Muhaisen, N., Khayyun, T., Al-Mukhtar, M. (2024). Drought forecasting model for future climate change effects in a regional catchment area in northern iraq. , 42(5), 525-539. doi: 10.30684/etj.2024.144458.1634
Nasser Kh. Muhaisen; Thair S. Khayyun; Mustafa M. Al-Mukhtar. "Drought forecasting model for future climate change effects in a regional catchment area in northern iraq". , 42, 5, 2024, 525-539. doi: 10.30684/etj.2024.144458.1634
Muhaisen, N., Khayyun, T., Al-Mukhtar, M. (2024). 'Drought forecasting model for future climate change effects in a regional catchment area in northern iraq', , 42(5), pp. 525-539. doi: 10.30684/etj.2024.144458.1634
Muhaisen, N., Khayyun, T., Al-Mukhtar, M. Drought forecasting model for future climate change effects in a regional catchment area in northern iraq. , 2024; 42(5): 525-539. doi: 10.30684/etj.2024.144458.1634

Drought forecasting model for future climate change effects in a regional catchment area in northern iraq

Engineering and Technology Journal
Volume 42, Issue 5, May 2024, Pages 525-539    PDF (2.07 M)
Document Type: Research Paper
DOI: 10.30684/etj.2024.144458.1634
Authors
Nasser Kh. Muhaisen* ; Thair S. Khayyun; Mustafa M. Al-Mukhtar
Civil Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.
Abstract
Climate change plays a crucial role in shaping the hydrological dynamics of rivers owing to its immediate implications on the driving meteorological parameters. Therefore, Understanding climate change and its implications is essential for sustainable water resource management. This study aims to assess the extent of climate change and its effects on streamflow in the Mosul Dam watershed Under three global warming Representative Concentration Pathways scenarios (i.e., 2.6, 4.5, and 8.5) based on mean climate data extracted from four Global Circulation Models (i.e., Beijing Climate Center, China, Commonwealth Scientific and Industrial Research Organization, Australia, Met Office Hadley Center, United Kingdom, and Norwegian Climate Center, Norway). For this purpose, the stochastic weather generator model (LARS – WG) and soil and water assessment tool (SWAT) were used. The hydrological model (SWAT) was calibrated and validated for 2001-2013 and 2014-2020, respectively. The performance of the swat model according to the four statistical parameters (i.e., coefficient of determination, Nash-Sutclife, Root mean square error to the standard deviation, and percent bias test) was classified as very good for two calibration and validation processes. Additionally, results showed that the mean temperature would probably rise by 1.3, 2.4, and 4.5°C under RCP 2.6, RCP 4.5, and RCP 8.5 at the end of this century, respectively. At the end of the century, the simulated average annual precipitation decreased from 772 mm/y to 756.7 and 741.6 mm/y under RCP4.5 and RCP8.5, respectively. In contrast, under the RCP2.6 scenario, the mean annual precipitation increased to 803 mm/year. As a result, the projected mean annual streamflow decreased from 501.52 m3/s to 429.7, 391.9, and 376.6 m3/s at the end of the century under RCP2.6, RCP4.5, and RCP8.5, respectively. Finally, the study region will potentially face water shortage due to climate change, exacerbated by population growth and increased water demands from agriculture and municipalities. Therefore, this paper emphasizes the need for reevaluating and adapting to accommodate changing streamflow patterns, ensuring a sustainable water supply for human needs while protecting the environment.

Highlights
  • This study evaluated climate effects on Mosul Dam streamflow under 3 warming scenarios with 4 climate models.
  • Findings projected temperature rise and diverse precipitation changes by 2100 based on scenarios.
  • This research is the inaugural extensive examination of physical and meteorological traits in Iraq, Turkey, and Syria.
Keywords
Climate change Tigris River Streamflow LARS; WG SWAT model
References
  1. Abbas, S.A. Wasimia, N. Al-Ansari, Assessment of Climate Change Impacts on Water Resources of Al-Adhaim, Iraq Using SWAT Model, Engineering, 8 (2016) 716-732. http://dx.doi.org/10.4236/eng.2016.810065
  2. Al-Mukhtar, V. Dunger, B. Merkel, Evaluation of the climate generator model CLIGEN for rainfall data simulation in Bautzen catchment area, Germany. Hydrol. Res., 45 (2014) 615–630.  https://doi.org/10.2166/nh.2013.073
  3. Wang, T. Yang, B. Yong, V. Krysanova, P. Shi., Environmental effects of climate change in the source regions of the Yellow River, J. Glaciol. Geocryol., 15 (2014) 1183–1192. https://doi.org/10.3390/w15112104
  4. Si, J. Li, Y. Yang, X. Qi, J. Li, Z. Liu, M. Li, S. Lu, Y. Qi, C. Jin, L. Qi, B. Yi, Y. Wang‏, Evaluation and prediction of groundwater quality in the source region of the Yellow River. Water, 14 (2022) 3946. https://doi.org/10.3390/w14233946
  5. Hagemann, C. Chen, J. Haerter, J. Heinke, D. Gerten, & C. Piani, Impact of a statistical bias correction on the projected hydrological changes obtained from three gcms and two hydrology models. J. Hydrometeorol., 12 (2011) 556–578. https://doi.org/10.1175/2011JHM1336.1
  6. Dehghan, N. Salehnia, N. Sayari, & B. Bakhtiari, Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: A case study in Fars Province, Iran. J. Arid. Land, 12 (2020) 318–330. https://doi:10.1007/s40333-020-0095-5
  7. Birara, R. Pandey, & S. Mishra, Projections of future rainfall and temperature using statistical downscaling techniques in Tana Basin, Ethiopia. Sustainable Water Resour. Manage., 6 (2020). https://doi.org/10.1007/s40899-020-00436-1
  8. Mohammed, & W. H. Hassan, Climate change and the projection of future temperature and precipitation in southern Iraq using a Lars-WG model. Model. Earth Syst. Environ., 8 (2022) 4205–4218. https://doi:10.1007/s40808-022-01358-x
  9. Osman, N. Al-Ansari, M. Abdellatif, S. B. Aljawad, & S. Knutsson, Expected future precipitation in central Iraq using Lars-WG Stochastic Weather Generator. Engineering, 6 (2014) 948–959. https://doi:10.4236/eng.2014.613086
  10. Phuong, T. Duong, N. Liem, V. Tram, D. Cuong & N. Loi, Projections of future climate change in the vu Gia Thu Bon River Basin, Vietnam by using statistical downscaling model (SDSM). Water, 12 (2020) 755. https://doi:10.3390/w12030755
  11. Kavwenje, L. Zhao, L. Chen, & E. Chaima, Projected temperature and precipitation changes using the statistical downscaling model in the Shire River Basin, Malawi. Int. J. Climatol., 42 (2021) 400–415. https://doi:10.1002/joc.7250
  12. Munawar, M. Tahir, & M. Baig, Twenty-first century hydrologic and climatic changes over the scarcely gauged Jhelum River basin of Himalayan region using SDSM and RCPS. Environ. Sci. Pollut. Res., 29 (2021) 11196–11208. https://doi:10.1007/s11356-021-16437-2
  13. Chen, K.Chau, Intelligent manipulation and calibration of parameters for hydrological models. Int. J. Environ. Pollut., 28 (2006) 432. https://doi:10.1504/ijep.2006.011221
  14. Martinec, A. Rango, R. Roberts, Snowmelt Runoff Model (SRM) User's Manual; Agricultural Experiment Station Special Report 100; College of Agriculture and Home Economics: Las Cruces, NM, USA, 2008; p. 180.
  15. Jajarmizadeh, S. Harun, & M. Salarpour, An assessment on base and peak flows using a physically-based model. Res. J. Environ Earth Sci., 5.(2013) 49–57.
  16. G. Arnold, D. N. Moriasi, P. W. Gassman, K. C. Abbaspour, M. J. White, R. Srinivasan, C. Santhi, R. D. Harmel, A. van Griensven, M. W. Van Liew, N. Kannan, M. K. Jha, SWAT: Model Use, Calibration, and Validation. American Society of Agricultural and Biological Engineers, 55 (2012) 1491-1508. https://doi:0.13031/2013.42256
  17. W. Gassman, M. R. Reyes, C. H. Green, J. G. Arnold, The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Direction. Trans. ASABE, 50 (2007) 1211–1250. https://doi.org/10.13031%2F2013.23637
  18. S. Al- Khafaji, M. Al-Mukhtar, & A. S. Mohena, Performance of SWAT Model for Long-Term Runoff Simulation within Al- Adhaim Watershed, Iraq. Int. j. Sci. Eng. Res., 8 (2017) 1510 – 1517.
  19. S. Khayyun, I. A. Alwan, A. M. Hayder,  Hydrological model for Hemren dam reservoir catchment area at the middle River Diyala reach in Iraq using ArcSWAT model. Appl. Water Sci., 9 (2019) 1-15. https://doi.org/10.1007/s13201-019-1010-0
  20. Koltsida, N. Mamassis, K. Andreas, Hydrological modeling using the SWAT Model in urban and peri-urban environments: The case of Kifissos experimental sub-basin (Athens, Greece), J. Hydrol. Earth Syst. Sci., (2021) 1-24. http://doi.org/10.5194/hess-2021-482
  21. Marahatta, L. P. Devekota, D. Aryal, Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part I: Model Development). Water, 13 (2021) 1-15. https://doi.org/10.3390/w13111546
  22. Al-Kakey, M. Al-Mukhtar, S. Berhanu, & V. Dunger, Assessing CFSR climate data for rainfall-runoff modeling over an ungauged basin between Iraq and Iran. Kuwait J. Sci., 50 (2023) 405-414, https://doi.org/10.1016/j.kjs.2022.12.004
  23. Abbasa, S. A. Wasimia, N. Al-Ansari, & S. Baby, Recent Trends and Long-Range Forecasts of Water Resources of Northeast Iraq and Climate Change Adaptation Measures, J. Water, 10 (2018) 1562. https://doi.org/10.3390/w10111562
  24. Al- Hilo, F. Saeed, & N. Al-Ansari, Impact of Climate Change on Water Resources of Dokan Dam Watershed. J. Eng., 11 (2019) 464-474. https://doi.org/10.4236/eng.2019.118033
  25. Gassman, A. Sadeghi, & R. Srinivasan, Applications of the SWAT model special section: Overview and insights, J. Environ. Qual., 43 (2014) 1–8. https://doi.org/10.2134/jeq2013.11.0466
  26. Shinde, N. Kamlesh, B. Sachin, & S. Manjushree, Water Quality Assessment and Application of SWAT Model for Hydrologic Simulations in a Mined Watershed. Clim. Chang. Environ. Sustain., 2 (2017) 111-121. http://dx.doi.org/10.5958/2320-642X.2017.00012.6
  27. Chaoyue Li, Haiyan Fang, Assessment of climate change impacts on the streamflow for the Mun River in the Mekong Basin, Southeast Asia: Using SWAT model, CATENA, 201 (2021) 105199. https://doi.org/10.1016/j.catena.2021.105199
  28. Hemrassi, M. Khadhroui, H. Habaieb, Hydrological modelling of stream flows in the Rmel watershed using SWAT model. J. new sci., Agriculture and Biotechnology, 12 (2017) 2684-2692.
  29. Samuel, A. Shaibu, & A. Raymond, Application of SWAT hydrological model for assessing water availability at the Sherigu catchment of Ghana and Southern Burkina Faso. HydroResearch 3 (2020) 124-133. https://doi.org/10.1016/j.hydres.2020.10.002
  30. Vilaysanea, K. Takaraa, L. Pingping, A. Inthavy, D. Weili, Hydrological stream flow modelling for calibration and uncertainty analysis using SWAT model in the Xedone river basin, Lao PDR. Procedia Environ. Sci., 28 (2015) 380 – 390. https://doi.org/10.1016/j.proenv.2015.07.047
  31. Al- Hadithi, A. Elaiwi, & K. Hassan, Management of natural Iraqi water resources, Aims and Challenges, 3rd International conference on sustainable engineering techniques. 881 (2020) 012181. https://doi.org/10.1088/1757-899X/881/1/012181
  32. Al-Madhhachi, A. Khayyun, & K. Wafa, Hydrological Impact of Ilisu Dam on Mosul Dam; the River Tigris. J. Geosci., 10 (2020) 1-14. https://doi.org/10.3390/geosciences10040120
  33. Zakaria, N. Al-Ansari, S. Knutsson, Historical and future climatic change scenarios for temperature and rainfall for Iraq. J. Civ. Eng. Archit., 7 (2013) 1574-1594. http://dx.doi.org/10.17265/1934-7359/2013.12.012
  34. Al-Khafaji, F. Saeed, Effect of DEM and land cover resolutions on simulated runoff of adhaim watershed by SWAT model. J. Eng. Technol., 36 (2018) 439–448. https://doi.org/10.30684/etj.36.4a.11
  35. Al- Dabbagh, Z. Optimum hydroelectric energy generated from Mosul dam reservoir based on inflow ranges. Thesis submitted to the University of Mosul in a Partial Fulfullment of the Requirements for the Degree of of Master in Water Resources Engineering Sciences/ Iraq, 2022.
  36. Saddique, M. Usman, C. Bernhofer, Simulating the impact of climate change on the hydrological regimes of a sparsely gauged mountainous basin, Northern Pakistan. Water, 11 (2019, 2141. https://doi.org/10.3390/w11102141
  37. Chakilu, S. Sándor, T. Zoltán, Change in stream flow of Gumara watershed, Upper Blue Nile Basin, Ethiopia under representative concentration pathway climate change scenarios. Water, 12 (2020) 3046. https://doi.org/10.3390/w12113046
  38. Jianhua, L. Jianming, L. Sujin, Q. Xuejiao,. Effects of climate change on surface runoff and soil moisture in the source region of the Yellow River. Water, 15 (2023) 2014. https://doi.org/10.3390/w15112104
  39. Mehan, T. Guo, M. Gitau, & D. Flanagan, Comparative study of different stochastic weather generators for long-term climate data simulation. Climate, 5 (2017) 26. https://doi.org/10.3390/cli5020026
  40. Gitau, S. Mehan, & T. Guo, Weather Generator effectiveness in capturing climate extremes. Environmental Processes, 5 (2018) 153–165. https://doi.org/10.1007/s40710-018-0291-x
  41. G. Arnold, D.N. Moriasi, P.W. Gassman, K.C. Abbaspour, M.J. White, R. Srinivasan, C. Santhi, SWAT: Model Use Calibration and Validation, Am. Soc. Agric. Biol. Eng.,  55 (2012) 1491-1508.
  42. Gassman, R. Reyes, C. Green, J. Arnold , The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions. Trans. ASABE, 50 (2007) 1211–1250. https://doi.org/10.13031/2013.23637
  43. Williams, Flood routing with variable travel time or variable storage coefficients, Trans. Asabe, 12 (1969) 0100–0103. https://doi.org/10.13031/2013.38772
  44. Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., & Yang, H. Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. J. Hydrol., 358 (2008) 1–23. https://doi.org/10.1016/j.jhydrol.2008.05.012
  45. Saeed, F.H. (2022). Climate Change Adaptation Multi-criteria Decision-Making Model for Conflict Resolution of Water Resources Allocation in Iraq. Thesis, University of Technology.
  46. Haitham, M. Al-Mukhtar, Assessment of future climate change impacts on water resources of Khabour River catchment, north of Iraq. J. Eng. Technol, 40 (2022) 695–709. https://doi.org/10.30684/etj.v40i5.1925
  47. Wu, J. Chen, Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal Climate River basin in South China, Environ. Manage., 51 (2013) 1174–1186. https://doi.org/10.1007/s00267-013-0045-5
  48. S. Ahl, S.W. Woods, H.R. Zuuring‏, Hydrologic calibration and validation of Swat in a snow‐dominated Rocky Mountain Watershed, Montana, u.s.a.1, J. Am. Water Resour. Assoc., 44 (2008) 1411–1430. https://doi.org/10.1111/j.1752-1688.2008.00233.x
  49. N. Moriasi, J.G. Arnold, M.W .Van Liew, R.L. Bingner, R.D Harmel, T.L. Veith‏, Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, Am. Soc. Agric. Biol. Eng., 50 (2007) 885–900. https://doi.org/10.13031/2013.23153
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