Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions

This paper develops a non-linear programming optimization model with an integrated soil water balance, to determine the optimal reservoir release policies, the irrigation allocation to multiple crops and the optimal cropping pattern in irrigated agriculture. Decision variables are the cultivated area and the water allocated to each crop. The objective function of the model maximizes the total farm income, which is based on crop–water production functions, production cost and crop prices. The proposed model is solved using the simulated annealing (SA) global optimization stochastic search algorithm in combination with the stochastic gradient descent algorithm. The rainfall, evapotranspiration and inflow are considered to be stochastic and the model is run for expected values of the above parameters corresponding to different probability of exceedence. By combining various probability levels of rainfall, evapotranspiration and inflow, four weather conditions are distinguished. The model takes into account an irrigation time interval in each growth stage and gives the optimal distribution of area, the water to each crop and the total farm income. The outputs of this model were compared with the results obtained from the model in which the only decision variables are cultivated areas. The model was applied on data from a planned reservoir on the Havrias River in Northern Greece, is sufficiently general and has great potential to be applicable as a decision support tool for cropping patterns of an irrigated area and irrigation scheduling.     

Irrigation modernization and water conservation in Spain: The case of Riegos del Alto Aragón

This study analyzes the effects of irrigation modernization on water conservation, using the Riegos del Alto Aragón (RAA) irrigation project (NE Spain, 123354 ha) as a case study. A conceptual approach, based on water accounting and water productivity, has been used. Traditional surface irrigation systems and modern sprinkler systems currently occupy 73% and 27% of the irrigated area, respectively. Virtually all the irrigated area is devoted to field crops. Nowadays, farmers are investing on irrigation modernization by switching from surface to sprinkler irrigation because of the lack of labour and the reduction of net incomes as a consequence of reduction in European subsidies, among other factors. At the RAA project, modern sprinkler systems present higher crop yields and more intense cropping patterns than traditional surface irrigation systems. Crop evapotranspiration and non-beneficial evapotranspiration (mainly wind drift and evaporation loses, WDEL) per unit area are higher in sprinkler irrigated than in surface irrigated areas. Our results indicate that irrigation modernization will increase water depletion and water use. Farmers will achieve higher productivity and better working conditions. Likewise, the expected decreases in RAA irrigation return flows will lead to improvements in the quality of the receiving water bodies. However, water productivity computed over water depletion will not vary with irrigation modernization due to the typical linear relationship between yield and evapotranspiration and to the effect of WDEL on the regional water balance. Future variations in crop and energy prices might change the conclusions on economic productivity.     

A furrow irrigation model to improve irrigation practices in the Gharb valley of Morocco

In developing countries, modernization of surface irrigation is the most common solution to water management problems in irrigated areas because it is well adapted to the socio-economical context. This solution was adopted in the Gharb area near Kenitra in Morocco where an experimental site was set up to obtain irrigation and drainage references. Meaningful improvements in irrigation efficiency and better crop yields have yet to result from the modernization effort. Different sources of heterogeneity affecting the infiltration process can hinder the improvement of irrigation efficiency even in a modernized furrow irrigation context. The respective impact of deterministic and stochastic heterogeneity sources on the advance-infiltration process is analyzed. Then, a model based on the spatial and temporal variability of infiltration is developed to simulate the impact of irrigation practices on water saving during an irrigation season. This work will later contribute to the elaboration of a modelling approach simulating fertilization and irrigation practices.     

大型水稻灌区高产节水灌溉优化配水模型研究

根据江苏省北部地区水资源供需矛盾突出的现状,以大型水稻灌区为研究对象,研究水资源的优化分配问题,从水稻水分生产函数和作物需水模型入手,建立了外引河湖水、内提回归水两种水源供水条件下的水稻全生育期适时调度优化配水数学模型。以灌区典型年供水资料,对优化配水模型进行了复核验证。所建立的模型,与灌区实际用水条件基本相符,为水稻灌区用水管理提供了一条新路。     

美国灌溉现状分析

以１９９７年的美国灌溉统计资料为基础，结合近２０多年的数据，本文详细分析了美国的农田灌溉在近２０多年的发展状况，并从地理位置、气候类型和灌溉规模等不同角度全面分析了美国各种灌溉方法的构成、灌溉所用动力类型和灌溉农田上的作物结构。结果显示，近２０多年来，美国总灌溉面积中喷灌所占比例在不断增加，而地面灌溉比例则不断降低。１９９７的资料显示，在目前美国的灌溉面积中，喷灌是以中心支轴式系统为主，微灌以地表滴灌为主，而地面灌中则有３种类型的系统使用的较多。在灌溉农田的作物结构上，干旱地区的饲草类作物种植比例明显高于其它地区，而湿润地区的粮食作物、瓜果蔬类作物和棉花的比例较高。这种比例关系随分析的角度不同而有所变化     

基于作物空间信息特征的灌区种植结构优化研究

针对目前北方许多大型灌区种植结构不合理、农业需水量偏大、水资源紧缺等问题,提出了一种基于作物空间信息特征的种植结构优化方法,通过调整种植结构和优化空间分布,减少农业需水量,提高农业效益。利用地统计学(GS)和地理信息系统(GIS)的空间处理能力,分区计算了灌区多年平均参考作物需水量(ET0)和作物需水量(ETc),并统计分区内作物单产和产值信息;构建了基于作物空间信息特征的多目标优化模型,设计了2种作物种植结构方案。结果表明,与传统多目标种植结构优化模型相比,基于作物空间信息特征的种植结构优化方法在节水效果和农业效益上都有一定的优势。     

基于Landsat 8的节水改造背景下盐渍化土壤含盐量反演

为探明沈乌灌域节水改造后因渠道衬砌、引排水量减少引起的土壤含盐量时空分布特征及变化规律,采用区域土壤信息定点监测,结合经典统计学、空间插值以及机器学习建模反演等技术手段,利用Landsat 8卫星获取光谱数据,通过对实测土壤含盐量、光谱指数及波段反射率进行处理,运用Adaboost回归、BP神经网络回归、梯度提升树回归、KNN回归、决策树回归、随机森林回归方法构建了沈乌灌域土壤含盐量空间反演模型。采用最优反演模型对沈乌灌域土壤含盐量空间分布特征进行了遥感反演。结果表明： 通过全变量单一回归法筛选出相关系数大于0.55的9个光谱因子,使用SPSS PRO软件构建6种机器学习反演模型,对比6种反演模型精度,验证集决定系数R2由大到小依次为随机森林回归、梯度提升树回归、Adaboost回归、KNN回归、决策树回归、BP神经网络回归。其中随机森林回归模型的拟合精度最佳,训练集与验证集的决定系数R2分别为0.834和0.86,说明随机森林回归模型的反演效果较好。反演结果表明：节水改造后非盐渍土面积增加391.7km2,占灌域总面积的21%,中度盐渍土面积、重度盐渍土面积、盐土面积分别减少95.61、63.37、45.7km2,分别占灌域总面积的5%、3%、2%。综上所述,节水改造工程完成后,沈乌灌域土壤盐渍化程度减轻,作物生长安全区面积增加,但由于渠道衬砌以及引排水量减少,土壤盐分淋洗效果减弱,土壤盐分在灌域内部运移,整体土壤环境得到改善,局部地区出现盐分聚集。     

Modelling of root ABA synthesis, stomatal conductance, transpiration and potato production under water saving irrigation regimes

Application of water saving irrigation strategies in agriculture has become increasingly important. Both modelling and experimental work are needed to gain more insights into the biological and physical mechanisms in the soil-plant system, which regulates water flow in the system and plays a central role in reducing crop transpiration. This paper presented a mechanistic model (Daisy) developed based on data obtained in the SAFIR project on measured leaf gas exchange and soil water dynamics in irrigated potato crops grown in a semi-field environment subjected to different irrigation regimes. Experimental data was compared to simulated results from the new enhanced Daisy model which include modelling 2D soil water flow, abscisic acid (ABA) signalling and its effect on stomatal conductance and hence on transpiration and assimilation, and finally crop yield. The results demonstrated that the enhanced Daisy model is capable of simulating the mechanisms underlying the water saving effects of the partial root-zone drying (PRD) irrigation as compared with the conventional full irrigation (FI). However the simulated effect on both crop yield and water use in this particular experiment was negligible indicating more experimental studies are necessary in order to improve on the model.     

Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration,crops coefficients,leaf area index and remotely-sensed vegetation indices

The monitoring of crop production and irrigation at a regional scale can be based on the use of ecosystem process models and remote sensing data. The former simulate the time courses of the main biophysical variables which affect crop photosynthesis and water consumption at a fine time step (hourly or daily); the latter allows to provide the spatial distribution of these variables over a region of interest at a time span from 10 days to a month. In this context, this study investigates the feasibility of using the normalised difference vegetation index (NDVI) derived from remote sensing data to provide indirect estimates of: (1) the leaf area index (LAI), which is a key-variable of many crop process models; and (2) crop coefficients, which represent the ratio of actual (AET) to reference (ET₀) evapotranspiration.A first analysis is performed based on a dataset collected at field in an irrigated area of the Haouz plain (region of Marrakesh, Central Morocco) during the 2002–2003 agricultural season. The seasonal courses of NDVI, LAI, AET and ET₀ have been compared, then crop coefficients have been calculated using a method that allows roughly to separate soil evaporation from plant transpiration. This allows to compute the crop basal coefficient (K_cb) restricted to the plant transpiration process. Finally, three relationships have been established. The relationships between LAI and NDVI as well as between LAI and K_cb were found both exponential, with associated errors of 30% and 15%, respectively. Because the NDVI saturates at high LAI values (>4), the use of remotely-sensed data results in poor accuracy of LAI estimates for well-developed canopies. However, this inaccuracy was not found critical for transpiration estimates since AET appears limited to ET₀ for well-developed canopies. As a consequence, the relationship between NDVI and K_cb was found linear and of good accuracy (15%).Based on these relationships, maps of LAI and transpiration requirements have been derived from two Landsat7-ETM+ images acquired at the beginning and the middle of the agricultural season. These maps show the space and time variability in crop development and water requirements over a 3 km × 3 km irrigated area that surrounds the fields of study. They may give an indication on how the water should be distributed over the area of interest in order to improve the efficiency of irrigation. The availability, in the near future, of Earth Observation Systems designed to provide both high spatial resolution (10 m) and frequent revisit (day) would make it feasible to set up such approaches for the operational monitoring of crop phenology and irrigation at a regional scale.     

Decision support framework for assessment of non-point-source pollution of groundwater in large irrigation projects

Agriculture is the main non-point polluter of groundwater in irrigated areas as fertilizers and other agrochemicals are the main contaminants in the water that drains out of the root zone to recharge the aquifer. Nitrates from fertilizers, dissolved in percolation losses from rice fields, are the source of pollution considered. The concentration of nitrates in the percolated water depends on the distributed field water and nitrogen balances over the area. Its concentration in the groundwater depends on the total recharge, pollution loading, groundwater flow and solute transport within the aquifer. The development and application of a GIS based decision support framework that integrates field scale models of these processes for assessment of non-point-source pollution of groundwater in canal irrigation project areas is presented. The GIS is used for representing the spatial variations in input data over the area and map the output of the recharge and nitrogen balance models. The latter are used to provide the spatially distributed recharge and pollutant load inputs to the distributed groundwater flow and transport models, respectively. Alternate strategies for water and fertilizer use can be evaluated using this framework to ensure long-term sustainability of productive agriculture in large irrigation projects. The development and application of the framework is illustrated by taking a case study of a large canal irrigation system in India.     

Mapping the total volumetric irrigation water requirements in England and Wales

The net volumetric (m³) irrigation water requirements for the main crop categories currently irrigated in England and Wales have been calculated and mapped within a geographic information system (GIS). The procedure developed by Knox et al. (1996, Agric. Water Manage., 31: 1–15) for maincrop potatoes (Solanum tuberosum) was extended to cater for the other crops currently irrigated. The annual irrigation needs (mm) for the eight major irrigated crop categories, grown on three contrasting soil types at 11 representative weather stations, were determined using a daily water balance irrigation scheduling model. The results were correlated with existing national datasets of climate, current land use, soils and irrigation practice, to generate volumetric (m³) irrigation water requirement maps at 2 km resolution.The total net volumetric irrigation water requirements for a UK ‘design’ dry year (defined as the requirement with a 20% probability of exceedance) are estimated to be 140 × 10⁶ m³ for the eight main crop categories currently irrigated and the 1994 cropping pattern. Previous theoretical dry year demand estimates, using scheduling models and large agroclimatic areas, were 109 × 10⁶ m³ and 222 × 10⁶ m³. The irrigation demand for other crops grown in the open would typically add another 4%.The procedure has been validated nationally, by comparing the calculated dry year demand for 1990 against government irrigation survey returns for 1990, for each crop category, and regionally against National Rivers Authority (NRA) abstraction records for 1990, for each NRA Region. The estimates obtained agree well with the reported distribution between crops and between regions.The most recent actual ‘dry’ year for which comparative data are available is 1990. It is estimated that the dry year requirements for the 1990 land use would have been 148 × 10⁶ m³. Although farmer demand, actual abstractions and crop requirements are not necessarily the same, irrigation survey returns to the Government indicated that 134 × 10⁶ m³ were actually applied, and the NRA estimated from meter returns that 138 × 10⁶ m³ were abstracted. It is noted, however, that some abstraction restrictions were in force, the scope of the data is slightly different and all figures contain inaccuracies. Potential applications for improving irrigation demand management and water conservation at regional and catchment levels are discussed with reference to two contrasting regions.     

Recent changes in the climatic yield potential of various crops in Europe

Recent changes in the simulated potential crop yield and biomass production caused by changes in the temperature and global radiation patterns are examined, using the Crop Growth Monitoring System. The investigated crops are winter wheat, spring barley, maize, winter rapeseed, potato, sugar beet, pulses and sunflower. The period considered is 1976-2005. The research was executed at NUTS2 level. Maize and sugar beet were the crops least affected by changing temperature and global radiation patterns. For the other crops the simulated potential yield remained stable in the majority of regions, while decreasing trends in simulated potential yields prevailed in the remaining regions. The changes appear in a geographical pattern. In Italy and southern central Europe, temperature and radiation change effects are more severe than elsewhere, in these areas potential crop yields of more than three crops significantly decreased. In the UK and some regions in northern Europe the yield potential of various crops increased.In a next step the national yield statistics were analyzed. For a large majority of the countries the yield increases of wheat, barley and to a lesser extent rapeseed are leveling off. Several explanations could be given, however, as the simulated yield potential for these crops decreased in various regions, the changing temperature and radiation patterns may also contribute to the diminishing yield increases or to the stagnation. In more than 50% of the investigated countries the maize, potato and sugar beet yields continue to increase. This can be attributed to improving production techniques, new crop varieties, sometimes in combination with an improving climatic potential. In some regions in northern Europe, yields continue to increase.     

美国德克萨斯州高地平原区地下水灌溉管理方法研究

德克萨斯州高地平原区是美国灌溉和旱地作物的生产基地,其灌溉水源主要来源于奥加拉拉(Ogallala)地下水含水层。然而,自从1950年灌溉农业发展以来,由于对奥加拉拉含水层地下水的过度开采,使得区域地下水位严重下降,有些地区地下水位下降超过50 m。为了保护地下水资源和实现地下水可持续利用,2000年以来美国德克萨斯州高平原地区在节水压采方面开展了一系列工作,取得了较好的成效。采取的主要措施包括:用德克萨斯州高地平原蒸腾蒸发网络(The Texas High Plains Evapotranspiration Network, TXHPET)进行灌溉及地下水管理,改变作物品种,改进灌溉技术,改变种植结构,保护性耕作方法,加强降雨管理,将小部分灌溉农田转为旱作农田等。该区域1958年的灌溉面积为183万hm~2,1974年灌溉面积达到峰值,为242万hm~2;1989年灌溉面积降为159万hm~2,由于喷灌技术的推广应用,2000年灌溉面积恢复到187万hm~2。1958年大多数灌区为地面灌溉,仅有11%的灌溉面积为喷灌。1974年之后,灌溉总面积在减少,主要灌溉方式转为喷灌,中心支轴式喷灌面积稳步增长。自1989年之后,喷灌在该区域快速发展,2000年喷灌面积已占该区域灌溉面积的72%。早期的喷灌系统在较高压力下运行,自20世纪80年代,低压喷灌系统已全面使用。我国华北地区长期超量开采地下水与美国德克萨斯州高原区地下水超采情况及问题相似。兹系统介绍了美国德克萨斯州高地平原区在地下水超采情况下采取的综合措施拟为我国地下水超采地区的地下水管理工作提供技术与经验参考。     

Combined use of optical and radar satellite data for the detection of tillage and irrigation operations: Case study in Central Morocco

The objective of this study is to present a new application of optical and radar remote sensing with high spatial (∼10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season.The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations.The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas.     

A methodology for up-scaling irrigation losses

This paper presents a methodology for up-scaling field irrigation losses and quantifying relative losses at the irrigation area level for potential water savings. Two levels of analysis were considered: First, the field level where irrigation is applied. Second, the irrigation area level, where the field level losses are aggregated, or up-scaled, using average loss functions. In this up-scaling approach, detailed crop-soil-water modelling can capture the variability of physical parameters (such as soils, crops, water table depth, and management practices) at the field level which are then used to derive loss functions for aggregating losses at higher scales (irrigation area level). This allows potential field-level adaptations and water management changes made by individual farmers to be assessed for impact at the larger irrigation area level. The APSIM farming systems model was used for simulation of crops (wheat, rice, and soybean) and their interaction with the wider system processes at the field level. Given the climate, soil, and management information (sowing, fertilisation, irrigation, and residue management), the model simulates infiltration, the soil moisture profile, plant water uptake, soil evaporation, and deep drainage on a daily basis. Then, by placing the field level analysis in the context of the wider irrigation system or catchment, it is possible to correlate field level interventions (e.g. water savings measures) with water requirements at these higher levels. Application of this method in the Coleambally Irrigation Area in NSW, Australia, demonstrated that an exponential function can describe the relationship between deep drainage losses and the water table depth for different soil, crop, and water table depth combinations. The rate of loss increase (slope of the curve) with the water table depth is higher on lighter (higher intake rates) soils than on heavy soils and is more pronounced in areas under rice cultivation. We also demonstrate that this analysis technique can assist in identifying spatial distribution of losses in irrigation areas, considering water table depth as an additional factor, leading to targeted areas for water-saving measures.     

Effects of rising atmospheric CO2 on crop evapotranspiration in a Mediterranean area

In the assessment of plant response to the climate changes, the effects of CO₂ increase in the atmosphere and the subsequent rise of temperatures must be taken into account for their effects on crop physiology. In Mediterranean areas, a decrease of water availability and a more frequent occurrence of drought periods are expected. The objective of this study was to assess the impact of elevated CO₂ concentration and high temperature on reference evapotranspiration (ETo) and crop evapotranspiration (ETc) in the Mediterranean areas. The Penman-Monteith equation was used to simulate the future changes of reference evapotranspiration (ETo) by the recalibration of the canopy resistance parameter. Besides, crop coefficients (Kc) were adjusted according to the future climate trend. Then the modified empirical model (ETc = ETo × Kc) was applied providing an effective quantification of the climate change impact on water use of irrigated crops grown in Mediterranean areas. In the studied area, water use assessment was carried out for the period from 1961 to 2006 (measured data) and for a period from 2071 until 2100 (simulated data), showing a future climatic scenario. Water and irrigation use of crops will change as a function of climate changes, thermal needs of single crops and time of the year when they grow. Climate simulation model foresees the tendency for a significant increase of temperatures and a decrease of total year rainfall with a change of their distribution. The temperature increase and the concomitant expected rainfall decrease lead to a rise of year potential water deficit. About the autumn-spring crops, as wheat, a further increase of water deficit, is not expected. On the contrary, for spring-summer crops as tomato, a significant increase of water deficit and thus of irrigation need, is foreseen. Actually, for crops growing in that period of the year, the substantial rise of evapotranspiration demand cannot be compensated by crop cycle reduction and partial stomatal closure.     

Determination of spatial water requirements at county and regional levels using crop models and GIS: An example for the State of Parana,Brazil

Due to the competitive use of available water resources, it has become important to define appropriate strategies for planning and management of irrigated farmland. To achieve effective planning, accurate information is needed for crop water use requirements, irrigation withdrawals, runoff and nitrate leaching as a function of crop, soil type and weather conditions at a regional level. Interfacing crop models with a geographic information system (GIS) extends the capabilities of the crop models to a regional level. The objective of this study was to determine the irrigation requirements, annual runoff and annual nitrate leaching for the most important crops of the Tibagi river basin in the State of Parana, Brazil. The computer tool selected for this study was the Decision Support System for Agrotechnology Transfer (DSSAT) version 3.5 (98.0) and its associated crop modeling and spatial application system AEGIS/WIN. It was assumed that farms within the same county use similar management practices. To achieve representative estimates of irrigation requirements, the weather data from stations located within each county or the nearest weather station were used. A weighting factor based on the proportion of soil type and crop acreage was applied to determine total annual irrigation withdrawals, annual runoff and nitrate leaching for each county in the river basin. The model predicted outputs, including yield, irrigation requirements, runoff and nitrate leached for different soil types in each county, were analyzed, using spatial analysis methods. This allowed for the display of thematic maps for irrigation requirements, annual runoff and nitrate leaching, and to relate this information with irrigation management and planning. The maximum annual irrigation withdrawal, runoff and nitrate leaching were 22,969 m³ per year, 31,152 m³ per year and 1488 t N per year in the Tibagi river basin. This study showed that crop simulation models linked to GIS can be an effective planning tool to help determine irrigation requirements for river basins and large watersheds.     

Retrieval of irrigated and rainfed crop data using a general maximum entropy approach

This paper presents a method to separate harvested area and yield for irrigated crops from rainfed crops in a region, given gross harvested area and yield, and climatic, agronomic and economic data for crops. The method is based on the principle of general maximum entropy, which combines incomplete data, empirical knowledge and a priori information to derive desired information. The model is applied to three large basins with aggregated climatic and agricultural conditions, and to five counties in Texas and California. The modeled results and assessed values in these study areas are compared. While the dependability of model outputs relies on empirical knowledge and judicious parameter estimation, the model remains reliable even for the significant level of uncertainty produced by subjectively predetermined major parameters. The model can be applied to retriving historical data for irrigated and rainfed crops; it can also be used for irrigated and rainfed agriculture planning based on climatic and technological projections. Moreover, the model provides other useful information, including water allocation by crop, water use efficiency and the impact of other agricultural inputs.