Hakan Arslan

Prof. Dr. Hakan Arslan

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 June 2022 in Stochastic Environmental Research and Risk Assessment
Verified
Journal Article
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BCBilal Cemek
Bilal Cemek
HAHakan Arslan
Hakan Arslan
EKERDEM KÜÇÜKTOPÇU
ERDEM KÜÇÜKTOPÇU
Halis SimsekHalis Simsek
Halis Simsek

20 August 2019 in Water
Verified
Journal Article
Open access
PDF file
HKHakan Kadioglu
Hakan Kadioglu
HHHarlene Mae Hatterman-Valenti
Harlene Mae Hatterman-Valenti
Xinhua JiaXinhua Jia
Xinhua Jia
XCXuefeng Chu
Xuefeng Chu
HAHakan Arslan
Hakan Arslan
Halis SimsekHalis Simsek
Halis Simsek
Lysimeter experiments were conducted under greenhouse conditions to investigate canola (Brassica napus L.) plant water use, growth, and yield parameters for three different water table depths of 30, 60, and 90 cm. Additionally, control experiments were conducted, and only irrigation was applied to these lysimeters without water table limitations. The canola plant’s tolerance level to shallow groundwater was determined. Results showed that groundwater contributions to canola plant for the treatments at 30, 60, and 90 cm water table depths were 97%, 71%, and 68%, respectively, while the average grain yields of canola were 4.5, 5.3, and 6.3 gr, respectively. These results demonstrate that a 90 cm water table depth is the optimum depth for canola plants to produce a high yield with the least amount of water utilization.

6 May 2022 in Journal of Plant Nutrition
Verified
Journal Article
Closed access
MKMehmet Sait Kiremit
Mehmet Sait Kiremit
HOHussein Mohamed Osman
Hussein Mohamed Osman
HAHakan Arslan
Hakan Arslan
Food sustainability is continuously restricted by water shortage and poor water quality in water-scarce regions. In this study, a pot experiment was carried out under rain shelter conditions to quantify the impact of the different levels of water salinity on the yield, leaf nutrients, and growth traits of garden cress under different water-deficit levels. Twelve treatments included three water-deficit (WD) levels (I0, I1, and I2 indicating 100, 80, and 60% of field capacity, respectively) in combination with four saline irrigation water levels (IWS) (S1, S2, S3, and S4, indicating 0.38, 2, 4, and 8 dSm−1, respectively). Also, multiple linear regression analysis was performed to predict garden cress yield using WD, IWS, and soil salinity (ECe) parameters in different combinations. The results showed that yield, leaf area, stomata, chlorophyll content, leaf Ca2+, K+, K+/Na+, and Ca2+/Na+ markedly decreased under water deficit and water salinity interaction. The highest and lowest ECe values were observed at the I2S4 (8.67 dSm−1) and I0S1 (0.88 dSm−1) treatments. The highest yield was found at I0S1 (166.1 g pot−1), and it was 49.8% and 62.0% higher than I1S4 and I2S4 treatments. The developed models have R2 larger than 0.92, showing that they could provide a valuable tool for evaluating and estimating the garden cress productivity under different WD and IWS conditions. Finally, we conclude that WD (80% of FC or lower) combined with a higher IWS of 0.38 dSm−1 is not recommended for irrigating garden cress, which will cause considerable yield and commercial quality reduction of garden cress plants.

17 October 2016 in Archives of Agronomy and Soil Science
Verified
Journal Article
Closed access
HAHakan Arslan
Hakan Arslan
NTNazlı Ayyıldız Turan
Nazlı Ayyıldız Turan
YDYusuf Demir
Yusuf Demir
AGAlper Güngör
Alper Güngör
BCBilal Cemek
Bilal Cemek
Geostatistical approaches (ordinary kriging (OK) and indicator kriging (IK)) were used in this study to investigate the spatial and temporal variations in groundwater nitrate concentrations in Çarşamba plain of Turkey. Groundwater samples were taken in April 2012, July 2012, September 2012 and March 2013 from 78 groundwater wells. The experimental semivariograms were often fitted well by a Gauss model for April 2012 and September 2012, whereas a spherical model was fitted to experimental semivariograms for July 2012 and March 2013. Spatial distribution maps revealed that groundwater nitrate concentrations were above the threshold value of 50 mg L−1 specified for drinking water in 4.3% of the study area in April 2012, 40.8% in July 2012, 32.8% in September 2012 and 19.1% in March 2013. Probability maps created with IK showed that 3.1% and 3.2% of the total area had very strong probability (0.8–1.0) of exceeding the threshold nitrate concentration in July 2012 and September 2012, respectively. Current findings revealed that groundwater nitrate concentrations changed seasonally and increased much more in summer. It was concluded that OK and IK may yield significant outcomes for groundwater management, identification of risky sites for potential pollution and identification of the sites with excessive fertilizer uses.