Modlfow的输入输出文件

本文主要是以modflow2005,且以安徽利辛区的文件为案例。

输入文件

NAM 文件(.nam)

这是一个总文件,其中写着该案例里面都包含哪些文件;
文件的后缀是.nam; 下面是一个详细的示例

LIST   53 '.\modflow_in\2018_2019_anhui.LST'
PCG    19 '.\modflow_in\han.pcg
BAS6  10 '.\modflow_in\2018_2019_anhui.BAS'
BCF6  11 '.\modflow_in\2018_2019_anhui.BCF'
RCH  18 '.\modflow_in\2018_2019_anhui.RCH'
OC  22 '.\modflow_in\2018_2019_anhui.OC'
CHD  30 '.\modflow_in\2006_2021_anhui.CHD'
DIS  34 '.\modflow_in\2018_2019_anhui.DIS'
DATA(BINARY) 150 '.\modflow_out\2018_2019_anhui.HDS'
DATA(BINARY) 151 '.\modflow_out\2018_2019_anhui.DDN'
DATA(BINARY) 154 '.\modflow_out\2018_2019_anhui.BGT'
DATA(BINARY) 152 '.\modflow_out\2018_2019_anhui.sig'
DATA(BINARY) 153 '.\modflow_out\2018_2019_anhui.HVT'

示例中的文件路径是采用相对路径,在viusal modflow2011中生成的是绝对路径,两者都可以,其实就是给fortran程序读,想一想只要fortran能读就行。

list文件

List文件是日志文件,记录着程序运行的过程和一些重要的输入输出变量。

BAS文件

模型的基础文件,由于模型的网格已经画好(Rows=”272” Layers=”2” Columns=”94”),所以会以数组的形式,指定每个cell是否激活,以及每个cell的高程,初始水头等。
第一个出现的数组是“Bnd for La 1yer”,是表示每个cell是激活状态,还是处于无效区。本案例中,每行94个值,出现272次;
layer1结束后是layer2

第二个出现的数组是初始水头“Starting Head for Layer 1”,数组的格式和出现顺序与上面是一样的。先layer1,后是layer2

PCG-求解器文件

modflow中有各种各样的方程求解,PCG求解时,需要输入相应的参数。
当不采用PCG求解器时,本文件也可以用其他文件代替,如Strongly Implicit Procedure Package Input(.sip)。

        MXITER ITER1 NPCOND
       hclose rclose        relax    nbpol     iprpcg   mutpcg      damp

        25        10         1
     .0010     1.e-2       1.0         0        10         1         1.

BCF6

Input for the Block-Centered Flow (BCF) Package

第1行

IBCFCB HDRY IWDFLG WETFCT IWETIT IHDWET
154 -1.00e+30 0 1.00e+00 1 0 0
IBCFCB 是fortran程序中的unit号,大于0时是将各cell的水平衡文件写入到该文件中,=0时代表不输出该项
HDRY cell没地下水的时候,水头变为多少,一般是-1.e30
IWDFLG 决定程序中是否启用wetting capability, =0是不采用
WETFCT 一个系数,用于cell从干变湿时计算初始水头
IWETIT 循环间隔,对于外部循环而言
IHDWET 计算cell从干变湿时计算初始水头-采用的方式;=0是5-32a,else 是5-32b

第2行

Ltype(NLAY)
3 3
第二行,模型有几层就有几个数,每个数是contains a combined code for each layer that specifies both the layer type (LAYCON) and the method of computing interblock conductance。
confined/unconfined—Transmissivity of the layer varies and is calculated from the saturated thickness and hydraulic conductivity. The storage coefficient may alternate between confined and unconfined values. Vertical flow from above is limited if the aquifer desaturates。

第3行

感觉是各项异性和各项同性的参数,每层一个数,并不是每一个cell赋值。
1.0代表是各向同性。不等于0时是K_COL/k_ROW

其余部分

之后是按照数组的形式,对每一个cell的以下变量赋值:

(1)primary storage coefficient;感觉是压力储存系数,案例中是6.e-5

(2)Conductivity

X -L0(本案例是0.5,每行第一个值是8.64的意思没看懂,转换单位?);
Vcont-L0 (is the vertical hydraulic conductivity divided by the thickness from a layer to the layer below (also called leakance);

(3) 然后是layer0的第2 storage,一般是给水度

     0     5.e-2 (10G11.4)                  -1 storage 2 Layer - 0

(4) 然后是Layer1的storage1(primary storage coefficient);X-方向传导度和给水度

     0        5. (10G11.4)                  -1 X-Conductivity Layer - 1
     0     1.e-1 (10G11.4)                  -1 storage 2 Layer - 1

RCH补给文件

该文件是地下水的补给文件,一般都会指定补给的位置和补给的大小,本案例中由于是和HYDRUS联合调用,已经在modflow程序中直接赋值;
同样处理的还有RIV输入文件.
NRCHOP 是补给的位置:1是最高那一层;3是水位所在那层;2是指定的层;
IRCHCB 是是一个选项和文件号:>0时会输出各river cell的水量平衡;=0时不输出;

     3       154  (NRCHOP  IRCHCB)
    18
     0        0. (15G11.4)                  -1 Recharge Period - 1
    18
     0        0. (15G11.4)                  -1 Recharge Period - 2
    18

默认的文件是指让每个应力期的各个cell补给均为0。

RIV 文件

modflow中的河流模块输入;
第一行MXACTR是229是指RIV的cell个数;IRIVCB是一个选项和文件号:>0时会输出各river cell的水量平衡;=0时不输出;

第二行开始为每个应力期的循环。229仍是个数;
之后每行数字是:

   layer      Row      Col  Stage     Cond    River_bot_z

   MXACTR-229       IRIVCB-154
   229
     1         3        14 2.70186e1 4.82407e2 2.51676e1
     1         2        14 2.70186e1 2.34609e2 2.51676e1
     1         6        15 2.70186e1 2.97759e2 2.51676e1
     1         5        15 2.70186e1  7.0974e2 2.51676e1
     1         4        15 2.70186e1  7.0974e2 2.51676e1
     1         8        16 2.70186e1  7.0974e2 2.51676e1
     1         7        16 2.70186e1  7.0974e2 2.51676e1
     1         6        16 2.70186e1 4.11981e2 2.51676e1
     1        11        17 2.70186e1 6.38204e2 2.51676e1
     1        10        17 2.70186e1  7.0974e2 2.51676e1
     1         9        17 2.70186e1 5.96629e2 2.51676e1
     1        14        18 2.70186e1 4.53556e2 2.51676e1
     1        13        18 2.70186e1  7.0974e2 2.51676e1
     .......

OC文件(output control)

数字形式

    IHEDFM    IDDNFM   IHENUN   IDDNUN
    然后是每个应力期循环
    INCODE   IHDDFL    IBUDFL   ICBCFL
    HDPR      DDPR      HDSV     DDSV
    然后是下个应力期循环....

     0         0       150       151
     0         1         1         1
     0         0         1         1
     0         1         1         1
     0         0         1         1
     0         1         1         1
     0         0         1         1
     0         1         1         1
     0         0         1         1
     0         1         1         1
     0         0         1         1

IHEDFM是输出水头的格式:IDDNFM是输出降深的格式;IHENUN和IDDNUN分别是输出水头和降深的文件号;
INCODE下一行将要读入文件的处理方式:<0和生一个应力期一样,下一行不用读;=0所有层一个处理方法;>0每层结果单独控制。
IHDDFL对于降深输出的控制变量:=0,不输出降深,不是0,看下一行的设置输出;
IBUDFL对于水均衡输出的控制变量:=0,不输出,不是0,看下一行的设置输出;
ICBCFL对于水均衡输出的控制变量:=0,不输出,不是0,看下一行的设置输出;

HDPR 水头的输出设置变量:=0时head is not printed for the corresponding layer;不为0时head is printed for the corresponding layer。
DDPR,HDSV,DDSV与HDPR类似

文字形式

# OC package for  MODFLOW-2005, generated by Flopy.
HEAD PRINT FORMAT   0
HEAD SAVE UNIT    51
DRAWDOWN PRINT FORMAT   0
DRAWDOWN SAVE UNIT    52
COMPACT BUDGET AUX

period 1 step 1 
  save head
  save drawdown
  save budget
  print head
  print budget

period 2 step 1 
  save head
  save drawdown
  save budget
  print head
  print budget

period 3 step 1 
  save head
  save drawdown
  save budget
  print head
  print budget

period 4 step 1 
  save head
  save drawdown
  save budget
  print head
  print budget

文字形式的输出格式通俗易懂,直接是按照应力期和时间步输入对应的文字。

CHD文件-水头文件

对于定水头或者变水头边界,需要将每个应力期的哪些cell水头已知,且开始和结束时的水头给出。

       204
       204
         2       256        16    25.351    25.260
         2       255        16    25.351    25.260
         2       255        17    25.351    25.260
         2       255        18    25.351    25.260
         2       254        18    25.351    25.260
         2       254        19    25.351    25.260
         2       253        19    25.351    25.260
         2       253        20    25.351    25.260
         2       252        20    25.351    25.260
         2       252        21    25.351    25.260
         2       252        22    25.351    25.260
         2       251        22    25.351    25.260
         2       251        23    25.351    25.260

DIS离散文件

模型的离散信息,前两行是注释
“#Discretization Package translator - (c) 2011 Schlumberger Water Services”
“#2018_2019_ANHUI.DIS Thu Nov 18 19:17:17 2021”

第三行: NLAY NROW NCOL NPER ITMUNI LENUNI
2 272 94 36500 4 2

ITMUNI是时间单位,0-未定义;1-秒;2-分;3-小时;4-天;5-年; LENUNI是长度单位:0-未定义;1-英尺;2-米;3-厘米;

第四行:LAYCBD,每层一个值;1代表是含水层底部有a Quasi-3D confining bed below it,0 代表没有,对于最下层肯定是没有。

第5行开始是空间离散,首先是一个数组DELR,数组大小等于COL数,每一个值代表第几列的宽度;第一行是 数字格式

下一个部分是每一行cell的长度DELC,其余类似。

下一个部分是地表高程,也是第一层(从上往下)含水层的上表面高程,一般都是地表高程;

下一个部分是模型的底部表面高程,或者bottom elevation of a model layer or a Quasi-3d confining bed。

最后一个部分是每个应力期内部的时间离散信息;

        PERLEN    NSTP    TSMULT  SS/tR
        1.         1        1.     TR
        1.         1        1.     TR
        1.         1        1.     TR
        1.         1        1.     TR
        1.         1        1.     TR
        1.         1        1.     TR
        

PERLEN是应力期长度;NSTP是该应力期分为几个step;TSMULT一个时间步长控制参数;SS/tR是代表该应力是瞬态还是稳态。


输出文件

HDS文件-水头的二进制文件

用flopy的工具包打开

DDN文件-降深的二进制文件

BGT文件-水量平衡文件

HVT文件-本次没用到

测试一下插入本地图片

图片名-测试图片

添加本地路径的时候,图片放在和日志同名的文件夹里,在路径中只用写照片的名字“moon.jpg”

如果图片显示出来,说明成功了

今天是孙,崔,邓三位师兄师姐预答辩。一些想法,还是很有用,分别记录如下
1 摘要第一段要对前人工作的总结,要写出不足待研究的地方。
2 论文进行研究的必要性,重要性,是什么科学问题,每一章之间的关联性。成果有什么用,对生产实际和科学贡献分别是什么,突出清晰。
3 科研术语要规范,不能自己创造词语
4 定性描述的术语,一般要给出一个定量的标准,多大是强,多大是弱
5 关于尺度的问题,一般给出尺度的定义,以及用来描述该尺度的指标
6 均衡模型一定要交代时间尺度,涉及到平均的问题
7 得出的结论与现有结论以及实际情况的对比
8 论文的主线一定要清晰,要给别人展现出你到底想解决什么问题,从一个中心,一条主线来回答你要解决的问题
9 改进的部分,细节部分要讲清楚。最好出现方法和路线,体现其合理性。
10 自己要解决的问题,不解决的话会在现实中带来什么问题,研究的必要性与重要性。该问题在科学上为啥没被解决。
11 方法要尽可能新方法,问题也要是未解决的比较难的问题。
12 影响因素要刨根问底
13 人所共知的事情不能用于自己的结论之中

后面又停了胡老师和史老师学生的答辩,根据评委讲的内容,可以总结如下几点:
1 国内外研究现状不能写得太散,要综合一下
2 技术路线是否是唯一、最优以及最先进
3 创新点的表述
(新现象,新规律,方法,理论,弄清了什么机理,开发了什么新技术,工艺等)
4 选择研究的对象是内容是客观存在的
5 指标要尽可能统一,方便比较
6 研究背景讲PPT要言简意赅
7 效率或者好处的提升的机理什么?为什么会提高,原因要解释清楚
8 通过数据的反映出来是模型结构的哪个方面不对
9 别人的东西与自己的规律要分开讲清楚。
10 实验结果的横向分析
11 不用太多展示有多好,要讲是好在什么原因。

开发日志

时间顺序

2020.8.26

重新安装VS2017+IVF2019

2020.8.27 开始写框架,水力传导度等参数

2020.8.28~2020.8.29

半隐式差分的格式一致也没弄出来。

2020.8.30

早上开始在弄边界,不知道为啥,一类的边界还是不收敛。中午去吃饭的时候整个人还是晕乎乎的。朱老师带着娃在车上叫我也没听见
下午最后也是没解决这个问题,但是参考了一下崔师姐和朱老师文章的差分格式。

2020.8.31

早上和崔师姐聊了一下。看她是怎么处理边界的。后面建议我不要重写,多参考hydrus1d的格式。以及一些处理的小技巧。
一维边界基本上是没问题了

2020.9.1

解决了2类边界的问题。变量名字打错了,是个大问题。晚上的时候准备编根系吸水的模型

2020.9.2

本来准备验证3类边界的。步子太大扯着淡。下午现在终于算是搞定了2+1类边界的处理。根系吸水目前还是没有试。
感觉Tp的处理还是很重要的。

Article

An Experimental Study on Concrete and Geomembrane Lining Effects on Canal Seepage in Arid Agricultural Areas

Xudong Han 1, Xiugui Wang 1,*, Yan Zhu 1, Jiesheng Huang 1, Liqing Yang 2, Zhifu Chang 2 and Feng Fu 2
1 State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei 430072, China; hanxudong@whu.edu.cn (X.H.); zyan0701@163.com (Y.Z.); sdjshuang@whu.edu.cn (J.H.)
2 Management Department of Yichang Irrigation Subdistrict, Hetao Irrigation District Management Bureau of Inner Mongolia, Bayannur, Inner Mongolia 015100, China; ylq13847801648@163.com (L.Y.);
czf13294782585@163.com (Z.C.); fufengwy@163.com (F.F.)
Correspondence: wangxg@whu.edu.cn; Tel.: +86-15337236043
Received: 11 July 2020; Accepted: 18 August 2020; Published: date
Abstract: Canal lining is commonly used to reduce seepage loss and increase water use efficiency. However, few studies have quantitatively estimated the seepage control effects of different lining materials under different service times. Ponding tests were conducted on the same canal section with four different lining statuses to investigate the canal lining effect on seepage control and its impact factors in arid areas. The cracks and holes in different lining materials were surveyed, and the canal seepage rates under the four test treatments were calculated by monitoring the water level change in the canal. The results show that the cracks in the joints of the two precast concrete slabs and holes in the geomembrane, which are located 0.25 m above the canal bottom on two sides of the canal, are responsible for the increased seepage loss. The new concrete and geomembrane lining combination reduces seepage by 86% compared with no lining, while seepage can be reduced by 68% using the concrete and geomembrane lining combination after three service years, and the amount decreases to 11% by using geomembrane lining with a three year service time. Based on the experiment and literature, a statistical relationship between the seepage reduction and lining service time was established, which provided a possible and easy way to estimate seepage losses from lined canals and improve the estimation accuracy using an empirical formula. Without considering the service time lining effect, the seepage loss is underestimated by 58%, and the canal water use efficiency is overestimated.
Keywords: Canal seepage; ponding test; canal lining; seepage losses; water conveyance efficiency

1. Introduction

In the past several decades, it has been a great challenge to maintain the sustainable use of water resources, especially in arid and semi-arid regions, due to increasing irrigation demands and climate change [1–3]. Since agricultural irrigation consumes the largest amount of water resources in some countries [4–8], decreasing agricultural water use becomes one of the most promising water-saving methods, in which the most important technology involves increasing water use efficiency [9]. A large amount of seepage loss is the main factor contributing to low water use efficiency when water is conveyed to fields by an irrigation system [10]. These seepage losses not only reduce the water efficiency of the canal system but also increase the groundwater table [11] and reduce water availability for domestic use downstream [12], leading to soil salinization and waterlogging [13].
There are many factors influencing canal seepage loss, including the canal cross-section profile, canal lining conditions, canal bed soil type, and groundwater table depth near the canal [6,14–16]. Canal lining is commonly used to reduce seepage loss, which has been proven to significantly increase the water conveyance efficiency [17]. However, canal linings are expensive and lose their efficacy gradually with service time. Significant seepage loss starts to occur from a lined canal after deterioration, especially with poor maintenance [18–20]. Thus, it is necessary to investigate the lining effect on controlling seepage loss to accurately estimate the agricultural water use efficiency and proper management of irrigation systems, effective irrigation plans, and irrigation project construction [21].
Many materials, such as geomembrane, bitumen, masonry, and concrete, have been reported in the literature to reduce seepage loss in canal lining [22–24]. Concrete and geomembrane are commonly used in most countries and are two kinds of main canal lining materials in China [25]. In Pakistan, test results have showed that the seepage losses through unlined canals were reduced 75% and 97% soon after construction by concrete and geomembrane, respectively [26]. In China, seepage loss can be reduced by 52-55%, according to the ponding test results on two canals before and after being lined with concrete for one year [27]. Additionally, the canal seepage loss reduced by geomembrane lining was 96.33% in the main and branch canals and 76% in lateral canals [28]. According to the results of an inflow–outflow test conducted in Ethiopia, seepage losses from primary canals were reduced by 45.3% by the geomembrane lining [29]. In recent years, to further reduce canal seepage and prevent lining frost damage, two or more kinds of lining materials have been combined [30]. It was found that the canal seepage loss was decreased by 91% and 25% compared with using concrete or geomembrane alone [28]. Tiwari concluded that clay, concrete, and geomembrane reduced seepage losses by 60%, 95%, and 30%, respectively [31]. The geomembrane combined with lime or clay could reduce seepage by 75%. The abovementioned tests were carried out on lined canals with very short service times, e.g., one year after construction [27], soon after construction [26], and other studies did not point to the specific time after construction of the lining [28,29,31]. These studies indicated the seepage effect of the newly built lining but cannot represent the variation in the lining efficacy on controlling seepage loss during a long service time period. The effect of a single lining in concrete with a geomembrane lining is not explicit.
It is commonly found that the lining effect of seepage control varies with the maintenance condition and service time of the canal [20,32,33]. Many studies have reported that the permeability of lining material changes obviously with increasing service time due to aging of the lining materials [32], poor operation and maintenance [26,29], damage by plant roots or animals [34–36], and damage from frost heaving [37]. The lining performance of canals decreases with an increase in the rate of cracking in the concrete lining or holes in the geomembrane lining [38]. Holes in the geomembrane lining and concrete lining cracking are common phenomena after construction, especially in seasonally frozen ground regions [37,39]. In Kansas, US, a 60 m long canal lined with geomembrane was found to have approximately 200 holes after ten years following construction in May 1992. Moreover, at least 40 additional holes were observed in October 1995 [39]. Rowe et al. evaluated the performance of a high-density polyethylene (HDPE) geomembrane after 14 years as a leachate lagoon liner [40]. They observed that seven holes and 21 cracks were on the slopes and found that the permeability coefficients were between four and five times higher than the values obtained for unaged HDPE geomembranes. The geomembrane liner most likely stopped being effective as a contaminant barrier for ionic species sometime between 0–4 years after installation, which was consistent with their discussion with the operators. Cracks are also commonly observed in concrete linings after construction [38,41]. The field investigation showed that the concrete lining in many canals was severely cracked after 8-9 years of construction, and minor cracking was observed in some other canals in the Khoozestan Province of Iran [42]. Swihart and Haynes reported that concrete lining started to develop cracks because of shrinkage during curing within the first couple of years and often continued to crack over time because of subgrade movement [41].
The abovementioned and other studies only mentioned the cracks and holes that occurred after the construction of the lining. However, only a few studies have focused on a quantitative description of the relationship between the quantity of cracks and holes and service time. Even fewer studies have investigated the change in the permeability of lining material with time and its relationship with the change in cracks or holes in the lining materials, which is important for quantitatively estimating the seepage control effect of lining canals under different service times. According to World Bank experts, canal lining with a 1% crack area has a seepage rate of 70% of that for unlined conditions [43]. Merkley also showed that if only 0.01% of the concrete canal lining is cracked, seepage in the lined and unlined canals is the same (i.e., no effect of the lining) [24]. Research has shown that there would be no difference in seepage losses between lined and unlined canals with the expansion of cracks on the canal surface [44].
The increase in the permeability of lining materials with time results in an increase in seepage loss, which obviously decreases the water efficiency of the canal [35,45]. Some researchers have concluded that the age or service time of the lining played an undeniable role in increasing the seepage losses [14,32]. The inflow–outflow method was used to measure the seepage loss under two canal sections with different service times in the Indus Basin of Pakistan, which showed that the lined canal under service times of 1–5 years reduced seepage by 47%, while it decreased to 30% under service times of 21–25 years compared with unlined canals [46]. The ponding tests were implemented in 103 canal sections to measure the seepage control effect under different service times of between 1–15 years [47]. However, few studies have estimated the explicit relationship between the seepage control effect of lining and service time. The studies were also carried out under different canal sections, in which the soil types of the canal bed and the nearby soil water characteristics were different. The difficulties in ensuring the same background condition in field experiments makes it difficult to find a benchmark for accurately estimating the relationship between the seepage control effect of the lining canal and the service time, which also makes it inaccurate to estimate seepage losses from lined canals using empirical equations [33].
The Hetao Irrigation District (HID) is in arid and semi-arid northern China with an irrigation area of 5.7 million ha. The irrigation water is mainly diverted from the Yellow River, which is approximately 4.7 billion m3 per year, accounting for 8% of the Yellow River runoff [48]. The irrigation water for HID from the Yellow River should be decreased to 4.0 billion m3 every year, as planned by the Chinese government [49]. The irrigation water use efficiency should be increased to 0.55 by 2030 to satisfy the requirement of agricultural development [50]. Canal lining is widely used in HID to increase the water efficiency of canal systems. From 1998 to the end of 2017, 1316 km of the main canals were lined, accounting for 20.8% of the total length. Single types of lining materials, including concrete with geomembrane, were frequently installed before the 2010s. A decrease in the seepage control of the lining canal has been found for long-term main, branch, lateral, and sub-lateral canals lined with concrete or concrete with geomembrane, which greatly decreases the water conveyance efficiency [51]. In recent years, a combination of different lining materials has been used to decrease seepage loss and prevent lining frost heave damage in HID [52]. Therefore, it is necessary to investigate whether the combination of different lining materials can guarantee the long-term durability of canal systems in this area.
This study investigated the seepage control effect change in the lining canal with service time and its relationship with the distribution of cracks and holes in lining materials. Four ponding tests were conducted on the same canal section with two kinds of different lining materials and a combination, and two service times, including no lining, a combination of new concrete and geomembrane lining, a combination of concrete and geomembrane lining with a service time of three years, and a geomembrane lining with a service time of three years. The cracks and holes in different lining materials were surveyed, and the canal seepage rates under the four test treatments were calculated. The attribution of cracks in the concrete and holes in the geomembrane to increase seepage loss were distinguished. Furthermore, the seepage control reduction factor with the service time was estimated by a simple linear formula, which can then be used to help calculate the water efficiency of the lined canal system after a specified service time.

2. Materials and Methods

2.1. Study Area

Field experiments were carried out at the Yonglian Experimental Station, which is located in the Renmin branch canal irrigation district (41°0′52.17″ N–41°8′4.98″ N, 107°59′8.62″ E–108°1′48.79″ E and altitude of 1028 m above sea level). The Renmin branch canal irrigation district is a part of the HID, as shown in Figure 1a. The climate in the area is arid continental, with average annual precipitation from 130 mm to 215 mm and average annual evaporation from water surface from 2100 mm to 2300 mm [53]. The freezing and thawing period lasts from late November to the middle of May, during which the maximum frozen depth is 1.0-1.2 m. The Renmin branch canal irrigation district is 12 km long from north to south and 3 km wide from east to west, with 29.75 km2 of farmland. The ground surface elevation decreases from 1028.9 m to 1025.4 m from southwest to northeast. The irrigation water is derived from the Yellow River by the Zaohuo trunk canal, delivered to the Renmin branch canal, and then distributed by its 25 lateral canals and 346 sub-lateral canals to fields. In April 2018, a field survey was conducted to determine the lining materials of each lateral and sub-lateral canal in the Renmin branch canal irrigation district. The locations and lining conditions of the lateral canals are shown in Figure 1a. The canal section of the Renmin canal, most of the lateral canals, and sub-lateral canals are trapezoidal. The main lining materials are concrete and geomembrane. The Renmin branch is approximately 12 km, which was lined with concrete and geomembrane in 2014-2016. The laterals were lined with the concrete from 2000 to 2015. The total length of lateral canals with linings is approximately 21.11 km, which accounts for 74% of the total length in the Renmin branch-controlled area. For sub-lateral canals, only the test canal was lined with concrete and geomembrane composite lining in 2015, and others are all unlined. The transformation of canals in the canal lining has been conducted in the study area to increase the water use efficiency.
The working regime of the canals in the area is as follows: the Renmin canal is continuously delivering water, and the lateral canals and sub-lateral canals are rotationally delivering water. The irrigation durations of canals in the same rotational group canal are equal. The gross discharge of the Renmin branch canal was approximately 1.0 m3/s according to the measurement. The field water efficiency is approximately 0.81 [54].
The ponding test was carried out on a sub-lateral canal of 30 m in length, the location of which is shown in Figure 1a. The average bottom width of the canal is 0.60 m, the vertical depth is 0.55 m and the top width is 1.84 m. The canal was lined by a combination of concrete and geomembrane in September 2015. The embankments on both sides of the canal were 1.5 m in width. The precast concrete panels were 0.6 m in length, 0.4 m in width, and 0.06 m in thickness, and the thickness of the polyethylene geomembrane was 0.3 mm. There was an approximately 3 cm sand layer between the precast concrete slabs and the polyethylene geomembrane. The joint between the precast concrete slabs was filled with concrete mortar.
The hourly precipitation and evaporation data were obtained from the automatic weather station installed 200 m away from the canal. There was no precipitation during the four ponding tests. Evaporation rates during the tests of four treatments were 5.47, 3.2, 2.6, and 2.0 mm/d, respectively.

Figure 1. The study area location and detail information about ponding test. (a) The geographic location of the Renmin irrigation area. (b) Sketch of the experimental design. (c) Sketch and section of the ponding test canal. Note: D1 is the joints in the bottom of canal; “W1” and “W2” are the joints perpendicular to the direction of the canal in the upper and lower left side of the canal; “E1” and “E2” are the joints perpendicular to the direction of the canal in the upper and lower right side of the canal ; “W3” and “E3” are the joints parallel to the direction of the canal in the left and right sides of the canal; ”Tw” is the top width of canal; ”Bw” is the bottom width of canal; ”Wd” is the water depth in canal.

2.2. Ponding Test

The ponding test was conducted according to the technical code for seepage control engineering on canals [55]. At each end of the 30 m experiment canal, two dikes were constructed with concrete and geomembrane, and the distance between the two dikes was approximately 1.5 m to form a water buffer to prevent water leakage from both ends. The ponding tests were carried out under four treatments according to the lining material of the canal, as listed in Table 1.

Table 1. Arrangement of four ponding treatments

Treatment Lining Material Canal Bottom Width (m) Slope Water Depth (m) Test Time
T1 Old concrete and Old geomembrane 0.58 1:1.13 0.40 22 September 2018 14:00-27 September 2018 14:00
T2 Old geomembrane 0.58 1:1.60 0.30 29 September 2018 11:00-1 October 2018 23:00
T3 No lining 0.58 1:1.60 0.30 3 October 2018 9:00-4 October 2018 23:00
T4 New concrete and New geomembrane 0.59 1:1.19 0.36 12 October 2018 9:00-18 October 2018 9:00

The first treatment was the combination of concrete and geomembrane lining with a service time of three years (marked as T1), which was based on the current lining condition of the canal. The second treatment was the geomembrane lining with a service time of three years (marked as T2), which was based on removing the precast concrete slabs when the ponding test of the T1 treatment was finished. The third treatment involved no lining (marked as T3) by removing the geomembrane when the ponding test of the T2 treatment was finished. After the ponding test of the T3 treatment, the canal was repaired and lined with a combination of new precast concrete slabs and new geomembrane, which was the fourth treatment, marked as T4. Before the experiment of each treatment, 10 sections of the canal were chosen to measure the canal section parameters, including the canal bottom width, slope, and water depth. The average section parameters of the four treatments are shown in Table 1.
Each ponding test was composed of a constant water level stage and a variable water level stage. During the constant water level stage, the water level variation was controlled within 5 mm, which means that additional water should be replenished to the canal before the water depth dropped by 5 mm. The change in water depth and duration time were recorded, which can be used to calculate the seepage rate. The constant water level stage was continued until the canal seepage rates of more than ten records remained stable, which means that the difference in the maximum and minimum seepage rates of the last records is smaller than 10% of the average seepage rate of the last ten records. Then, the variable water level stage started. The water depth dropped without replenishing the water. The water level was recorded automatically every 5 min by a water level gauge. The water depths in the four treatments were set as 0.4, 0.3, 0.3, and 0.36 m, as shown in Table 1.

2.3. Lining Damage Survey

To determine the detailed reasons for the decrease in the seepage control effect of the lining material over time, the status of the joint mortar between the precast concrete slabs and the distribution of holes on the geomembrane were investigated and classified before the T1 treatment. When investigating the joint status, the location of joints was considered. As shown in Figure 1c, there are 7 kinds of joints distinguished by their locations, which are the joints in the bottom of the canal (marked as D1), joints perpendicular to the direction of the canal in the upper and lower left side of the canal (marked as W1 and W2), joints perpendicular to the direction of the canal in the upper and lower right side of the canal (marked as E1 and E2), and joints parallel to the direction of the canal in the left and right sides of the canal (marked as W3 and E3). The joint status was classified into three groups according to the type of filling material, marked as Groups A, B, and C, which are filled by mortar, earth, or no filling material, respectively. Group A can be further divided into three classes, marked as A1, A2, and A3; A1 indicates that the mortar was in good condition without any damage, A2 indicates that there were small holes or cracks in the mortar, and A3 indicates that the mortar was damaged by through cracks. Group B was also divided into two classes, marked as B1 and B2; the joint was fully filled by earth in B1, while the joint was partially filled with earth in B2. Furthermore, the position and diameter of holes, along with the location, length, and width of cracks on the geomembrane, were measured to evaluate the damage status of the geomembrane.

2.4. Calculation of Ponding Test Results

There are usually two indicators calculated by the ponding test to represent the seepage loss of the canal, e.g., seepage loss per unit length of the canal (named the seepage rate) and seepage loss per unit wet area (named the seepage intensity), which can be calculated as follows:
(1)
(2)
where S is the canal seepage rate per unit length of the canal (m3/(m·h); ∆V is the change in stored water per unit length in the test section (m3/m); ∆t is the length of observation duration (h); E is the evaporation rate per unit length of the canal (m3/(m·h); P is the precipitation per unit length of the canal (m3/(m·h); Qs is the infiltration intensity (m3/(m2·h)); and χ is the wetted perimeter of the canal section (m).
The reduction factor of the canal lining was used to describe the lining effect, which can be calculated as follows [56]:
(3)
where β is the reduction factor of the lining; Sl is the seepage rate per unit length of the canal after lining (m3/(m·h); and Ss is the seepage rate per unit length of the canal before lining (m3/(m·h)).
The contribution of the concrete or geomembrane in the composite lining was calculated as follows to indicate the effect of the single material in the composite lining.
(4)
(5)
where Cg is the contribution of geomembrane to the reduction in seepage; Cc is the contribution of concrete to the reduction in seepage; ΔSg is the seepage reduced by the geomembrane lining alone (m3/(m·h); and ΔSc is the seepage reduced by the concrete lining alone (m3/(m h)).
The ∆Sg and ∆Sc are calculated by Equations. (6)–(7) as follows:
(6)
(7)
where Ss is the seepage rate per unit length of canal before lining (m3/(m·h)); Sg is the seepage rate per unit length of canal lined by geomembrane (m3/(m·h)); βg is the reduction factor of geomembrane lining alone time; Sc is the seepage rate per unit length of canal lined by concrete (m3/(m·h)); βc is the reduction factor of concrete lining alone.
The βc is calculated by a multiplicative model according to literature [56] as Equation (8), and βg and βcg are calculated as Equations (9) and (10) as follows:
(8)
(9)
(10)
where βcg is the reduction factor of geomembrane and concrete combined lining; and Socg is the seepage rate per unit length of canal lined by concrete and geomembrane (m3/(m·h)). Ss, Sg and Socg are obtained from the ponding test results.

2.5. Fitting of the Seepage Rate and Seepage Intensity

To study the seepage rate variation with time during the stable water level stage of the four treatments, the modified Kostiakov model [57] was used to fit the relationship between the cumulative infiltration water and time during the four treatments. The modified Kostiakov model is outlined as follows:
(11)
where CI is the cumulative infiltration at time t (m3/m); t is the infiltration time (h); ic is the infiltration rate at the steady state condition (m3/(m·h)); and k and A are empirical constants, which can be obtained from curve fitting.
The relationship between seepage intensity and infiltration time was fitted by Equation (12). The fitted results a and b were used to calculate the seepage loss of other canals in the study area.
(12)
where Qs is the seepage rate at unit area (m3/(m2·h)); h is the water depth in the canal (m); and a and b are empirical constants obtained from the experimental results by curve fitting.

2.6. Calculation of the Water Efficiency of the Canal System

The water efficiency of the canal system can be calculated by the following formula:
(13)
(14)
where ηs is the water conveyance efficiency of the canal system; Iout is the water taken from the sub-lateral canals to the field (m3); Iin is the total amount of water intake from the canal system (m3); Ssum is the total seepage water loss from the canal system (m3); E is water loss due to evaporation from the canals in the study area (m3); and Wother is the water loss due to other reasons (m3), such as overtopping the bunds, bund breakage and runoff in the drain.
Because canal seepage and evaporation loss are the main sources of water loss during water conveyance [19], and evaporation loss only accounts for a small amount of the total loss from the canal [58], E and Wother in Equation (14) are ignored, and Equations (13) and (14) is simplified as Equation (15)
(15)
The total seepage water from the canal system can be calculated by summing the seepage water from a single canal as follows:
(16)
where Sepi is the total seepage water from canal i (m3), which is calculated by Equation (15):
(17)
where Sepi is the total seepage water from canal i (m3); Δt is the irrigation duration of the canal (h); and Sepij is the seepage rate of segment j in canal i (m3/h).
(18)
where Qsj is the seepage rate per unit wet area (m3/(m2·h)) of segment j, which is calculated by Equation (10); χj is the wetted perimeter of the canal section in segment j (m); γj is the reduction factor of the groundwater table depth in segment j, which is determined by the groundwater table depth and canal flow [56]; ΔLj is the canal length of segment j; and βj is the reduction factor of the canal lining in segment j. It should be noted that the effect of the service time of the canal lining on β was considered in this study.

3. Results and Discussion

3.1. Damage Characteristics of Canal Lining

The damage statuses of all joints among the precast concrete slabs in the 30 m experiment canal are listed in Table 2.

Table 2. The statistics of crack in concrete lining in different location.

Location D1 W1 W2 W3 E1 E2 E3 Sum Percentage(%)
A1 60 27 32 2 19 31 14 125 44.33
A2 0 14 7 13 21 14 11 80 28.37
A3 0 3 4 8 2 1 5 23 8.16
B1 0 1 4 6 1 0 5 17 6.03
B2 0 0 1 11 2 0 7 21 7.45
C 0 3 0 7 3 0 3 16 5.67
Sum 60 48 48 47 48 46 45 282 100
Note: D1 is the joints in the bottom of canal; “W1” and “W2” are the joints perpendicular to the direction of the canal in the upper and lower left side of the canal; “E1” and “E2” are the joints perpendicular to the direction of the canal in the upper and lower right side of the canal ; “W3” and “E3” are the joints parallel to the direction of the canal in the left and right sides of the canal. D1, W1, W2, W3, E1, E2 and E3 are plotted in Figure 1c. A1 indicates that the mortar was in good condition without any damage. A2 indicates that there were small holes or cracks in the mortar, while A3 indicates that the mortar was damaged by perfoliate cracks. B1 indicates that the mortar was joint was fully filled by earth. B2 indicates that the mortar was joint was partly filled by earth. C indicates that joints do not have any filling material.

The total number of the joints in test canal was 282, which is equal to 940 per 100 m of canal. More than half of the joints on the two sides of the canal were damaged after three years. The damage statuses of A1 and A2 accounted for 44% and 28%, respectively. The remaining damage statuses from A3 to C accounted for 28%, which means that the damage of most joints was serious. More serious damage were found in the joints that were parallel to the canal direction (W3 and E3) compared with those perpendicular to the canal direction (W1, W2, E1 and E2), which may be caused by the frost heaving force since this area undergoes half of a year’s seasonal freezing–thawing period [59]. The maximum frozen depth is deeper than 1.0 m in this area [60]. The tensile stress generated by frost heaving is smaller than the maximum allowable tensile stress of the concrete because of the small size of the slab, but the shear stress is equal to or larger than the allowable shear stress of the filling material [61]. Thus, the joints occurred prior to being damaged by the frost heaving force, which can release the tensile stress of the frost heaving and decrease the damage to the concrete slabs. This may result in major damage to mortar joints in this area. Figure 2 shows the sketch of mechanical failure of the concrete slab joints. The maximum bending moment caused by the frost heaving force occurred at a height of 1/3 from the bottom to the top bank of the canal [52], which resulted in more serious damage to the W3 and E3 locations than the W1, W2, E1, and E2 locations. No damage was found on the joints between the precast concrete slabs at the bottom of the canal, as shown in Table 2. Although these joints encountered the frost heaving force, they were covered by silty soil, and there was a sand layer between the concrete slabs and geomembrane, which can relieve the damage of the frost heaving force. This finding is consistent with investigation results of other researchers [61].

Figure 2. The sketch of mechanical failure of the concrete slabs joints. (a) The sketch of initial concrete lining structure. (b) The sketch of concrete lining damage.
There were 42 and 83 holes observed in the geomembranes of the west and east banks, respectively. The number and cumulative frequency of holes with different diameters on the geomembrane located on the west and east sides of the canal are shown in Figure 3.

Figure 3. The number of holes with different diameters in the geomembrane and their cumulative frequency.
The holes with diameters smaller than or equal to 10 mm accounted for more than 78%, the numbers of which on the left and right sides of the canal accounted for 86% and 64%, respectively. These holes were mainly caused by weed roots. In addition, 15 holes with diameters larger than 25 mm accounted for 12%, which was caused by the wooden wedge used to keep the geomembrane in place when it was installed. The distribution of hole numbers in the west and east banks at different heights is shown in Figure 4a and Figure 4b. The distribution was fitted by the normal distribution, which is basically consistent with the statistical value distribution. The cumulative frequency of holes located at different vertical positions from the bottom of the canal on the geomembrane is shown in Figure 4c.
Figure 4. The number and cumulative frequency of holes in the geomembrane at different heights from the bottom of the canal. (a) The frequency number of holes in the geomembrane in west side of canal at different heights from the bottom of the canal. (b) The frequency number of holes in the geomembrane in east side of canal at different heights from the bottom of the canal. (c) Cumulative frequency of holes in the geomembrane at different heights from the bottom of the canal.
Since the hydrothermal conditions were almost the same for the two sides of the canal, the difference in the distribution of holes caused by weed root growth was very small. Therefore, the holes in the geomembrane of the canal sides were the same, and both obey a normal distribution. Most holes occurred within a height above the bottom of the canal of 14–34 cm, which was consistent with the distribution of weed roots on both sides of the canal. Weeds grew on those damaged joints on both sides of the canal and along the canal bank, which was the major cause of geomembrane damage. During the growing period, the weed roots grow through the lining and cause damage. Then, the damage left the holes, which made the water seep through the lining. This causes more serious damage the following year in terms of frost heaving. Similar results were found by Kraatz and Zhang Haiyan et al. [14,62]. This indicated that the weed grown at the bank and bottom of the canal should be removed in a timely manner to keep damage at bay.

3.2. Infiltration During the Stable Water Level Stage

The cumulative infiltration and its fitting equation by the modified Kostiakov model (see Equation (11)) during the stable water level stage during the four treatments are shown in Figure 5.
Obvious differences can be found in the infiltration time and cumulative infiltration at the end of the stable water level stage. It was approximately 17.74 h before the T1 treatment became stable, while it was 9.90, 4.61, and 7.00 h for the T2, T3, and T4 treatments, respectively; the corresponding maximum cumulative infiltration water was 0.673, 0.205, 0.088, and 0.300 m3/m, respectively, which may be caused by the difference in the initial soil moisture. The drier soil has a larger infiltration capacity [16,63]. As a result, the T1 treatment had the largest maximum cumulative infiltration due to having the smallest soil moisture. The seepage rate was relatively large initially and gradually decreased to its stable seepage rate, as shown in Figure 5. This is a common infiltration process due to the increasing dominance of gravity-driven flow over capillarity-driven flow with increased penetration depth [16,64]. The steady seepage rates (ic) in the T1, T2, T3, and T4 treatments were 0.022, 0.016, 0.019, and 0.004 m3/(h·m), respectively. It can be found that ic in T4 was the minimum in terms of the best seepage control effect, which shows that canal seepage was obviously reduced by the newly installed composite lining. The canal water depths of the T2 treatment and T3 treatment were similar (see Table 1), but the ic in the T2 treatment was 16% smaller than that in the T3 treatment, which suggested that the geomembrane with three years of service time had little seepage control effect. The ic of T1 is more than T2, which is due to the higher water depth (0.4 m) as shown in the Table 1, and the incomplete geomembrane lining that the canal section above 0.25 m height from canal bottom were not totally covered by geomembrane lining for the reason of construction.

Figure 5. The cumulative infiltration and seepage rate per meter of canal for the four treatments: (a) T1; (b) T2; (c) T3; and (d) T4. Note: The canal lining of T1, T2, T3, and T4 treatment was geomembrane and concrete with a three year service time, geomembrane with a three year service time, no lining, and new precast concrete slabs and new geomembrane.

3.3. The Seepage Rate Under the Variable Water Depth Stage and the Seepage Control Effect Under Different Canal Lining Treatments

The seepage rate under the variable water depth stage was calculated according to Equation (1), as shown in Figure 6.

Figure 6. The canal seepage rate of four treatments. Note: The canal lining of T1, T2, T3, T4 treatment is geomembrane and concrete with a three year service time, geomembrane with a three year service time, no lining and new precast concrete slabs and new geomembrane.
The reduction factor β under different canal lining treatments when the water depth was 25 cm was calculated by Equation (3), as listed in Table 3.

Table 3. The seepage rate reduced and reduction factor of each lining.
| Lining material | New concrete and New geomembrane | Concrete and geomembrane (both 3years) | Concrete (3years) | Geomembrane (3years) | No lining |
|——————————–|———————————-|—————————————–|——————-|———————-|————|
| Seepage rate (L/(h·m)) | 1.942 | 4.632 | 6.241* | 13.051 | 14.660 |
| Reduced seepage rate (L/(h·m)) | 12.718 | 10.028 | 8.419* | 1.609 | 0.000 |
| Reduction factor | 0.132 | 0.316 | 0.35* | 0.890 | 1.000 |

The result of concrete is estimated from seepage difference of T1 and T2 treatments.
It was found that there was little difference between the seepage rate in T1 treatment and T2 treatment at all canal water depths from Figure 6. Additionally the lining reduction factor of the T2 treatment when the water depth was 25 cm was 0.89, which means that the geomembrane lining can reduce seepage loss by 11% after three years of service compared with the unlined canal. The result was similar to the research [29,31], in which the seepage loss reduced by the geomembrane used was smaller than 30-35% and 45.3%, respectively. However, this value was obviously smaller than those obtained by testing the new geomembrane lining [28,36,65], which is approximately 90%, showing that the holes and cracks in the geomembrane can significantly decrease the seepage control effect, and their impacts should not be ignored.
As plotted in Figure 6, a larger seepage rate occurred in both of T2 treatment and T3 treatment than in the T1 treatments at different water depths. Table 3 also shows the seepage rate reduced and reduction factor of each lining condition when the water depth was 25 cm. The reduction factor β in the T1 treatment was 0.32, which means that the combination of concrete and geomembrane lining with a service time of three years can still reduce seepage loss by 68% compared with the unlined T3 treatment. The seepage control effect was significantly improved when using geomembrane and concrete together, as the T2 treatment only reduced seepage loss by 11%, which coincides with the conclusion by Akkuzu et al. [30] that the seepage control effect was obviously improved when geomembrane and concrete were used together. The possible reason is that the geomembrane was pressed by the concrete to be closely pressed to the soil, which increased the seepage path after the water passed through the holes or cracks along the contact surface of the geomembrane. The geomembrane also blocked cracks in some concrete slabs and lengthened the seepage path to decrease seepage losses.
From the comparison of the result of T1 treatment and T4 treatment in Figure 6 and Table 3, it can be seen that the absolute seepage loss from combined lining increased by 128% due to the lining damages (e.g., holes and cracks) after three years as discussed in Section 3.1, although 68% seepage loss still can be reduced by the concrete and geomembrane lining after three years. However, the lining efficacy difference between T1 and T4 treatment is not very large, because most joints in concrete lining are not totally cracked (See Table 1), although the geomembrane with a three year service time has been close to non-functional.
Since the ponding test was not conducted on the canal lined only with precast concrete slabs with a service time of three years (marked as OC), the reduction factor β of OC with a 25 cm water depth was obtained by comprehensively considering the seepage rate reduced by the T1 treatment and T2 treatment. The calculated reduction factor β of OC was 0.35, which showed that the precast concrete slab lining after three years of use can also reduce seepage loss by 65% compared with the unlined treatment. This value is close to 50–75% according to other researchers [12,26,27]. The experimental results of the present study show that the effect of the precast concrete slab lining was better than that of geomembrane lining under the same service time, although aged and cracked concrete lining are generally considered to decrease in terms of impermeability [24,44,66].
To distinguish the contributions of geomembrane and precast concrete slab linings on the seepage control effect in the composite lining, the contribution of each was calculated according to Equations (4)–(10), as shown in Figure 7.

Figure 7. The contribution of concrete and geomembrane with a three year service time in the composite lining.
Because the geomembrane damage was heavier than that of the concrete, the contribution of the concrete lining in combined lining was generally more than geomembrane lining. When the water depth in the canal increased from 5 cm to 25 cm, the contribution of concrete increased from 70% to 90%, but the contribution of geomembrane decreased from 30% to 10%. The main seepage paths of the canal were cracks in the joints between precast concrete slabs and holes in the geomembrane. The crack size in the joint basically increased linearly with height away from the bottom of the canal, while the number of holes in the geomembrane increased with height from the bottom of the canal in a non-linear manner. The holes on the geomembrane below 24 cm from the bottom of the canal account for 71% of the total (Figure 4c). Therefore, the seepage control contribution of concrete in the composite lining increased with the water depth of the canal, while the geomembrane decreased.
3.4. Relationship between the Seepage Control Effect of the Combination of Concrete and Geomembrane Lining and the Service Time
The lining reduction factors of the combination of concrete and geomembrane lining under different service times collected from different studies are listed in Table 4. Two of them, representing service times of 0 years (T4 treatment) and three years (T1 treatment), were obtained by ponding tests in this study, and others were obtained from the literature. The reduction factor of the newly constructed lining with the concrete and geomembrane ranged from 0.03-0.15, as listed in Table 4. After two years, the reduction factor became 0.29, and the values ranged from 0.32–0.34 after three years. After 10 years, the reduction factor became 1.0, which shows that the canal lining lost its function [66]. The relationship between the seepage control effect of the combination of concrete and geomembrane lining and the service time is shown in Figure 8.

Figure 8. The relationship between the lining seepage reduction factor (β) and service time (t). Note: reduction factor (β) is the proportion of seepage rate of a canal with lining to that without lining. A bigger reduction factor (β) means more seepage rate from a lined canal.
A linear fitting line was used to quantify the relationship between the reduction factor of the combination of concrete and geomembrane lining and its service time; see Equation (19):
(19)
where β is the reduction factor; Y is the service time (year); and β0 and β1 are the regression parameters, in which β0 is the reduction factor of the lining at Y = 0, and β1 is the decrease rate in the reduction factor per year (1/year). According to the data in Table 4, β0 and β1 were 0.08 and 0.09, respectively. The fitting curve agreed well with the data, the R2 of which was 0.99, as shown in Figure 8. This equation provides a possible and easy way to estimate the seepage loss of lined canals for a given year.
Table 4. Statistical results of lining reduction factor in China from literatures.
Service Time Reduction Factor Literature Test Place Remark
0 0.14 This paper Inner Mongolia Built in 2018, tested in 2018
3 0.32 Inner Mongolia Built in 2018, tested in 2018
0 0.1-0.15 Literature [67] Shaanxi
0 0.05 Literature [68] Shaanxi
10 1.0 Literature [66] Inner Mongolia Lined after 2002, tested in 2012
10 1.0
0 0.08 Literature [69] Shandong Built in 2018, tested in 2018
0 0.03 Literature [28] Ningxia
4 0.46 Literature [70] Inner Mongolia Built in 2014, tested in 2018
2 0.29 Built in 2016, tested in 2018
3 0.34 Built in 2015, tested in 2018
5 0.5 Literature [47] Zhejiang

3.5. Estimation of the Water Efficiency of the Canal System in the Renmin Canal Irrigation Area Under Different Scenarios

To evaluate the water efficiency of the canal system in different transformation schemes, two scenarios were assumed as follows: (1) the lining status of all canals in the study area remained status quo (current status scenario); (2) all canals were relined by a new composite lining of concrete and geomembrane in 2018 (relined scenario). Assume that the initial year in the two scenarios was 2018. The water efficiency of the canal system, the seepage loss from the canal during autumn irrigation, and their variation trend between 2018 and 2030 were calculated.

3.5.1. Comparison of both Methods to Calculate the Reduction Factor of the Canal Lining

According to the method suggested by Ministry of Water Resources of China (MWRC) [65], the reduction factor of canal lining β in Equation (18) is not changed with its service time. It is found that β declines with service time, as shown in Equation (19). To compare the differences between the two methods, the seepage loss, water efficiencies of different levels of canals and water efficiency of the whole canal system in the Renmin canal irrigation area during autumn irrigation in the current scenario are listed in Table 5.
Table 5. Result of canal seepage loss and water efficiency of canal system.
Methods Reduction Factor is not Changed with Service Time Reduction Factor Declines with Service Time Seepage Loss Error
Canal Gross Water (103 m3) Seepage Loss (103 m3) ηs or η Gross Water (103 m3) Seepage Loss (103 m3) ηs or η Absolute Error (103 m3) Relative Error
Sub-lateral canals 3874.99 105.11 0.973 3876.20 106.32 0.970 −1.21 −1%
Lateral canals 3884.78 9.79 0.997 3937.35 61.15 0.984 −51.36 −84%
Branch canal 3918.72 33.94 0.991 4088.71 151.36 0.963 −117.42 −78%
Canal system 3918.72 148.84 0.962 4088.71 318.83 0.922 −169.99 −53%
Note: ηs is water conveyance efficiency of canal system; η is water conveyance efficiency of canal
The calculated water efficiency of the canal system when using Equation (19) to calculate the reduction factor was 0.922 with a gross irrigation water of the Renmin branch canal of 4.09 million m3, and the total seepage loss from the canals was 318.83 thousand m3. The seepage loss water from the sub-lateral canals, lateral canals, and branch canal was 106.32, 61.15, and 151.36 thousand m3, respectively. The water efficiency of the canal system when not considering the impact of service time on the reduction factor was 0.962, with a total canal seepage loss of 148.84 thousand m3. The seepage loss water from the sub-lateral canals, lateral canals, and branch canal was 105.11, 9.79, and 33.93 thousand m3, respectively. According to the observation results of the Renmin canal flow, the total irrigation water from the Renmin canal was approximately 4,043,520 m3. Considering the error taken from ignoring evaporation and other losses, the estimated result 4.09 million m3 when considering the service time is closer to the observed value of 4,043,520 m3 during autumn irrigation. The seepage loss relative error of the canal system, branch canal, lateral canals, and sub-lateral estimation without considering the lining effect variation with time were −53%, −78%, −84%, and −1%, respectively, which shows that the temporal variation in the lining effect can not be ignored in the estimation of canal seepage loss. The results without consideration of the lining effect variation is similar to results of previous studies [33,35], in which there are big error in the seepage loss estimation result from lined canal by empirical equation (Moritz equation, Davis–Wilson equation) [14,30]. The proposed relationship between reduction factors is not only suitable in present study, but also can be adopted in existed empirical equations to improve the estimation accuracy.

3.5.2. Estimation of the Water Efficiency of the Canal System in the Renmin Canal Irrigation Area

The total seepage loss of the canal system and water conveyance efficiency results calculated under two scenarios by using Equation (19) to calculate the reduction factor is shown in Figure 9.

Figure 9. Estimation of seepage loss from canals and water conveyance efficiencies of the canal system (ηs) in the reline scenario and current scenario in 2018-2030.
The seepage loss of the canal system in the relining scenario in the study area was 64,727 m3 smaller than 318,834 m3 in the current scenario in the first year. The water efficiency of the canal system increased from 0.922 in the current scenario to 0.983 in the relined scenario. This shows that the lining obviously reduces the seepage loss. However, as the newly built lining lacks sufficient maintenance and proper management with increasing service time, the seepage loss under the two scenarios increases, and the water efficiency of the canal system decreases until the lining loses its seepage control function. The average annual increase in seepage and the decrease in the water efficiency of the canal system in the two scenarios were 66,808 m3 and 0.013 and 76,446 m3 and 0.017, respectively.
After 10.2 years, the lining lost all of its anti-seepage function, and the reduction factor became 1.0. The seepage loss from the canal system was 871,745 m3, and the water efficiency of the canal system was 0.81, which is close to a similar irrigation system under high-level management in Portugal [71] and the ηs of irrigation system without lining in Pakistan, which is 0.56-0.82, when only the seepage losses is considered [14]. Due to the calculation, the other water loss and the variation of other canal condition (e.g., canal bed roughness etc.) except the seepage loss were ignored and the inflow was considered as a constant value, which means a high management level, the 0.81 is higher than the existing ordinary irrigation system. Compared to the current condition, if the canal lining is properly managed and repaired, the aging damage rate of the lining will be delayed, and the good seepage control function of the lining will be maintained. This means that parameter β1 in formula (19) is lowered, and the service life of the canal is increased and more water can be saved in the whole service time of lining.

4. Conclusions

This study investigated the relationship between the seepage control effect change in the canal lining and service time by ponding tests. The cracks and holes in different lining materials were surveyed, and the attributions of the cracks in concrete and holes in the geomembrane to increase seepage loss were analyzed. A simple linear formula was established to represent the relationship between the seepage control reduction factor and the service time, which was used to estimate the water efficiency of the lined canal system after a certain service time. The main conclusions are as follows:
(1) The cracks in the mortar joints between the precast concrete slabs caused by frost heaving and holes on the geomembrane caused by grass roots contribute to an increase in the seepage loss of the lined canal.
(2) The seepage control effect of the composite lining is better than that of the separate lining because the concrete precast slabs and geomembrane were used together to compensate for each other’s partial defects to enhance the function of the lining for each other.
(3) The lining effect decreases with service time, which is caused by the increase in cracks at the joint between the precast concretes and holes in the geomembrane. In the study area, the reduction factors of the composite lining in the current year and after three years were 0.14 and 0.32, respectively.
(4) Based on the test results and existing literature, the relationship between the reduction factor β and service time Y of the composite lining can be expressed as β = 0.09Y + 0.08. It was expected that the seepage control effect of the newly constructed lining would lose its function completely after 10.2 years. If the canal has proper management and maintenance, the service time of canal can be prolonged and more water can be saved by decreasing the canal seepage losses.
(5) The current method suggested by MWRC (2018) produces great error in the estimation of canal seepage because neglecting the lining function decreases with time. A case study showed that the relative error is approximately 53% and that the water conveyance efficiencies of the canal system in the current scenario and relined scenario were 0.922 and 0.983, respectively.
(6) Limitation: More tests should be conducted for the perfection of parameter β1 in different areas.

Author Contributions: Conceptualization, X.W. and J.H.; methodology, X.W. and J.H.; software, X.H.; validation, X.H., X.W., and Y.Z.; formal analysis, X.H.; investigation, X.W., L.Y., Z.C., and F.F.; resources, X.W.; data curation, X.H.; writing—original draft preparation, X.H.; writing—review and editing, Y.Z. and X.W.; visualization, X.H. and Y.Z.; supervision, X.W.; project administration, X.W.; funding acquisition, X.W. and Y.Z.; data collection L.Y., Z.C., and F.F. All authors have read and agreed to the published version of the manuscript.
Funding: This research was supported by the National Key Research and Development Program for the 13th Five-year Plan (grant number 2016YFC0400203) and Natural Science Foundation of China (grant numbers 51790533 and 51779178).
Acknowledgments: We thank Yiyi Deng and Liping Sun for their assistance in the experiment.
Conflicts of Interest: The authors declare no conflict of interest

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该软件的创作目的如下:渠系水利用系数是衡量渠系工作状况、渠系管理水平的综合指标。目前对渠系水利用系数的计算大多仍停留在传统的表格手工测算上。

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1 引言

1.1 编写目的

本文档主要对渠系水利用系数2.0版本中相对于1.0版本的改进之处进行说明

1.2 基本说明

在大型的农田灌溉中,常需要用到大量、复杂的渠道进行输配水。在水流的输配过程中,会产生水量损失。渠道的水量损失包括渠道水面蒸发损失、渠床渗漏损失、闸门漏水损失、渠道退水损失等。水面蒸发损失一般不足渗漏损失水量的5%,在渠道流量计算中常忽略不计。闸门漏水和渠道退水主要取决于工程质量及用水管理水平,可以通过加强灌区的管理工作予以限制,在计算渠道流量时不予考虑。因此,通常把渠床渗漏损失水量近似看做渠系的总输水量的损失量水,渗透损失水量和渠床土壤性质、地下水埋藏深度和出流条件、渠道输水时间等因素有关。
渠系水利用系数是指末级固定渠道流入田间实际的水占从总干渠渠首流入渠系的水量比例,该系数是评价渠系工程状况、运行状况和管理水平的一个综合指标。渠系水利用系数的准确测算,不仅是评估渠系工程状况和管理水平的基础,还关系到地区农业用水安全与粮食安全的长远发展。目前,国内外对于渠系水利用系数的研究多倾向于测定方法和计算公式的修正方面,如在分析大型灌区渠系水利用系数时,考虑渠道越级现象、回归水利用、管理水平三方面的影响,定量计算越级修正系数、回归水利用修正系数以及确定管理水平修正系数等,但实现该类研究的主要途径大多仍停留在传统的表格手工测算上。采用传统表格手工测算的缺点主要有:灌区现场实测测算工作量大、耗资庞大;当计算结果不合理或错误时,检查、修改均较繁杂,大多只是重复性工作;手工计算缺少对原始数据的合理性分析。
因此,急需采用计算机技术对渠系水利用系数进行分析测算,以提高渠系水利用系数的测算效率及准确性,对于推求某个地区、某个灌区科学合理的渠系水利用系数,实现数据管理的信息化、标准化,评价、指导节水灌溉的发展,都具有十分重要的实践与理论意义。本软件即为渠系水利用系数的测算软件。
1.0版本很好地解决了续灌时利用现有规范和教材推导计算灌区渠系水利用系数的问题。但是在具体计算的过程中只有考斯加科夫公式,对于渠道渗漏量计算时各灌区之间造成渗漏不同的土质差异,衬砌效果随时间变化的现象,以及渠道轮灌渠道和续灌渠道同时存在时的计算没有考虑。2.0版本重点解决了上述4个问题,提高了渗漏损失计算精度,整个计算过程也更加符合灌区实际。

2详细说明

2.1渠道渗漏计算原理

2.1.1软件1.0版本计算方法

1.0版本中的渠道渗漏计算方法,主要是根据《农田水利学》[1]以及《灌溉排水设计规范》[2]中的计算方法,利用考斯加科夫公式,计算渠道渗漏速率,公式如下:
渠道的渗漏速率根据公式(2.1)推导的来计算:

                     (2.1)

(2.2)

式中:σ是单位渠道流量损失率;是渗漏速率,m³/s;Q1和Q0是渠道的渠首毛流量和渠尾净流量,m³/s参数A和m,根据土壤类型决定,β是渗水量衬砌折减系数,γ是地下水顶托修正系数;L是渠道长度,km;参数A和m。上述参数均根据文献[1,2]中取值,见表2.1、表2.2、表2.3。
具体在计算时采用Q1和Q0的均值代入式(2.1)计算损失率,不断试算得到渠道的毛流量,进而得到渗漏速率。

表2.1渠道土壤参数A和m表

渠床土质 透水性 A值 m值
黏土 0.70 0.30
重壤土 中弱 1.30 0.35
中壤土 1.90 0.40
轻壤土 中强 2.65 0.45
砂壤土及砂质壤土 3.40 0.50

表2.2 地下水顶托系数表(γ)

渠道净流量(m³/s) |地下水埋深(m)|
—|—|—|—|—|—|—|—|—
| |<3 |3| 5| 7.5|10| 15| 20| 25
1| 0.63| 0.79| —| —| —| —| —| —
3| 0.5| 0.63| 0.82| —| —| —| —| —
10| 0.41| 0.5| 0.65| 0.79| 0.91| —| —| —
20| 0.36| 0.45| 0.57| 0.71| 0.82| —| —| —
30| 0.35| 0.42| 0.54| 0.66| 0.77| 0.94| —| —
50| 0.32| 0.37| 0.49| 0.6| 0.69| 0.84| 0.97| —
100|0.28| 0.33| 0.42| 0.52| 0.58| 0.73| 0.84| 0.94

表2.3 衬砌渗水量折减系数(β)

防渗措施 衬砌渠道渗水损失修正系数
渠槽翻松夯实(厚度大于0.5m) 0.30~0.20
渠槽原土夯实(影响深度不小于0.4m) 0.70~0.50
灰土夯实(或三合土夯实) 0.15~0.10
混凝土护面 0.15~0.05
黏土护面 0.40~0.20
浆砌石护面 0.20~0.10
沥青材料护面 0.10~0.05
塑料薄膜 0.10~0.05

2.1.2软件2.0版本计算方法

软件2.0版本中,有两种渗漏计算方法,一是对2.1.1中的计算公式进行积分改进[3,4],另一种是利用渠道的渗漏速率与水深之间的关系进行计算。

2.1.2.1改进积分型计算

式(2.1)中σ是单位渠道流量损失率,同时σ也可以写成式(2.3)
(2.3)
式中:dQ是渠道流量变化量,m³/s;Q是在渠道长度微元dL处的流量,m³/s;dL是微元的长度,km。
联立(2.1)和(2.3)得到
(2.4)
(2.5)

(2.6)
式中:是渗漏速率,m³/s;Q1和Q0是渠道的渠首毛流量和渠尾净流量,m³/s; 参数A、m、β、γ与2.1.1中意义相同;L是渠道长度,km。

2.1.2.2基于分段逐渐计算的方法

渠道的渗漏速率不但是渠道流量的函数,也可以表示为渠道水深的函数。在静水法试验的结果整理以及一般的研究中,常通过渠道的渗漏强度和断面来计算渗漏速率,见式(2.7)。
(2.7)
式中:S是渗漏速率,m³/s;Qs是渠道的渗漏强度,m³/(s·m);χ是渠道的湿周。渗漏强度一般通过式(2.6)进行计算。
(2.8)
式中:Qs是渠道的渗漏强度,L/(h·m2);a和b是拟合数据得到的参数,h为渠道水深,m。新软件中利用该方法进行计算时,需要用户自己定义土壤类型,并输入对应的参数a和b.
考虑到渠道沿程由于流量损失及断面的变化,将整个渠道分段逐段计算其渗漏损失以及渠首或渠尾的流量。渠道的流量,根据式(2.9)计算:
(2.9)
式中:Qi+1和Qi是渠道渠段i进口或出口的流量,L/h;∆S是渠长为的渠段的渗漏强度,L/(h·m2); 是渗漏速率,L/h;
渠道的渗漏速率根据式(2.10)进行计算:
(2.10)
式(2.10)中:是土渠的渗漏强度,根据式(2.11)计算;γ是地下水顶托修正系数,根据地下水埋深和渠道流量决定[1,5]。β是渠道渗漏量衬砌折减系数;是渠道长度,m。从末级渠道的尾部开始分段计算渠道的渗漏速率和渗漏总量,通过分段计算可得到渠首的总流量及放水总量。
(2.11)
式中:Qs是渠道的渗漏强度,L/(h·m2);a和b是拟合数据得到的参数,h为渠道水深,m。
根据公式(2.12)~(2.14)可求解得到各级渠道水深h:
(2.12) (2.13) (2.14)
式中:Q0是渠道流量,m³/s;A是渠道断面面积,m2;C是谢才系数,;R是水力半径,m;j是渠道的纵坡;n是渠道糙率;χ是渠道湿周,m; m为渠道边坡

2.2渗漏计算中渠道衬砌的折减系数

2.0版本相比1.0版本,很重要的一个改进是新版本中考虑到了式(2.1)中,衬砌折减系数β会随时间变化。
老版本中β是一个根据材料类型(见表2.3)确定的一个定值,并且不会随着时间变化。这与现实当中衬砌材料的效果逐渐变差不相符合,因此新版本中,采用式(2.15)计算
(2.15)
式中:Y是衬砌服役时间,年;α是每年衬砌折减系数增加的值;其中是衬砌建设当年(Y=0时)折减系数。这两个参数由用户自己输入,当β大于1.0时取1.0。

2.3渗漏计算中土壤渗漏量自定义参数

软件2.0版本相比1.0版本的另一改进之处是,可以添加自定义的土壤参数,以及渠道衬砌参数。

2.3.1土壤类型参数

无论是采用考斯加科夫公式或者还是利用渗漏强度公式计算,均需要有土壤类型及其对应的参数。1.0版本中的土壤类型与参数完全来自于《灌溉与排水工程规范》,在计算时对于各个灌区的特殊性考虑不足。2.0版本中,用户可以在软件现在已有的突然类型参数基础上,增加自己的灌区特有的土壤入渗参数A和m或者a和b。

2.3.2渠道衬砌衬砌参数

软件可以通过自定义的衬砌参数α和来控制衬砌效果逐年变化的过程。

2.4渠道的工作制度

1.0版本中,渠道的工作制度均为续灌。这种情况在一般的中型以上灌区中很少出现。在灌区中,一般骨干渠道,干渠和支渠采用续灌的方式,而低级别的斗渠和农渠采用轮灌方式。当然有些灌区的干渠和支渠也会采用轮灌的形式进行灌溉。
2.0版本中最大的改进就是增加了渠道的灌溉制度选择,用户可以在每个渠道对应的分组表中,设置分组数来试验控制渠道是轮灌和还是续灌。具体计算时的差异分述如下:

2.4.1 续灌的计算流程

灌溉水从水源地引入田间,需要渠道进行输配水。一般从引水河流开始,经过总干渠——支渠——斗渠——农渠,又因渠道在输水过程,会因为水面蒸发、渠床渗漏、闸门漏水等影响,不可避免地产生水量损失,这就出现了净流量、毛流量、损失流量的概念。它们之间的关系是:
(2.16)
计算从最末级渠段开始。设定好渠道等级及上下级关系后,即从末端渠道联接的田间流量开始,逆向推导每一级渠道的净流量(分配给下级各条渠道流量的总和)与毛流量(从水源地或上级渠道引入的流量),即第i+1级渠道的毛流量即为第i级渠道的一条支渠道的净流量。

2.4.2 轮灌时软件的计算流程

1.0版本中所有渠道均为续灌,采用自田间至水源,逐级推算各渠道的毛流量及损失。轮灌时,首先采用进行续灌运算,得到各级渠道续灌时的毛流量和净流量。而后将渠道的毛流量之比作为分摊上级渠道输水流量的比例根据。具体计算过程如下。

2.4.2.1渠道流量计算

轮灌的计算过程中,上级渠道的流量是已知值,通过下级渠道中同时工作的渠道来决定下级渠道的毛流量。以图2-1为例。上级渠道的毛流量为QS,该渠道包括6条下级渠道,其中渠道1、2和3为一个轮灌组,渠道4、5和6为一组。
续灌时,根据Q1、Q2、Q3可以求得上级渠道流量Qs。轮灌时,为保证渠道1、2和3在同时灌溉结束,Q1、Q2、Q3真实值保持续灌时的比例,等于各自渠道续灌时流量乘以一个固定比例k,通过试算得到满足渠首流量Qs的k值,再乘以续灌时Q1、Q2、Q3的值,即可得到轮灌时Q1、Q2、Q3的流量值,以此类推,直到得到最末级渠道(农渠)的毛流量。

图2-1 轮灌水流分配图

2.4.2.2灌溉时间和水量的计算

得到农渠的毛流量后,由于没有下级渠道,可以直接推求得到该级渠道的净流量。根据灌溉面积、灌溉定额和田间水利用系数,可以求得农渠的工作时间,工作时毛水量和净水量。同一组农渠的工作时间是斗渠在该轮灌组工作期间的工作时间,该时间乘以斗渠毛流量即为斗渠在该轮灌组的毛水量,农渠的毛水量之和,即为斗渠的净水量。同一斗渠各个轮灌组的毛水量、净水量之和就是整个斗渠的毛水量和净水量。根据支渠与斗渠的轮灌组安排可以求得支渠的相应结果。干渠和更高级渠道同理。

2.5渠道水及渠系水利用系数的计算

1.0版本中因为所有渠道的工作制度都是续灌,工作时间相同,因通过流量之比即可得到渠道用水效率。而轮灌时,各轮灌组之间的渠道工作时间一般并不相同,因此通过渠道的净水量与毛水量之比来计算渠道输水效率。

2.5.1续灌各级别利用效率计算

(1)渠系水利用系数:末级固定渠道流入田间实际的水占干渠渠首流入水量的比例。本软件中采用的计算表达式为:
(2.17)
(2)渠道水利用系数(用符号表示):某渠道的净流量与毛流量的比值。本软件中采用的计算表达式为:
(2.18)
(3)某级别的渠道水利用系数(用符号表示):某级别渠道的净流量与毛流量的比值。本软件中采用的计算表达式为:
(2.19)
(4)灌溉水利用系数(用符号表示,计算时需给定田间水利用系数):实际灌入农田的有效水量和渠首引入水量的比值。本软件中采用的计算表达式为:
(2.20)

2.5.2轮灌时各级别利用率计算

(1)渠系水利用系数:末级固定渠道流入田间实际的水占干渠渠首流入水量的比例。本软件中采用的计算表达式为:
(2.21)
(2)渠道水利用系数(用符号表示):某渠道的净流量与毛流量的比值。本软件中采用的计算表达式为:
(2.22)
(3)某级别的渠道水利用系数(用符号表示):某级别渠道的净流量与毛流量的比值。本软件中采用的计算表达式为:
(2.23)
(4)灌溉水利用系数(用符号表示,计算时需给定田间水利用系数):实际灌入农田的有效水量和渠首引入水量的比值。本软件中采用的计算表达式为:
(2.24)

7使用情况

软件已经成功在内蒙、江西和湖北得到使用和验证。

软件开发人员

韩旭东 王修贵 刘馨井雨 许雅欣 黄韬幸 肖雪

联系邮箱

wangxg@whu.edu.cn
hanxudong@whu.edu.cn

参考文献

[1] 郭元裕. 农田水利学[M]. 北京: 中国水利水电出版社, 1997.
[2] 李现社, 刘斌, 张利民等. 灌溉与排水工程设计规范[M]. 北京: 中国计划出版社, 2018.
[3] (苏联)A.H.考斯加可夫著,陈益秋译. 土壤改良原理[M]. 北京: 中国工业出版社, 1965.
[4] 门宝辉. 渠道流量损失及谁利用系数公式的探讨[J]. 中国农村水利水电, 2000, 4: 33–34.
[5] KOSTIAKOV A N. On the dynamics of the coefficient of water-percolation in soils and on the necessity for studying it from a dynamic point of view for purposes of amelioration[J]. Society of Soil Science, 1932, 14(1932): 17–21.

软件版权归武汉大学所有

简要介绍

该软件的创作目的如下:渠系水利用系数是衡量渠系工作状况、渠系管理水平的综合指标。目前对渠系水利用系数的计算大多仍停留在传统的表格手工测算上,手工计算存在几个缺点:当计算结果不合理或错误时,检查、修改均较繁杂,大多只是重复性工作;手工计算缺少对原始数据的合理性分析。本软件以逆向递推水量平衡法为核心算法,将计算方法编写成程序,利用计算机进行辅助计算,提高计算效率及结果的精度。

该软件的主要功能如下:灌区信息录入、数据导入、计算、结果查询与导出、数据保存。

该软件的适用行业及用途如下:适用于中小型灌区对灌溉水利用系数、渠道水利用系数、渠系水利用系数等评价指标的的计算,并能通过改变参数对多种渠道衬砌方案进行模拟和计算,从而评价、指导节水灌溉的发展。

该软件的技术特点如下:界面简洁,符合水利规划人员的思维特点,只需基础数据便可用软件进行灌溉水利用系数测算,与传统的手工表格计算相比,具有节省人力、时间,提高计算结果精度的优点。

2 软件概述

2.1 目标

本软件将以渠系水利用系数诸多算法中最经典的计算方法——逆向递推水量平衡法为核心算法[详见:郭元裕主编,农田水利学(第三版),北京:中国水利水电出版社,1997年10月],建立集“灌区信息录入、数据导入与导出、数据计算、结果查询与导出”等功能为一体的渠系水利用系数测算系统,利用计算机程序解决传统手工计算出错率高、重复性大的问题,提高区域渠系水利用系数测算的准确度和测算效率。在给定田间水利用系数的情况下,本软件还可以计算灌区的灌溉水利用系数。

2.2 功能

2.2.1 灌区信息录入功能

包括新建灌区、打开灌区、保存灌区、退出。
新建灌区:建立新的灌区文档,输入灌区基本信息。提供“灌区名称”、“灌区类型”、“灌区面积”、“设计灌区面积”、“总引水量”、“工程管理状况”6个基本信息输入框。
打开灌区:打开已经建立并保存的灌区文件。
保存灌区:保存经过计算、修改的最新灌区文件。
退出:退出灌区信息录入菜单。

2.2.2 数据导入功能

初始版本中,考虑四级渠系。需要通过收集灌区干、支、斗、农四个级别渠道的长度、衬砌情况、地下水埋深及对应田块信息、田间水利用系数等基本数据,分别输入给定的“干渠信息输入表”、“支渠信息输入表”、“斗渠信息输入表”、“农渠信息输入表”、“田块信息输入表”中,数据全部输入完成后,才能将表格导入本软件。

2.2.3 计算功能

程序读取导入到本软件的数据,并采用逆向递推水量平衡法进行计算。

2.2.4 结果查询与导出功能

包括渠道关系图查询、渠道参数查询、渠系水利用系数查询、灌溉水利用系数查询、各级别渠道水利用系数查询、渠道水利用系数查询。
渠道关系图查询:查看各级别渠道间关系。
渠道参数查询:查看各渠道衬砌段数目、材料、土壤类型、地下水埋深。
渠系水利用系数查询:查看渠系水利用系数测算结果。
灌溉水利用系数查询:查看灌区灌溉水利用系数测算结果。
各级别渠道水利用系数查询:查看干渠、支渠、斗渠、农渠中某一级别或某几个级别的渠道水利用系数。
渠道水利用系数查询:查看某一条或几条渠道的渠道水利用系数。
以上查询结果均能以Excel或WPS电子表格形式从程序导出。

2.3 性能

2.3.1 数据精确度

数据显示精度精确到小数点后四位,数据输出及处理数据的精度为小数点后15位。

2.3.2 时间特性

数据导入时间:数据导入速度与用户硬盘读写速度有关,一般在15秒以内。
响应时间:所有查询操作均能够做到及时响应,计算操作响应时间一般在1秒以内。

2.3.3 灵活性

本软件基于Windows操作平台,安全稳定;可单机运行,无需提供网络条件,不受办公地点的限制,可供灌区管理单位、科研人员及研究生随时随地学习使用;无需安装操作即可打开软件,具有良好的可移植性。

3 运行环境

3.1 硬件环境

本系统服务器端硬件环境同客户端,硬件要求如下:
客户端:任意机型。
(1)内存最小容量:512MB
(2)输入设备:键盘、鼠标,输出设备:显示器
(3)图形显卡支持DirectX

3.2 支持软件

(1)windows操作系统
(2)Excel或WPS等电子表格软件
(3)Microsoft.Net环境支持

6操作命令一览表

操作命令 功能
登录 点击登录本软件
文件 点击选择新建灌区、打开灌区、保存灌区、退出
新建灌区 点击输入灌区基本信息
打开灌区 点击打开已保存的灌区
保存灌区 点击对最新灌区信息进行保存
导入 点击向本程序导入数据
计算 点击进行计算
结果查询 点击查询渠道关系图、渠道参数、渠系水利用系数、灌溉水利用系数、各级别渠道水利用系数、渠道水利用系数
帮助 点击获得使用帮助
确定 点击确认本次操作
取消 点击取消本次操作
退出 点击退出本软件

7使用情况

软件已经成功在内蒙、江西和湖北得到使用和验证。

软件开发人员

王修贵、许雅欣、黄韬幸、黄永忠、谢亨旺、吴灏、韩旭东

联系邮箱

wangxg@whu.edu.cn
hanxudong@whu.edu.cn

参考文献

《基于渗漏损失的渠系水利用系数分析》
《灌溉水利用系数在不同年型的变化特征--以湖北省温峡口灌区为例》