泾惠渠灌区需水与用水管理分析
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摘要
通过对泾惠渠灌区多年渠首引水和灌区用水资料进行统计分析,结合灌区多年降水情况、实际种植结构与灌溉制度、农民实际用水习惯、灌区各级渠道水的利用系数等,分析灌区不同水文年理论灌溉需水量与实际灌溉引水量及其用水过程,对灌区的需水过程,实际供水过程和灌区现行灌溉制度下的需水过程做对比分析,得出以下研究结果:
(1)利用Penman—Monteith公式计算了灌区1993-2000年的参考作物蒸发蒸腾量;对影响参考作物蒸发蒸腾量的各个因子进行主成分分析,根据其贡献率,确定了新影响因子;通过BP神经网络模型和多元线性回归模型两种模型对ET_0的预测值与Penman—Monteith公式计算结果的比较发现,多元线性回归模型预测的最大误差和平均相对误差的绝对值分别为31.50%和11.66%,而BP神经网络模型预测的最大误差和平均相对误差绝对值仅为21.30%和7.81%,BP神经网络模型比多元线性回归模型有更高的拟合精度,可利用BP神经网络模型对灌区的参考作物蒸发蒸腾量进行预测。
(2)通过对灌区代表站点气象、降水资料的频率分析,确定了灌区的典型年;通过对典型站点参考作物蒸发蒸腾量的对比,最终确定了灌区选取泾阳站气象资料作为确定灌区作物需水量的基本资料。通过对单作物系数法、双作物系数法的比较,并根据灌区实际情况确定了灌区主要作物全生育期逐月的作物系数;确定出了灌区主要作物全生育期需水量:冬小麦为299.49mm~348.69mm;夏玉米为410.55mm～559.09mm;棉花为583.82mm～745.04mm。通过对不同水文年份的作物需水过程进行分析,确定了主要作物的需水规律及其需水强度极值,其中;冬小麦为2.75 mm/d～3.02 mm/d;夏玉米为5.01 mm/d～5.86 mm/d;棉花为5.31 mm/d～6.21 mm/d。
(3)利用灌区渠系实际分水、配水资料,以及灌区实际灌溉定额,采用首尾测定法对灌区的灌溉水利用系数进行确定,结果表明灌区的灌溉水利用系数在0.503～0.598之间变动,多年平均灌溉水利用系数为0.548。灌区灌溉水利用系数波动不大,而且上下波动幅度大致相当,说明灌区管理水平相对较高,渠系运行状况良好;运用GM(1,1)灰色预测模型对灌区2009-2013年5年的灌溉水利用系数进行预测,灌溉水利用效率的预测值在0.561～0.572之间变化。
(4)运用水量平衡方程确定了灌区主要作物以及全灌区的理论灌溉总需水量,灌区理论灌溉总需水量在3.22×10~8m~3～4.68×10~8m~3之间。其中:冬小麦的需水量约为0.68×10~8m~3～1.44×10~8m~3;夏玉米的需水量约为1.07×10~8m~3～2.16×10~8m~3;棉花需水量约为0.13×10~8m~3～0.26×10~8m~3 ;其它作物的需水约为0.91×10~8m~3～1.39×10~8m~3。考虑灌区的实际情况确定的灌区灌溉总需水量在20776.9×10~4m~3～30728.7×10~4m~3之间,多年平均需水量约为26561.7×10~4m~3。由于灌区为渠井结合的大型灌区,综合考虑井灌及地下水的补给,灌区渠灌净需水量在11488.9×10~4m~3～16991.8×10~4m~3之间,多年平均渠灌总需水量为14928.9×10~4m~3。
(5)通过对灌区1993～2001年需引水量和实引水量的对比分析,发现二者差距不大。灌区仅在特旱干旱年出现亏缺,其它水文年份(湿润年、中等年和干旱年)则基本平衡,灌区最大亏水出现在2000(P=90%,特旱年),亏水量为4380.3×10~4m~3,该年灌区的灌水满足率仅为0.739。
(6)通过对灌区1993～2001年需水过程和用水过程进行对比分析,发现二者存在较大差异。灌区需水从三月份以来开始上升,但渠灌引水并没有显著增加,相反却有下降的趋势,这主要是由两方面原因造成的,首先渠首的引水流量受到了河源来水量以及河流含沙量等诸多制约因素的影响,实际的配水过程不可能和灌区的需水过程完全吻合;其次灌区实施错峰引水,即在用水不紧张的时候,加大引水流量,将水引至灌区内的小型调蓄水库蓄存起来。三、四月份以后用水紧张,来水量减少,而且河流来水含沙量增大,使灌区该阶段取水量维持在较低状态,有时甚至被迫停止引水。
(7)通过对灌区现行灌溉制度的分析,确定了灌区不同水文年份按照灌溉制度的需水过程线,冬灌渠首需引水量在9.081 m~3/s～10.90 m~3/s之间,春灌渠首需引水量逐渐增大,灌区夏灌渠首最大需引水量达52.58 m~3/s。通过和实际渠灌引水过程线进行比较分析,表明灌区现行的灌溉制度在湿润年份基本可以满足灌区的用水需求,其它水文年份(中等年、干旱年)灌区的冬春现行的灌溉制度,基本可以满足灌区的需水需求,但是夏灌随着干旱程度的增加二者的差距在拉大。综上所述,泾惠渠灌区虽然属于亏水灌区,但在施行非充分灌溉的基础上,结合灌区渠井双灌并重的实际情况,灌区现行的灌溉制度基本能满足灌区的的用水需求,灌区的运行状态良好。
Statistical analysis of annual data was conducted for water diversion from head and water use of irrigation. Annual rainfall was considered as well as actual planting structure and irrigation system, actual water habit of farmers, water use coefficient of channel at all levels in irrigation district.Then theoretical irrigation water demand and practical irrigation water diversion as well as water use process. Water demand process, actual water supply process and water demand of actual irrigation system in irrigation district were analyzed, The main contents were as follows:
(1) Penman—Monteith equation was used to calculate reference crop evapotranspiration from 1993 to 2000. Principal component analysis of each factor was done which affecting reference crop evapotranspiration and determined new factors according to their contribution. ET_0 which was predicted by BP neural network model and multiple linear regression model was compared with that calculated by Penman—Monteith equation. It indicated that the maximum error and the average relative error of prediction by multiple linear regression model were 31.50 percent and 11.66 percent, but the value by BP neural network model were only 21.30 percent and 7.81 percent. Therefore, the accuracy of BP neural network model was higher than that of multiple linear regression model and BP neural network model could be used to predicted ET_0.
(2)Typical years were determined by analyzing weather of representative site and frequency of rainfall data. The comparasion of reference crop evapotranspiration among typical sites eventually confirmed jingyang site used to determine the basic data of crop water requirement. Month-by-month crop coefficients of the whole main corp growth period were ascertained by comparing single crop coefficient, dual crop coefficient as well as the actual situation. Crop water demand was also confirmed each month in the whole growth period, which of winter wheat was 299.49 milimeters to 348.69 milimeters, summer maize 410.55 milimeters to 559.09 milimeters, and cotton 583.82 milimeters to 745.04 milimeters. Furthermore, water requirement regulation and extreme value of water requirement intensity were ascertained by analyzing crop water requirement process of different hydrological years, which of winter wheat was 2.75 milimeters per day to 3.02 milimeters per day, summer maize 5.01 milimeters per day to 5.86 milimeters per day and cotton 5.31 milimeters per day to 6.21 milimeters per day.
(3)The data of actual water segrating of canal system and water distribution were utilized as well as practical irrigation quota to determine water efficiency of irrigation, which also was confirmed by terminal method. The result indicated that water efficiency of irrigation varied from 0.503 to 0.598 and average annual water efficiency of irrigation was 0.548. The fluctuaion of coefficient was not serious and the fluctuation between the minimum limit and the upper bound was equivalent. It proved that the management level was high in the irrigation district and operation of canal system was good. GM (1,1) grey forcasting model was used to predict irrigation water use efficiency from 2009 to 2013, which ranged from 0.561～0.572.
(4)Water balance equation was adopted to determine the theoretical total irrigation water requirement which varied 3.22×10~8m~3 to 4.68×10~8m~3,which of winter wheat was about 0.68×10~8m~3 to 1.44×10~8m~3 ,summer maize 1.07×10~8m~3 to 2.16×10~8m~3 ,cotton 0.13×108m~3 to 0.26×10~8m~3and others 0.91×10~8m~3 to 1.39×10~8m~3. If the actual situation was considered, the total water requirement varied from 2.08×10~8m~3 to 3.07×10~8m~3 and the average annual water requirement was about 2.67×10~8m~3.The cannal and well both were used in the irrigation district.Then,well irrigation and groundwater supply were considered.Therefore, the net water requirement of channel irrigation ranged from 1.15×10~8m~3 to 1.70×10~8m~3 and the average annual total water demand of it was 1.49×10~8m~3.
(5)The comparasion between water diversion required and actual water diversion during the year from 1993 to 2001 showed that the difference between them was not large. Water deficit merely occurred in the dry year and arid year, however, water kept balanced in other hydrological years—rainy years and medium years.The maximum water deficit appeared in 2000(P=90%,dry year) and the amount of water deficit was 4.38×10~7m~3. In the year, irrigation requirement rate was only 0.739.
(6) It indicated that there existed large difference between them by comparing water requirement process and water use process. Water requirement rised from March, but there was no significant increase in water diversion, on the contrary, showing the downward trend. It was two reasons that led to the phenomen. Firstly, diversion discharge of head was influenced by such factors as inflows of water source and silt content of river, and practical water distribution process and water requirement process didn’t completely coincide. Secondly, water diversion staggering the peak was conducted, in other words, water diversion increased and water was imported to regulating reservoir when water was in great demand. Water was in great demand after March or April, when inflows decreased and silt content of river rised. It maked water intake keep low in the stage, sometimes, water diversion was forced to cease.
(7) The analysis of the current irrigation system ascertained water requirement curve of different hydrological years according to the irrigation system. Water diversion of head needed was between 9.081 m~3/s～10.90 m~3/s in winter. It increased gradually in winter and spring, reaching the maximum 52.58 m~3/s in summer. Compared with the actual water diversion curve, the current irrigation system basically satisfied water use in the rainy years and water requirement in other hydrological years (medimum years, arid years) in winter and spring. However, the difference of them both in summer increased as the degree of aridity rised. The irrigation district belonged to the area of water defict. The measures were taken that deficit irrigation was conducted combined with canal irrigation and well irrigation. Then the irrigation system basicall satisfied water use in the irrigation district and the i irrigation district run well.
(1)利用Penman—Monteith公式计算了灌区1993-2000年的参考作物蒸发蒸腾量;对影响参考作物蒸发蒸腾量的各个因子进行主成分分析,根据其贡献率,确定了新影响因子;通过BP神经网络模型和多元线性回归模型两种模型对ET_0的预测值与Penman—Monteith公式计算结果的比较发现,多元线性回归模型预测的最大误差和平均相对误差的绝对值分别为31.50%和11.66%,而BP神经网络模型预测的最大误差和平均相对误差绝对值仅为21.30%和7.81%,BP神经网络模型比多元线性回归模型有更高的拟合精度,可利用BP神经网络模型对灌区的参考作物蒸发蒸腾量进行预测。
(2)通过对灌区代表站点气象、降水资料的频率分析,确定了灌区的典型年;通过对典型站点参考作物蒸发蒸腾量的对比,最终确定了灌区选取泾阳站气象资料作为确定灌区作物需水量的基本资料。通过对单作物系数法、双作物系数法的比较,并根据灌区实际情况确定了灌区主要作物全生育期逐月的作物系数;确定出了灌区主要作物全生育期需水量:冬小麦为299.49mm~348.69mm;夏玉米为410.55mm～559.09mm;棉花为583.82mm～745.04mm。通过对不同水文年份的作物需水过程进行分析,确定了主要作物的需水规律及其需水强度极值,其中;冬小麦为2.75 mm/d～3.02 mm/d;夏玉米为5.01 mm/d～5.86 mm/d;棉花为5.31 mm/d～6.21 mm/d。
(3)利用灌区渠系实际分水、配水资料,以及灌区实际灌溉定额,采用首尾测定法对灌区的灌溉水利用系数进行确定,结果表明灌区的灌溉水利用系数在0.503～0.598之间变动,多年平均灌溉水利用系数为0.548。灌区灌溉水利用系数波动不大,而且上下波动幅度大致相当,说明灌区管理水平相对较高,渠系运行状况良好;运用GM(1,1)灰色预测模型对灌区2009-2013年5年的灌溉水利用系数进行预测,灌溉水利用效率的预测值在0.561～0.572之间变化。
(4)运用水量平衡方程确定了灌区主要作物以及全灌区的理论灌溉总需水量,灌区理论灌溉总需水量在3.22×10~8m~3～4.68×10~8m~3之间。其中:冬小麦的需水量约为0.68×10~8m~3～1.44×10~8m~3;夏玉米的需水量约为1.07×10~8m~3～2.16×10~8m~3;棉花需水量约为0.13×10~8m~3～0.26×10~8m~3 ;其它作物的需水约为0.91×10~8m~3～1.39×10~8m~3。考虑灌区的实际情况确定的灌区灌溉总需水量在20776.9×10~4m~3～30728.7×10~4m~3之间,多年平均需水量约为26561.7×10~4m~3。由于灌区为渠井结合的大型灌区,综合考虑井灌及地下水的补给,灌区渠灌净需水量在11488.9×10~4m~3～16991.8×10~4m~3之间,多年平均渠灌总需水量为14928.9×10~4m~3。
(5)通过对灌区1993～2001年需引水量和实引水量的对比分析,发现二者差距不大。灌区仅在特旱干旱年出现亏缺,其它水文年份(湿润年、中等年和干旱年)则基本平衡,灌区最大亏水出现在2000(P=90%,特旱年),亏水量为4380.3×10~4m~3,该年灌区的灌水满足率仅为0.739。
(6)通过对灌区1993～2001年需水过程和用水过程进行对比分析,发现二者存在较大差异。灌区需水从三月份以来开始上升,但渠灌引水并没有显著增加,相反却有下降的趋势,这主要是由两方面原因造成的,首先渠首的引水流量受到了河源来水量以及河流含沙量等诸多制约因素的影响,实际的配水过程不可能和灌区的需水过程完全吻合;其次灌区实施错峰引水,即在用水不紧张的时候,加大引水流量,将水引至灌区内的小型调蓄水库蓄存起来。三、四月份以后用水紧张,来水量减少,而且河流来水含沙量增大,使灌区该阶段取水量维持在较低状态,有时甚至被迫停止引水。
(7)通过对灌区现行灌溉制度的分析,确定了灌区不同水文年份按照灌溉制度的需水过程线,冬灌渠首需引水量在9.081 m~3/s～10.90 m~3/s之间,春灌渠首需引水量逐渐增大,灌区夏灌渠首最大需引水量达52.58 m~3/s。通过和实际渠灌引水过程线进行比较分析,表明灌区现行的灌溉制度在湿润年份基本可以满足灌区的用水需求,其它水文年份(中等年、干旱年)灌区的冬春现行的灌溉制度,基本可以满足灌区的需水需求,但是夏灌随着干旱程度的增加二者的差距在拉大。综上所述,泾惠渠灌区虽然属于亏水灌区,但在施行非充分灌溉的基础上,结合灌区渠井双灌并重的实际情况,灌区现行的灌溉制度基本能满足灌区的的用水需求,灌区的运行状态良好。
Statistical analysis of annual data was conducted for water diversion from head and water use of irrigation. Annual rainfall was considered as well as actual planting structure and irrigation system, actual water habit of farmers, water use coefficient of channel at all levels in irrigation district.Then theoretical irrigation water demand and practical irrigation water diversion as well as water use process. Water demand process, actual water supply process and water demand of actual irrigation system in irrigation district were analyzed, The main contents were as follows:
(1) Penman—Monteith equation was used to calculate reference crop evapotranspiration from 1993 to 2000. Principal component analysis of each factor was done which affecting reference crop evapotranspiration and determined new factors according to their contribution. ET_0 which was predicted by BP neural network model and multiple linear regression model was compared with that calculated by Penman—Monteith equation. It indicated that the maximum error and the average relative error of prediction by multiple linear regression model were 31.50 percent and 11.66 percent, but the value by BP neural network model were only 21.30 percent and 7.81 percent. Therefore, the accuracy of BP neural network model was higher than that of multiple linear regression model and BP neural network model could be used to predicted ET_0.
(2)Typical years were determined by analyzing weather of representative site and frequency of rainfall data. The comparasion of reference crop evapotranspiration among typical sites eventually confirmed jingyang site used to determine the basic data of crop water requirement. Month-by-month crop coefficients of the whole main corp growth period were ascertained by comparing single crop coefficient, dual crop coefficient as well as the actual situation. Crop water demand was also confirmed each month in the whole growth period, which of winter wheat was 299.49 milimeters to 348.69 milimeters, summer maize 410.55 milimeters to 559.09 milimeters, and cotton 583.82 milimeters to 745.04 milimeters. Furthermore, water requirement regulation and extreme value of water requirement intensity were ascertained by analyzing crop water requirement process of different hydrological years, which of winter wheat was 2.75 milimeters per day to 3.02 milimeters per day, summer maize 5.01 milimeters per day to 5.86 milimeters per day and cotton 5.31 milimeters per day to 6.21 milimeters per day.
(3)The data of actual water segrating of canal system and water distribution were utilized as well as practical irrigation quota to determine water efficiency of irrigation, which also was confirmed by terminal method. The result indicated that water efficiency of irrigation varied from 0.503 to 0.598 and average annual water efficiency of irrigation was 0.548. The fluctuaion of coefficient was not serious and the fluctuation between the minimum limit and the upper bound was equivalent. It proved that the management level was high in the irrigation district and operation of canal system was good. GM (1,1) grey forcasting model was used to predict irrigation water use efficiency from 2009 to 2013, which ranged from 0.561～0.572.
(4)Water balance equation was adopted to determine the theoretical total irrigation water requirement which varied 3.22×10~8m~3 to 4.68×10~8m~3,which of winter wheat was about 0.68×10~8m~3 to 1.44×10~8m~3 ,summer maize 1.07×10~8m~3 to 2.16×10~8m~3 ,cotton 0.13×108m~3 to 0.26×10~8m~3and others 0.91×10~8m~3 to 1.39×10~8m~3. If the actual situation was considered, the total water requirement varied from 2.08×10~8m~3 to 3.07×10~8m~3 and the average annual water requirement was about 2.67×10~8m~3.The cannal and well both were used in the irrigation district.Then,well irrigation and groundwater supply were considered.Therefore, the net water requirement of channel irrigation ranged from 1.15×10~8m~3 to 1.70×10~8m~3 and the average annual total water demand of it was 1.49×10~8m~3.
(5)The comparasion between water diversion required and actual water diversion during the year from 1993 to 2001 showed that the difference between them was not large. Water deficit merely occurred in the dry year and arid year, however, water kept balanced in other hydrological years—rainy years and medium years.The maximum water deficit appeared in 2000(P=90%,dry year) and the amount of water deficit was 4.38×10~7m~3. In the year, irrigation requirement rate was only 0.739.
(6) It indicated that there existed large difference between them by comparing water requirement process and water use process. Water requirement rised from March, but there was no significant increase in water diversion, on the contrary, showing the downward trend. It was two reasons that led to the phenomen. Firstly, diversion discharge of head was influenced by such factors as inflows of water source and silt content of river, and practical water distribution process and water requirement process didn’t completely coincide. Secondly, water diversion staggering the peak was conducted, in other words, water diversion increased and water was imported to regulating reservoir when water was in great demand. Water was in great demand after March or April, when inflows decreased and silt content of river rised. It maked water intake keep low in the stage, sometimes, water diversion was forced to cease.
(7) The analysis of the current irrigation system ascertained water requirement curve of different hydrological years according to the irrigation system. Water diversion of head needed was between 9.081 m~3/s～10.90 m~3/s in winter. It increased gradually in winter and spring, reaching the maximum 52.58 m~3/s in summer. Compared with the actual water diversion curve, the current irrigation system basically satisfied water use in the rainy years and water requirement in other hydrological years (medimum years, arid years) in winter and spring. However, the difference of them both in summer increased as the degree of aridity rised. The irrigation district belonged to the area of water defict. The measures were taken that deficit irrigation was conducted combined with canal irrigation and well irrigation. Then the irrigation system basicall satisfied water use in the irrigation district and the i irrigation district run well.
引文
白美健. 2001.大型灌区灌溉系统性能评价.[硕士学位论文].北京:中国水利水电科学研究院
蔡明科,魏晓妹,粟晓琳. 2007.宝鸡峡灌区耗水量变化规律及影响因素分析研究.水土保持研究
陈博,欧阳竹. 2010.基于BP神经网络的冬小麦耗水预测.农业工程学报, 24(4):81-86
陈玉明,郭国双,王广兴.1995.中国主要作物需水量与灌溉.北京:水利水电出版社
邓聚龙. 1986.灰色系统基本方法.武汉.华中理工大学出版社
邓聚龙. 2002.灰模拟与灰预测.武汉:华中科技大学出版社
樊军,邵明安,土全九. 2008.黄土地参考作物蒸散量多种计算方法的比较研究.农业工程学报,24(3):98-99.
高峰,赵竞成,许建中.2004.灌溉水利川系数测定方法研究.灌溉排水学报,23 (1):14-20
葛哲学,孙志强.2008.神经旺络理论与MATLAB 2007实现.北京:电子工业出版字: 108-117.
郭小玲.2007.作物需水量预测模型研究及其在灌溉管理信息系统中的应用[硕士学位论文].武汉:华中科技大学
泾惠渠志编写组.1991.泾惠渠志.陕西:三秦出版社
康绍忠,蔡焕杰.1996.农业水管理学.北京:中国农业出版社
康绍忠,粟晓玲,杜太生.2009.西北旱区流域尺度水资源转化规律及其其节水调控模式.北京:中国水利水电出版社:398-400
李卫东.2008.应用多元统计分析.北京:北京大学出版社
李英能.2003.浅论灌区灌溉水利川系数.中国农村水利水电,(7):23-26
刘昌明,陈志恺. 2001.中国水资源现状评价和供水发展趋势分析.北京:中国水利水电出版社
刘坤,郑旭荣,谢云.2005.玛纳斯河流域农业节水潜力分析.石河子大学学报(自然科学版),23(2):237- 239
刘钰,蔡甲冰,徐迪.2002.作物蒸发量的实时预报和田间验证,(6):25-63
刘战.2009.灌溉水利用系数的影响因素及提高措施.陕西水利, (04):108-156
卢嘉锡,1996.中国科学技术史.水利卷.北京:中国科学出版社:27-34
吕廷波,佟玲.2010.基于首尾测定法的石羊河流域灌溉水利用率估算及分析.石河子大学学报(自然科学版).28(2):231-236
茆智,李远华.2002.实时灌溉预报.中国工程科学,4(5):24-36
茆智.2009.灌溉用水有效利用系数测算分析有助于进一步明确农业节水的主攻方向.中国水利,(3) :5~6
山仑,康绍忠,吴普特.2004.中国农业节水.北京:中国农业出版社:34-36
陕西省水利水土保持厅,1991.陕西省作物需水量及分区灌溉模式:71-73
邵新星. 2009.浅谈灌溉水利用系数测定中存在问题及影响因素.陕西水利,(04):96-128
沈小谊,黄永茂,沈逸轩.2003.灌区水资源利用系数研究.中国农村水利水电. (01):78-121
沈逸轩,黄永茂,沈小谊,朱世静.2005.年灌溉水利用系数的研究.中国农村水利水电,(07) :45-67
施彦,韩力群,廉小亲.2009.神经网络计算方法与实例分析.北京:北京邮电大学出版社
石玉林,卢良恕.2001.中国农业需水与节水高效农业建设.北京:中国水利水电出版社:122～130
史晓楠,王全九,王新.2006.参考作物腾发量计算方法在新疆地区的适用性研究.农业工程学报,22(6):19-22.
孙国斌,王密侠,尚虎军.2008.陕西省灌溉水利用系数测算软件的开发与应用[硕士学位论文].灌溉排水学报.28(1):128-130
孙景生,刘祖贵,张寄阳.2002.风沙区参考作物蒸发蒸腾量的计算.灌溉排水学,21(2):17-20
孙景生.2004.时间序列法在参考作物腾发量分析与模拟中的应.北京:中国农村水利水电,(8):34-42
谭芳,崔远来,王建漳.2009.灌溉水利用率影响因素的主成分分析—以漳河灌区为例.中国农村水利水电,(2):70-73
汪富贵.2001.灌区灌溉水利用系数的分析方法.节水灌溉,(6):25-26.
王洪斌,闻绍珂,郭清.2008.灌溉水利用系数传统测定方法的修正.东北水利水电, (04):86-90
王仰仁,李明思,康绍忠.2003.立体种植条件下作物需水规律研究.水利学报.,(7):90-95
网伦平,陈亚新等.2001.内蒙古河套灌区灌溉排水与盐碱化防治.北京:水利水电出版社.
徐俊增,彭世彰,张瑞美. 2006.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.水利学报,37(3) 376-379
许建中.赵竞成,高峰.2005.灌溉水利用系数综合测定法实例分析.(1):55-58.
严雷,赵晓波. 2009 .峡口灌区灌溉水利用系数测算.节水灌溉,(06):48-54
姚付启,张振华,钱为君. 2008.烟台果园土壤温度影响因素及其预测模型研究.农业系统科学与综合研究,22(2):201-204
张大海,江世芳,史开泉.2008.灰色预测公式的理论缺陷及改进.系统工程理论与实践,(8):140-124
张代远. 2006.神经网络新理论与方法.北京:清华大学出版社
张德丰. 2009.MATLAB神经网络仿真与应用.北京:电子工业出版社:79-83
张东,张贤瑞.玛水军.2009.等天津市现状灌溉水利用率测算研究.节水灌溉, (2):42-44
张芳,李水鑫,张玉顺.2008.河南省现状灌溉水利用率的测算研究.人民黄河,30(1): 5l-54
张涛,张成利,李楠楠.2006.灌溉水利用系数的传统测定方法存在的问题及影响因素分析.地下水,(03) :49-87
张涛,张成利,李楠楠. 2006.灌溉水利用系数的传统测定方法存在的问题及影响因素分析.地下水,28 (3):81- 82
张亚平.2007.陕西省现状灌溉水利用率测算方法与问题讨论.水资源与水工程程学报,16 (3):60- 62
张勇刚,卫星.2009.灌区提高灌溉水利用系数的措施.黑龙江水利科技,( 3):76-89
赵璐,蔡焕杰,王建. 2010.ET0的主因子和主成分神经网络模型比较.节水灌溉,(3)23-25
赵旭,李毅,刘俊明.2009.新疆地区参考作物蒸发蒸腾量的灰色模型预测.农业工程学报, (10):50-53.
Allen R G. 1998.Crop Evapotranspiration Guidelines for Computing Crop WaterRequirements FAO Irrigationand Drainage Paper, 56:18-35
Ayars J E, Hutmacher R B.1994. Crop Coefficients for irrigating cotton in the presence of groundwater . Irrigation Science, 15(1):45~52
Cabelguenne,M DebaekeP,H.Puech J.1997.Real time irrigation management using the EPIC-PHASE model and weather forecasts ,32:227~238
Cowing J.2001.Real-time scheduling of supplemental irrigation for potatoes using a decisionmodel and short-term weather forecasts, 47:137~153
Doorenbos J, Pruitt W O.1977.Crop Water requirements. Irriagtion and Drain Paper No. 24.Rome, Italy: Food and Agric. Organization of the United Nations
FAO.1977.Irrigation and Drainage Papers 24.Crop Water Requirements.Rome
Feddes R A. 1978. Simulation of Field water use and crop yield. Center for Agric. Publishing and Documentation, Wageninge
Frere M, Popov G F. 1979. Agrometeorological crop monitoring and forecasting. Rome: FAO, Plant Production and Protection Paper, No.17
Godwin D,Meyer W S,Xevi E,White R G J.2006.SWAGMAN? Destiny:A simulation model of irrigated crops as affected by irrigation practice,water tables and salinity.1.Model description.Unpublished,Griffith:CSIRO Land and Water:1～20
Govindarajan S,Ambujam N K,Karunakaran K.2008.Estimation of paddy water productivity(WP) using hydrological model:an experimental study.Paddy Water Environment,6:327～339
Groves D,Lempert R.2007.A new analytic method for finding policy-relevant scenarios.Global Environmental Change,17:73～85
Guo S,Wang J,Xiong L,Ying A,Li D.2002.A macro-scale and semi-distributed monthly water balance model to predict climate change impacts in China.Journal of Hydrology,268:1～15
Hall W A.1960.Performance parameters of irrigation systems.Transactions of the ASAE,3(1):75～76
Hansen V E.1960.New concepts in irrigation efficiency.Transactions of the ASAE,55～64
Harle K J,Howden S M,Hunt L P.2007.The potential impact of climate change on the Australian wool industry by 2030.Agricultural Systems,93:61～89
Hart W E,Reynolds W N.1965.Analytical design of sprinkler systems.Transactions of the ASAE,8:83～85,89
Hennessy K B,Fitzharris B C,Bates N,Harvey S M,Howden L,Hughes J,Salinger, Warrick R.2007. Australia and New Zealand. In Climate Change 2007:Impacts,Adaptation and Vulnerability. In: Parry M L,Canziani O F,Palutikof J P,van der Linden P J, Hanson C E,Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change,Cambridge University Press,Cambridge,UK:507～540
Hennessy K,Ian Macadam,Whetton P.2006.Climate change scenarios for initial assessment of risk in accordance with risk management guidance.Canberra:Australian Greenhouse Office:1～36
Herrera-Pantoja M,Hiscock K M.2008.The effects of climate change on potential groundwater recharge in Great Britain.Hydrological Processes,22:73～86
Herron N,Davis R,Jones R.2002.The effects of large～scale afforestation and climate change on water allocation in the Macquarie River catchment,NSW,Australia.Journal of Environmental Management,65(4):369～381
Hobbs B F.1997.Bayesian Methods for Analysing Climate Change and Water Resource Uncertainties.Journal of Environmental Management,49:53～72
Hoogenboom G.2000.Contribution of agrometeorology to the simulation of crop production and its applications.Agricultural and Forest Meteorology,103:137～157
Howden M,Jones R N.2004.Risk assessment of climate change impacts on Australia’s wheatindustry.New Directions for a Diverse Planet:Proceedings of the 4th International Crop Science Congres Brisbane http://www.cropscience.org.au/icsc2004/symposia/6/2/1848
Howden S M,O’Leary G J.1997.Evaluating options to reduce greenhouse gas emissions from an Australian temperate wheat cropping system.Environmental Modelling and Software,12:169～176
Humphreys E,Lewin L G,Khan S,Beecher H,Lacy J,Thompson J, Batten G,Brown a, Russell C,Christen E.2006.Integration of approaches to increasing water use efficiency in rice-based systems in southeast Australia.Field Crops Research,97:19～33
Hunsaker D J. 1999. Basel crop coefficients and water use for early maturity cotton. Trans of the ASAE, 42(4):927-936
Ines A V M,Honda K,Das Gupta A,Droogers P,Clemente R S.2006.Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture.Agricultural Water Managemant,83:221～232
Ines A V M,Honda K.2005.On quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms:A numerical study for mixed-pixel environment.Advances in Water Resources,28:856～870
IPCC,2001a.Climate change 2001:The Scientific Basis.In:Houghton J T,Ding Y,Griggs D J,Noguer M,van der Linden P J,Dai X,Maskell K,Johnson C A.IPCC Third Assessment Report:Climate Change 2001.Cambridge University Press:Cambridge,UK:21～98
IPCC,2007.Summary for Policymakers.In:Parry M L,Canziani O F,Palutikof J P,van der Linden P J,Hanson C E.Climate Change 2007:Impacts,Adaptation and Vulnerability.Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press,Cambridge,UK:7～22
IPCC.2007a.Climate Change 2007: Impacts, Adaptation and Vulnerability. In:Parry M L,Canziani O F,Palutikof J P,van der Linden P J,Hanson C E.Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press:Cambridge,UK:1～976
IPCC.2007b.Climate models and their evaluation.In:Solomon S,Qin D,Manning M,Chen Z, Marquis M,Averyt K B,Tignor M,Miller H L.Climate Change 2007:The Physical Science Basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press:Cambridge,United Kingdom and New York,USA:1～142
Irrigation insights No. 5.2005.Water use efficiency, an information package.National program for sustainable irrigation edited by Anne Currey
Ismail S M,Ozawa K,Khondaker N A.2008.Influence of single and multiple water application timings on yield and water use efficiency in tomato(var. First power).Agricultural Water Management,95:116～122
Ismail S M,Ozawa K.2007.Improvement of crop yield,soil moisture distribution and water use efficiency in sandy soils by clay application.Applied Clay Science,37:81～89 http://www.iwmi.cgiar.org/Research_Impacts /Research _Themes/ Theme_1/index.aspx
Kumar M,Raghuwanshi N S, Singh R, et al. 2002Estimating evapotranspiration using artificial neural network.Journal of Irrigation and Drainage Engineering, ,128(4):224-233.
Ministry of Water Resources and Electric Power,P.R.C. Irrigation and Drainage in China.beijing: China Water Resources and Electric Power Press: 19～25
Penman H. L.1948.Natural evaporation from open water, bare soil and grass .Proceedings of the Royal Society of London Ser, 3: 120-146 .
Sammis T W, Mapel C L, Lugg D G. 1985. Evapotranspriation crop coefficients predicted using growing-degree–days. Trans of the ASAE, 28(3):773-780
Slack D C, Martin A E, Sheta F A.1996.Crop coefficients normalized for variability with growing-degree–days. In ASAE Proc. Int. conf. on Evapotranspriation and Irrigation Scheduling: 892-898
Smith M. 1991.Report on the expert consultation on revision of FAO methodologies for crop water requirements .Land and Water Development Division FAO Rome,54
Steel D D, sajid A H, Pruuty L D .New corn Evapotranspriation crop curves foe southeast North Dakota .Trans of the ASAE, 39(3):931-936
Stegman E C. Corn crop curve comparison for the central and Northern Plains of the U. S. Applied Engineering in Agriculture, 4(3):226-233
Wright J L, Jensen M E. Development and evaluation of evapotranspriation models for irrigation scheduling. Trans of the ASAE, 21(1):88-96
蔡明科,魏晓妹,粟晓琳. 2007.宝鸡峡灌区耗水量变化规律及影响因素分析研究.水土保持研究
陈博,欧阳竹. 2010.基于BP神经网络的冬小麦耗水预测.农业工程学报, 24(4):81-86
陈玉明,郭国双,王广兴.1995.中国主要作物需水量与灌溉.北京:水利水电出版社
邓聚龙. 1986.灰色系统基本方法.武汉.华中理工大学出版社
邓聚龙. 2002.灰模拟与灰预测.武汉:华中科技大学出版社
樊军,邵明安,土全九. 2008.黄土地参考作物蒸散量多种计算方法的比较研究.农业工程学报,24(3):98-99.
高峰,赵竞成,许建中.2004.灌溉水利川系数测定方法研究.灌溉排水学报,23 (1):14-20
葛哲学,孙志强.2008.神经旺络理论与MATLAB 2007实现.北京:电子工业出版字: 108-117.
郭小玲.2007.作物需水量预测模型研究及其在灌溉管理信息系统中的应用[硕士学位论文].武汉:华中科技大学
泾惠渠志编写组.1991.泾惠渠志.陕西:三秦出版社
康绍忠,蔡焕杰.1996.农业水管理学.北京:中国农业出版社
康绍忠,粟晓玲,杜太生.2009.西北旱区流域尺度水资源转化规律及其其节水调控模式.北京:中国水利水电出版社:398-400
李卫东.2008.应用多元统计分析.北京:北京大学出版社
李英能.2003.浅论灌区灌溉水利川系数.中国农村水利水电,(7):23-26
刘昌明,陈志恺. 2001.中国水资源现状评价和供水发展趋势分析.北京:中国水利水电出版社
刘坤,郑旭荣,谢云.2005.玛纳斯河流域农业节水潜力分析.石河子大学学报(自然科学版),23(2):237- 239
刘钰,蔡甲冰,徐迪.2002.作物蒸发量的实时预报和田间验证,(6):25-63
刘战.2009.灌溉水利用系数的影响因素及提高措施.陕西水利, (04):108-156
卢嘉锡,1996.中国科学技术史.水利卷.北京:中国科学出版社:27-34
吕廷波,佟玲.2010.基于首尾测定法的石羊河流域灌溉水利用率估算及分析.石河子大学学报(自然科学版).28(2):231-236
茆智,李远华.2002.实时灌溉预报.中国工程科学,4(5):24-36
茆智.2009.灌溉用水有效利用系数测算分析有助于进一步明确农业节水的主攻方向.中国水利,(3) :5~6
山仑,康绍忠,吴普特.2004.中国农业节水.北京:中国农业出版社:34-36
陕西省水利水土保持厅,1991.陕西省作物需水量及分区灌溉模式:71-73
邵新星. 2009.浅谈灌溉水利用系数测定中存在问题及影响因素.陕西水利,(04):96-128
沈小谊,黄永茂,沈逸轩.2003.灌区水资源利用系数研究.中国农村水利水电. (01):78-121
沈逸轩,黄永茂,沈小谊,朱世静.2005.年灌溉水利用系数的研究.中国农村水利水电,(07) :45-67
施彦,韩力群,廉小亲.2009.神经网络计算方法与实例分析.北京:北京邮电大学出版社
石玉林,卢良恕.2001.中国农业需水与节水高效农业建设.北京:中国水利水电出版社:122～130
史晓楠,王全九,王新.2006.参考作物腾发量计算方法在新疆地区的适用性研究.农业工程学报,22(6):19-22.
孙国斌,王密侠,尚虎军.2008.陕西省灌溉水利用系数测算软件的开发与应用[硕士学位论文].灌溉排水学报.28(1):128-130
孙景生,刘祖贵,张寄阳.2002.风沙区参考作物蒸发蒸腾量的计算.灌溉排水学,21(2):17-20
孙景生.2004.时间序列法在参考作物腾发量分析与模拟中的应.北京:中国农村水利水电,(8):34-42
谭芳,崔远来,王建漳.2009.灌溉水利用率影响因素的主成分分析—以漳河灌区为例.中国农村水利水电,(2):70-73
汪富贵.2001.灌区灌溉水利用系数的分析方法.节水灌溉,(6):25-26.
王洪斌,闻绍珂,郭清.2008.灌溉水利用系数传统测定方法的修正.东北水利水电, (04):86-90
王仰仁,李明思,康绍忠.2003.立体种植条件下作物需水规律研究.水利学报.,(7):90-95
网伦平,陈亚新等.2001.内蒙古河套灌区灌溉排水与盐碱化防治.北京:水利水电出版社.
徐俊增,彭世彰,张瑞美. 2006.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.水利学报,37(3) 376-379
许建中.赵竞成,高峰.2005.灌溉水利用系数综合测定法实例分析.(1):55-58.
严雷,赵晓波. 2009 .峡口灌区灌溉水利用系数测算.节水灌溉,(06):48-54
姚付启,张振华,钱为君. 2008.烟台果园土壤温度影响因素及其预测模型研究.农业系统科学与综合研究,22(2):201-204
张大海,江世芳,史开泉.2008.灰色预测公式的理论缺陷及改进.系统工程理论与实践,(8):140-124
张代远. 2006.神经网络新理论与方法.北京:清华大学出版社
张德丰. 2009.MATLAB神经网络仿真与应用.北京:电子工业出版社:79-83
张东,张贤瑞.玛水军.2009.等天津市现状灌溉水利用率测算研究.节水灌溉, (2):42-44
张芳,李水鑫,张玉顺.2008.河南省现状灌溉水利用率的测算研究.人民黄河,30(1): 5l-54
张涛,张成利,李楠楠.2006.灌溉水利用系数的传统测定方法存在的问题及影响因素分析.地下水,(03) :49-87
张涛,张成利,李楠楠. 2006.灌溉水利用系数的传统测定方法存在的问题及影响因素分析.地下水,28 (3):81- 82
张亚平.2007.陕西省现状灌溉水利用率测算方法与问题讨论.水资源与水工程程学报,16 (3):60- 62
张勇刚,卫星.2009.灌区提高灌溉水利用系数的措施.黑龙江水利科技,( 3):76-89
赵璐,蔡焕杰,王建. 2010.ET0的主因子和主成分神经网络模型比较.节水灌溉,(3)23-25
赵旭,李毅,刘俊明.2009.新疆地区参考作物蒸发蒸腾量的灰色模型预测.农业工程学报, (10):50-53.
Allen R G. 1998.Crop Evapotranspiration Guidelines for Computing Crop WaterRequirements FAO Irrigationand Drainage Paper, 56:18-35
Ayars J E, Hutmacher R B.1994. Crop Coefficients for irrigating cotton in the presence of groundwater . Irrigation Science, 15(1):45~52
Cabelguenne,M DebaekeP,H.Puech J.1997.Real time irrigation management using the EPIC-PHASE model and weather forecasts ,32:227~238
Cowing J.2001.Real-time scheduling of supplemental irrigation for potatoes using a decisionmodel and short-term weather forecasts, 47:137~153
Doorenbos J, Pruitt W O.1977.Crop Water requirements. Irriagtion and Drain Paper No. 24.Rome, Italy: Food and Agric. Organization of the United Nations
FAO.1977.Irrigation and Drainage Papers 24.Crop Water Requirements.Rome
Feddes R A. 1978. Simulation of Field water use and crop yield. Center for Agric. Publishing and Documentation, Wageninge
Frere M, Popov G F. 1979. Agrometeorological crop monitoring and forecasting. Rome: FAO, Plant Production and Protection Paper, No.17
Godwin D,Meyer W S,Xevi E,White R G J.2006.SWAGMAN? Destiny:A simulation model of irrigated crops as affected by irrigation practice,water tables and salinity.1.Model description.Unpublished,Griffith:CSIRO Land and Water:1～20
Govindarajan S,Ambujam N K,Karunakaran K.2008.Estimation of paddy water productivity(WP) using hydrological model:an experimental study.Paddy Water Environment,6:327～339
Groves D,Lempert R.2007.A new analytic method for finding policy-relevant scenarios.Global Environmental Change,17:73～85
Guo S,Wang J,Xiong L,Ying A,Li D.2002.A macro-scale and semi-distributed monthly water balance model to predict climate change impacts in China.Journal of Hydrology,268:1～15
Hall W A.1960.Performance parameters of irrigation systems.Transactions of the ASAE,3(1):75～76
Hansen V E.1960.New concepts in irrigation efficiency.Transactions of the ASAE,55～64
Harle K J,Howden S M,Hunt L P.2007.The potential impact of climate change on the Australian wool industry by 2030.Agricultural Systems,93:61～89
Hart W E,Reynolds W N.1965.Analytical design of sprinkler systems.Transactions of the ASAE,8:83～85,89
Hennessy K B,Fitzharris B C,Bates N,Harvey S M,Howden L,Hughes J,Salinger, Warrick R.2007. Australia and New Zealand. In Climate Change 2007:Impacts,Adaptation and Vulnerability. In: Parry M L,Canziani O F,Palutikof J P,van der Linden P J, Hanson C E,Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change,Cambridge University Press,Cambridge,UK:507～540
Hennessy K,Ian Macadam,Whetton P.2006.Climate change scenarios for initial assessment of risk in accordance with risk management guidance.Canberra:Australian Greenhouse Office:1～36
Herrera-Pantoja M,Hiscock K M.2008.The effects of climate change on potential groundwater recharge in Great Britain.Hydrological Processes,22:73～86
Herron N,Davis R,Jones R.2002.The effects of large～scale afforestation and climate change on water allocation in the Macquarie River catchment,NSW,Australia.Journal of Environmental Management,65(4):369～381
Hobbs B F.1997.Bayesian Methods for Analysing Climate Change and Water Resource Uncertainties.Journal of Environmental Management,49:53～72
Hoogenboom G.2000.Contribution of agrometeorology to the simulation of crop production and its applications.Agricultural and Forest Meteorology,103:137～157
Howden M,Jones R N.2004.Risk assessment of climate change impacts on Australia’s wheatindustry.New Directions for a Diverse Planet:Proceedings of the 4th International Crop Science Congres Brisbane http://www.cropscience.org.au/icsc2004/symposia/6/2/1848
Howden S M,O’Leary G J.1997.Evaluating options to reduce greenhouse gas emissions from an Australian temperate wheat cropping system.Environmental Modelling and Software,12:169～176
Humphreys E,Lewin L G,Khan S,Beecher H,Lacy J,Thompson J, Batten G,Brown a, Russell C,Christen E.2006.Integration of approaches to increasing water use efficiency in rice-based systems in southeast Australia.Field Crops Research,97:19～33
Hunsaker D J. 1999. Basel crop coefficients and water use for early maturity cotton. Trans of the ASAE, 42(4):927-936
Ines A V M,Honda K,Das Gupta A,Droogers P,Clemente R S.2006.Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture.Agricultural Water Managemant,83:221～232
Ines A V M,Honda K.2005.On quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms:A numerical study for mixed-pixel environment.Advances in Water Resources,28:856～870
IPCC,2001a.Climate change 2001:The Scientific Basis.In:Houghton J T,Ding Y,Griggs D J,Noguer M,van der Linden P J,Dai X,Maskell K,Johnson C A.IPCC Third Assessment Report:Climate Change 2001.Cambridge University Press:Cambridge,UK:21～98
IPCC,2007.Summary for Policymakers.In:Parry M L,Canziani O F,Palutikof J P,van der Linden P J,Hanson C E.Climate Change 2007:Impacts,Adaptation and Vulnerability.Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press,Cambridge,UK:7～22
IPCC.2007a.Climate Change 2007: Impacts, Adaptation and Vulnerability. In:Parry M L,Canziani O F,Palutikof J P,van der Linden P J,Hanson C E.Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press:Cambridge,UK:1～976
IPCC.2007b.Climate models and their evaluation.In:Solomon S,Qin D,Manning M,Chen Z, Marquis M,Averyt K B,Tignor M,Miller H L.Climate Change 2007:The Physical Science Basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press:Cambridge,United Kingdom and New York,USA:1～142
Irrigation insights No. 5.2005.Water use efficiency, an information package.National program for sustainable irrigation edited by Anne Currey
Ismail S M,Ozawa K,Khondaker N A.2008.Influence of single and multiple water application timings on yield and water use efficiency in tomato(var. First power).Agricultural Water Management,95:116～122
Ismail S M,Ozawa K.2007.Improvement of crop yield,soil moisture distribution and water use efficiency in sandy soils by clay application.Applied Clay Science,37:81～89 http://www.iwmi.cgiar.org/Research_Impacts /Research _Themes/ Theme_1/index.aspx
Kumar M,Raghuwanshi N S, Singh R, et al. 2002Estimating evapotranspiration using artificial neural network.Journal of Irrigation and Drainage Engineering, ,128(4):224-233.
Ministry of Water Resources and Electric Power,P.R.C. Irrigation and Drainage in China.beijing: China Water Resources and Electric Power Press: 19～25
Penman H. L.1948.Natural evaporation from open water, bare soil and grass .Proceedings of the Royal Society of London Ser, 3: 120-146 .
Sammis T W, Mapel C L, Lugg D G. 1985. Evapotranspriation crop coefficients predicted using growing-degree–days. Trans of the ASAE, 28(3):773-780
Slack D C, Martin A E, Sheta F A.1996.Crop coefficients normalized for variability with growing-degree–days. In ASAE Proc. Int. conf. on Evapotranspriation and Irrigation Scheduling: 892-898
Smith M. 1991.Report on the expert consultation on revision of FAO methodologies for crop water requirements .Land and Water Development Division FAO Rome,54
Steel D D, sajid A H, Pruuty L D .New corn Evapotranspriation crop curves foe southeast North Dakota .Trans of the ASAE, 39(3):931-936
Stegman E C. Corn crop curve comparison for the central and Northern Plains of the U. S. Applied Engineering in Agriculture, 4(3):226-233
Wright J L, Jensen M E. Development and evaluation of evapotranspriation models for irrigation scheduling. Trans of the ASAE, 21(1):88-96