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    Determining the Changing Irrigation Demands of Maize Production in the Cukurova Plain under Climate Change Scenarios with the CROPWAT Model
    (Mdpi, 2023) Sen, Burak
    This study delves into the critical issue of climate change and its impact on maize cultivation, focusing on irrigation water requirements (IWR) and crop evapotranspiration (ETc) values over three distinct time periods: 1971-2000 (RF), 2025-2054 (P1), and 2069-2098 (P2), under the climate scenarios of RCP4.5 and RCP8.5 in the AR5 of the IPCC via the CROPWAT model. The research reveals significant increases in mean temperatures, particularly during summers, in both scenarios, signifying the substantial influence of climate change on the Cukurova Region's climate. Daily average evapotranspiration (ETo) values for the study periods demonstrate noteworthy increases, with the most pronounced rise observed in July for P2 under RCP8.5, emphasizing the seasonality and magnitude of the change. Moreover, the study underscores a consistent escalation in irrigation water requirements from RF to P2 periods for both scenarios, highlighting the pressing need for water resource management strategies in agriculture. Under RCP4.5, the study found that average simulated ETc increased by 9.2% for P1 and 11.7% for P2 compared to the RF period. In the harsher RCP8.5 scenario, ETc values displayed a substantial 20.0% increase for P2 and exhibited a wide range of variation across the study periods. In the light of these escalating climate change impacts, this study underscores the imperative of understanding and addressing the challenges encountered in maize cultivation. The findings emphasize the consistent rise in temperature and irrigation demands, underscoring the necessity for proactive adaptive strategies to ensure the sustainability of agricultural practices and long-term food security. As climate change continues to exert its influence, this research serves as a call to action for policymakers, agricultural stakeholders, and researchers to prioritize adaptation efforts to safeguard the future of maize production and the global food supply.
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    Evaluation of the Impacts of Climate Change on Irrigation Requirements of Maize by CROPWAT Model
    (Springer, 2023) Yetik, Ali Kaan; Sen, Burak
    In the presented study, the eventual effects of climate change on maize farming under Mediterranean climatic conditions were investigated by CROPWAT Model. Irrigation scheduling and determining water requirements are of great importance in adapting the climate change. The CROPWAT model is a software used to calculate the response of crop water requirements to different climatic conditions and irrigation strategies. The reference (1961-1990) and the future (2070-2099) climate data determined by the ICTP's Regional Climate Model system version 3 (RegCM3) were used as climate data in the study. According to the results, the mean reference evapotranspiration of growing season in the study site will be 0.49 mm day(-1) higher on average in the future. In the period of 2070-2099, irrigation water requirements for maize will be 7.37% more on average than they were from 1961 to 1990. For the periods of 1961-1990 and 2070-2099, average crop evapotranspiration was calculated to be 480.1 and 513.4 mm, respectively. These simulation results revealed that irrigation scheduling in maize farming in Mediterranean climatic zones should be adjusted to the climate change.
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    Trends and variability in precipitation across Turkey: a multimethod statistical analysis
    (Springer Wien, 2024) Yetik, Ali Kaan; Arslan, Bilge; Sen, Burak
    Analyzing trends in precipitation data is crucial for understanding the effects of climate change and making informed decisions about water management and crop patterns. The objective of the presented study was to investigate precipitation trends, analyze temporal and spatial variations and identify potential change points in Turkey throughout the period from 1980 to 2019. Precipitation data were analyzed for both regional and 81 meteorological stations in Turkey on a monthly, seasonal, and annual basis. Spearman rank correlation and Mann-Kendall tests were utilized to detect possible trends and Sen's slope test to estimate the magnitude of change throughout the entire time series. The average precipitation amount of Turkey was determined 639.2 mm between the years 1980 and 2019. While Central Anatolian and Eastern Anatolian regions had below 639.2 mm, other regions were above. The range of seasonal precipitation values were found for winter 128.7-320.8 mm, 108.9-260.0 mm for spring, 43.9-109.3 mm for summer, and 79.7-238.4 mm for autumn. The analysis of the data revealed no significant increase or decrease in annual values on a regional basis, with the greatest change on a seasonal basis being observed in the winter. The 40-year trends of annual precipitation data belonging to 81 stations were decreasing in 23 provinces and increasing in 58 provinces, and 11 of them (14% of the total) were found to be statistically significant. Moreover, November was found to be a month of particular significance in terms of precipitation changes across the country, with a decrease observed in 80 out of 81 provinces. Spatial distribution analysis showed that the magnitude of variation in precipitation decreased as one moved from the southern to the northern regions of the country.
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    VALIDATION OF DAILY PRECIPITATION ESTIMATES OF THE REGIONAL CLIMATE MODEL REGCM4 OVER THE DOMAINS IN TURKEY WITH NWP VERIFICATION TECHNIQUES
    (PARLAR SCIENTIFIC PUBLICATIONS (P S P), 2014) Sen, Burak; Kilinc, Recep; Sen, Baha; Sonuc, Emrullah
    We present a validation study for a 50-km resolution version of the RegCM4 regional climate model over the East Mediterranean Basin. In this study, the observation and evaluation of the model results against each other as well as graphication, which mostly generates scatter plot graphs of the atmosphere for operational weather forecasting models (NWP, numerical weather prediction), with 11 different statistical verification score values were evaluated by calculating the regional climate model results. As a result of the analysis, it has been estimated that the rainfall is 42% higher than the estimated average amount RegCM4 simulations based on the 50 observation stations. Meteorological Service (TSMS, Turkish State Meteorological Service) observation network monitored 50 stations based on the average of Frequency Bias Index (FBI), Proportion Correct (PC), Probability of Detection (POD), False Alarm Ratio (FAR), False Alarm Rate (F), Hanssen-Kuipers Skill Score (KSS), the Threat Score (TS), Equitable Threat Score (ETS), Heidke Skill Score (HSS), The Odds Ratio (OR), and Odds Ratio Skill Score (ORSS) values which are as follows, respectively: 0.70, 0.70, 0.52, 0.32, 0.38, 0.39, 0.21, 0.34, 5.99, and 0.69. The objective score values calculated for RegCM4 climate model were found to be close to the score values of the NWP models. Given these values, which were found to be successful for RegCM4 model dynamics, the results generated by other models, recovery/adaptation techniques will be used for the application of hydrological studies.
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    Validation of daily precipitation estimates of the regional climate model RegCM4 over the domains in Turkey with NWP verification techniques
    (Parlar Scientific Publications, 2014) Sen, Burak; Kilinç, Recep; Sen, Baha; Sonuç, Emrullah
    We present a validation study for a 50-km resolution version of the RegCM4 regional climate model over the East Mediterranean Basin. In this study, the observation and evaluation of the model results against each other as well as graphication, which mostly generates scatter plot graphs of the atmosphere for operational weather forecasting models (NWP, numerical weather prediction), with 11 different statistical verification score values were evaluated by calculating the regional climate model results. As a result of the analysis, it has been estimated that the rainfall is 42% higher than the estimated average amount RegCM4 simulations based on the 50 observation stations. Meteorological Service (TSMS, Turkish State Meteorological Service) observation network monitored 50 stations based on the average of Frequency Bias Index (FBI), Proportion Correct (PC), Probability of Detection (POD), False Alarm Ratio (FAR), False Alarm Rate (F), Hanssen-Kuipers Skill Score (KSS), the Threat Score (TS), Equitable Threat Score (ETS), Heidke Skill Score (HSS), The Odds Ratio (OR), and Odds Ratio Skill Score (ORSS) values which are as follows, respectively: 0.70, 0.70, 0.52, 0.32, 0.38, 0.39, 0.21, 0.34, 5.99, and 0.69. The objective score values calculated for RegCM4 climate model were found to be close to the score values of the NWP models. Given these values, which were found to be successful for RegCM4 model dynamics, the results generated by other models, recovery/adaptation techniques will be used for the application of hydrological studies. © by PSP.