Maximizing the water productivity for any agricultural system is considered an adaptation to the potential climate change crisis. It is required, especially in arid and semi-arid environments in Iraq. Therefore, this study assessed the potential impact of climate change on the different environments in the Qadissiya and Nineveh provinces. The ensemble of six GCM models employed for the regional climate model of the HCLIM-ALADIN in high-resolution 10*10 km2 and Aqua-Crop was used to examine the response of water productivity and yield of winter wheat. With and without CO2 concentration changing under different water regimes in the near term (2020-2040) and mid-term (2041-2060) related to the reference period (1995-2014). The model was validated in both provinces to indicate good performance of RRMSE (4.54- 7.1) and d, R2 ( 1- 0.99). The main findings revealed an increase in water productivity, yield production, and transpiration reduction under the CO2-changing scenario and behaved stable under the fixed concentration scenario. The developed schedule enhanced water productivity in both locations. The assessment study examined the resilience of arid and semi-arid agricultural lands under future climate change.
This study was conducted to examine the anatomical aspects of
Land snails constitute an important group of mollusks distributed worldwide. This study reports on land snails found in Iraq. A survey of terrestrial gastropods was performed during their activity seasons in gardens, agricultural lands and nurseries in Iraq from March 2022 to September 2023. Fifteen terrestrial snails belonging to seven families were documented. The species Euchondrus michonii (Bourguignat, 1853) was identified and recorded based on several distinct conchological characters for the first time in Iraq. The recently collected specimens, along with those previously recorded in Iraq, were included in this checklist. Essential information on each species is also presented. As there is no previous checklist or study that
... Show MoreThe Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from
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In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min
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