TY  - JOUR
AU  - Srdić, Sretenka
AU  - Srđević, Zorica
AU  - Stričević, Ružica
AU  - Čereković, Nataša
AU  - Benka, Pavel
AU  - Rudan, Nada
AU  - Rajić, Milica
AU  - Todorović, Mladen
PY  - 2023
UR  - https://www.mdpi.com/2073-4441/15/17/3065
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/6429
AB  - The study evaluated nine empirical methods for estimating reference evapotranspiration (ETo) in Bosnia and Herzegovina (BiH) across different climatic zones. The methods compared were the Hargreaves–Samani method (HS), the modified Hargreaves–Samani method (HM), the calibrated Hargreaves–Samani method (HC), the Priestley–Taylor method (PT), the Copais method (COP), the Makkink method (MAK), the Penman–Monteith method based on air temperature and overall average windspeed (PMT2), the Penman–Monteith method based on air temperature and regional average windspeed (PMT1.3), and the Penman–Monteith method based on air temperature and site-specific windspeed (PMTlok). These methods were tested against the “Food Agricultural Organization-Penman Monteith approach” (FAO-PM). The evaluation was performed using data from 20 meteorological stations in BiH, considering a common irrigation season (April–October) for two periods (2000–2005 and 2018–2022). The stations represented three climatic zones: semi-arid (SA), dry sub-humid (DSH), and moist sub-humid (MSH). The performance and ranking of the ETo methods were analyzed using the TOPSIS method. The trend of ETo during the common irrigation season for the period from 2018 to 2022 was determined using the Mann–Kendall test. The results of the study indicated that the HC method showed the best performance across all three climatic zones. The average root mean square error (RMSE) was 0.67 mm day−1, 0.49 mm day−1, and 0.50 mm day−1 for the SA, DSH, and MSH zones, respectively. As an alternative to the HC method, the PT method is recommended for its favorable results in both periods and in all zones. On the other hand, the HS method exhibited the highest average overestimation, particularly in the MSH zone, where ETo values were 18% higher compared with those of the FAO-PM method. The COP method also showed high overestimation and was not recommended for use. Regarding the MAK method, it resulted in underestimation during the period from 2000 to 2005, ranging from 17% in the DSH zone to 11% in the MSH zone. However, its performance improved during the period from 2018 to 2022, for which it ranked second place in the MSH zone. Among the PMT methods, the PMTlok, which utilized local average windspeed, yielded the best results. Despite performing well in the neighboring country of Serbia, the HM method showed poor overall performance in BiH. The findings of this study can serve as a foundation for further research in BiH to enhance irrigation practices in response to climate changes.
T2  - Water
T2  - Water
T1  - Assessment of Empirical Methods for Estimating Reference Evapotranspiration in Different Climatic Zones of Bosnia and Herzegovina
IS  - 17
SP  - 3065
VL  - 15
DO  - 10.3390/w15173065
ER  - 

@article{
author = "Srdić, Sretenka and Srđević, Zorica and Stričević, Ružica and Čereković, Nataša and Benka, Pavel and Rudan, Nada and Rajić, Milica and Todorović, Mladen",
year = "2023",
abstract = "The study evaluated nine empirical methods for estimating reference evapotranspiration (ETo) in Bosnia and Herzegovina (BiH) across different climatic zones. The methods compared were the Hargreaves–Samani method (HS), the modified Hargreaves–Samani method (HM), the calibrated Hargreaves–Samani method (HC), the Priestley–Taylor method (PT), the Copais method (COP), the Makkink method (MAK), the Penman–Monteith method based on air temperature and overall average windspeed (PMT2), the Penman–Monteith method based on air temperature and regional average windspeed (PMT1.3), and the Penman–Monteith method based on air temperature and site-specific windspeed (PMTlok). These methods were tested against the “Food Agricultural Organization-Penman Monteith approach” (FAO-PM). The evaluation was performed using data from 20 meteorological stations in BiH, considering a common irrigation season (April–October) for two periods (2000–2005 and 2018–2022). The stations represented three climatic zones: semi-arid (SA), dry sub-humid (DSH), and moist sub-humid (MSH). The performance and ranking of the ETo methods were analyzed using the TOPSIS method. The trend of ETo during the common irrigation season for the period from 2018 to 2022 was determined using the Mann–Kendall test. The results of the study indicated that the HC method showed the best performance across all three climatic zones. The average root mean square error (RMSE) was 0.67 mm day−1, 0.49 mm day−1, and 0.50 mm day−1 for the SA, DSH, and MSH zones, respectively. As an alternative to the HC method, the PT method is recommended for its favorable results in both periods and in all zones. On the other hand, the HS method exhibited the highest average overestimation, particularly in the MSH zone, where ETo values were 18% higher compared with those of the FAO-PM method. The COP method also showed high overestimation and was not recommended for use. Regarding the MAK method, it resulted in underestimation during the period from 2000 to 2005, ranging from 17% in the DSH zone to 11% in the MSH zone. However, its performance improved during the period from 2018 to 2022, for which it ranked second place in the MSH zone. Among the PMT methods, the PMTlok, which utilized local average windspeed, yielded the best results. Despite performing well in the neighboring country of Serbia, the HM method showed poor overall performance in BiH. The findings of this study can serve as a foundation for further research in BiH to enhance irrigation practices in response to climate changes.",
journal = "Water, Water",
title = "Assessment of Empirical Methods for Estimating Reference Evapotranspiration in Different Climatic Zones of Bosnia and Herzegovina",
number = "17",
pages = "3065",
volume = "15",
doi = "10.3390/w15173065"
}

Srdić, S., Srđević, Z., Stričević, R., Čereković, N., Benka, P., Rudan, N., Rajić, M.,& Todorović, M.. (2023). Assessment of Empirical Methods for Estimating Reference Evapotranspiration in Different Climatic Zones of Bosnia and Herzegovina. in Water, 15(17), 3065.
https://doi.org/10.3390/w15173065

Srdić S, Srđević Z, Stričević R, Čereković N, Benka P, Rudan N, Rajić M, Todorović M. Assessment of Empirical Methods for Estimating Reference Evapotranspiration in Different Climatic Zones of Bosnia and Herzegovina. in Water. 2023;15(17):3065.
doi:10.3390/w15173065 .

Srdić, Sretenka, Srđević, Zorica, Stričević, Ružica, Čereković, Nataša, Benka, Pavel, Rudan, Nada, Rajić, Milica, Todorović, Mladen, "Assessment of Empirical Methods for Estimating Reference Evapotranspiration in Different Climatic Zones of Bosnia and Herzegovina" in Water, 15, no. 17 (2023):3065,
https://doi.org/10.3390/w15173065 . .

TY  - JOUR
AU  - Lipovac, Aleksa
AU  - Bezdan, Atila
AU  - Moravčević, Djordje
AU  - Djurović, Nevenka
AU  - Ćosić, Marija
AU  - Benka, Pavel
AU  - Stričević, Ružica
PY  - 2022
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/6223
AB  - The objective of this study is to assess the possibility of using unmanned aerial vehicle (UAV) multispectral imagery for rapid monitoring, water stress detection and yield prediction under different sowing periods and irrigation treatments of common bean (Phaseolus vulgaris, L). The study used a two-factorial split-plot design, divided into subplots. There were three sowing periods (plots; I—mid April, II—end of May/beginning of June, III—third decade of June/beginning of July) and three levels of irrigation (subplots; full irrigation (F)—providing 100% of crop evapotranspiration (ETc), deficit irrigation (R)—providing 80% of ETc, and deficit irrigation (S) providing—60% of ETc). Canopy cover (CC), leaf area index (LAI), transpiration (T) and soil moisture (Sm) were monitored in all treatments during the growth period. A multispectral camera was mounted on a drone on seven occasions during two years of research which provided raw multispectral images. The NDVI (Normalized Difference Vegetation Index), MCARI1 (Modified Chlorophyll Absorption in Reflectance Index), NDRE (Normalized Difference Red Edge), GNDVI (Green Normalized Difference Vegetation Index) and Optimized Soil Adjusted Vegetation Index (OSAVI) were computed from the images. The results indicated that NDVI, MCARI1 and GNDVI derived from the UAV are sensitive to water stress in S treatments, while mild water stress among the R treatments could not be detected. The NDVI and MCARI1 of the II-S treatment predicted yields better (r2 = 0.65, y = 4.01 tha−1; r2 = 0.70, y = 4.28 tha−1) than of III-S (r2 = 0.012, y = 3.54 tha−1; r2 = 0.020, y = 3.7 tha−1). The use of NDVI and MCARI will be able to predict common bean yields under deficit irrigation conditions. However, remote sensing methods did not reveal pest invasion, so good yield predictions require observations in the field. Generally, a low-flying UAV proved to be useful for monitoring crop status and predicting yield and water stress in different irrigation regimes and sowing period.
PB  - MDPI
T2  - https://www.mdpi.com/2073-4441/14/22/3786
T1  - Correlation between Ground Measurements and UAV Sensed Vegetation Indices for Yield Prediction of Common Bean Grown under Different Irrigation Treatments and Sowing Periods
IS  - 22
IS  - 3786
VL  - 14
DO  - https://doi.org/10.3390/w14223786
ER  - 

@article{
author = "Lipovac, Aleksa and Bezdan, Atila and Moravčević, Djordje and Djurović, Nevenka and Ćosić, Marija and Benka, Pavel and Stričević, Ružica",
year = "2022",
abstract = "The objective of this study is to assess the possibility of using unmanned aerial vehicle (UAV) multispectral imagery for rapid monitoring, water stress detection and yield prediction under different sowing periods and irrigation treatments of common bean (Phaseolus vulgaris, L). The study used a two-factorial split-plot design, divided into subplots. There were three sowing periods (plots; I—mid April, II—end of May/beginning of June, III—third decade of June/beginning of July) and three levels of irrigation (subplots; full irrigation (F)—providing 100% of crop evapotranspiration (ETc), deficit irrigation (R)—providing 80% of ETc, and deficit irrigation (S) providing—60% of ETc). Canopy cover (CC), leaf area index (LAI), transpiration (T) and soil moisture (Sm) were monitored in all treatments during the growth period. A multispectral camera was mounted on a drone on seven occasions during two years of research which provided raw multispectral images. The NDVI (Normalized Difference Vegetation Index), MCARI1 (Modified Chlorophyll Absorption in Reflectance Index), NDRE (Normalized Difference Red Edge), GNDVI (Green Normalized Difference Vegetation Index) and Optimized Soil Adjusted Vegetation Index (OSAVI) were computed from the images. The results indicated that NDVI, MCARI1 and GNDVI derived from the UAV are sensitive to water stress in S treatments, while mild water stress among the R treatments could not be detected. The NDVI and MCARI1 of the II-S treatment predicted yields better (r2 = 0.65, y = 4.01 tha−1; r2 = 0.70, y = 4.28 tha−1) than of III-S (r2 = 0.012, y = 3.54 tha−1; r2 = 0.020, y = 3.7 tha−1). The use of NDVI and MCARI will be able to predict common bean yields under deficit irrigation conditions. However, remote sensing methods did not reveal pest invasion, so good yield predictions require observations in the field. Generally, a low-flying UAV proved to be useful for monitoring crop status and predicting yield and water stress in different irrigation regimes and sowing period.",
publisher = "MDPI",
journal = "https://www.mdpi.com/2073-4441/14/22/3786",
title = "Correlation between Ground Measurements and UAV Sensed Vegetation Indices for Yield Prediction of Common Bean Grown under Different Irrigation Treatments and Sowing Periods",
number = "22, 3786",
volume = "14",
doi = "https://doi.org/10.3390/w14223786"
}

Lipovac, A., Bezdan, A., Moravčević, D., Djurović, N., Ćosić, M., Benka, P.,& Stričević, R.. (2022). Correlation between Ground Measurements and UAV Sensed Vegetation Indices for Yield Prediction of Common Bean Grown under Different Irrigation Treatments and Sowing Periods. in https://www.mdpi.com/2073-4441/14/22/3786
MDPI., 14(22).
https://doi.org/https://doi.org/10.3390/w14223786

Lipovac A, Bezdan A, Moravčević D, Djurović N, Ćosić M, Benka P, Stričević R. Correlation between Ground Measurements and UAV Sensed Vegetation Indices for Yield Prediction of Common Bean Grown under Different Irrigation Treatments and Sowing Periods. in https://www.mdpi.com/2073-4441/14/22/3786. 2022;14(22).
doi:https://doi.org/10.3390/w14223786 .

Lipovac, Aleksa, Bezdan, Atila, Moravčević, Djordje, Djurović, Nevenka, Ćosić, Marija, Benka, Pavel, Stričević, Ružica, "Correlation between Ground Measurements and UAV Sensed Vegetation Indices for Yield Prediction of Common Bean Grown under Different Irrigation Treatments and Sowing Periods" in https://www.mdpi.com/2073-4441/14/22/3786, 14, no. 22 (2022),
https://doi.org/https://doi.org/10.3390/w14223786 . .