Investigating spatiotemporal variations of precipitation across Iran over 1957-2016 using the CRU gridded dataset

Precipitation affects quantity and quality of water resources and agricultural production. Therefore, the estimation and analysis of its spatial-temporal variations is of great importance. In many regions of Iran, limited spatial-temporal information is available due to sparse distribution of monitoring stations and short observational records. On the other hand, dependency of rain-fed and irrigated production systems on precipitation increases the importance of the analysis of spatiotemporal variations of this weather variable. One way to address this limitation is to use regional/global gridded datasets. In this study, monthly precipitation data were obtained from the CRU dataset (developed principally by the UK's Natural Environment Research Council (NERC) and the US Department of Energy) and used to investigate temporal trends in annual, seasonal and monthly precipitations in 675 grid cells (0.5°×0.5°) across Iran over two periods, 1957-1986 and 1987-2016. The results of the previous studies showed that the CRU gridded dataset offers quality data in Iran, especially for trend analysis. Also, the accuracy of the CRU dataset was validated in 14 selected stations regarding monthly precipitations and temporal trends over two different periods, pre-1987 and post-1987. The significance of temporal trends was assessed using a modified version of the rank-based nonparametric Mann-Kendall (MK) test. Trend magnitudes (i.e. slope) were estimated with the Theil-Sen approach and the Trend Free Pre-whitening (TFPW) procedure was applied to remove the effect of serial correlation. The results confirm the acceptable accuracy of the CRU dataset for trend analysis purposes, especially over the last three decades, except in the northern strip of the country (RMSE=10.71mm, R2=0.84). Two 30-year periods (1957-1986 and 1987-2016) were compared in terms of spatial patterns and temporal trends. Annual precipitation over the last three decades (1987-2016) has decreased as compare to the previous 30-year period (1957-1986) in most parts of the country. Over the last three decades, around 42% and 50% of the country’s total area experienced significant and insignificant decreasing trends in annual precipitation, respectively. National average annual precipitation has decreased by 15.78 mm/decade over the same period. Three important regions regarding agricultural production experienced the most significant reductions in annual precipitation: (1) Ardebil, East Azerbaijan, Kurdistan, Kermanshah, Ilam, Lorestan, Zanjan, Hamadan, and parts of West Azerbaijan, Markazi and Gilan (in the west and northwest), (2) Sistan and Baluchestan, Kerman, and southern parts of South Khorasan (in the south and south east), and (3) North Khorasan, northern parts of Razavi Khorasan and east of Golestan (in the east and north east). Reduced annual precipitation was mainly attributed to the reduction in seasonal precipitations in winter and spring, which have critical role in agricultural production and domestic water supply. Temporal trends were also analysed at the monthly scale. January, February, March and December revealed the largest number of grid cells with significant decreasing trends over 1987-2016 while November is the only month with significant number of grid cells experiencing significant increasing trends. The results of this study show that the monthly time series of the CRU TS 4.01 dataset, which has an almost complete spatial and temporal coverage in Iran over the last 60 years, are promising alternatives to weather station observations especially in data-scarce regions of Iran. Analysis of variations and the seasonal and monthly scales help understand the recent climate change and target the most crucial features of it when it comes to formulating adaptation strategies

Impact of genotypic variations in transpiration rate on Australian wheat productivity

Crop water productivity has been receiving special attention in regards to productivity and food security. Limited-transpiration rate (LTR) at high vapour pressure deficit (VPD) has potential to improve drought adaptation. The quantification of the impact of LTR on water consumption, biomass accumulation and yield formation requires the use of dynamic crop modelling to simulate physiological and environmental processes at a suitable time scale and across environments. Here, a new module for the new generation of Agricultural Production Systems sIMulator (APSIM-NextGen) was developed and evaluated, which enables the simulation of atmospheric (VPD) and edaphic water effects on transpiration, biomass production and yield. The module was used to assess the potential of the LTR trait at improving transpiration efficiency at 60 sites across the Australian wheatbelt. Results showed that selection for the LTR trait could result in a 2.5% increase in grain yield nationally through significantly higher transpiration efficiency. Greatest productivity gains were found in eastern part of the wheatbelt where crops rely heavily on stored soil moisture and saving water mid-day (i.e. under high VPD) allows crops to consume it at more critical stages later during the crop cycle

Investigating Spatiotemporal Variations of Precipitation across Iran over 1957-2016 using the CRU Gridded Dataset

Precipitation affects quantity and quality of water resources and agricultural production. Therefore, the estimation and analysis of its spatial-temporal variations is of great importance. In many regions of Iran, limited spatial-temporal information is available due to sparse distribution of monitoring stations and short observational records. On the other hand, dependency of rain-fed and irrigated production systems on precipitation increases the importance of the analysis of spatiotemporal variations of this weather variable. One way to address this limitation is to use regional/global gridded datasets. In this study, monthly precipitation data were obtained from the CRU dataset (developed principally by the UK's Natural Environment Research Council (NERC) and the US Department of Energy) and used to investigate temporal trends in annual, seasonal and monthly precipitations in 675 grid cells (0.5°×0.5°) across Iran over two periods, 1957-1986 and 1987-2016. The results of the previous studies showed that the CRU gridded dataset offers quality data in Iran, especially for trend analysis. Also, the accuracy of the CRU dataset was validated in 14 selected stations regarding monthly precipitations and temporal trends over two different periods, pre-1987 and post-1987. The significance of temporal trends was assessed using a modified version of the rank-based nonparametric Mann-Kendall (MK) test. Trend magnitudes (i.e. slope) were estimated with the Theil-Sen approach and the Trend Free Pre-whitening (TFPW) procedure was applied to remove the effect of serial correlation. The results confirm the acceptable accuracy of the CRU dataset for trend analysis purposes, especially over the last three decades, except in the northern strip of the country (RMSE=10.71mm, R2=0.84). Two 30-year periods (1957-1986 and 1987-2016) were compared in terms of spatial patterns and temporal trends. Annual precipitation over the last three decades (1987-2016) has decreased as compare to the previous 30-year period (1957-1986) in most parts of the country. Over the last three decades, around 42% and 50% of the country’s total area experienced significant and insignificant decreasing trends in annual precipitation, respectively. National average annual precipitation has decreased by 15.78 mm/decade over the same period. Three important regions regarding agricultural production experienced the most significant reductions in annual precipitation: (1) Ardebil, East Azerbaijan, Kurdistan, Kermanshah, Ilam, Lorestan, Zanjan, Hamadan, and parts of West Azerbaijan, Markazi and Gilan (in the west and northwest), (2) Sistan and Baluchestan, Kerman, and southern parts of South Khorasan (in the south and south east), and (3) North Khorasan, northern parts of Razavi Khorasan and east of Golestan (in the east and north east). Reduced annual precipitation was mainly attributed to the reduction in seasonal precipitations in winter and spring, which have critical role in agricultural production and domestic water supply. Temporal trends were also analysed at the monthly scale. January, February, March and December revealed the largest number of grid cells with significant decreasing trends over 1987-2016 while November is the only month with significant number of grid cells experiencing significant increasing trends. The results of this study show that the monthly time series of the CRU TS 4.01 dataset, which has an almost complete spatial and temporal coverage in Iran over the last 60 years, are promising alternatives to weather station observations especially in data-scarce regions of Iran. Analysis of variations and the seasonal and monthly scales help understand the recent climate change and target the most crucial features of it when it comes to formulating adaptation strategies

Numerical Investigation of Forced Convection of Nanofluid Flow in Microchannels: Effect of Adding Micromixer

In the present study, forced convection of CuO–water nanofluid in a two dimensional parallel plate microchannel with and without micromixers has been investigated numerically. Two horizontal hot baffles were inserted between the adiabatic plates and three vertical baffles, which were attached on the plates, worked as micromixers in order to improve the cooling process. The effect of Reynolds number, Re = 10, 30, 60, 100, and 150 and nanoparticles volume fraction, from 0 to 4%, were examined on flow field and heat transfer. Different geometrical configurations for the arrangement of the hot baffles were tested. A FORTRAN code based on finite volume method was developed to solve the governing equations and SIMPLER algorithm was used for handling the pressure-velocity coupling. Simulations showed that the presence of micromixers and increasing the Reynolds number as well as nanoparticles volume fraction, increase the average Nusselt number. In order to achieve maximum heat transfer, best arrangements for the baffles were reported. It was also observed that the size of recirculation zones, which are created behind the micromixer baffles, increases with increasing Reynolds number and leads to better cooling

Environmental characterization facilitate G × E interaction to highlight the role of stay-green traits for genetic gain

Environmental characterization (EC) one influential approach for understanding the performance of genotypes in different environments. Sometimes interactions between environment and genotype limit the genetic gain for complex traits in breeding programs, especially drought. Stay green lines are able to retain green leaf area longer than standard lines leading to superior adaptation under water-limitation. Modelling framework has been used analytically in breeding to dissect complex traits, such as yield under water limitation, into critical trait components (e.g. stay-green, flowering time, root architecture). Characterization can help to select more heritable genotypes that can be subjected to high throughout phenotyping, and make more sensible targets for genomic selection by the following search aims: (1) Characterise stressed environments (accounting for climate and soil characteristics, management practices, and crop development) to characterise the timing and severity of the stress and non-stress, (2) Identify the potentially adaptive cultivars and traits in each specific environment, and (3) Determine the correlation between stay-green traits and yield in the different environment types

Assessing the performance of SWAT model in Zayandeh-Rud Watershed

Life in Esfahan province is dependent on Zayandeh Rud. Therefore, sustaining the quality and quantity of Zayandeh Rud water is of much importance. The first step for adopting correct management decisions is to have continuous awareness of water quality and quantity, temporal changes, and spatial variations and, eventually, specification of main source of pollution. One of the models being used worldwide in such studies is SWAT. The first step in using this king of models is to prove their ability to simulate hydrologic cycle in a the watershed. The main goal of this study was to assess SWAT performance in Zayandeh Rud watershed in order to simulate river flow rate values. Model Calibration and validation were done by using average daily flow in four stations named Ghal’e Shahrokh, Zayandeh Rud Dam, Pole Kole and Varzaneh. Observed and simulated values were compared by statistics including R2, NS and COE values to evaluate the model perditions against the observed values. The results of these values for flows at four stations for calibration process were ranged between 60.2 to 80.1, 59.4 to 79.0 and 72.6 to 82.0, respectively. According to past studies and the quality of the data used in this study, these values seem acceptable. The values for validation period were 60.4 to 72.0, 60.1 to 69.1 and 64.7 to 70.8, respectively. Among these four stations, measured and simulated flows at Pole Kole and Ghal’e Shahrokh matched well and weak, respectively. In general, the results showed that SWAT could be a proper tool for simulating the flow rate values of the river