Effect of climate change in variety specific sugarcane (Mid Term Defense).pptx

Effect of climate change in variety specific sugarcane; A case study in Nepal

1. Effect of climate change in variety specific sugarcane cultivation in Southern part of Nepal using DSSAT-CANEGRO Model: A case study in National Sugarcane Research Program (Jeetpur-Simra) TRIBHUVAN UNIVERSITY INSTITUTE OF ENGINEERING PURWANCHAL CAMPUS DEPARTMENT of AGRICULTURAL ENGINEERING Submitted To Department of Agricultural Engineering M.Sc. in Land & Water Engineering Submitted By Er. Ravi Prasad Chaudhary Roll No :- 078MSLWE004 M.Sc. in Land & Water Engineering 1 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

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3. Sugarcane has been cultivated in Nepal for many years, though specific historical records of its introduction are sparse. It's an ancient crop originally spread by Austronesian and Papuan people and has a significant presence in South Asian agriculture [ 1 ]. Sugarcane holds significant importance as a cash crop in Nepal, contributing to the country's agricultural sector and economy. Nepal ranks 41 st in global sugarcane production . Among 14 districts of Nepal, Bara stands out as one of larger sugarcane-producing regions [2]. Nepal's sugarcane production has seen substantial growth, from 245,635 tonnes in 1973 to 3.16 million tonnes in 2022 and Productivity has increased from 20 tons per hectare in 1961 to 53 tons per hectare in recent years[3]. The 3 rd major cash crop as sugarcane cultivation as in area with average 68,181 ha in decreasing way with average producing 3,380,864 MT throughout the country[4]. 3 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

4. 4 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE Continue … Sugar is a low-cost energy source that can alleviate malnutrition problems. About 80% of the global sugar produced from sugarcane are cultivated in 120 countries with approximately 27 million ha and an average production is 1.8–2 billion tons per year[5]. Increased temperatures can enhance sugarcane yield in some regions until 2060 AD. However, sugarcane is highly sensitive to temperature fluctuations , which can affect its growth and sugar yield [6]. The impact varies by geographic location and the adaptive capacity of sugarcane farming practices. Regions with better adaptive strategies might mitigate some negative effects[7]. The DSSAT (Decision Support System for Agro technology Transfer) model is a comprehensive tool [8] (Wide production Application[9], Advanced Functionality[10], Climate Impact Studies & Calibration and Validation[11]) designed to aid in the research and management of crop.

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6. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 6 Sugarcane Cultivation in Madhesh Province S.N Districts Area (Ha) Prod.(Mt) Yield(Mt/Ha) 1 Saptari 200 5992 29.92 2 Siraha 2872 136516 47.53 3 Dhanusha 3605 141977 39.39 4 Mahottari 7148 367162 51.36 5 Sarlahi 17360 902722 52 6 Rautahat 8513 342264 40.21 7 Bara 2840 132721 46.73 8 Parsa 1019 47062 46.19

7. 1.2 Statement of Problem 7 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

8. 1.3 Research Objectives 8 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

9. 1.4 Scope of Study 9 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE This study benefited to: Creation of soil, crop management and weather files data that are collected from the National Sugarcane Research program, jeetpur-simra (Bara) and Department of hydrology and meteorological Station Parwanipur. Determination of genetic and ecotype coefficient of sugarcane cultivar using DSSAT crop simulation model. Correlation of simulated and observed yield values as well as creation of relationship between various crop stages. sugarcane yield simulation under various climate change scenario using DSAT-CANEGRO model. Evaluation of varietal adaptation and optimization in crop management practices in future scenarios.

10. 2. Literature Review 10 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE Source: (James W Jones et al. 2017) 2.1 History of Agriculture Model

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12. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 12 Source: FAOSTAT (Aug19, 2023) 2.2 Sugarcane Cultivation and Its Importance in Nepal

13. 2 .3 Climatic Parameters on Sugarcane Cultivation June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 13

14. 3. RESEARCH METHODOLOGY 3.1 Research Flowchart 14 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

15. Daily weather parameters collected from Metrological Stations Parwanipur (1990-2022)   Soil Data collected during field visit & National Sugarcane Research Program Manual Reports Weather File (Daily Tmax, Tmin, Solar Radiation, Rainfall) Soil File (% clay, % silt, %Stone, %OC, %N, CEC, PH Value)   Sugarcane Varieties Cultivated in National Sugarcane Research Program   Sugarcane Crop management practice information’s collected Genetic Coefficient File (Twenty genetic parameters for five sugarcane verities)   Crop Management File (Planting, irrigation, Fertilizer and other field operation data ) DSSAT-CSM-CANEGRO Sugarcane Model Crop growth development & Simulation for different years Treatment Combination with Environmental Modification Model Calibration (F/Y 2020/21 & 2021/22 ) Model Validation ( F/Y 2018/19, 2019/20 )   Model Accuracy Assessment Parameters Correlation Coefficient Coefficient of Determination Root mean Square Error 3.2 Research Design 15 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

16. 3.3 Study Area The study area will be carried out in National Sugarcane Research Program, Chhatrapipra Jitpur-Simra Bara district, Nepal which is geographically extends between latitude 27.1341° N & Longitude 85.0649° E. 16 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

17. 17 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 3.4 Experimental Detail and Field Layout Experimental Design RCBD Treatments 5 cultivars Replications 3 Plot Size 6 Rows X 6m Plot Spacing 75cm Harvested Area 13.5 m2

18. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 18 3.5 Model Input and Data Collection

19. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 19 SLB 20 40 60 80 100 120 SLMH O A E B C R SLLL 0.114 0.176 0.188 0.185 0.181 0.179 SDUL 0.283 0.32 0.342 0.33 0.317 0.314 SSAT 0.556 0.471 0.461 0.455 0.452 0.421 SRGF 0.99 0.95 0.54 0.44 0.24 0.11 SSKS 1.62 1.32 9.63 0.25 1.23 0.23 SBDM 1.4 1.42 1.43 1.45 1.45 1.55 SLOC 1 0.85 0.65 0.46 0.41 0.37 SLCL 12.5 25.4 28.8 29.3 28.8 28.6 *TU78MSLWE4 NSRP SIL 120 Loam @SITE COUNTRY LAT LONG FAMILY JEETPUR NEPAL 27 85 ALFISOL SLB Depth, base of layer, cm SLMH Master horizon SLLL Lower limit of plant extractable soil water, cm3 cm-3 SDUL Drained upper limit, cm3 cm-3 SSAT Upper limit, saturated, cm3 cm-3 SRGF Root growth factor, soil only, 0.0 to 1.0 SSKS Sat. hydraulic conductivity, macrospore, cm h-1 SBDM Bulk density, moist, g cm-3 SLOC Organic carbon, % SLCL Clay (<0.002 mm), %

20. 3.6 Genetic Coefficient June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 20 Verities Observed Simulated Co 86032 110.02 111.7 Co 0118 79.97 82.1 BO 120 73.92 76.7 CoSe 98255 95.30 102.1 CoS 08272 96.57 93.4 Genetic Coefficient of Sugarcane Varieties S.N Parameter Code Co-86032 Co-0118 BO-120 CoSe-98255 CoS-08272 1 MaxPARCE 6.8 5.3 5.3 5.3 5.15 2 APFMX 0.88 0.85 0.8 0.88 0.88 3 STKPFMAX 0.73 0.62 0.62 0.65 0.64 4 SUCA 0.62 0.65 0.61 0.48 0.45 5 TBFT 25 22 25 20 21 6 LFMAX 12 13 12 10 11.5 7 MXLFAREA 360 345 350 343 320 8 MXLFARNO 14.5 11 13 11 10 9 PI1 68.5 54 69 59 53 10 PI2 167 151 165 152 154 11 PSWITCH 18 12 18 11 12 12 TTPLNTEM 53 43 52 38 87 13 TTRATNEM 30 30 30 30 30 14 CHUPIBASE 715 630 830 720 610 15 TT_POPGROTH 330 335 310 345 320 16 POPTT16 13.3 13.3 13.3 10.3 12.3 17 TAR0 0.02 0.02 0.02 0.02 0.02 18 TDELAY 50 50 50 50 50 19 LER0 0.25 0.25 0.25 0.25 0.25 20 SER0 0.14 0.14 0.14 0.14 0.14 21 LG_AMBASE 220 220 220 205 220 22 AQP_UP5 0.45 0.45 0.45 0.45 0.45

21. 4. Result & Discussion F/Y 2021/22 ( t/ha) Varieties Observed Simulated CoS 86032 103.98 113.3 Co 0118 120.5 129.7 BO 120 84.44 90 CoSe 98255 94.4 97 CoS 08272 114.6 123.9 F/Y 2020/21 ( t/ha) Varieties Observed Simulated CoS 86032 103.98 112.9 Co 0118 120.5 126.7 BO 120 84.44 92.4 CoSe 98255 94.4 98.7 CoS 08272 114.6 125.9 21 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

22. F/Y 2019/20 ( t/ha) Varieties Observed Simulated CoS 86032 88.37 108.8 Co 0118 105 124.3 BO 120 78.8 89.2 CoSe 98255 78.3 91.1 CoS 08272 112.1 120.4 F/Y 2018/19 ( t/ha) Varieties Observed Simulated CoS 86032 88.37 114.4 Co 0118 125.93 131.5 BO 120 78.8 92.5 CoSe 98255 78.3 100.1 CoS 08272 112.1 126.6 22 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE

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25. 25 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE Stalk Development Stage

26. 26 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE F/Y R 2 R RMSE   nRMSE MAPE (%) 2018/19 0.598 0.773 48.612 0.484 49.3 2019/20 0.889 0.943 56.31 0.588 59.19 2020/21 0.8713 0.933 54.36 0.621 61.4 2021/22 0.759 0.871 15.072 0.187 17.4 Model Accuracy Assessments The calculation is obtained using Agricultural And Metrological Software online by inserting yearly simulated and observed yield in distinguish financial year. The Mean absolute percentage error (MAPE) is one of the most commonly used KPIs (key performance indicator) to measure forecast accuracy.

27. 27 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE Climate Projection Scenario The air temperature and rainfall predicted for two future periods (Near future (NF): 2020– 2039 & Far future (FF): 2040–2059 under two Representative Concentration pathway scenarios (RCP 4.5 and RCP 8.5) were used and compared with the observed data for historical period (1991–2020) as presented in Table 4.7 & 4.8 (a & b). Source: https ://climateknowledgeportal.worldbank.org/country/nepal

28. 28 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE Co-86032 Co-0118 BO-120 CoSe-98255 CoS-08272 Para- meters Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Tmax (˚C) 3 108.8 -2.60 83.7 1.95 77.5 1.04 103.7 1.57 95 1.71 2 109.2 -2.24 83.7 1.95 77.5 1.04 103.4 1.27 94.8 1.50 1 109.3 -2.15 83.8 2.07 77.5 1.04 102.6 0.49 94.7 1.39 -1 109.6 -1.88 83.5 1.71 77.2 0.65 100.6 -1.47 93.4 0.00 -2 109.9 -1.61 82.9 0.97 76.8 0.13 99.1 -2.94 92.5 -0.96 Tmin(˚C)   Co-86032   Co-0118   BO-120   CoSe-98255   CoS-08272   Para- meters Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change 2 109.4 -2.06 83.7 1.95 77.5 1.04 103.5 1.37 94.9 1.61 1 109.5 -1.97 83.8 2.07 77.5 1.04 102.6 0.49 94.7 1.39 -1 109.5 -1.97 83.5 1.71 77.2 0.65 100.6 -1.47 93.4 0.00 -2 109 -2.42 82.9 0.97 76.8 0.13 99.1 -2.94 92.5 -0.96 -3 108.1 -3.22 82.1 0.00 76.1 -0.78 96.9 -5.09 91.3 -2.25 Solar radiation(MJ/m2/day)   Co-86032   Co-0118   BO-120   CoSe-98255   CoS-08272   Para- meters Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change 3 123.2 10.30 97.7 19.00 90.3 17.73 117 14.59 109.4 17.13 2 119.3 6.80 93 13.28 86 12.13 112.8 10.48 104.4 11.78 1 114.8 2.78 88.3 7.55 81.7 6.52 107.6 5.39 99.3 6.32 -1 103.6 -7.25 79 -3.78 73.1 -4.69 96.2 -5.78 88.9 -4.82 -2 97.3 -12.89 74.3 -9.50 68.9 -10.17 90.2 -11.66 83.7 -10.39 -3 91 -18.53 69.6 -15.23 64.5 -15.91 84.4 -17.34 78.3 -16.17 Sensitivity Analysis with Weather Parameters in Germination Stage

29. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 29 CO2 Concentration (Default value 380 ppm)   Co-86032   Co-0118   BO-120   CoSe-98255   CoS-08272   Para- meters Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change 500 109.9 -1.61 83.5 1.71 77.4 0.91 101.9 -0.20 94.1 0.75 720 109.8 -1.70 83.5 1.71 77.4 0.91 101.9 -0.20 94.1 0.75 Tmax(˚C) and Tmin(˚C)   Co-86032   Co-0118   BO-120   CoSe-98255   CoS-08272   Para- meters Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change 3 108.7 -2.69 84.2 2.56 77.8 0.39 105.1 2.94 95.5 2.25 2 108.6 -2.78 83.8 2.07 77.5 0.00 104.4 2.25 95.1 1.82 1 109.3 -2.15 83.8 2.07 77.5 0.00 103.5 1.37 92.5 -0.96 -1 109.1 -2.33 82.9 0.97 76.8 -0.91 99.1 -2.94 90.2 -3.43 -2 107.1 -4.12 81.1 -1.22 75 -3.26 94.7 -7.25 86.3 -7.60 -3 103.3 -7.52 78.3 -4.63 72.1 -7.04 89.8 -12.05 84.3 -9.74 Tmax(˚C), Tmin(˚C) and Solar radiation(MJ/m2/day)   Co-86032   Co-0118   BO-120   CoSe-98255   CoS-08272   Para- meters Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change Simulated (t/ha) % change 3 121.8 9.04 97.5 18.76 90.1 17.47 119.9 17.43 110.9 18.74 2 118.3 5.91 90 9.62 86 12.13 115 12.63 105.7 13.17 1 114.4 2.42 88.4 7.67 81 5.61 109.2 6.95 100.2 7.28 -1 103 -7.79 78.3 -4.63 72.5 -5.48 93.7 -8.23 87.3 -6.53 -2 94.8 -15.13 72 -12.30 66.8 -12.91 84.1 -17.63 79.8 -14.56 -3 85.4 -23.55 65 -20.83 60 -21.77 74.5 -27.03 71.7 -23.23

30. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 30 Sensitivity Analysis with Weather Parameters in Development Stage

31. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 31 Cultivars Early plant Field observed Late Planting 45 days (Oct.) 30 days (Mid Oct.) 15days (Nov) (Mid Nov) 15 days (Dec.) 30 days (Mid Dec.) Co-86032 81.6 116.6 109.7 111.7 110.7 113.5 Co-0118 55.9 88.6 83.1 82.1 85 87 BO-120 52.5 80.5 75.7 76.7 78.9 78.4 CoSe-98255 69.7 109.5 100.1 102.1 102.7 104.4 CoS-08272 61.1 100.6 98.7 93.4 95.7 98.1 Evaluation of Agronomic Adaptation Measures Mid Oct. is best time for planting the sugarcane.

32. 5.Recommendation & Conclusion June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 32 The CANEGRO model simulated showed the highest producing yield for variety Co-86032 i.e. 111.70 t/ha whereas variety BO-120 produced the lowest yield similar crop management practices in an experimental field. Therefore, in sequence the varieties Co-86032, CoSe-98255, CoS-08272, Co-0118 and BO-120 are recommended for high cane yield producing sugarcane industries . The combine effect (solar radiation, Tmax, Tmin) is highly sensitive and huge change in percentage value of simulated yield. The production showed more in Co-0118, CoS-08272 and CoSe-98255 cultivar which was close to 18.76% but CoSe-98255 showed 27.03% decreased in yield on decrement of (-3) from base values . In the development stage, the simulation model was run with similar weather parameters to evaluate the % change in yield on increment and decrement. The output was only changed but effect seemed to be lower than germination stage . In overall, the research work highlighted that the simulated sugarcane yield model is directly proportional to weather parameters to almost varieties & came in conclusion that effect of climate change sensitivity to solar radiation is maximum than maximum temperature, minimum temperature, rainfall and CO2 concentration levels .

33. 33 June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE REFERENCES en.wikipedia.org – Sugarcane knoema.com - Nepal Sugar cane production, 1961-2023 Neupane , Prem Raj, Tek Narayan Maraseni , and Michael Köhl . 2017. “The Sugarcane Industry in Nepal: Opportunities and Challenges.” Environmental Development 24: 86–98 . samriddhi.org - The bitter side of Nepal's sugar economy nature.com - Measuring climate change's impact on different sugarcane onlinelibrary.wiley.com - The impact of climate change and climate extremes on Zhao DuLi , Zhao DuLi , and Li YangRui Li YangRui . 2015. “Climate Change and Sugarcane Production: Potential Impact and Mitigation Strategies .” Singels , A, M Jones, and M Van der Berg. 2008. “DSSAT v. 4.5 DSSAT/CANEGRO: Sugarcane Plant Module: Scientific Documentation.” Mount Edgecombe: International Consortium for Sugarcane Modeling: South African Sugarcane Research Institute . Jones, James W, Gerrit Hoogenboom , Cheryl H Porter, Ken J Boote , William D Batchelor , L A Hunt, Paul W Wilkens, Upendra Singh, Arjan J Gijsman , and Joe T Ritchie. 2003. “The DSSAT Cropping System Model.” European Journal of Agronomy 18 (3–4): 235–65. Verma , Amit Kumar, Pradeep Kumar Garg, K. S.Hari Prasad, and Vinay Kumar Dadhwal . 2023. “Variety-Specific Sugarcane Yield Simulations and Climate Change Impacts on Sugarcane Yield Using DSSAT-CSM-CANEGRO Model.” Agricultural Water Management 275 (July 2022): 108034. https://doi.org/10.1016/j.agwat.2022.108034 .

34. June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 34 11. Carvalho , André Luiz de, José Leonaldo de Souza, Alexsandro Claúdio Dos Santos Almeida, Gustavo Bastos Lyra, Guilherme Bastos Lyra, Iedo Teodoro , Ricardo Araújo Ferreira Junior, Ivomberg Dourado Magalhães , and Lekson Rodrigues Santos. 2018. “Sugarcane Productivity Simulation under Different Planting Times by DSSAT/CANEGRO Model in Alagoas, Brazil.” Emirates Journal of Food and Agriculture 30 (3): 190–98. https://doi.org/10.9755/ejfa.2018.v30.i3.1640 . MoALD, 2021. 2021. “Statistical Information On Nepalese Agriculture (2077/78 ).” Publications of the Nepal in Data Portal 73: 274. https://nepalindata.com/resource/statistical-information-nepalese-agriculture-207374-201617/.

35. Thank You June 15, 2024 IOE PURWANCHAL CAMPUS, FINAL THESIS DEFENCE 35 Any Queries