Mohammad Ali Gholami Sefidkouhi

Bio: Mohammad Ali Gholami Sefidkouhi is an academic researcher from Sari Agricultural Sciences and Natural Resources University. The author has contributed to research in topics: Evapotranspiration & Environmental science. The author has an hindex of 8, co-authored 14 publications receiving 831 citations.

Surface irrigation simulation models: a review

Abstract: This paper reviews the literature and results of more than one hundred published articles in scientific journals with respect to simulation of surface irrigation. The results showed that 53.4% of the simulations belong to furrow systems. It is 35.9% for border systems and 10.7% for basin irrigation. However, satisfactory simulations were 70.3%, 63.6%, and 54.5% for border, basin, and furrow systems, respectively. The priority of irrigation methods to simulate using hydrodynamic (HD) and other models is border, basin, and furrow irrigation. It is border, furrow, and basin for kinematic wave (KW) and volume balance (VB) models. Finally, this priority is basin, border, and furrow for zero inertia (ZI) model. Meanwhile, the models estimated advance and infiltration phases better than recession and runoff phases during an irrigation event.

Simulation of open- and closed-end border irrigation systems using SIRMOD

Abstract: In many regions in the world, more than 90% of areas equipped for irrigation apply surface methods. The major problem of the surface irrigation system is low performance due to poor design, operation, and maintenance. Use of the mathematical models for simulation of surface irrigation is necessary for reducing costs and decrease of time in analysis of indexes including application efficiency and distribution uniformity. This study aims to simulate border irrigation systems using the SIRMOD (surface irrigation simulation, evaluation and design, developed by Utah State University, Logan, UT, USA) software package under open- and closed-end conditions. For this purpose, 22 sets of data including four no-cultivated open-end borders, nine no-cultivated closed-end borders, and nine cultivated closed-end borders were used. The results showed that the models predicted open-end conditions better than closed-end for recession time. In addition, the hydrodynamic (HD) and the zero inertia (ZI) models estimated volume...

Agricultural water management in the world during past half century

Abstract: The present paper aims to estimate the areas equipped for irrigation and desirability of agricultural water management in the world. For this purpose, all necessary information was gathered from Food and Agriculture Organization and checked using World Bank Group. The selected 18 indices were analysed for all 26 regions in the area studied, and the extent of area equipped for irrigation to cultivated area was estimated by 2 different formulas and other 9 indices. In addition, an average index was calculated using various methods to assess region conditions for agricultural water management. The results show that Central Asia is the best region for agricultural water management and the value of relative error is less than 20%. The capability of irrigation and drainage systems was studied using other eight indices with more limited information. The results indicated that trial-and-error policies should be avoided and expert comments be applied to irrigation systems for any crop.

Estimation of actual evapotranspiration by using MODIS images (a case study: Tajan catchment)

Abstract: Evapotranspiration (ET) is one of the most effective variables to determine water balance in a region. Accurate estimation of ET flux is vital for agricultural scheduling and water resource management. One of the ways for estimation of ET is applying energy budget methods in which parameters are determined by using remote-sensing technique. The surface energy balance algorithm for land (SEBAL) is one of the most important algorithms for estimation of ET using satellite images. This model estimates ET via estimation of all energy components in the surface such as net radiation flux, soil heat flux and sensible heat flux. This paper aims to investigate accuracy of actual ET estimation using SEBAL algorithm in comparison with calculated values by Food and Agriculture Organization (FAO) Penman–Monteith in Tajan catchment and area of Sari Dasht Naz Agricultural Corporation, Iran. In this investigation, seven images of moderate resolution imaging spectroradiometer (MODIS) were used from February to July 2011. T...

Commercial astaxanthin production derived by green alga Haematococcus pluvialis: A microalgae process model and a techno-economic assessment all through production line

Abstract: The freshwater green microalgal strain Haematococcus pluvialis is the richest source for the production of astaxanthin. Astaxanthin is member of the xanthophyll family of carotenoids and constitutes the highest value product derived by microalgae. So far, algal astaxanthin amounts to

Optimization of neural networks for precipitation analysis in a humid region to detect drought and wet year alarms

Abstract: In this study, annual precipitation was forecast by coding in MATLAB software environment based on a non-linear autoregressive neural network (NARNN), non-linear input–output (NIO) and NARNN with exogenous input (NARNNX). Historical precipitation data (27 precipitation gauge stations located in Gilan, Iran) were used as two 21 year sets from 1968 to 1988 and from 1989 to 2009 for calibration and testing of the networks, respectively. Results showed that the accuracy of the NARNNX was better than that of the NARNN and NIO, based on r values. However, performance of the networks was not satisfactory because the number of neurons in the hidden layer and the roles of training, validation and testing phases were lacking flexibility and change. Optimization of the number of neurons in the hidden layer and the determination of the best role among the different phases led to improvement of network accuracy. The r values were <0.73 only for five stations in the optimized NARNN and <0.74 only for those stations with optimized NIO.