作物需不量与灌溉制度模拟

从作物需水量的基本概念出发，以水量平衡原理为基础，建立了模拟农田根层土壤水循环的计算机模型－ＩＳＡＲＥＧ。这一模型具有多种功能，可模拟根层土壤水分变化，评价给定的灌溉制度计算作物需水量和灌溉需水量，也可用以制订多种供水限制条件下的优化灌溉制度。     

作物灌溉随机模拟技术研究

作物灌溉随机模拟技术包括作物需水量的随机模拟与预报研究、作物灌溉的随机方法研究等内容。国内外作物需水量的随机模拟与预报研究模型有：自回归滑动平均模型(ARMA)、自回归模型(AR)、倍加模型、传递函数噪声模型(TFN)、线性分解模型等；作物灌溉的随机方法研究有：解析法、随机模拟法等。随机模拟方法具有较强的普适性，是今后作物灌溉随机方法重点研究的课题。     

一种基于根,冠相互作用机制设计灌溉方案的方法

本文根据根、冠间相互作用机制及其对土水环境响应特征，建立了以土壤水分为参变量的根、冠关系模拟调控模型，并基于常规及适应跟踪控制思想，给出了２种计算作物需水量、规划灌溉方案的方法．作为例子，分别计算出了１９９２—１９９４两年冬小麦生长季内逐日１ｍ土体应具备的水量，模拟值与实测值经统计相关检验，均达到了极显著水平．实验证明，两种方法可用来根据不同生产目标，制定农田灌溉方案．     

关中地区粮食作物灌溉需水量的探讨

以往设计灌溉制度时，由于对作物需水规律掌握的不够全面，特别是忽视了产量水平的高低，往往脱离实际，为了探讨这一问题，中以关中地区冬小麦、夏玉米为例，论述了其需水量与籽粒产量的关系、适宜土壤含水量下限以及利用土壤储水的特性等，提出了计算其灌溉需水量的方法和关中地区一般干旱年的灌溉需水量，为了充分利用水资源，建议今后适当加大作物土壤计划层深度，发展地膜覆盖栽培，改革加强作物节水灌溉科研工作，并设法筹集     

作物缺水条件下灌溉供水量最优分配

针对灌区水源短缺情况，建立了一种对有限水量在多种作物之间进行最优分配的两层分解协调模型：第一层为基于作物水分生产函数，求解单作物非充分灌溉条件下最优灌溉制度的动态规划模型；第二层为将有限水量在多种作物之间进行最优分配的动态规划模型实例计算表明，模型是合理可行的     

沙漠绿洲灌区主要粮经作物需水规律及灌溉制度试验研究(续)

5节水高产灌溉制度分析5．1灌溉定额作物灌溉定额取决于作物需水量和需水规律以及作物生育期内的降水量，在地下水埋藏较深，不计地下水补给量和旱作物灌溉时不允许发生深层渗漏，作物生育期灌溉定额可表示为：式中M——生育期内灌溉定额；ET——全生育期需水量；P0——生育期内有效降雨（总降水量的0.8倍）；W0、We——播种前、收割后土壤储水量（采用综合评判的两个最佳结果的平均值），m3／亩。依据1988－1992年5种作物综合评判最佳结果及节水高产需水量的上下限，以（4）式分析计算最佳灌溉定额为春小麦223.3－307．7m3／亩、“带田…     

茶叶需水量与灌溉制度研究

作物需水量是作物进行科学灌溉以及制定作物灌溉制度的主要依据,通过试验,研究了茶叶需水量和需水规律,分析了茶叶灌溉制度,多年生的茶叶需水总量平均为1274. 60 mm,年平均日需水量为3. 49 mm,茶叶的灌水计划湿润层深度定在50 cm比较合适,年生长期各月的平均日耗水强度从1. 07～6. 51 mm/d不等,灌溉定额为307. 2 mm。     

水稻需水量等值图在灌溉管理中的应用

作物需水量等值线图主要是用于进行灌溉制度设计、推求灌溉定额和进行灌溉评价。如何更好地应用该图，正确确定作物需水量ＥＴ、降雨量Ｒ和灌溉定额Ｑ三者的关系，是普遍关注的问题．本文以吉林省水稻需水量成果图分析应用为例，较全面地介绍了应用该成果建立ＥＴ、Ｒ和Ｑ三者关系的方法及不同系列排须的ＥＴ图的应用情况。为需水量研究成果图更加完善起到了推动作用。     

一种基于根、冠相互作用机制设计灌溉方案的方法

根据根、冠间相互作用机制及其对土水环境响应特征，建立了以土壤水分为参变量的根、冠关系模拟调控模型，并基于常规及适应跟踪控制思想，给出了2种计算作物需水量、规划灌溉方案的方法. 作为例子，分别计算出了1992、1994两年冬小麦生长季内逐日1m土体应具备的水量，模拟值与实测值经统计相关检验，均达到了极显著水平.实验证明，两种方法可用来根据不同生产目标，制定农田灌溉方案。     

作物根区底部土壤水分向上运移通量的计算方法

本文用河北雄县试验站的实测资料验证了一维土壤水动力学模型—WAVE模型(Water and Agrochemicals in the Soil and Vadose Environment)，率定了土壤水力学特性参数和作物根系吸水函数。在此基础上，应用该模型模拟不同地下水埋深和不同作物腾发量条件下根区底部向上水分通量的变化，从而得到地下水对根层的补给量与根层土壤储水量的关系。把这一关系用于制定和评价灌溉制度的水量平衡模型当中，提高了模型的适用范围和模拟精度。     

基于SHAW模型的河套灌区秋浇渠系优化配水模型研究

河套秋浇是为满足来年春播作物水盐需求而进行的保墒淋盐灌溉。针对传统基于作物需水预测成果进行渠系配水存在的预报依赖性强和中长期预报精度低问题,本文提出了一种不需要作物需水预测成果的渠系优化配水模型框架,该框架依据春播初期作物水盐要求,将SHAW模型嵌入优化配水模型,确定秋浇配水计划。河套灌区永济灌域2016年秋浇配水计划编制实例研究表明:与传统基于需水预测的配水方法相比,新方法得到的配水计划可以在不增加渠首引水量及渠道输水损失总量基础上显著提升淋盐效果,使春播初期0～40 cm土层水盐状态更加适宜于作物播种,春播初期土壤0～40 cm土层平均盐分超标由60%以上降低至5%以下,同时配水公平性也得到提升。     

Technical Communication: Two-Phase Stochastic Dynamic Programming Model for Optimal Operation of Irrigation Reservoir

A two-phase stochastic dynamic programming model is developed for optimal operation of irrigation reservoirs under a multicrop environment. Under a multicrop environment, the crops compete for the available water whenever the water available is less than the irrigation demands. The performance of the reservoir depends on how the deficit is allocated among the competing crops. The proposed model integrates reservoir release decisions with water allocation decisions. The water requirements of crops vary from period to period and are determined from the soil moisture balance equation taking into consideration the contribution of soil moisture and rainfall for the water requirements of the crops. The model is demonstrated over an existing reservoir and the performance of the reservoir under the operating policy derived using the model is evaluated through simulation.     

A Modified Constrained State Formulation of Stochastic Soil Moisture for Crop Water Allocation

In response to uncertainty in crop water allocation, several methodologies have been proposed in the literature, most of them considering rainfall as a stochastic variable affecting soil moisture. A methodology considering uncertainties both in irrigation depth and soil moisture is more realistic for irrigated crops as developed here using an explicit stochastic optimization model. This new work is based on an earlier constrained state formulation which did not consider the irrigation depth as stochastic. In constrained state formulation methods, the first and second moments of state variables are developed considering the uncertainties which are then used as constraints in an optimization model. In contrast to alternative methods that are dynamic programming-based, the proposed optimization method can be solved using standard nonlinear optimization tools. Performance of the proposed model is evaluated for the case of two different crops, winter wheat and barley. Model verification is performed by comparing the results with simulation results. The model is quite acceptable and shows considerable improvement over analogous models.     

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.     

SIMETAW# - a Model for Agricultural Water Demand Planning

A successful water management scheme for irrigated crops requires an integrated approach, which accounts for water, soil, and crop management. SIMETAW# is a user friendly soil water balance model that assesses crop water use, irrigation requirements, and generates hypothetical irrigation schedules for a wide range of crops experiencing full or deficit irrigation. SIMETAW# calculates reference evapotranspiration (ET_o), and it computes potential crop evapotranspiration (ET_c), and the evapotranspiration of applied water (ET_aw), which is the amount of irrigation water needed to match losses from the effective soil root zone due to ET_c that are not replaced by precipitation and other sources. Using input information on crop and soil characteristics and the distribution uniformity of infiltrated irrigation applications in full or deficit conditions, the model estimates the mean depth of infiltrated water (IW) into each quarter of the field. The impact of deficit irrigation on the actual crop evapotranspiration (ET_a) is computed separately for each of the four quarters of the cropped field. SIMETAW# simulation adjusts ET_o estimates for projected future CO₂ concentration, and hence the model can assess climate change impacts on future irrigation demand allowing the user to propose adaptation strategies that potentially lead to a more sustainable water use. This paper discusses the SIMETAW# model and evaluates its performance on estimating ET_c, ET_a, and ET_aw for three case studies.     

基于作物水分生产函数下的限额灌溉制度优化研究

通过对小麦、玉米、棉花等主要农作物的分阶段受旱试验，获得了三年的限额灌溉试验观测数据；采用非充分灌溉条件下的土壤水分运动理论分析试验数据，建立了限额灌溉条件下的作物蒸发蒸腾模型。结合试验数据分析水分亏缺对作物产量的影响，采用多元回归分析法求解水分生产函数模型参数。采用动态规划法研究了水资源不足条件下的限额灌溉制度的多阶段优化法。研究成果表明，在产量能达到充分灌溉条件下产量的90％的情况下，可节约灌溉用水40％，能为水资源极其短缺地区的农业高效用水提供有力的技术支撑。     

黄河下游灌区农田灌溉制度与供需平衡分析

在簸箕李引黄灌区上游和下游选择典型试验区，开展了连续两年的冬小麦一夏玉米连作种植模式下的田间试验观测，用模拟灌溉制度的计算机模型ISAREG对各试验处理进行模拟，验证了模型的模拟精度。依据模拟结果对现行灌溉制度进行了评价。模拟对比了灌区内3个县4个不同干旱程度典型年气候条件下10种主要作物的两种灌溉制度方案，包括充分灌溉和部分非充分灌溉方案，计算了不同方案的田间灌溉需水过程，分析了不同方案下灌区水资源供需平衡状况。研究表明，簸箕李灌区只有采用改进的田间灌水技术和有控制的非充分灌溉制度，才能使灌区供水和需水在平水年基本达到平衡。     

冬小麦节水高效灌溉制度试验研究

通过冬小麦生长不同时期、不同土壤水分下限控制水平的灌溉试验,提出了冬小麦在当年水文和生产条件下的耗水规律、耗水量与产量的关系,提出了冬小麦试验年的优化土壤水分下限控制指标和灌溉制度,并对其研究方法也作了论述.     

Optimizing Approach of Water Allocation to Off-Takes During Reduced Flows

Multi-objective optimization models with an index were developed based on farmers’ preferences, local requirements, supplies available at the head of the canal, system losses, crop demand about different growth stages, and field soil moisture balance. The models were applied using linear programming. The Model 1 determines the cropping pattern by maximizing net economic benefits using a monthly basis lumped volume available at the head of the canal and is set to the minimum and maximum area constraints along with the constraint of minimum main crop area. The areas for different crops given by the first model form input for the Model 2. The other inputs of Model 2 included periodic supply available at the head of the primary canal (7-day period in this study), root growth depth, demand, and soil moisture constants. The Model 2 optimizes the sum of relative yields of all the crops and provide the irrigation levels of various crops for specified periods. Finally, the distributed area and irrigation levels determined by Model 2 are used in conjunction with the losses to decide flow rates of off takes. The complete program was implemented in the West branch irrigated area of Mirpurkhas subdivision. The results showed that the resources were allocated to off-takes in a competitive and conflict-free manner.