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Maize Irrigation Scheduling in Plovdiv Region: Impact of Climate Uncertainties and Soil Characteristics

This study focuses on the validation of a maize irrigation scheduling model in the Plovdiv region of Bulgaria. The research analyzes the impact of climate uncertainties and soil characteristics on irrigation season duration. Various irrigation strategies are evaluated to assess their effectiveness in reducing irrigation demand. Economic criteria are considered to determine the optimal irrigation scheduling alternatives. The findings provide valuable insights for efficient irrigation practices in maize cultivation.

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Maize Irrigation Scheduling in Plovdiv Region: Impact of Climate Uncertainties and Soil Characteristics

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  1. N.Poushkarov Institute of Soil Science, Sofia, Bulgaria Model Validation for Maize Irrigation Scheduling in Plovdiv Region Impact of Climate Uncertainties and Soil Characteristics on Irrigation Season Duration Prof. D.Sc. Eng.Zornitsa Popova Prof. Dr. Luis Santos Pereira Prof. D.Sc. Eng.Zornitsa Popova Ass. Prof. Dr. Katerina Doneva BALWOIS 2010 CONFERENCE 25-29 May 2010, Ohrid, Republic of Macedonia

  2. Variability of climate and soil characteristics produces uncertainties of irrigation scheduling in Bulgaria. In former studies the simulation model ISAREG was calibrated for two maize hybrids of different water stress resistance in a vertisol (TAW = 173 mm m-1) and a chromic cambisol (TAW = 136 mm m-1) soils in East Central Bulgaria and then used to build irrigation scheduling alternatives in agreement imposed by the irrigation methods. • The objective of the first study is: • To assess the impacts of several maize irrigation scheduling strategies for reduced irrigation demand оn irrigations’ number and irrigation season duration in both soils in the Thracian Lowland by application of the formerly validated ISAREG model to the period 1970-2005. • IDs and ISD are computed considering an economic criteria: the cost of YDmax produced by skipping the last irrigation event in the season should not be larger then the expenses related to that event.

  3. Irrigation scheduling alternatives (1) refilling the soil reservoir adopting management-allowed depletion fraction (MAD) of 0.60 and with application depths of 110-120 mm; For furrow-irrigated maize in the vertisol soil at Pustren site (TAW=193 mm 1.1m-1), Stara Zagora: (2) refilling the soil reservoir adopting MAD=0.47 and application depths of 90 mm; (3) refilling the soil reservoir adopting MAD=0.33 and application depths of 60 mm; (4) partially refilling the soil reservoir adopting MAD=0.47 and application depths of 60 mm.

  4. Cracking level • Fig. 3 Simulation of the available soils water (ASW, mm) for three alternatives scheduling irrigation before soil cracking in the year of extreme irrigation demand (1981) at Pustren (a vertisol soil): • alternative 2 for continuous-flow furrow irrigation; • alternatives 3; • 4 for surge-flow furrow irrigation • with identification of the date of the last irrigation when aiming at maximum yield (the full line) and when the last irrigation event is skipped (the line in dashes).

  5. Irrigation scheduling alternatives (2) consists of refilling the soil reservoir and adopting a MAD = 0.60 when the application depths are 90 mm; For surge furrow and sprinkler irrigation in the chromic cambisol soil at Zora (TAW =150 mm 1.1m-1): (3) consists of refilling the soil reservoir and adopting MAD=0.40, thus with application depths of 60 mm; (4) consists of partially refilling soil reservoir with application depths of 60 mm but adopting MAD = 0.60.

  6. Fig. 4 Simulation of the available soils water (ASW, mm) for the three irrigation scheduling alternatives in the year of extreme irrigation demand (1981) at Zora site (a chromic cambisol): • alternative 2 for furrow irrigation; • alternative 3; • alternative 4 for surge furrow / sprinkler irrigation, • with identification of the date of the first and last irrigation when aiming at maximum yield (the full line) and when the last irrigation event is skipped (the line in dashes).

  7. Figure 5. Irrigation season duration (ISD) in relation to the probability PIDs for irrigation scheduling alternative 2 at: a) Pustren, a vertisol; b) Zora, a chromic cambisol, Stara Zagora, 1970-1992.

  8. (TAW = 173 mm m-1) (TAW = 136 mm m-1) Figure 6. Comparison of irrigation season duration (ISD) probability curves for the irrigation scheduling alternatives at sites: a) Pustren, a vertisol; b) Zora, a chromic cambisol, Stara Zagora, 1970-1992.

  9. Table 2. Irrigation season duration (ISD) related to the irrigation scheduling alternative and the number of required irrigation events for economically justified water saving, a vertisol soil, Pustren, Stara Zagora, 1970-1992.

  10. Table 3. ISD related to the irrigation scheduling alternative and the number of required irrigations for economically justified water saving, a chromic cambisol soil, Zora, Stara Zagora, 1970-1992.

  11. CONCLUSIONS 1) The number of irrigation events in the vertisol (TAW=173 mm m-1) ranges from 2 to 4 for alternative 2 and reaches 2 - 6 (alternatives 3 and 4). Comparing with the vertisol, additional irrigation is required in the average and high irrigation demand years in the chromic cambisol soil (TAW=136 mm m-1). 2) The larger are the TAW and MAD the shorter is the irrigation season. When water is depleted from the deeper soil layers (alternatives 2 and 4, MAD>0.47) average IDS is 26 - 29 days in the vertisol and 37 – 38 days in the chromic cambisol. Alternative 3 (MAD=0.33-0.40) leads to ten-day longer irrigation season on the average. 3) Irrigation season starts earliest in the very dry year: on 8/06 (alternative 3) and 10 days latter (alternatives 2 and 4). It begins usually on 1-16/July in the years of average IDs (PIDs>=60%). The last possible irrigation is between 21/08 and 2/09 (alternative 2) in the chromic cambisol (TAW=136 mm m-1) and from 7 to 14/08 in the vertisol (TAW=173 mm m-1). 4) The irrigation practice of largest soil water depletion (strategy 1) produces the shortest maize irrigation season. However such practice is associated with significant deep percolation of water and nitrogen (up to 50%) due to the preferential flows when cracks are formed. Additionally the poor uniformity of irrigation water distribution causes significant yield losses in the dry seasons. Thus it should be avoided in future.

  12. The objective is to explore eight-year (1984-1991) datasets of field experiments with maize at Tsalapitsa, Plovdiv region (alluvial SL soil , TAW = 116 mm m-1) for: calibration and validation of Kc and depletion fraction p adapted to the local environmental conditions; deriving Ky for the maize hybrid H708 used in the experiments. Following this study, the model is supposed to be further used for development of irrigation scheduling strategies of reduced irrigation demand in the region. The second paper reports on using independent historic datasets relative to experiments with rainfed, deficit and fully irrigated maize for further testing ISAREG in South Middle Bulgaria.

  13. Precipitation and ETo Tsalapitsa, Plovdiv region Pr during the usual irrigation season (July to August) Average monthly Pr (a) average ETo-PM (b) for the whole period 1984-1991;

  14. Observed and simulated SM (cm3 cm-3) versus time (1988);model calibration/validation for: (a) rainfed 1; (b ) full irrigation treatment 2; mild stress treatments 12 (c) and 13 (d)

  15. Observed and simulated SM (cm3 cm-3) versus time (1988) model calibration/validation for: and high stress treatments 9 (e) and 11 (f) Milky ripening

  16. Comparing the ISAREG simulated versus observed SM, cm3 cm-3 relative to 1988 : (a) the calibration treatments 1 and 2; (b) the validation treatments 3 – 13.

  17. Validation of crop coefficients Kc using long-term data Comparing simulated and observed seasonal ETa (mm) for the complete set of treatments: a) over the whole period 1984-1990; b) for the “very dry” years 1988-1990; c) for the “wetter” years 1984-1987

  18. Validation of the derived Kys (H708) using long-term data One-to-one simulated versus observed YDfor the complete set of irrigation treatments relative to: a) the whole period 1984-1991 (Ky=1.5); b) the “very dry” years 1988-1990 heaving yo<0.3 (Ky=1.75); c) the “wetter” years 1984-1987 heaving yo>0.3 (Ky=1.3), maize varieties H708.

  19. The validation of the ISAREG model using historic data on maize cropped in a SL soil under dry climate and various irrigation treatments has been successfully performed. Model predictions of SM along the season and seasonal ETa using the calibrated curves of Kc and depletion fraction p are appropriate for the variable irrigation and rainfed conditions. The accuracy of the calibrated model was tested against experimental data (1984-1990) from all irrigation and rainfed treatments by comparing the computed versus observed seasonal ETa. Statistical tests relative to the “very dry” years (1988-1990) show the smallest AEE = 9.9 mm per season. A statistical test was performed to compare the model predicted using the different Ky (1.5; 1.75 and 1.3) versus observed YD due to water stress. The AEE were smaller when Ky was adapted to the “very dry” and “wetter” seasons: 0.09 for the former and 0.06 for the latter versus AEE=0.12 when the value Ky =1.5 was applied to the whole period. It can therefore be concluded that the methodologies used for calibrating, validating and testing the model using historic field data were appropriate. The obtained results support model use for developing water saving and environmentally oriented irrigation practices in the Plovdiv region, South Middle Bulgaria. Conclusions

  20. ACKNOWLEDGEMENTS We gratefully acknowledge the financial support of Drought Management Center for South East Europe Project, South East Europe Transnational Cooperation Programme co-funded by the European Union, for implementation and dissemination of our studies’ results on crop vulnerability to droughts and irrigation management in Bulgaria. Thank you for your attention!

  21. Seasonal precipitation at Pustren field (○) during the maize cropping season (May to September) for the period 1929-2005, respective 3-years average (▬▬) and an approximate trend line (dash line) relative to the period 1970-2005.

  22. Results and discussions • Fig.2 Comparison of probability curves of IDs relative to a vertisol (dashed line) and a chromic cambisol (full line) : • alternative 1 with 110-120 mm application depths; • b) alternative 2 with 90 mm application depths for continuous-flow improved furrow irrigation above the cracking level; • c) alternative 3 and d) alternative 4 with 60 mm application depths for surge-flow furrow and sprinkler irrigation, Stara Zagora, 1970-1992.

  23. Main soil physical and hydraulic properties of the Alluvial soil at Tsalapitsa site

  24. The treatments consisted of: (a) full irrigation with applications of the required irrigation depth (2, 6 and 7); (b) irrigation with applications exceeding by 1.3 times the required irrigation depth (3); (c) mild stress with application of 70% of the required depth (4, 12, 13 and 14); (d) stressed with application of 40% of the required depth (5); (f) highly stressed with application of 20 % of the required depth (9, 10 and 11). The deficit irrigation was realised by constantly reducing the required application depth (treatments 4, 5) or by satisfying the irrigation demands only in a given period/periods (treatments 9 – 13). Some treatments (6, 7) used to be irrigated more frequently (one or twice a week). Detailed information relative to these experiments is published by Varlev et al. (1988;1990; 1994), Kirkova et al.(1988, 1994), Varlev et al. (1999), Varlev, 2008 Irrigation experiments

  25. Model calibration and validation procedures Ky were formerly derived by regressing ei=ETa/ETmax against yi =Ya/Ymax (Varlev et al.,1994;1999, Varlev, 2008). Ky =(1-Ya/Ymax)=Ky (1- ETa /ETmax)

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