小波随机耦合模型在三江平原井灌区地下水位预测中的应用

近些年来,由于水田面积迅速增加,导致三江平原井灌水稻区地下水位普遍下降,"吊泵"、局部超采现象时有发生.为解决上述问题,以853农场为例,对实测地下水埋深资料进行差分处理,采用小波理论和随机水文学方法建立了逐月地下水埋深小波随机耦合模型,精度检验结果表明,模型有效性和可靠性较高.预测结果表明,若仍然采用过去的地下水开采模式,853农场未来地下水埋深将会持续下降,因此当地应加强地下水资源的科学管理.该模型揭示了区域地下水动态变化规律,为853农场乃至整个三江平原地下水资源的可持续利用提供了科学依据.     

基于混沌的三江平原月降水时间序列分析

三江平原是我国最大的淡水沼泽区,近年来降水的减少是导致湿地减少的一个重要的自然因素.别拉洪河是三江平原上比较有代表性的沼泽性河流.以别拉洪水文站的降水序列为例,通过相空间重构,分别计算了序列的关联维、最大Lyapunov指数以及Kolmogorov熵等几个序列特征量.计算表明:三江平原月降水序列中是存在明显的混沌特征的,这为以后建立三江平原月降水的混沌预测模型提供了理论依据.     

应用Logistic模型对建三江农场水稻生产潜力的分析

本文首先建立了建三江农场水稻单产变化的 Logistic模型 ,通过对模型的微分方程形式的离散 ,得一二次函数 ,进行回归分析 ,得出模型中参数的估计值 .对模型进行分析得出现阶段水稻单产的最大潜力和水稻增产速度最快的时间段 ,对于指导水稻生产 ,优化农业生产结构 ,都具有很深的现实意义     

三江平原湿地非使用价值支付意愿的影响因素

为了更好地保护三江平原湿地生态系统,应用条件价值评估法(CVM)这一当前国际上流行的生态系统经济价值评价方法,对三江平原湿地的非使用价值进行评价.研究中采用实地调研的方式,进行支付意愿问卷调查,共发放支付卡式CVM问卷552份,回收有效问卷513份.得出三江平原湿地2007年人均支付意愿为71.66元/年.通过对问卷数据的描述性统计,得到支付意愿的分布情况和在各单一因素影响下的变化规律.用主成分分析简化影响因素,运用有序多分类Logit模型,得到在所有影响因素中,个人平均年收入、个人受教育程度以及个人环保态度是影响受访者对三江平原湿地非使用价值支付意愿的主要因素.研究结论使得三江平原湿地开发和保护价值比较成为可能,为政府制定相关政策提供理论基础与科学依据.     

基于小波去噪和WNN-ARIMA组合模型的年径流预测

为解决单一的小波神经网络预测精度不高的问题,提出一种新的基于小波去噪和WNN-ARIMA组合模型,应用小波阈值去噪法对小波神经网络的输入值进行预处理,同时对模型残差值进行ARIMA模型修正.利用该组合模型对洮河流域下巴沟站年径流量进行预测,预测趋势和预测值与原始实测数据吻合度高,表明此组合模型可靠性强,可以有效预测年径...     

几种模拟逐日降水的分布函数比较分析

在模拟逐日降水方面,将马尔科夫链和某种分布函数相结合建立随机模型的方法在国外很多地区被证明是有效的,但该方法在我国的适用性研究并不多见.本文应用哈尔滨48年的实测降水资料,基于一阶马尔科夫两状态转移概率,分别采用皮尔逊Ⅲ型分布、伽玛分布和偏正态分布函数模拟了哈尔滨的1000年逐日降水过程.对比分析结果表明,伽玛分布更适合模拟哈尔滨的逐日降水过程,基于伽玛分布函数模拟的月份降水量和降水天数与实测降水数据符合较好.     

小波变换在期货价格序贯相关分析中的应用

针对金融时间序列普遍具有非平稳、自相关等特点,通常建立ARIMA模型进行识别.但模型的构建中,常受到一些随机扰动的影响,使模型拟合的误差增大.文章试将小波分析良好的局部性与ARIMA模型的简捷实用相结合,采用基于小波分析的累积式自回归滑动平均方法(WARIMA)拟合模型中的序贯相关,实证分析得出,WARIMA模型显著降低了拟合误差.     

半参数回归模型中小波估计的随机加权逼近速度

把小波光滑方法和随机加权方法结合在一起，获得了半参数回归模型中参数分量的小波估计的随机加权逼近速度为σ(n^-1/2)。因此，从大样本意义上说，小波光滑方法和随机加权方法对半参数回归模型是可用的。     

基于Kriging模型和提升小波变换的随机模型修正北大核心CSCD

为提高随机模型修正效率,减小计算量,提出了一种基于Kriging模型和提升小波变换的随机模型修正方法.首先,对加速度频响函数进行提升小波变换,提取第5层近似系数代替原频响函数.其次,采用拉丁超立方抽样抽取待修正样本,将其作为Kriging模型的输入,对应的近似系数作为输出,构建Kriging模型.提出了一种引入莱维飞行(Lévy flight)的蝴蝶优化算法(LBOA),并将其应用于Kriging模型相关参数的寻优中,提高Kriging模型的精度.最后,以最小化Wasserstein距离为目标,通过鲸鱼优化算法求解待修正参数的均值.测试函数结果表明,LBOA在寻优能力、收敛精度和稳定性等方面有了很大的提升.数值算例的修正误差均低于0.4%,验证了所提模型修正方法具有较高的修正精度和效率.     

基于小波变换的小样本随机振荡序列灰色预测模型

针对GM(1,1)幂模型对于小样本振荡序列对含突变信息无能为力的问题,提出了基于小波变换的小样本振荡序列灰色预测模型.首先,针对原始数据序列建立GM(1,1)幂模型描述其总体趋势特征;然后,利用小波变换提取GM(1,1)幂模型残差序列所包含的有用信号和随机噪声,并结合GM(1,1)幂模型构成新的时间相应函数;最后,以与原始平均误差最小为原则确定小波变换的小波基和分解层次并对小波进行重构GM(1,1)幂模型残差序列,并结合原始GM(1,1)幂模型对随机振荡序列进行预测.算例中通过对城市用水量的拟合及预测结果表明:应用基于傅立叶变换的GM(1,1)幂振荡序列模型和基于分数阶离散GM(1,1)幂模型研究了振荡序列模型平均误差分别为3.22%和5.66%,而本文的方法平均误差为1.11%.算例研究表明,此方法能够快速高效的解决GM(1,1)幂模型对小样本有突变趋势振荡序列的预测问题.     

A decision tool for optimal irrigated crop planning and water resources sustainability

In the present study, the conjunctive use policies of surface and ground water resources are developed for minimizing water shortage in an irrigation district subject to constraints on groundwater withdrawals and crop planning capacities. An integrated soil water balance algorithm is coupled to a non-linear optimization model in order to carry out water allocation planning in complex deficit agricultural water resources systems based on an economic efficiency criterion. Various options of conjunctive use water resources along with current and proposed cropping patterns have been explored by Koohdasht Irrigation District (KID), a semi-arid region in I.R. Iran. The analysis provides various scenarios, which can help managers in decision-making for the optimum allocation plans of water resources within the irrigation area. The results reveal that the proposed model, as a decision tool for optimal irrigated crop planning and water resources sustainability, may be used for maximizing the overall net benefits and global water productivity of an irrigation district considering an allowable annual recharge of groundwater. Findings indicate the importance of the conjunctive water management modeling, which can be easily implemented and would enhance the overall benefits from cropping activities in the study area.     

基于混沌粒子群优化算法的灰色GM(1,1)模型在地下水埋深预测中的应用

将混沌优化算法与粒子群优化算法相结合,形成新的混沌粒子群优化算法.利用混沌运动的遍历性,避免陷入局部最优.同时,粒子群算法能加快混沌优化算法的收敛速度,使搜索效率得到提高.用混沌粒子群优化算法优化灰色GM(1,1)模型中的参数,通过横向和纵向比较,优化效果良好,模型预测精度得到了提高.运用该模型对三江平原地下水埋深进行动态预测,预测结果可为有关决策部门提供参考.     

CONTROLLING GROUNDWATER QUALITY WITH ENDOGENOUS REGULATORY INSTRUMENTS

ABSTRACT. This research presents a competitive dynamic model that endogenously evaluates the economics of regulatory tax-policy options. This model is then applied to an irrigated corn production area west of Kearney, Nebraska, where the average groundwater contamination level from nitrates is reported to be 8.7 parts per million (ppm). Results indicate that no regulatory policies are necessary for maintaining potable groundwater quality with either a surge-flow irrigation system or a sprinkler irrigation system. In areas where conventional furrow irrigation technology is being used, higher net economic benefits result from the adoption of a variable-tax on nitrogen fertilizer use, followed by a constant-unit tax and a pollution tax.     

A multi-objective optimal allocation model for irrigation water resources under multiple uncertainties

This paper proposed a multi-objective optimal water resources allocation model under multiple uncertainties. The proposed model integrated the chance-constrained programming, semi-infinite programming and integer programming into an interval linear programming. Then, the developed model is applied to irrigation water resources optimal allocation system in Minqin’s irrigation areas, Gansu Province, China. In this study, the irrigation areas’ economic benefits, social benefits and ecological benefits are regarded as the optimal objective functions. As a result, the optimal irrigation water resources allocation plans of different water types (surface water and groundwater) under different hydrological years (wet year, normal year and dry year) and probabilities are obtained. The proposed multi-objective model is unique by considering water-saving measures, irrigation water quality impact factors and the dynamic changes of groundwater exploitable quantity in the irrigation water resources optimal allocation system under uncertain environment. The obtained results are valuable for supporting the adjustment of the existing irrigation patterns and identify a desired water-allocation plan for irrigation under multiple uncertainties.     

GLOBAL WARMING,IMPACT ON AGRICULTURE AND ADAPTATION STRATEGY

Abstract Sensitivity of the Southeastern US agriculture sector to temperature increases will be based largely on accompanying changes in precipitation, extent of the warming, and relative impact on competing crops grown in the area. The impact of climate change in 10 Southeastern US counties was investigated under three different climate scenarios for two different reference years (2030 and 2090). Seven major crops grown in the area were selected to study the impact on crop yield, irrigation acreage, and optimal choice of crops in a representative farm in each of the southeastern states. If warming is moderate and also brings a considerable increase in precipitation—as indicated by the Hadley model—then, the effect on yields, water use, and income will be mostly benign. If warming is moderate without increased precipitation and the water for irrigation is available, then the effects on the agriculture sector are still mostly negligible. If warming is not moderate and no increased precipitation materializes, farmers could realize quite dramatic negative consequences for row crop agriculture in the Southeastern United States.     

加权马尔科夫链在鄂尔多斯市年降水量预测中的应用

鄂尔多斯市是内蒙古自治区重要的农牧渔业生产区.本文采用样本均值—标准差分级法,将鄂尔多斯市11个气象站1961-2019年的年降水量序列划分为丰水年、偏丰水年、平水年、偏枯水年,枯水年5个状态;以年降水量序列各阶自相关系数rk为权值,建立了加权马尔科夫预测模型,对鄂尔多斯市2017年、2018年、2019年的年降水量数值和所处状态进行预测.结果显示相对误差分别为1.3%,6.9%,4.5%,预测精度较高,方法得当.于是利用精度检验后的加权马尔科夫模型预测了鄂尔多斯市2020年降水量为312.81mm,划分为平水年.同时利用马尔科夫模型的遍历性,讨论了鄂尔多斯市年降水量的极限分布和丰枯状态重现期.研究结果表明,鄂尔多斯市59a来降水过程中枯水年、偏枯水年、平水年、偏丰水年、丰水年5种状态出现的概率分别为0.1358、0.1941、0.3693、0.1926、0.1083,即出现平水年的可能性最大,重现期为2.71a;出现丰水年的可能性最小,重现期为9.23a.上述研究结果与降水量序列及所处状态是保持一致的,由此可见利用加权马尔科夫链预测鄂尔多斯地区的年降水量是可行且有效的.     

Applying stochastic goal programming: A case study on water use planning

A decision support model to help public water agencies allocate surface water among farmers and authorize the use of groundwater for irrigation (especially in Mediterranean dry regions) is developed. This is a stochastic goal programming approach with two goals, the first concerning farm management while the other concerns environmental impact. Targets for both goals are established by the agency. This model yields three reduction factors to decide the different reductions in available surface water, standard groundwater and complementary groundwater that the agency should grant/authorize for irrigation, this depending on if it is a dry or wet year. In drought periods, the model recommends using more groundwater (in percentage) than in wet periods. A case study using year-to-year statistical information on available water over the period 1941–2005 is developed through numerical tables. A step-by-step computational process is presented in detail.     

Optimal cropping patterns under water deficits

A mathematical programming model is proposed for optimal cropping patterns under water deficits in dry regions. Crops may be deliberately under-irrigated in order to increase the total irrigated area and possibly the profit. An operating policy will identify both the total area and the irrigation level allocated to a given selected crop taking into account the possible successors and predecessors of this crop. Both annual and seasonal crops are examined in the same study. The model starts by identifying the optimal operating policy for each grower in the region having a given stock of irrigation water. Then, in order to allocate water efficiently among growers, the model determines the global optimal cropping plan of the entire region. To solve efficiently the problem, a decomposition algorithm is developed. Also some useful economic interpretations are given.