Evaluating the Effect of Combined Water and Salinity Stresses in Estimating the Fodder Maize Biological Yield Through Periodic Evaporation and Transpiration

IntroductionThe rise in water demand and reduction of water quality and soil in irrigating areas, especially in dry and semi-arid areas of the world, have turned into one of the most crucial challenges for water and soil engineering in recent years. This issue leads us toward optimal quantitative and qualitative management of these valuable resources aimed at achieving economic performance and water productivity. The periodic evaporation and transpiration of the plant in the conditions of simultaneous water and salinity stress are known as one of the most important factors in the qualitative and quantitative growth of the plant yield. Applying mathematical models that simulate the relationship between field variables and yield can be seen as a useful tool in water and soil management issues in such a situation, which has the potential to ensure optimal use of the water and soil resources of any country by providing the plant's water needs and preventing its further loss.Materials and MethodsA factorial experiment was performed in 2019 based on completely randomized blocks design with three replications in plots with an area of 9 square meters at the agricultural and animal husbandry farm of Aliabad Fashafuyeh, located in Qom province to examine the simultaneous effect of different levels of water stress and salinity on the periodic evaporation-transpiration and fresh yield of the single cross 704 forage corn cultivar. The applied treatments included the irrigation water salinity at three electrical conductivity levels of 1.8 (S0), 5.2 (S1), and 8.6 (S2) deci Siemens/meter (dS/m), which were prepared by mixing saline well water of the region with fresh (drinking) water and three water stress levels of 100% (W0), 75% (W1), and 50% (W2) of the plant's water requirement. The depth of soil moisture in the corn plant root zone was measured by the TDR device at five depths of 7.5, 12, 20, 40, and 60 cm during different growth stages of the plant using pairs of 7.5, 12, and 20 cm stainless steel electrodes.Results and DiscussionThe simultaneous water and salinity stresses, which led to the reduced amount of periodic evaporation-transpiration of the yield compared to ideal conditions (without stress), were simulated by additive and multiplicative models. The results suggested a decrease in the evaporation and transpiration with the increased simultaneous water and salinity stresses so that the amount of total evaporation-transpiration in different treatments was measured to be between 692.7 and 344.9 mm and the fresh yield was estimated between 50.4 and 3.2 tons per hectare. Also, the highest amount of periodic evaporation and transpiration in all treatments was found to occur in the development and intermediate stages, and the relative fresh yield in the W0S0 to W2S2 treatments was calculated between 66% and 100%. The results of modeling the relative yield of the crop based on the amounts of relative evaporation and transpiration of corn in different growth stages and under the different treatments of water stress and salinity, indicated that Singh's additive model and Rao's multiplicative model were appropriate, while the Minhas model was recognized to be inappropriate in this estimation.ConclusionThe research results suggested the significant impact of water stress and salinity at least at the 95% level on evaporation and transpiration and the corn yield. Moreover, the effect of the sensitivity of different growth stages of the plant on the reduction of evaporation and transpiration of corn varies so that in the three treatment groups W0, W1, and W2, the highest average decrease in slope was related to the final stage (13.6%) followed by the middle stage with an average decrease of 8.4% compared to the control treatment. Therefore, the highest decrease rate in evaporation-transpiration slope has been observed in these two growth stages due to the beginning of flowering, fruit formation, and physiological ripening of seeds. These results come from the lack of sufficient water storage and increased salinity of irrigation water in the soil. Water stresses and salinity will reduce water absorption and evaporation-transpiration, and ultimately, reduce crop production due to the decreased amount and potential of water in the soil. Another finding to be mentioned is the priority of water stress compared to salinity stress in reducing evaporation and transpiration and production yield. Also, by managing water and salinity stresses in the critical stages of plant growth (especially the middle stage), which is the time of flowering and the beginning and completion of the maize production process, a significant reduction in the crop can be somewhat prevented

Estimation of Water Footprint Compartments in National Wheat Production

Introduction: Water use and pollution have raised to a critical level in many compartments of the world. If humankind is to meet the challenges over the coming fifty years, the agricultural share of water use has to be substantially reduced. In this study, a modern yet simple approach has been proposed through the introduction concept ‘Water Footprint’ (WF). This concept can be used to study the connection between each product and the water allocation to produce that product. This research estimates the green, blue and gray WF of wheat in Iran. Also a new WF compartment (white) is used that is related about irrigation water loss. Materials and Methods: The national green (Effective precipitation), blue (Net irrigation requirement), gray (For diluting chemical fertilizers) and white (Irrigation water losses) water footprints (WF) of wheat production were estimated for fifteen major wheat producing provinces of Iran. Evapotranspiration, irrigation requirement, gross irrigation requirement and effective rainfall were got using the AGWAT model. Yields of irrigated and rain-fed lands of each province were got from Iran Agricultural-Jihad Ministry. Another compartment of the wheat production WF is related about the volume of water required to assimilate the fertilizers leached in runoff (gray WF). Moreover, a new concept of white water footprint was proposed here and represents irrigation water losses, which was neglected in the original calculation framework. Finally, the national WF compartments of wheat production were estimated by taking the average of each compartment over all the provinces weighted by the share of each province in total wheat production of the selected provinces. Results and Discussion: In 2006-2012, more than 67% of the national wheat production was irrigated and 32.3% were rain-fed, on average, while 37.9% of the total wheat-cultivated lands were irrigated and 62.1% was rain-fed from more than 6,568 -ha. The total national WF of wheat production for this period was estimated as 42,143 MCM/year, on average. Different compartments of wheat WF were estimated for 236 plains in fifteen selected provinces. For irrigated areas, the green WFs ranged from 499 to 1,023 m3/ton, the blue WFs from 521 to 1,402 m3/ton, the gray WFs from 337 to 822 m3/ton, and the white WFs from 701 to 2,301 m3/ton. The average total WF for irrigated areas among all the selected provinces is about 3,188 m3/ton, with almost equal shares of blue and green water. For rain-fed areas, the green WFs ranged from 1,282 to 4,166 m3/ton and the gray WFs from 100 to 740 m3/ton. The average total WF for rainfed areas is about 3,071 m3/ton with the share of green WF being nine times the gray WF. In irrigated areas, the percentages of green, blue, gray and white WFs are 23, 25, 17 and 35% of total WF, respectively in each province. The average total WF for irrigated areas is about 3,188 m3/ton with comparable shares of blue and green water. In irrigated areas, Fars, Khorasan and Khuzestan provinces have the largest of the total WF with 5,575, 5,028 and 4,123 MCM/year, respectively. In addition to large cultivated areas and high rates of potential evapotranspiration, high values of gray and white water is another reason for the high volume of total WF in these provinces. Conclusions: The results showed that the green WF related about wheat production in our country is about 2.3 times the blue WF. It confirmed the importance of green water in wheat production. Also the gray water footprint was assessed which is related about nitrogen application. Besides, the white water footprint was proposed here, which represents irrigation water losses. Results showed that the total water footprint in wheat production for the whole country is about 42,143 MCM/year on average over the period of 2006-2012. The ratios of green, blue, gray and white water were 41, 18, 16 and 25%, respectively. Different compartments of wheat WF were estimated for 236 plains over fifteen selected provinces. Total shares of gray and white water footprint were 41% of total wheat production water footprint. The average total WF for irrigated areas among all selected provinces is about 3,188 m3/ton, with almost equal shares of blue and green water. The authors admit that the accuracy of these results is subject to the quality of the input data

Evaluación de modelos para estimar la infiltración y rugosidad del riego por surcos

Several methods have been proposed for estimating infiltration and roughness parameters in surface irrigation using mathematical models. The EVALUE, SIPAR_ID, and INFILT models were used in this work. The EVALUE modeluses a direct solution procedure, whereas the other two models are based on the inverse solution approach. The objective of this study is to evaluate the capacity of these models to estimate the Kostiakov infiltration parameters and the Manning roughness coefficient in furrow irrigation. Twelve data sets corresponding to blocked-end and free drainingfurrows were used in this work. Using the estimated  parameters and the SIRMOD irrigation simulation software, the total infiltrated volume and recession time were predicted to evaluate the accuracy of the mathematical models. TheEVALUE and SIPAR_ID models provided the best performance, with EVALUE performing better than SIPAR_ID for estimating the Manning roughness coefficient. The INFILT model provided lower accuracy in cut-back irrigation than in standard irrigation. The performance of SIPAR_ID and INFILT in blocked-end and free draining furrows was similar.En el riego por superficie se han propuesto varios métodos basados en modelos matemáticos para estimar los  parámetros de infiltración y rugosidad. En este trabajo se han utilizado los modelos EVALUE, SIPAR_ID e INFILT. El modelo EVALUE utiliza un procedimiento de solución directa, mientras que los otros dos se basan en un enfoque de solución inversa. El objetivo de este estudio fue evaluar la capacidad de estos modelos para estimar los parámetros deinfiltración de Kostiakov y el coeficiente de rugosidad de Manning en el riego por surcos. Se utilizaron en doce evaluaciones de riego por surcos, bien bloqueados en el extremo o bien con desagüe libre. Utilizando los parámetros estimados y el software de simulación de riego por gravedad SIRMOD, se predijeron el volumen total infiltrado y el tiempo de receso para evaluar la precisión de los modelos  matemáticos. Los modelos EVALUE y SIPAR_ID proporcionaronel mejor rendimiento, dando mejores resultados EVALUE que SIPAR_ID para estimar el coeficiente de rugosidad de Manning. El modelo INFILT fue menos preciso en el riego con recorte de caudal que en el riego estándar. El rendimiento de SIPAR_ID e INFILT fue similar en los surcos bloqueados en el extremo y con desagüe libre

Evaluation of the Influence of Different ETO Estimation Methods in Simulation of Wheat Actual Evapotranspiration and Biomass by AquaCrop Model

IntroductionEvaluation of plant models in agriculture has been done by many researchers. The purpose of this work is to determine the appropriate plant model for planning and predicting the response of crops in different regions. This action is made it possible to study the effect of various factors on the performance and efficiency of plant water consumption by spending less time and money. Since the most important agricultural product in Iran is wheat, so proper management of wheat fields has an important role in food security and sustainable agriculture in the country. The main source of food for the people in Iran is wheat and its products, and any action to increase the yield of wheat is necessary due to limited water and soil resources. Evapotranspiration is a complex and non-linear process and depends on various climatic factors such as temperature, humidity, wind speed, radiation, type and stage of plant growth. Therefore, in the present study, by using daily meteorological data of Urmia, Rasht, Qazvin, Mashhad and Yazd stations, the average daily evapotranspiration values based on the results of the FAO-Penman-Monteith method are modeled and the accuracy of the two methods temperature method (Hargreaves-Samani and Blaney-Criddle) and three radiation methods (Priestley-Taylor, Turc and Makkink) were compared with FAO-56 for wheat.Materials and MethodsThe present study was conducted to evaluate the accuracy and efficiency of the AquaCrop model in simulation of evapotranspiration and biomass, using different methods for estimation reference evapotranspiration in five stations (Urmia, Qazvin, Rasht, Yazd and Mashhad). Four different climates (arid, semi-arid, humid and semi-humid) were considered in Iran for wheat production. The equations used to estimate the reference evapotranspiration in this study are: Hargreaves-Samani (H.S), Blaney-Criddle (B.C), Priestley-Taylor (P.T), Turc (T) and Makkink (Mak). Then, the results were compared with the data of the mentioned stations for wheat by error statistical criteria including: explanation coefficient (R2), normal root mean square error (NRMSE) and Nash-Sutcliffe index (N.S).Results and DiscussionThe value of the explanation coefficient (R2) of simulation ET and biomass in the Blaney-Criddle method is close to one, which shows a good correlation between the data. The NRMSE and Nash-Sutcliffe values for both parameters and the five stations are in the range of 0-20 and close to one, respectively, which indicates the AquaCrop model's ability to simulate ET and biomass. On the other hand, the value of R2 in the Hargreaves-Samani method for biomass close to one, NRMSE in the range of 0-10 and Nash-Sutcliffe index is more than 0.5, which indicates a good simulation. The NRMSE index in the evaluation of ET and biomass wheat is excellent for the Blaney-Criddle method and about Hargreaves-Samani for ET is poor and for the biomass is excellent.The Turc method with NRMSE in the range of 0-30, explanation coefficient close to or equal to one and a Nash-Sutcliffe index of one or close to one can be used to simulate ET and biomass at all five stations. Also, for biomass simulation, Priestley-Taylor and Makkink methods have acceptable statistical values in all five stations.Based on the value of explanation coefficient (R2) of estimation ET and biomass wheat for radiation methods, the correlation between the data in all three radiation methods is high. Percentage of NRMSE index of Makkink method for wheat in ET evaluation in Qazvin station is poor category and in Urmia and Rasht is good and in Mashhad and Yazd is moderate and about biomass in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd) is excellent category, the error percentage of Priestley-Taylor method for wheat in ET evaluation in Yazd station is good and the rest of the stations is poor, about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd). The error rate of Turc method for wheat in ET evaluation in Urmia, Rasht and Mashhad stations is good and in Qazvin and Yazd is poor and about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd).ConclusionAccording to the results obtained using Blaney-Criddle method with R2 value close to one, NRMSE in the range of 0-20% (excellent to good) and Nash-Sutcliffe index close to one and Turc method with R2 value close to one, NRMSE in the range of 0-10% (excellent) and Nash-Sutcliffe index close to one was showed a good accuracy of AquaCrop model in simulation of evapotranspiration and biomass with these methods of estimation of evapotranspiration compared to other methods

Evaluating models for the estimation of furrow irrigation infiltration and roughness

Several methods have been proposed for estimating infiltration and roughness parameters in surface irrigation using mathematical models. The EVALUE, SIPAR_ID, and INFILT models were used in this work. The EVALUE model uses a direct solution procedure, whereas the other two models are based on the inverse solution approach. The objective of this study is to evaluate the capacity of these models to estimate the Kostiakov infiltration parameters and the Manning roughness coefficient in furrow irrigation. Twelve data sets corresponding to blocked-end and free draining furrows were used in this work. Using the estimated parameters and the SIRMOD irrigation simulation software, the total infiltrated volume and recession time were predicted to evaluate the accuracy of the mathematical models. The EVALUE and SIPAR_ID models provided the best performance, with EVALUE performing better than SIPAR_ID for estimating the Manning roughness coefficient. The INFILT model provided lower accuracy in cut-back irrigation than in standard irrigation. The performance of SIPAR_ID and INFILT in blocked-end and free draining furrows was similar.En el riego por superficie se han propuesto varios métodos basados en modelos matemáticos para estimar los parámetros de infiltración y rugosidad. En este trabajo se han utilizado los modelos EVALUE, SIPAR_ID e INFILT. El modelo EVALUE utiliza un procedimiento de solución directa, mientras que los otros dos se basan en un enfoque de solución inversa. El objetivo de este estudio fue evaluar la capacidad de estos modelos para estimar los parámetros de infiltración de Kostiakov y el coeficiente de rugosidad de Manning en el riego por surcos. Se utilizaron en doce evaluaciones de riego por surcos, bien bloqueados en el extremo o bien con desagüe libre. Utilizando los parámetros estimados y el software de simulación de riego por gravedad SIRMOD, se predijeron el volumen total infiltrado y el tiempo de receso para evaluar la precisión de los modelos matemáticos. Los modelos EVALUE y SIPAR_ID proporcionaron el mejor rendimiento, dando mejores resultados EVALUE que SIPAR_ID para estimar el coeficiente de rugosidad de Manning. El modelo INFILT fue menos preciso en el riego con recorte de caudal que en el riego estándar. El rendimiento de SIPAR_ID e INFILT fue similar en los surcos bloqueados en el extremo y con desagüe libre

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS †

Iran's climate-sensitive agriculture and water resources are vulnerable to climate change and investigation of climatic trends helps in preparing adaptation strategies. Weather stations are sparsely distributed and access to complete weather data is limited. In such situations, gridded global/regional data sets are promising alternatives. Here, monthly time series of seven weather variables (i.e. monthly averages or monthly totals of daily values) were obtained from the Climatic Research Unit TS V4.01 and Global Precipitation Climatology Centre V7 gridded data sets in 675 grid cells covering the country and analysed over the periods 1957–1986 and 1987–2016 at annual, seasonal and monthly scales. Over the two periods and at a national scale, mean temperature has increased by 0.004 (P = 0.717) and 0.04 °C yr−1 (P = 0.000), while the diurnal temperature range has not significantly changed (P > 0.6). Annual total precipitation experienced an insignificant increase (0.81 mm yr−1; P = 0.666) over the first period but declined by 2.12 mm yr−1 (P = 0.041) over the second. Potential evapotranspiration (PET) has increased by 0.32 (P = 0.398) and 1.43 mm yr−1 (P = 0.015), respectively. Since 1987, significant increasing trends in temperature were detected all over the country. While significant increasing trends in annual precipitation were detected in the central regions and south-west over the first period, decreasing trends prevailed during 1987–2016 in the south, southwest and east with winter being the largest contributor to annual trends. Over the last three decades, annual PET has increased mostly in the north-west and south-east while significant increasing trends were detected in 89% of grid cells, except in a few cells in the north-east. Cloud cover, vapour pressure and frequency of frost days were also analysed. These results are crucial for policy-makers, researchers and engineers in the country and internationally who usually base their decisions and designs on outdated data sparsely distributed in space

Development of a Multi-Aspects Groundwater Vulnerability Index in the Transboundary Aquifer between Syria, Iraq, and Turkey in light of the water conflict and climate change

Groundwater vulnerability assessment is an effective tool in the joint management of transboundary groundwater, especially in developing countries where data is scarce, monitoring networks are insufficient, and water is both a cause and a target of conflicts. The Jezira Tertiary Limestone Aquifer Transboundary System (JTLATS) region, which Syria, Iraq, and Turkey share, gives a clear description of the shared water problem in developing countries with arid and semiarid environments. In this study, a comprehensive multidisciplinary Groundwater Vulnerability Index (GVI) was developed as a distributed composite index to assess the groundwater vulnerability in JTLATS by combining different environmental and political socioeconomic datasets and models for three periods between 2003 and 2017. The JTLATS was categorized into five zones: very low, low, moderate, high, and very high vulnerability. The results showed a low vulnerability in the southern regions of the aquifer. In comparison, the areas with high vulnerability are primarily spread in the northern and western parts of the JTLATS and along the Euphrates river. The results showed an increase in the percentage of areas with high vulnerability from 10.45% in (2003-2007) to 13.42% and 20.57% of the aquifer area in (2007-2011) and (2011-2017), respectively. The groundwater vulnerability in the aquifer increased with the spread of political instability in both Syria and Iraq and the increase in cultivated areas in Turkey.Godkänd;2023;Nivå 0;2023-01-01 (hanlid)</p