Groundwater Table E ff ects on the Yield , Growth , and Water Use of Canola ( Brassica napus L . ) Plant

Lysimeter experiments were conducted under greenhouse conditions to investigate canola (Brassica napus L.) plant water use, growth, and yield parameters for three different water table depths of 30, 60, and 90 cm. Additionally, control experiments were conducted, and only irrigation was applied to these lysimeters without water table limitations. The canola plant’s tolerance level to shallow groundwater was determined. Results showed that groundwater contributions to canola plant for the treatments at 30, 60, and 90 cm water table depths were 97%, 71%, and 68%, respectively, while the average grain yields of canola were 4.5, 5.3, and 6.3 gr, respectively. These results demonstrate that a 90 cm water table depth is the optimum depth for canola plants to produce a high yield with the least amount of water utilization.

EFFECT OF WATER

INTRODUCTION
Growth in the world population increases the agricultural production to meet demand for more varied diets and causes of water scarcity in agricultural, environmental, and municipal water consumption. It was projected that, world population will be about 9 billion in 2050 and this high population will cause extreme water scarcity in many countries (Hamdy et al., 2003;U.N. 2004;Ghamarnia et al., 2012). Thus, the necessary solutions must be investigated to control excessive amount of irrigation water utilization. One solution could be encouraging the farmers to use shallow groundwater. Approximately 80% of available water resource in the world is being used in the agricultural applications. The gap between the availability of adequate water versus water needs will increase and hence, the management of groundwater utilization in agriculture will be accepted as an alternative strategy to deal with the potential water crisis.
Improved and well-managed water use efficiency (WUE) is one of the most important purposes of agricultural water management systems and it increases the productivity and reliability of crop yield. Consumption of groundwater is an extremely significant part of WUE.
Describing WUE for irrigation is complicated (Howell, 2001). It was defined that WUE is a grain crop yield or total crop biomass per unit of water use (Sinclair et al., 1984;ASABE standards, 2008).
A good quality of groundwater can be accepted as supplemental irrigation water source that supplies crops' water demands depending on crop species. Some crops such as canola (Brassica napus L.), soybean (Glycine max), and safflower (Carthamus tinctorius) are able to use saline groundwater and hence those crops will help to increase the utilization of groundwater and to decrease the utilization of surface irrigation water. Because shallow groundwater can reduce both drainage and irrigation requirements, it needs to be managed correctly (Hamdy et al., 2003;Yang et al., 2007;Ghamarnia et al., 2012). In addition, there are obvious relationships between water table management (WTM), crop productivity and environmental pollution. The environmental and economic benefits of WTM decrease environmental pollution and increase crop productivity and irrigation intervals. To supply sufficient soil moisture content to the crops, WTM should be well performed (Mejia et al., 2000).
Consumption of shallow groundwater as a crop water supply depends on several factors such as groundwater table depths, groundwater availability and quality, crop species, distribution of plant root system, weather conditions, and soil type (Ghamarnia et al., 2012;Huo et al., 2012).
The amount and quality of groundwater is also affected by the irrigation method and management practices because applying an excessive amount of irrigation water can increase the amount of groundwater utilization. It is not possible to control all these parameters in the field conditions because groundwater contributions are highly variable and difficult to estimate.
Therefore, lysimeters are often used to conduct the experiment that simulates only a single parameter at a time (Luo and Sophocleous, 2010).
Lysimeters in the greenhouse conditions allow to conduct more complex field studies in the controlled environment. Lysimeter studies have been carried out to estimate groundwater depth and contribution and determine the effects of different water table levels on crop grain yields. Lysimeters can be also used to predict the amount of crop water use from the groundwater table (Mejia et al., 2000;Ayars et al., 2006;Putz et al., 2018).

Statement of Objective
The main scope of this study is to determine an optimum shallow groundwater depth to achieve high yield of canola plant. The specific objectives and the hypotheses of the study are as follows: • To determine the optimum groundwater depth for canola growth and yield parameters at water

Importance of the Study
As the global population grows, the demand for fresh water in many regions is increasing dramatically. This population increase causes more water stress for agriculture, production of energy, industrial uses, and human consumption. Even though many countries have never faced the lack of water yet, water can no longer be accepted as an infinite source. Population increases will gradually decrease the amount of water needs for each person. Thus, it is required to find additional strategies to decrease the impact of water crises across the globe (Hamdy et al., 2003;Condon et al., 2004;Ripoll et al., 2014;).
In addition to the population growth, water availability, quality, and quantity for domestic and industrial demand are affected by water pollution, agricultural utilization, and technological developments. Water resources have been irrefutably decreasing throughout the world. One of the most important factors to increase pressure on freshwater resources is urbanization along with population growth. Many developed countries suffer from migration from the rural area to urban area because of estimated changes in water use efficiency (Vorosmarty et al., 2000;Okello et al., 2015).
Farmers who have limited water for crops, must consider deficit irrigation method or using an alternative crop that may have low irrigation demand. However, unprogressive deficit irrigation applications can cause water stress that reduces crop productivity (Payero et al., 2006;Payero et al., 2009). To deal with this problem, improved and well managed WUE should be preferred. Consuming water from groundwater can combined deficit irrigation to increase WUE in arid and semi-arid areas (Howell, 2001;Franzen, 2013).

North Dakota Canola Production
Canola is a potential oil-seed and alternative biofuel crop mostly grown in Northern High Plains of the USA. It can be grown under inadequate irrigation and weather conditions and therefore it is highly adapted in cold weather conditions with insufficient water availability. A comparison between soybean and canola showed that, while a typical Midwest soybean farm can manufacture about 60 gallons of soybean oil per acre, standard canola can produce 111 gallons of oil per acre (Johnston et al., 2002;CAST, 2008;Herget et al., 2016).
High temperature may cause abiotic stress on canola plant and influences its growth.
Canola's sensitivity for high temperature is higher in the flowering period than podding period.
During the blooming season of canola plant, heat stress may shorten the flowering period. Thus, farmers might have a vast amount of dry matter instead of canola seeds at the end of the harvest period (Johnston et al, 2002;Kutcher et al, 2010).
North Dakota (ND) state is located in the midwestern and northern regions of the United States. It has a continental climate condition which has the important difference between low and high temperatures. The lowest and highest average temperatures in ND for 2018 are determined as 0 and 82°F in the months of January and July, respectively. In addition to the high air temperature variations, irregular rainfall, low humidity, and shallow groundwater are the important difficulties that impact on crop growth and yield in ND. However, two common types of canola, winter (B. rapa) and spring (B. napus) canola can be grown in ND. Although winter canola can be produced in ND and northwestern Minnesota, ND farmers mainly preferred to plant spring canola since spring canola can survive under the hard winter condition and its yield growth is higher than winter canola. (Kandel, 2010;NOAA, 2018) According to the ND Agricultural Statistics report, canola planted area has been increased from 0.910 million acres to 1.590 million acres between 2008 and 2017 in ND. In addition, the second highest area in ND, 1.560 million acres, was harvested in 2017 (USDA, 2018).

Effect of Water Table Depth on Plant Water Use and Crop Yields
Groundwater quality becomes very important for crop water use and yield parameters. If the plant roots can reach the water table level, the amount of irrigation water should be recalculated because inefficient plant water use reduces the crop yields. It is not possible to accept all groundwater resource as a water supply. Groundwater quality needs to be considered before recalculation of amount of irrigation water. Additionally, irrigation method and management, soil hydraulic properties, and hydraulic conductivity affect crop water use efficiencies from shallow water table (Kahlown and Ashraf, 2005;Luo and Sophocleous, 2010).

Previous Researches and Results
As of the author's knowledge, there is not a study available to explain the relationship between groundwater depth and canola plant growth using lysimeters. Therefore, other studies were evaluated to understand the lysimeter systems. Hutmacher et al. (1996)  Less than 10% of cotton total water use from shallow groundwater was observed at more than 20 dS m -1 salinity treatments. It has been found that growers need to consider both influence of shallow groundwater uptake and salinity tolerance of crop for sustained productivity. Mejia et al. (2000) conducted a two-years field experiment to determine the effect of two different water table depths of 50 and 75 cm on both corn and soybean crops to determine the grain yields. A free drainage system was conducted 100 cm below the soil surface for both treatments. Corn harvesting results in the first year were compared with and without free irrigation system. Free drainage treatment of corn grain yield weight was found 13.8% higher than no drainage treatment at 50 cm water To determine groundwater contribution to safflower, Ghamarnia and Golamian (2012) carried out an experiment using lysimeters. Silty loam soil was packed in twenty lysimeters and randomized block design was used with four replications. Treatments were performed and classified based on groundwater salinity levels.

Root System
Crop root distribution is important to understand soil and plant response to water utilization. Although root is the most important vegetative part of the crop (Lesczynski and Tanner, 1976), root contribution is the least measured parameter in the literature (Ayars et al., 2006). Shallow groundwater can be accepted as a crop water supply, if crop root reach shallow groundwater level. Crop roots need to be well developed to reach deeper groundwater levels (Soppe and Ayars, 2003). The development of root is depending on several factors such as soil density, pH, and fertility. If soil has; low bulk density, high fertility, and pH the crop root can be well developed at the lower water table levels (Borg and Grimes, 1986).
Crops' roots need efficient amount of oxygen to complete growing period. Saturated root zone supplies lower amount of oxygen to crops. Since soil texture in ND includes saturated root zone, crop cannot reach potential harvesting results. Dry area in the root zone is the most important part of crop planting. More root contribution is generally observed at the end of growing period. Since crops have well developed root system during the last period of crop growth, the highest amount of water use from groundwater occurs in this cycle (Ayars et al., 2006;Franzen, 2013).

Soil Hydraulic Properties
Soil hydraulic functions need to be determined to calculate evapotranspiration for water table in lysimeter studies (Schindler et al., 2010). The level of water table, soil salinity, climate, and hydraulic conductivity influence evaporation rate. The amount of water in the root zone depends on hydraulic properties of unsaturated soil zone. Soil type is a significant factor in terms of influence of water use from water table since unsaturated soil hydraulic conductivity is the property of the soil type. To save water in agriculture and improve water use efficiency, soil hydraulic properties need to be determined. (Zhang et al., 1999;Ayars et al., 2006)

Management of Drainage and Irrigation System
The influence of excessive amount of water in the field is significant for crop grain yields and field operations. To provide optimum amount of water for crops, drainage systems are mostly preferred to be installed into the subsoil. Drainage systems discharge excessive amount of water from soil and provide optimal water table level and soil moisture content in the root zone.
For easy plantation and obtaining reliable results from below ground parameters (root, root-soot ratio and etc.), drainage systems could be applied in the field experiments (Skaggs and Schilfgaarde, 1999;Rijal et al., 2012).
Drainage system management need to be well performed since non-functional drainage management methods may cause to discharge necessary water for crop in the root zone. Because of inefficient drainage system, plant root cannot take sufficient amount of water from groundwater, and deficient amount of irrigation water can cause water stress. Thus, crop grain yield loses can be occurred because of crop water stress. Another effect of insufficient drainage management is that water table level can increase to unexpected level. Excessive amount of water in the root zone causes undeveloped crop root zone and grain yield losses (Kahlown and Ashraf, 2005;Ayars et al., 2006).

The Method Used to Determine Groundwater Contribution to Crops
Water balance equations are used to describe the water fluxes in the soil profile. In addition, to calculate crop water use from groundwater and soil water content changes in desired period of time, different modified water balance equations were performed in several experiments. Hillel (1998) used Eq.2.1 to calculate water content changes in the root zone.
To calculate water use from groundwater, a field experiment can be conducted. The parameters that need to be measure in a field experiments are groundwater table depth, groundwater availability and quality, crop species, distribution of plant root system, weather condition, and soil type. It is not possible to control all these parameters in the specific time interval under the field conditions. Thus, groundwater contributions are highly variable and difficult to estimate for field experiments. For this reason, lysimeters were mostly utilized as reliable research tools to measure the amount of water loses by evaporation and transpiration.
The actual groundwater contribution to crops can be determined by monitoring the amount of water changes in the lysimeters (Jia et al., 2006;Luo and Sophocleous, 2010).

Introduction
Crop water use from groundwater has already broadening last twenty years in the United States. Furthermore, shallow groundwater could be used more as a crop water supply since flooding and drought events could be increased because of unpredictable weather conditions.
Thus, shallow groundwater contributions to crops became important agricultural application for water resources management (Tebaldi et al., 2006;Scanlon et al., 2010).
To determine relationship between crop water use from groundwater and different water table depths, many studies were performed using different parameters (Ayars et al., 2006). Torres and Hanks (1989) was conducted an experiment to determine groundwater contribution to wheat crop using two different soil textures, silty clay loam and fine sandy loam. Different water

Experimental Design and Preparation of Lysimeters
This study has been conducted in a greenhouse located at ND State University campus, Fargo, ND. Thirty-two lysimeters were used in the study with four treatments, which were three different water table treatments include 30, 60, and 90 cm water table depths with no irrigation application and a control treatment (no water table) with surface irrigation application ( Figure   3.1). Each treatment had 8 replications so that 24 lysimeters (8 replications x 3 different water   In the control treatment lysimeters (Tcontrol) three soil water potential sensors (TEROS-21, METER Group, Inc.) were used to determine the irrigation timing and the amount of water needs for the irrigation. Each three water potential sensors were placed at different depths of 15, 45, and 75 cm in a lysimeter. For the remaining treatments (T30, T60, and T90) total six soil water potential sensors were used and placed in the appropriate depths. One soil water potential sensor was placed in the 15 cm from the top of the soil surface in T30 lysimeter. Two soil water potential sensors were placed in the 15 and 45 cm depths in T60 lysimeter. Three soil water potential sensors were placed in the 15, 45, and 75 cm depths in T90 lysimeter. To ensure hydraulic contact between sensors and moisture in the soil, all the sensors were placed horizontally in the lysimeters. All 9 water potential sensors were plugged in two Em50G (Decagon Inc) datalogger at 10-minute intervals.  Figure 3.3.
To provide same water curved conditions to all lysimeters, proper planting bed was prepared. At the beginning of the experiments, all the lysimeters were filled with water to the soil surface in the lysimeters. Then, the valves at the bottom of the lysimeters were opened and water in the lysimeters was drained. About 30 hours later, the valves were closed to keep the adequate moisture in the lysimeters to use for germination process. Mariotte bottles were connected and adjusted for desired level for each lysimeters. Ten seeds were sowed from 1 to 3 cm soil depths.
During the germination process, three healthier canola plants were kept in each lysimeter.  Although iron deficiency was observed at the beginning of experiment, beneficial nematodes, supplements and chemicals have never applied during the whole experiment.

Plant Root Measurements and Crop Water Use Determination
After harvesting the canola, 16 lysimeters from four randomly selected treatments were cut vertically to determine canola plant root dry mass in each treatment. In order to analyze where, Cr is capillary rise, P is precipitation, I is irrigation, R is runoff, Dp is deep percolation, ET is evapotranspiration, ∆S is the change in soil water content.
Irrigation, precipitation, runoff, and deep percolation were not applied in this study since the experiments was performed in controlled greenhouse. After evaluation of the controlled environment condition, the soil water balance equation was used to determine ET for each treatment (Eq. 3.2).
ET= Cr + S1 -S2 (Eq.3.2) S1 demonstrates initial soil moisture condition and S2 shows final soil moisture condition in the lysimeters Water reduction in the Mariotte bottles was measured every 15 days to determine capillary rise in the lysimeters. The amount of water use of canola was calculated using soil water balance equation (Eq. 3.1) (Hillel, 1998).
To determine the initial moisture conditions of the lysimeters at the beginning of the experiment, the soil water potential sensors were used. After cutting sixteen lysimeters, soil water content was measured, and the final moisture conditions of the sixteen lysimeters were determined for both irrigated and non-irrigated treatments.

Irrigation Scheduling
As mentioned earlier, the soil water release curve (Figure 3.4) was used to consider 50% of the total available moisture as the readily available moisture in the soil profile of control treatment. The irrigation depths for each lysimeters were calculated by using Equation 3.3 (Majumdar, 2001).
where, d is the equivalent depth of water in cm, Fci is field capacity of the layer in percent by weight, Mbi is current water content of the layer in percent by weight, Asi is apparent specific gravity (Bulk density), Di is the depth of each layer, n is the number of layers.  The summary of physical properties of soil-sand mixture was determined based on laboratory test results (Table 3.2). To determine the soil water retention curve, water in the lysimeters was drained out from the lysimeters through valve at the bottom of the lysimeter until the readily available moisture content in the lysimeter become 50%. For the control experiments, necessary amount of irrigation was applied at the surface of the lysimeters to maintain the soil field capacity as 0.32 cm 3 /cm 3 .

Statistical Analysis
Randomized complete block design model with eight replications and four treatments were applied in this study (Figure 3.1). The effect of different groundwater levels on canola growth and yield parameters (crop water use, plant height, seed weight, pod weight, total biomass, root-shoot ratio and root distribution) were analyzed by using one-way analysis of variance (ANOVA) with P ≤ 0.05 level of significance (R Studio, R Core Team 2017).
Statistical Package for the Social Sciences version 25 (SPSS) and Duncan homogeneous test comparisons with the P = 0.05 probability level were used to conduct mean separation tests on four different treatments. Main fold analysis was performed to obtain mean graphics.

ET0 and Air Temperature in the Greenhouse
To determine relationship between evapotranspiration and temperature in the greenhouse and interpret the temperature and ET0 changes during the different canola growing stages (germination, growing, and harvesting), daily average ET0 rates and temperature data were collected between November 4, 2018 (planting) and February 4, 2019 (harvesting). According to the result obtained from ETgages, the lowest and highest temperature in the greenhouse were determined as 15.5 o C and 29.5 o C, respectively. The lowest temperature was observed first 10 days of canola growing period because of extreme ambient cold temperatures. Temperatures in the greenhouse were 25±5 o C from November 14, 2018 to February 4, 2019 (Figure 3.5).
The lowest daily ET0 was measured as 3.80 mm during the germination stage of canola.
After first 10 days of canola growing period, ET0 rates were fluctuated, and the highest ET0 was measured as 7.80 mm. Cumulative ET0 was calculated as 577 mm during total experiment process (92 days). Figure 3.5. explains correlation relationship between evapotranspiration and temperature. When the greenhouse temperature reduced in any time, ET0 also decreased comparatively.

Crop Water Use
To prevent water stress and applied excessive amount of irrigation water, water content was kept between field capacity (0.32 cm 3 /cm 3 ) and critical point (0.27 cm 3 /cm 3 ) for control treatments. Three different plant root depths were considered for water requirement calculations.   Volumetric water content was always maintained between field capacity and RAM. Available soil moisture in the root zone was fluctuated and it exceeded 50% of total available soil moisture level twice.
Four control treatment lysimeters were cut to calculate total evapotranspiration. As explained earlier, the same amount of irrigation water applied to all control treatment lysimeters.
Based on the data obtained from the sensors, the amount of cumulative irrigation water was found as 752 mm for each lysimeters. Calculated cumulative canola plant water use were varied from 733 to 749 mm. Thus, average ETc was calculated as 740 mm for treatment lysimeters (Table 3.3).  These results showed that, there are inverse relationship between WTD and evapotranspiration. Additionally, same inverse relationship was obtained between WTD and groundwater contribution. When water table level increased from 90 to 30 cm, the amount of water use from groundwater increased (Figure 3.7).

Growth and Yield Parameters
According to the statistical results for growth and yield parameters, differences among Tcontrol, T30 and T60 for mean plant height was not significant, but T90 was significantly higher than other treatments. The highest mean canola plant height was 134.6 cm at T90 treatment and the lowest mean plant height was 113.3 cm at T30 treatment. Similar inverse relationship between WTD and groundwater contribution was observed between plant height and WTD. When WTD level increased from 90 to 60 cm in the lysimeters, canola plant height decreased from 134.6 to 113.3 cm.
Obvious significant differences between each treatment were obtained for mean total biomass, pod weight and seed weight per plant. The highest mean total biomass, pod weight and seed weight were calculated as 22.1, 12.6, and 6.3 gr at T90 treatment, respectively. The lowest mean total biomass, pod weight, and seed weight results were calculated as 15.1, 9.5, and 4.8 gr at T30 treatment, respectively. These results showed that, higher water table depths decreased canola harvesting results. Overall, statistical results proved that there is a negative correlation between the canola plant growth and yield parameters and WTD.
The water use results between water table treatments and control treatment showed that, Tcontrol lysimeters consumed the highest amount of water (Table 3.3 and Table 3.4). After harvesting, plant height, total biomass, pod and seed weights results showed that T90 treatment produced the highest yield values compare to other treatmnets. Tcontrol treatment had the second highest yield (Table 3.5). As explained earlier, Tcontrol used optimum amount of irrigation water, 740 mm, and T90 consumed 501 mm water from groundwater. However, better growth and yield result were obtained in T90 treatment.

Water Use Efficiency (WUE)
WUE was calculated for both grain yield (harvested seed weight) and total biomass (harvested total dry matter). Since sixteen lysimeters were cut, average grain yield and total biomass values of sixteen lysimeters were used for grain yield and biomass WUE calculations.
The same statistical difference grain yield and total biomass results of thirty-two lysimeters was extrapolated using sixteen lysimeters data in response to WTD (Table 3.6).  The relationship between WUE of canola total biomass and graind yield was found. The correlation of both WUE values were determined (Figure 3.9). The effects of different WTD levels on both grain yield and total biomass WUE were observed. The significant differences between the treatments were found in terms of grain yield and total biomass WUE values. The highest grain yield and biomass WUEs for T90 were calculated as 0.0126 and 0.0449 g lys -1 mm -1 . The lowest values for both parameters were calculated at T30 treatment (Table 3.6). Table 3.6. Statistical analysis of canola mean grain yield, total biomass, water use, and water use efficiency results. These results belong to sixteen lysimeters.
Note: Statistical results of WUE are inditaced with letters in table Table 3.6.

Dry Root Mass
After cutting 16 lysimeters as mentioned earlier, soil profile was divided in three different layers as 0-30, 30-60 and 60-90 cm (measured from the top) to determine percentage of root mass distribution in terms of WTD (Table 3.7). Overall, the highest root-mass was found in Tcontrol at 0-30 cm (4.52 g and 54.6%). There is a linear relationship between WTD and root mass for Tcontrol. When WTD increased from 90 to 30 cm, root weight increased from 0.73 to 4.52 g.
Since Tcontrol did not have WTD, lower amount of root was found in deeper soil layers. The significant differences were observed in 0-30 cm layers between T90 and other treatments and more root mass was observed in 60-90 cm in treatment T90. The highest average root weight  There is no significant difference between T30 and Tcontrol for total root weight distribution. However, the lowest mean of total root weight was determined as 8.27 g for Tcontrol.
The mean total root mass of T90 was always two-fold of Tcontrol (Figure 3.10 and Figure A.1).
Comparatively, lower dry root mass was measured at the 2 nd and 3 rd layers of the Tcontrol, T30, and T60 but higher dry root mass was found at the 2 nd and 3 rd layers of the T90. Similar to other results (grain yield, plant height, total biomass, pod weight, and WUE), the best root mass results were obtained from T90 (Table 3.7).

Root-Shoot Ratio
To analyze the relationship between total biomass and roots mass, root-shoot ratio was calculated for sixteen lysimeters. Total root weight was divided by total biomass to calculate root-shoot ratio. The result of root, total biomass and root-shoot ratio data are presented in Figure   3.12.   The lowest root-shoot ratio was found in Tcontrol lysimeter, 0.39. Root-shoot ratio of T90 was 0.76, which was the highest root-shoot ratio. Even though total biomass of canola plant in Tcontrol was more than T30 and T60, root-shoot ratio of Tcontrol was lower than other treatments.
According to results, T90 was chosen as a best plant for root-shoot ratio.

Summary
In this study, canola plant height, water use from different groundwater levels, optimum amount of irrigation water, total biomass WUE, grain yield WUE, root mass, root-shoot ratio and harvesting results (total biomass, pod and seed weight) were determined and compared with three different water tables and optimum amount of irrigation under the adjustable weather conditions in the greenhouse. Investigated NDOLA-01 type of canola plant results showed that the plant was affected by different water table levels since inverse and linear relationship were found in results depends on different WTD. Significant statistical difference was observed among the treatments. Determination of above and below ground parameters include total biomass and root weight showed that 90 cm water table depth of lysimeters produced the best results. Similarly, the lowest crop water use from water table was found at the T90 treatments.
The highest crop water use was calculated at the irrigated lysimeters, and it was significantly higher than 90 cm lysimeters.
Considering harvesting results, canola plant showed significant statistical differences among the treatments. The highest measured pod weight, total biomass, and seed weight were found at the 90 cm lysimeters although 90 cm treatments consumed lowest amount of water from the groundwater. The highest harvesting results with the lowest amount of consumed water showed the highest total biomass and grain yield WUE. On the other hand, the lowest harvesting results and the highest crop water use were obtained from 30 cm lysimeters. It was assumed that canola crop tend to use continuously water from groundwater when roots reached the groundwater. As a consequence of that high WTD level (30 cm) made negative impact on canola.
Below ground parameters such as root distribution in each specified soil depth (0-30, 30-60, and 60-90 cm) were examined clearly. The significant statistical difference was not found between root distribution and layers. However, stronger and heavier roots were found near the water table level. Opposite the root weight in each layer, total root weight was affected by WTD, and the significant statistical differences occurred among the treatments. Total root weight at the 90 cm lysimeter was significantly higher than other treatments. Irrigated treatment had lowest total root weight. It was projected that canola root at the drier lysimeter developed root structure since canola plant was in tendency to reach water.
In terms of crop total biomass WUE and grain yield WUE, grain yield parameters, harvesting results, root mass distribution and root-shoot ratio; it was observed that 90 cm was the best water table depth for canola in this lysimeter experiment.

Recommendations for Future Work
▪ All these experiments could be conducted in the real farm conditions using lysimeter techniques.
▪ In this study, three water table depths between 30 and 90 cm were tested. Beyond 90 cm depth could be studied to determine canola plant's behavior.
▪ Using the same soil packing and weather conditions, 90 cm WTD with optimum amount of irrigation water could be performed.
▪ Other crops that grown in ND could be studied.
▪ Tap water with no salinity was used in this experiment. Saline water in different concentrations could be added in the experiments as a future study.