Iranian Journal of Soil and Water Research
Year:2020 | Volume:51 | Issue:8|Papers Count:20

Precipitation forecasting is one of the most important tools in water resources planning and management. Recently, new methods called atmospheric dynamic models have been used to predict many hydro-climate variables including precipitation. Before using the predictions of these models in planning and decision making, the accuracy of the mentioned predictions and their bias correction should be evaluated. Therefore the objective of this study is to ascertain the biases and to combine the results of precipitation forecasting with a set of global dynamic forecasting models. To achieve this aim, firstly the precipitation forecast results of each model were compared separately with the regional recorded precipitation data in the period of 1982 to 2017. Using this approach, the systematic errors were removed and corrected, i. e. using the quantile mapping method. This work was done for different forecast periods and also for different months. Furthermore, based on the accuracy of each model, a hybrid/multi-model prediction system was developed using Bayesian averaging method (BMA). The results showed that after the bias correction, using the quantitative mapping, at least one model among 78 prediction models have a relatively high correlation value of about 0. 7. This result was recorded for the next one-month horizon. This correlation was increased to more than 0. 8, by combining 78 predictive members, using Bayesian averaging method. Therefore, the accuracy of the predicted precipitation increases significantly using bias correction in tandem with combining the prediction models.

Climatic conditions and soil properties such as salinity are very important and influential factors in vegetation of any region. The salinity of the groundwater and the accumulation of salts in the surface layers of the soil due to evaporation and capillary rise have caused salinization in a part of Qazvin plain that has had adverse effects on the growth of plant species in an area of 60, 000 hectares. In order to control the devastating effects of Salt Marsh development in the area, interceptor drain has been constructed in the central Salt Marsh core. The purpose of this study was to analyze the Effectiveness of Interceptor Drain on Soil Salinity and Vegetation Changes during 5 years with 10 exclosures. To investigate the effects of drain construction, the statistical analysis was performed in a factorial randomized complete block design. The results show that the electrical conductivity of deep soil is 18% more than the electrical conductivity of surface soil. The results of comparing the average soil electrical conductivity based on Duncan's method showed that the average soil electrical conductivity was highest in 2013 and the lowest in the fourth year after the beginning of the study. Since the main source of soil leaching in the area of excavated crops is runoff, therefore the most important cause of soil electrical conductivity variations with different years can be related to the amount of spring rainfall. The results of statistical analysis showed that the electrical conductivity of the soil decreased gradually by passing years in the constructed exclosures. The results of variance analyses of vegetation percentages in exclosures showed that the constructed interceptor drain has had a significant effect on vegetation changes during the studied years and the spatial effectiveness of the drain on vegetation changes has been 300 m.

In this study, hourly values of precipitation and air temperature in Karoon 4 basin in southwestern of Iran were simulated with WRF numerical model to evaluate the accuracy of the model for flood prediction. The flood event was selected in March 2016. For global boundary conditions of the model, global data with a resolution of 0. 75 were used. The WRF model was implemented using eight different configurations, including a convective schema, two planetary boundary layer schemes, two microphysical schemes, a surface layer schema, and two shortwave radiation schemes to obtain a suitable configuration for simulating temperature and precipitation. The results showed that in the simulation of hourly precipitation, the combination of MYJ boundary layer design with other micro-physics and short-ray projections yields better results than YSU schema. The best values of IOA (matching coefficient) between observed and estimated precipitation of the model was 0. 77, 0. 76, 0. 74 and 0. 52 in Shahrekord, Saman, Koohrang and Lordegan, respectively, by combining MYJ boundary layer, Lin physics and Dudhia short radiation. While in simulating hourly air temperature, the YSU boundary layer schema combination with other schema showed better performance. So that with this combination, the heighest conformity coefficient (0. 47) was obtained between the estimated and observed hourly temperature. The estimated rainfall adjusted by MYJ boundary layer configuration, Lin physics, GODDARD short radiation and MYJLG has performed better prediction for peak dischage than the other schemas, so that the lowest Nash coefficient and RMSE were-0. 293 and 37 respectively, with this combination. Therefore, the combination of MYJ boundary layer schema, Lin cloud microphysics schema, and GODDARD radiation schema appear to be the best for estimation of precipitation and temperature and consequently for prediction of the March 2016 flood in the Karun 4 basin.

Seasonal and annual precipitation variations are subject to numerous natural and climatic factors such as climate teleconnection indices (CTIs). The purpose of this study is to investigate the correlation between CTIs and autumnal precipitation in 30 catchments of Iran. For this purpose, autumnal precipitation data were selected from 717 synoptic, climatological and rain gauge stations over a 28-year (1988– 2015) climate period, and their correlation with eight CTIs including SOI, MEI, NAO, AO, NCP, C-SST, M-SST, and P-SST were obtained in eight-time lags. Finally, their correlation significance were investigated and analyzed. The results showed a significant positive correlation between the MEI (29. 1% to 43. 3% of the western, southern, eastern and northeast watershed stations) and the NAO (29. 4% of the northwest basin stations), While the SOI (23. 3-53. 7 stations of the western, southern, eastern and northeast watersheds) and C-SST (23. 3 of the southeast watershed stations) had significant negative correlation. In terms of the time step, it was found that the Oct-MEI (43. 3% of the stations had a positive correlation) and Aug-SOI (53. 7% of the stations had a negative correlation) had a significant correlation with most of the studied stations. From the watershed point of view, it was found that the frequency of significant correlations in different catchments varied between 10. 9 and 36%. The results of this study show that about 10 watersheds have a significant correlation with more than 30% of CTIs which changes in each watershed. Consequently, the CTIs with different time steps can be used as predictor variables for autumn precipitation in Iran watersheds.

The aim of this study was to determine the critical limits and optimal range of relative bulk density (RBD) obtained using proctor test (RBDProctor) and axial stress of 200 kPa (RBD200kPa) for a silty clay loam soil which were determined based on relative grain yield, relative shoot dry, relative height and relative root volume of sunflower (Helianthus annuus L. ). The relative values were obtained by dividing the absolute mean values of mentioned traits to observed maximum values of each trait. A range of soil bulk density (1. 35 to 1. 59 Mg m-3) was prepared in 10 bins (40 cm × 50 cm with 50 cm depth) using rollers of different weights. The bins were located out-doors after sowing sunflower and the weight of bins and drained water volume were measured daily. The soil water content was retained in the range of field capacity (FC) to 0. 6FC through irrigation. The optimal ranges of RBDProctor and RBD200kPa were assumed to be the ranges in which the relative traits of sunflower were greater or equal to 0. 95 of maximum value predicted by obtained equations fitted to relative data versus RBD. Sunflower yield was maximum at RBDProctor equal to 0. 854 and the optimal range of RBDProctor based on relative grain yield was from 0. 823 to 0. 884. In this range sunflower relative grain yield was greater or equal to 95%. The corresponding values of RBD200kPa were 0. 975, 0. 940 to 1. 009, respectively. This finding revealed that at the RBD values less than lower limit and greater than upper limit of starting restriction, unsuitable physical conditions reduce sunflower relative grain yield.

In soil laboratories of Iran to determine the initial soil particle size distribution (PSD) curve, different methods and strategies and pretreatments are used to remove soil cement materials, which in many cases make it difficult to compare the results and also evaluate their accuracy. The current research was performed to achieve an economical, simple and accurate protocol to mesure the soil PSD analysis. First, 112 soil samples from the top and sub soils were collected from 16 provinces. Then 91 soil samples were selected based on hydrometer method and they were analyzed mechanically with and without removal of different cement agents; such as Organic matter, lime, iron and aluminum oxides and combined removal of organic matter and iron oxide. Results showed that the removal of cement agent increases the clay fraction and reduces the silt and sand fractions. The removal of cement agents should be conducted where i) organic matter content is more than %4 or ii) iron oxides is more than %2 or iii) the amount of organic matter + iron oxides is more than %5. In average, the removal of organic matter and iron oxide increases clay fraction 7%. Since the carbonates are often exist as the primary particles in the Iranian soils, the removal of carbonates is not suggested from the soils with more than %10 carbonates. Finally it is concluded that the cement agent in some soils may cause incorrect determination of soil texture class.

The accumulation of heavy metals in agricultural soils, in addition to environmental pollution, increases the concentration and uptake of heavy metals in plants. In order to investigate the uptake and translocation of lead in four cultivars of winter wheat (Zare, Pishgam, Mihan and Orum), the effect of six levels of soil contamination by Pb (0, 25, 50, 100, 200 and 400 mg Pb/kg soil from lead nitrate [Pb(NO3)2] source) on the proposed cultivars were investigated as a factorial pot experiment with completely randomized design and three replications in the greenhouse conditions. The results showed that the levels of contaminated soil by Pb had a significant effect (P < 0. 01) on Pb uptake of different cultivars of wheat. The highest amount of Pb uptake was measured in Mihan cultivar at level of 400 mg Pb/kg soil and was 2. 67 mg in pot. The highest fresh weights of biomass, the highest accumulation of Pb in root and aerial parts, and the highest amount of Pb uptake by wheat were observed in Mihan and Pishgam cultivars at all levels of soil contamination, indicating that these cultivars have higher abilities to uptake and transfer Pb from the root to the aerial parts. The translocation factor of Pb was less than one for all four wheat cultivars at levels of 0 to 100 mg Pb/kg soil, while the bioaccumulation factor of Pb was more than one. As in the proposed wheat cultivars, the concentration of Pb in the root was higher than the one in aerial parts, they can be classified as excluder plants at these levels. Further studies are recommended in the field.

The CE-QUAL-W2 program as a physical model for quality and hydrodynamic simulation of water reservoirs has a high computational cost. Therefore, finding surrogate models to give optimal results in short term would have a great practical importance especially in simulation-optimization problems. In this study, the capability of the NARX model as a surrogate model was investigated to simulate the outlet salinity from strongly stratified reservoirs. For this purpose, the CE-QUAL-W2 model was used and calibrated to simulate the outlet salinity of the Upper Gotvand Reservoir over 10 years. Regarding the possibility of release from different reservoir intakes, by monthly change of release ratios, several problems were defined and a library of the physical model results was formed. Then different NARX architecture scenarios were introduced and trained using the library results. The results obtained from different scenarios indicate that the NARX neural network model has a high capability to simulate the CE-QUAL-W2 model results of outflow salinity, so that the correlation coefficient is always above 0. 91. In the selected scenario, a very good agreement is observed between the results of the two models, with a correlation coefficient of 0. 95, mean absolute percentage error of 8. 7% and Nash-Sutcliffe coefficient of 0. 79. The simulation time required for the NARX neural network model is less than 0. 06% of the time required to run the physical model for the same problem. The results show that the NARX model can be used as a suitable surrogate model for CE-QUAL-W2 to predict the long-term reservoir outlet salinity and reduces the cost of computing while maintains accuracy.

This study was carried out to investigate the morpho-physiological and biochemical responses of Japanese raisin (Hovenia dulcis L. ) seedlings to stress conditions of salinity (Electrical conductivity), nitrate and Pb. The experiment was conducted in a factorial experiment based on completely randomized design with three stress factors including nitrate (0, 30 and 60 mg L-1), salinity (0, 3 and 6 dSm-1) and Pb (0, 300 and 600 mg L-1) and three replications. Plants were grown under greenhouse conditions for four months. The highest shoot fresh weight was observed in treatments of 300 and 600 mg/kg Pb with zero salinity and nitrate level and the lowest fresh weight was belonged to the treatment of 6 dS/m salinity, 600 mg/kg Pb and 30 mg/L nitrate. The highest Pb concentration of shoot (72 mg kg-1 dry matter) was reported in treatment of 600 mg kg-1 Pb and with zero salinity and nitrate level. The highest value of lipids peroxidation occurred at treatment of 600 mg kg-1 Pb, indicating the plant defense mechanisms activity under these conditions. Furthermore, the synthesis of proline as a plant response to stress conditions significantly increased at 600 mg kg-1 Pb; whereas, nitrate application led to reduce malondialdehyde production in plant.

Nowadays, soil contamination with heavy metals is one of the major environmental concerns. Among heavy metals, lead is one of the main concerns due to its effects on human health and environment. The most important sources of this pollution in most parts of the world are mines, industrial waste, chemical fertilizers and pesticides. In order to investigate the adsorption capacity of lead by the ornamental plant of viola (Viola tricolor) and to find the morphological and physiological responses of plant against lead stress, a study in contaminated soil with different levels of lead (0, 200 and 400 mg/kg) was done in a completely randomized design with five repetitions in the greenhouse of the Faculty of Agriculture, University of Tehran. The results showed by increasing the concentration of lead in the soil, its amount increased in three parts of shoots, roots and flowers of the plant and the highest accumulation of lead in the roots was found to be 41. 27 mg/kg. The high lead pollution reduced the fresh and dry weight of shoots and roots and the root length as compared to the control. Also, total antioxidants and glycine betaine as a defensive factor against stress were found at a concentration of 400 mg/kg lead, which were 61. 3% and 114. 33 μ mol/g, respectively. Therefore, violet can be recommended as an adsorbent of lead and a stress reliever in urban and industrial green space cultivation.

To determine the water exchanges between surface and ground waters through river bed, it is necessary to have an accurate estimation of hydraulic conductivity of the river bed. But, the measurement of river bed hydraulic conductivity is difficult, time-consuming and costly. The grain size analysis methods estimate the hydraulic conductivity using the data obtained from the grain size distribution curve and the porosity of the soil, without any field measurements. The purpose of this study is to compare the estimated hydraulic conductivities, using some grain-size analysis equations (Kg), with the values measured by permeameter (Kv) method in Karkheh, Dez and, Shavoor river beds in Shush County, Khuzestan Province. In this study, the accuracy of seven empirical equations were investigated using 18 samples obtained from the measuring stations. The Kv values at Karkheh, Dez, and Shavoor river bed were measured to be 2. 15, 2. 94 and 0. 03 m/day, respectively. In Shavoor River bed with clay texture, all the equations overestimate the Kg up to 84. 6 times more than the Kv. While, in the other rivers with coarse grains, the estimated Kg by Alyamani-sen was less than the Kv, and the Kg estimated by Terzaghi, Hazen, Beyer and USBR was more than the Kv and the Kg estimated by Slichter and Kozney equations resulted a Kg close to the Kv. Moreover, the ratio of the new proposed C coefficient to the original C coefficient of equations were calculated between "0. 15 to 2. 1". Based on the results, it is necessary to use the modified coefficient of C for utilization of grain size methods.

Soil moisture reduction is one of the main effective factors on wind erosion and dust storm. Mulch application is a convenient strategy to enhance soil water retention. This study was performed to evaluate the effects of recombinant organic and mineral mulches on water retention in different matric potential including 330, 1000, 3000, 5000 and 15000 cm in erodible soils (Silty loam). in this study the effectiveness of three recombinant mulch types including organic (O) combination of Bagass biochar, Arabic gum and Gelatin in three levels, organic-mineral mulch (M) named MNF in three kevels consist of 1, 3 and 5% and Hydrogel combined with nanosilica (H) in three levels 1, 3 and 5%, incorporated with soil in the plots with 5*30*50 cm dimension, at 75% of FC for 2 and 4 incubations periods were evaluated on soil moisture properties. The experiment was performed as factorial in randomized completely design with 3 replications. With increasing the treatments levels in two and four month incubation persids, soil water retention increased significantly (P<0. 01) at the proposed suctions. Also application of treatments to the soil enhanced the organic carbon and aggregate stability, meaningfully. The highest organic carbon content and aggregate stability was observed for organic mulch (the combination of Bagasse biochar, Arabic gum and Gelatine). Moreover, at high levels of Hydrogel combined with Nanosilica and also MNF the enhancement in aggregate stability was observed for two month incubation. In addition the TGA analyses clearly show the high resistance of produced mulches against temperature. The high resistance against temperature is a positive item related to the recombinant mulches in order to apply the hotspots. In general, the application of recombinant organic and mineral mulch is a convenient scenario to cover the purposes of sustainable management.

Nitrogen is one of the most widely used nutrients for crop development. Application of nitrogen fertilizers plays a crucial role in increasing agricultural yield and production. In order to achieve maximum crop yield and reduce the negative environmental effects, application of nitrogen fertilizers should be based on the dynamics between nitrogen supply and crop demand. In order to manage the consumption of nitrogen fertilizers, it is necessary to accurately predict the crop nitrogen requirements at different growth stages. In present study, the concept of critical nitrogen concentration (Nc) has been used as an effective approach to determine nitrogen status and estimate nitrogen requirement of basil. For this purpose, basil was cultivated in the research greenhouse of the College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Different nitrogen fertilizer treatments were applied at seven levels with three replications. Crop dry matter and nitrogen concentrations were measured seven times during the growth period. Then nitrogen nutrition index (NNI) and basil nitrogen requirement (NR) were calculated for the first experiment. Results showed that, there was a significant regression relationship between basil NNI and NR (R2> 0. 96). Accordingly, the NR prediction model was developed using NNI values and day after planting (DAP). Then, accuracy and performance of the NR-NNI relationship were verified by the second experiment data. The values obtained for RMSE, NMB and NRMSE statistical indicators were less than 1 kg / ha, 0. 10% and 3. 10%, respectively, which indicates high accuracy of the model for prediction of crop nitrogen requirement. In general, results showed that estimation of crop NR based on the concept of Nc could be used as a scientific and suitable approach for managing nitrogen application in agricultural production.

Different regions have different potentials in dust release, and the increase in dust storms indicates the dominance of the desert ecosystem in each region. Prediction of the occurrence of dust storms in critical regions allow desion-makers to efficiently manage and to mitigate its probable damages to landscape. This study aims to predict the frequency of dust storm days (FDSD) over two critical regions (west and southeast) in Iran on a seasonal scale. To this end, the hourly dust data and World Meteorological Organization codes were gathered in six synoptic stations of Zabol and Zahedan (southeast Iran), Abadan, Ahvaz, Bostan, and Masjed Soleiman (west Iran) covering the statistical period of 25 years (1990-2014). After calculating the frequency of dust storm days, using four artificial intelligence methods including multi-layer perceptron (MLP), adaptive neuro-fuzzy inference system (ANFIS), radial basis function (RBF), and general regression neural network (GRNN), the frequency of dust storm days for the next season were predicted. The results showed an increase in the accuracy of the predictions with increasing the number of dust storm days in such a way that based on the results obtained from the MLP model, the correlation coefficient between the observed and predicted values of the frequency of dust storm days for Masjed Soleiman and Zabol stations were 0. 8 and 0. 97, respectively; explaining that Zabol have the highest frequency among these stations. Also, according to the results of ANFIS, RBF, and GRNN models, the correlation coefficient calculated for prediction in Masjed Soleiman and Zabol stations varied from 0. 41 to 0. 95, 0. 35 to 0. 92 and 0. 22 to 0. 98, respectively. Overall, by comparing the results of the proposed models, ANFIS had the best performance which was followed by GRNN. The results of this study can be useful in managing the issues caused by dust storms and in the combating plans to desertification in the study regions.

Phosphorus (P) is the second macronutrients and zinc (Zn) is the most important micronutrients that their deficiencies are the most important global nutrient disorders in the world paddy fields. The current field study was conducted to evaluate the effect of Zn and P foliar application (each at three levels) on their content in rice tissues and grains bio-fortification (Zn and protein content). A field experiment as factorial form was conducted in a completely randomized block design with three replications in 2017-2018, at research farm of Rice Institute in Rasht, Iran. The results of the variance analysis indicated that all the applied treatments and their interactions significantly influenced the Zn and P content of rice tissues, Zn and protein contents of rice grains. The heighest zinc content increased in the leaves four times, in the stem and panicle three times and the phosphorous content increased in all organs two times, at flowering and ripening stages. The highest content of grain Zn in Hashemi and Guilaneh cultivars, treated by foliar application of Zn (using 5 ppt ZnSO4) one week before flowering and grain filling stages, were recorded to be about 39. 06 mgkg-1 (27. 11% more than the control) and 35. 37 mgkg-1 (27. 37 % more than the control ), respectively. Also, the highest content of grain protein in Hashemi and Guilaneh cultivars with no significant difference treated by foliar application of Zn (using 5 ppt ZnSO4) one week before flowering and grain filling stages were recorded to be about 11% (32. 37% more than the control) and 10. 67% (38. 21 % more than the control), respectively. The proposed cultivars have been similarly responded to the applied treatments. It can be concluded that the foliar application of Zn, one week before flowering and grain filling stages might be a quick and proper solution to enhance grain Zn and protein content.

The Flip bucket is one of the spillway components of dams used to dissipate the flow kinetic energy. In these dissipaters, Part of supercritical flow energy due to air friction and partly due to mixing and turbulence in the erosion cavity that is formed at the landing site is dissipated. One of the geometrical parameters affecting the hydraulic performance of flip buckets is the angle of the bucket edge. In this study, using FLOW 3D software and RNG K-ε turbulence model, flow on Gavoshan Dam spillway and flip bucket was simulated in order to determine the hydraulic flow characteristics and the effect of bucket edge angle on the hydraulic flow pressure, outlet depth, velocity and developing of outlet jet as well. In order to validate the parameters obtained from numerical analysis, the experimental results of Gavoshan dam spillway hydraulic model have been used. Comparison of the results of numerical model with experimental data indicates acceptable agreement of the numerical results. The results show that increasing the angle of the bucket edge has a little effect on the maximum pressure on the bucket while it increases the depth and decreases the outlet flow velocity of the bucket. The 30° angle was determined as the optimum angle of the flip bucket edge in terms of increasing energy dissipation rate. Also for a fixed flip bucket edge angle with increasing discharge, the horizontal length of the upper and lower nappes of the jet are increased.

The increased levels of Arsenic, a poison element, in the soils and waters of Hashtrood city have caused different health issues for the people. Due to the lack of information about the arsenic content of the soils, the present study was conducted to survey the soil arsenic distribution and the possibility of reducing arsenic release from the soils. For this purpose, 53 soil samples from the top layer were collected and the arsenic concentration and distribution map was determined. Additionally, in order to evaluate the effect of iron hydroxide and gypsum as soil amendments, five polluted soil samples were selected and treated with the proposed amendments; each at three levels. The results revealed that the agricultural soils of the studied area are polluted by arsenic, as its average concentration was 49. 36 mg/kg, but more than 80 percent of the studied soils had a lower concentration than the standard level. The agricultural soils of Ghopoz and Ghezellou showed the highest arsenic contamination. Application of iron hydroxide reduced the arsenic releasement in different soils significantly, as 10 ton/hectare iron hydroxide application reduced arsenic solution 64. 5, 82. 4, 83. 7, 98. 9, and 100 percent in the soils of 1, 2, 3, 4, and 5, respectively. Increasing the level of iron hydroxide application decreased arsenic release more intensively. Similarly, the gypsum decreased the arsenic release significantly and its reduction was more by increasing gypsum application In comparison to gypsum, the iron hydroxide was much more effective in controlling the arsenic releasement.

One of the important aspects in describing river behavior is its curvature. The production of successive bends in natural rivers is an inevitable component of the process through which the river changes. Understanding the flow behavior in the interaction between the main channel and the floodplain, especially during floods, is necessary to protect soil and water structures. This study was conducted to better understand the hydrodynamics of the middle and turbulent flow in compound meandering channels. According to the natural conditions of most rivers, due to variation of discharge and depth ratios (flow depth in floodplain to flow depth in the main channel), in this study, a rectangular meander laboratory channel with a constant sinuosity 1. 3 for different depth ratios of 0. 35 and 0. 55 was investigated. The results showed that the size of velocity components (u, v, w) at 0. 35 relative depth was greater than 0. 55, which indicating higher vortex strength and interaction intensity between the main channel and floodplain at lower relative depth. Also, by investigating the secondary flows, the existence of clockwise and counterclockwise rotational eddy currents in the main channel and floodplains and the location of these currents were determined.

Sugar beet is one of the main products with high water requirement in Urmia Lake basin. Planting spacing and irrigation method of sugar beet has an important impact on increasing irrigation efficiency, crop yield and physical water productivity of this crop. In order to investigate the effect of planting spacing on irrigation efficiency, physical water productivity and crop yield, a field study was conducted on two pilot farms (A and B) in Miandoab irrigation network under farmer’ s management during 2017. In this study a part of each farm was considered as control (common planting spacing and border irrigation) and the other part was considered as treatment (change the planting spacing and surface irrigation method from border to furrow irrigation). The control part of the farm included a low height groove inside the border and at 50 cm intervals (IA-C and IB-C) and the treatment part of each farm included two-row crop planting of sugar beet (so-called 40×60 cm: IIA-T and IIB-T) and furrow irrigation. According to the results, the maximum water application efficiency was obtained about 77. 2% in IIA-T and the lowest efficiency was obtained about 10. 2% in IB-C. The average irrigation efficiency (in 12 irrigation) in IIA-T and IIB-T were 54. 5% and 51. 1%, respectively and in IA-C and IB-C were 38. 7% and 39. 3%, respectively. Based on the results, by changing the planting pattern from common spacing to two-row (40×60) and irrigation method from border to furrow, the average water consumption reduced about 29. 7% and the average yield increase from 64. 3 to 74 ton/ha (increase by 15. 2%). Also, the average physical productivity of sugar beet increased from 3. 75 to 6. 47 kg/m3 (increase of 2. 71 kg/m3).

In order to investigate the yield and water use efficiency of wheat (Chamran 2), rapeseed (Hyola 50), potato (Sante) and corn (704) under different levels of irrigation, the present research was carried out in two years 2017-2018 and 2018-2019 as complete randomized block design with four replications at Agricultural Research Center of Jiroft. Irrigation levels were 50, 75 and 100 % of the crop's water requirement. The Yield, biomass, harvest index and water use efficiency were investigated for the proposed crops. The results showed that the effect of irrigation levels was significant during two years on grain yield, biomass and water use efficiency at 1% level and on harvest index at 5% level. By increasing irrigation water, both grain yield and biomass were increased significantly in all crops. Potato and rapeseed had the highest (0. 65-0. 74) and the lowest (0. 20-0. 25) water index, respectively. On the other hand, potato and rapeseed showed the highest (10. 68-22. 76 kg/m3) and the lowest (1. 29-1. 84 kg/m3) water use efficiency, respectively. The 75% irrigation level is recommended due to lower decrease in yield and higher increase in water use efficiency. In general, according to the results of this study, the highest water use efficiency was observed in potato, wheat, maize and rapeseed plants, respectively. Overall potato and maize rotation is recommended due to higher water use efficiency in Jiroft.