requires accurate irrigation scheduling which, in turn, requires the accurate measurement of crop water requirement. Irrigation is applied to replenish depleted moisture for optimum plant growth. Reference evapotranspiration plays an important role for the determination of water requirements for crops and irrigation scheduling. Various models/approaches varying from empirical to physically base distributed are available for the estimation of reference evapotranspiration. Mathematical models are useful tools to estimate the evapotranspiration and water requirement of crops, which is essential information required to design or choose best water management practices. In this paper the most commonly used models/approaches, which are suitable for the estimation of daily water requirement for agricultural crops grown in different agro-climatic regions, are reviewed. Further, an effort has been made to compare the accuracy of various widely used methods under different climatic conditions.