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Adar, E. M., & Külls, C. (2002). MCM sf–Mixing-cell model for a steady flow MIG–Mixing-cell input generator: A short manual for installation and operation of MCM sf using the MIG–mixing-cell input generator.
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Külls, C. (2014). Ecohydrological principles in economic models of water resources in drylands and desert restoration.
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Külls, C., & Bittner, A. (2013). Passive barriers for long-term containment of Uranium and Vanadium.
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Külls, C., Bittner, A., & Marx, V. (2013). Strategic Assessment of Water Resources for the Erongo Uranium Province.
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Rehm-Berbenni, C., Druta A., Åberg, G., Neguer J., Külls, C., Patrizi, G., et al. (2005). Isotope Technologies Applied to the Analysis of Ancient Roman Mortars.
Abstract: Results of the CRAFT Project EVK4 CT-2001-30004
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Gunkel, A. K., C. (2006). Towards agent-based modelling of stakeholder behaviour – a pilot study on drought vulnerability of decentral water supply in NE Brazil. International Congress on Environmental Modelling and Sofware, .
Abstract: 3rd International Congress on Environmental Modelling and Sofware – Burlington, Vermont
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Külls, C. (2004). Demonstration des Potentials der Nitrat-Isotopenanalytik für die Strategieentwicklung der Sanierung Nitrat-belasteter Brunnen.
Abstract: Demonstration des Potentials der Nitrat-Isotopenanalytik für die Strategieentwicklung der Sanierung Nitrat-belasteter Brunnen
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Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying Evapotranspiration and Drainage Losses in a Semi-Arid Nectarine (Prunus persica var. nucipersica) Field with a Dynamic Crop Coefficient (Kc) Derived from Leaf Area Index Measurements. Water, 14(5).
Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.
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Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying Evapotranspiration and Drainage Losses in a Semi-Arid Nectarine (Prunus persica var. nucipersica) Field with a Dynamic Crop Coefficient (Kc) Derived from Leaf Area Index Measurements. Water, 14(5).
Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.
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Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying Evapotranspiration and Drainage Losses in a Semi-Arid Nectarine (Prunus persica var. nucipersica) Field with a Dynamic Crop Coefficient (Kc) Derived from Leaf Area Index Measurements. Water, 14(5).
Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.
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