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پایایی، تاب‌آوری و آسیب‌پذیری حوزه آبخیز چالوس مبتنی بر شاخص خشک‌سالی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری علوم و مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور

2 استاد، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور

3 دانشجوی کارشناسی ارشد علوم و مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور

چکیده

خشک‌سالی از جمله بلایای طبیعی مرتبط با آب و هوا و یکی از بزرگ‌ترین تهدیدهای بقای انسان است که تأثیرات نامطلوبی بر پایداری اجتماعی، اقتصادی و محیط‌ زیستی می‌گذارد. حال آن‌که مقوله‌های مرتبط بر آن و از جمله تأثیر آن بر سلامت حوزه آبخیز کمتر مورد توجه قرارگرفته است. بر همین اساس، در این پژوهش سعی شده است تا سلامت حوزه آبخیز چالوس بر اساس تغییرات پایایی (Rel)، تاب‌آوری (Res) و آسیب‌پذیری (Vul) تحت تأثیر خشک‌سالی مستند به دوره آماری ۱۳۶۵ تا ۱۳۹۴ مورد ارزیابی قرار گیرد. برای انجام این پژوهش، داده‌های بارندگی نُه ایستگاه با روش عکس مجذور فاصله برای آبخیز میان‌یابی شد. سپس، با تعیین میانگین و انحراف معیار داده‌ها، شاخص خشک‌سالی (SPI) تعیین شد. همچنین، برای محاسبه شاخص‌های Rel، Res و Vul از مقدار میانه شاخص SPI استفاده شد. سپس، با محاسبه مقدار میانگین هندسی این شاخص‌ها وضعیت کلی سلامت آبخیز تعیین شد. نتایج پژوهش نشان داد، شاخص SPI در دوره آماری مذکور با مقادیری بین 1.43- و 2.25 الگویی همانند بارندگی داشته و با افزایش بارندگی در انتهای دوره، این شاخص نیز مقادیر مثبت بیشتری را به‌ خود اختصاص داده است. ارزیابی سلامت آبخیز نیز نشان داد که شاخص‌های Rel، Res و Vul به‌ترتیب 0.5، 0.23 تا 0.62 و 0.06 تا یک را داشته است. میانگین هندسی این شاخص‌ها نیز  بین 0.19 تا 0.58 بود. نهایتاً متوسط شاخص سلامت حوزه آبخیز چالوس بر اساس پویایی شاخص خشک‌سالی 0.45 و در گروه "متوسط" بود که نتایج به‌دست ‌آمده دلالت بر متوسط بودن شرایط اقلیمی حاکم بر منطقه و طبعاً نقش ماشه‌ای دخالت‌های انسانی در تهدید سلامت آبخیز چالوس دارد. یافته‌های بررسی نقش مهمی در تبیین شیوه‌های مدیریت سازگار حوزه آبخیز مذکور ایفا خواهد کرد.

کلیدواژه‌ها

عنوان مقاله [English]

Reliability, resilience, and vulnerability of Chalous Watershed based on drought index

نویسندگان [English]

  • Reza Chamani 1
  • Seyed Hamidreza Sadeghi 2
  • Mehdi Vafakhah 2
  • Maryam Naghdi 3

1 PhD Student in Watershed Management, Faculty of Natural Resources, Tarbiat Modares University, Noor. Iran

2 Professor of Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran

3 MSc Student, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran

چکیده [English]

Drought is one of the natural disasters related to climate and one of the most important threats to human survival leading to adverse effects on social, economic, and environmental sustainability. In this study, it has been tried to evaluate the changes in reliability, resilience, and vulnerability of the Chalous Watershed under the influence of drought in the period of 1982-2017. In this vein, rainfall data of nine stations were interpolated using invers distance squared method to the whole watershed. The SPI drought index was then determined through determining the mean and standard deviation of the data. To calculate Rel, Res and Vul indices, the mean value of SPI Index was used. By calculating the geometric mean value of these indicators, the general health status of the watershed was determined and quantified. The results showed that the SPI Index in this period varied between -1.43 and 2.25. Drought index had a similar pattern to that of rainfall with an increasing trend at the end of the period. The watershed health assessment also showed that the indicators of reliability, resilience, and vulnerability were found 0.5, from 0.23 to 0.62 and from 0.06 to 1, respectively. The geometric mean of these indices was also ranged between 0.19 and 0.58. The overall health condition of the Chalous Watershed based on the dynamics of drought index with a mean index of 0.45 was classified as “moderate”. The findings of the current research will play an important role in explaining the methods of adaptive management of the watershed.

کلیدواژه‌ها [English]

  • Healthy watershed
  • Integrated watershed management
  • Ecosystem health
  • Watershed degradation
مراجع
  1. Abeysingha, N.S. and U.R.L.N. Rajapaksha. 2020. SPI-based spatiotemporal drought over Sri Lanka. Advances in Meteorology, 2020: 1–10.
  2. Ahmed Suliman, A.H., T.A. Awchi, M. Al-Mola and S. Shahid. 2020. Evaluation of remotely sensed precipitation sources for drought assessment in semi-arid Iraq. Atmospheric Research, 242: 105007.
  3. Ahn, S.R. and S.J. Kim. 2019. Assessment of watershed health, vulnerability and resilience for
    determining protection and restoration priorities. Environmental Modelling and Software, 122: 103926.
  4. Ali, M., R.C. Deo, T. Maraseni and N.J. Downs. 2019. Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms. Journal of Hydrology, 576: 164-184.
  5. Alilou, H., O. Rahmati, V.P. Singh, B. Choubin, B. Pradhan, S. Keesstra and S.H.R. Sadeghi. 2019. Evaluation of ‎watershed health using Fuzzy-ANP approach considering geo-environmental and topo-hydrological ‎ Journal of Environmental Management, 232: 22–36.
  6. Danandeh Mehr, A., A.U. Sorman, E. Kahya and M. Hesami Afshar. 2019. Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara, Turkey. Hydrological Sciences Journal, 2: 1-40.
  7. Freire-González, J., C. Decker and J.W. Hall. 2017. The economic impacts of droughts: a framework for analysis. Ecological Economics, 132: 196–204.
  8. Ghorbanniya khaybari, V., M.M. Mirsanjari and M. Armin. 2017. Forecasting of forest land change in the Chaloosrood Watershed. Remote Sensing and GIS in Natural Resources, 8: 79-91 (in Persian).‎
  9. Hakimdoust, S.Y., A. Mohhamadpour zindi and M.S. Gerami. 2017. Spatial analysis of showers in Mazandaran Province in the GIS environment. Journal of Geographical Data (SEPEHR), 26: 191-203 (in Persian).‎
  10. Han, Z.M., S.Z. Huang, Q. Huang, G. Leng, H. Wang, L. He, W. Fang and P. Li. 2019. Assessing GRACE-based terrestrial water storage anomalies dynamics at multi-timescales and their correlations with teleconnection factors in Yunnan Province, China. Journal of Hydrology, 574: 836-850.
  11. Hashimoto, T., D.P. Loucks and J. Stedinger. 1982. Reliability, resilience and vulnerability for water resources system performance evaluation. Water Resources Research, 18: 14–20.
  12. Hazbavi, Z., J.E.M. Baartman, J.P. Nunes, S.D. Keesstra and S.H.R. Sadeghi. 2018. Changeability of reliability, resilience and vulnerability indicators with respect to drought patterns. Ecological Indicators, 87: 196–208.
  13. Hazbavi, S.D., Z. Keesstra, J.P. Nunes, J.E.M. Baartman, M. Gholamalifard and S.H.R. Sadeghi. 2018. Health comparative comprehensive assessment of watersheds with different climates. Ecological Indicators, 93: 781–790.
  14. Hazbavi, Z. and S.H.R. Sadeghi. 2017. Watershed health characterization using reliability–resilience–vulnerability conceptual framework based on hydrological responses. Land Degradation and Development, 28: 1528–1537.
  15. ‎Hazbavi, Z., S.H.R. Sadeghi, M. Gholamalifard and A.A. Davudirad. 2019. Watershed health assessment ‎using the Pressure–State–Response (PSR) framework. Land Degradation and Development, 31: 3–19. ‎
  16. Hoque, Y.M., C. Raj, M.M. Hantush, I. Chaubey and R.S. Govindaraju. 2014. How do land-use and climate change affect watershed health? a scenario-based analysis. Water Quality, Exposure and Health, 6: 19–33.
  17. Hosseinpour, M. and A. Fatehi Marj. 2018. Spatial analysis of meteorological drought during the first half of the water year 2013-2014 compared to the same period of the last water year using SPI and PN indexes in Iran. Watershed Engineering and Management, 10: 495-506 (in Persian).‎
  18. Hui, R., J. Herman, J. Lund and K. Madani. 2018. Adaptive water infrastructure planning for nonstationary hydrology. Advances in Water Resources, 118: 83-94.
  19. Jahangir, M.H., L. Noor Azar and S.M.E. Azimi. 2019. Analysis of the head of drought branches SPTI, SPI, SPEI using SOFM roots compared network in the province of Chahar Mahal Bakhtiari. Eco Hydrology, 6: 837-847 (in Persian).‎
  20. Karimi, V. and D. Akbari Nudehi. 2019. Comparison of meteorological drought indices in Mazandaran Province. Nayvar, 43: 73-85 (in Persian).‎
  21. Karimi, V., M. Habibnejad rosshan and A. Abkar. 2011. Investigation of meteorological drought Indexes in Mazandaran synoptic stations. Investigation of meteorological drought indices in synoptic stations of Mazandaran. Irrigation and Water Engineering, 2: 15-25 (in Persian).‎
  22. Khoshravesh, M., M. Mir Naseri and M. Pesar Koloo. 2017. Change detection of precipitation trend of northern part of Iran using Mann-Kendall non-parametric test. Journal of Watershed Management Research, 8: 223-231 (in Persian).‎
  23. Madanchi, P., K.M. Shahdi, K. Habibnejad and A. Fatehi Marj. 2019. Zoning climatic drought and drought magnitude using SPI Index and Kirijing geostatistical method, case study: Kerman Province. Irrigation and Water Engineering of Iran, 10: 203-226 (in Persian).‎‎
  24. McKee, T.B., N.J. Doesken and J. Kleist. 1393. The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology. AMS, Boston, MA. 179-184.
  25. Mehdi, B., R. Ludwig and B. Lehner. 2015. Evaluating the impacts of climate change and crop land use change on Streamflow, Nitrates and Phosphorus: a modeling study in Bavaria. Journal of Hydrology: Regional Studies, 4: 60–90.
  26. Mesbahzadeh, T. and N. Alipour. 2018. Evaluation of the effect of drought on the occurrence of dust phenomenon using PNI, SPI and ZSI indices. Rangeland and Watershed Management, 71: 505-5015 (in Persian).‎
  27. Milly, P.C.D., J. Betancourt, M. Falkenmark, R.M. Hirsch, Z.W. Kundzewicz, D.P. Lettenmaier and V. Krysanova. 2015. On critiques of “stationarity is dead: water management? Water Resources Research, 51: 7785-7789.
  28. Min, S.K., X. Zhang, F.W. Zwiers and G.C. Hegerl. 2013. Human contribution to more intense precipitation extremes. Nature, 498: 378-381.
  29. Mir akbari, M., Gh. Mortezaei Feriz Hendi and M. Mohseni Saravi. 2018. Investigation of the effect of meteorological drought on surface and groundwater resources by GRI, SPI, SPEI and SDI indices. Watershed Management Science and Engineering, 12: 70-80 (in Persian).‎
  30. Mohhamadpour zidi, A., K. Bozorgmer and S.Y. Hahimdoust. 2014. Spatial study of climatic drought based on standard precipitation SPI, case study: Mazandaran Province. Geographical Arrangement of Space, 4: 179-194 (in Persian).‎

 

  1. Mosaffaie, J. 2015. Comparison of two methods of regional flood frequency analysis by using L-moments. Water Resources Management, 42: 313–321.
  2. Mosaffaie, J. and A. Salehpour Jam. 2018. Economic assessment of the investment in soil and water conservation projects of watershed management. Arabian Journal of Geosciences, 11: 2-10.
  3. Munir Hayet Khan, M., N. Shazwani Muhammad and A. El-Shafie. 2020. Wavelet based hybrid ANN-ARIMA models for meteorological drought forecasting. Journal of Hydrology, 590: 125380.
  4. Olighiniya, T., N. Rasuli Majd and A. Hezar Jeribi. 2019. Evaluation and comparison of drought indices of West Azerbaijan Province using PI, CZI, PNI indexes and Geographic Information System (GIS). Irrigation Science and Engineering, 42: 175-188 (in Persian).‎
  5. Poff, N.L., C.M. Brown, T.E. Grantham, J.H. Matthews, M.A. Palmer, C.M. Spence, R.L. Wilby, M. Haasnoot, G.F. Mendoza, K.C. Dominique and A. Baeza. 2016. Sustainable water management under future uncertainty with eco-engineering decision scaling. Nature Climate Change, 6: 25-34.
  6. Ren, K., S. Huang, Q. Huang, H. Wang, G. Leng, W. Fang and L. Li. 2020. Assessing the reliability, resilience and vulnerability of water supply system under multiple uncertain sources. Journal of Cleaner Production, 252: 119806.
  7. Rezaei, H., N. Khanmohamadi, M. Montaseri and J. Behmanesh. 2018. Evaluating the selection of the most suitable probability distribution function for using the RDI and SPI drought indices. Journal of Soil and Water Science, 25: 29-40 (in Persian).‎
  8. Sadeghi, S.H.R., Z. Hazbavi and M. Gholamalifard. 2019. Interactive impacts of climatic, hydrologic, and anthropogenic activities on watershed health. Science of the Total Environment, 648: 880–893.
  9. Sadeghi, S.H.R. and Z. Hazbavi. 2017. Spatiotemporal variation of watershed health propensity through reliability-resilience-vulnerability based drought index, case study: Shazand Watershed in Iran. Science of the Total Environment, 587: 168–176.
  10. Sadeghi, S.H.R. and Z. Hazbavi. 2016. Watershed health (part 1) conceptual model of reliability, flexibility and vulnerability. Extension and Development of Watershed Management, 14: 39–43 (in Persian).‎
  11. ‎Sadoddin, A., V.B. Sheikh, M. Ownegh, A. Najafi Nejad and S.H.R. Sadeghi. 2016. Development of a national mega research project on the integrated watershed management for Iran. Environmental Resources Research, 4: 231–238.
  12. Santos, C.A.G., R.M.B. Neto, T.V.M. do Nascimento, R.M. da Silva, M. Mishra and T.G. Frade. 2021. Geospatial drought severity analysis based on PERSIANN-CDR estimated rainfall data for Odisha state in India )1983–2018(. Science of the Total Environmental, 750: 141258.
  13. Smakhtin, V.U. and D.A. Hughes. 2004. Review, automated estimation and analyses of drought indices in South Asia. International Water Management Institute, 3: 1-24.
  14. Sobral, B.S., J.F. de Oliveira-Júnior, G. de Gois, E.R. Pereira-Júnior, P.M. de Bodas Terassi, J.G.R. Muniz-Júnior and M. Zeri. 2019. Drought characterization for the state of Rio de Janeiro based on the annual SPI index: trends, statistical tests and its relation with ENSO. Atmospheric Research, 220: 141-154.  
  15. Tirivarombo, S., D. Osupile and P. Eliasson. 2018. Drought monitoring and analysis: Standardized Precipitation Evapotranspiration Index [SPEI] and Standardized Precipitation Index [SPI]. Physics and Chemistry of the Earth, 106: 1-10.
  16. Vafakhah, M., M.R. Javadi and J. Najafi Majed. 2015. The effect of land use change on runoff in Chalousrood Watershed. Eco Hydrology, 2: 211-220 (in Persian).‎‎
  17. Van Loon, A.F. and H.A.J. van Lanen. 2013. Making the distinction between water scarcity and drought using an observation-modeling framework. Water Resources Research, 49: 1483–1502.
  18. Wang, G., Sh. Mang, H. Cai, Sh. Liu, Zh. Zhang, L. Wang and J. Innes. 2016. Integrated watershed management: evolution, development and emerging trends. Journal of Forestry Research, 27: 967–994
  19. Wiegand, A.N., C. Walker, P.F. Duncan, A. Roiko and N. Tindale. 2013. A systematic approach for modelling quantitative lake ecosystem data to facilitate proactive urban lake management. Environmental Systems Research, 2: 1-12.
  20. Won, J., J. Choi, O. Lee and S. Kim. 2020. Copula-based Joint Drought Index using SPI and EDDI and its application to climate change. Science of the Total Environment, 744: 140701.
  21. Yusefi, H., A.M. Kashki, A. Karami and E. Rihani. 2018. Comparison and configuration of groundwater quality in Bojnourd Plain during drought and wet seasons using indicators SPI, RAI, and PN. Eco Hydrology, 5: 993-1005 (in Persian).‎‎
مهندسی و مدیریت آبخیز
دوره 14، شماره 1
فروردین 1401
صفحه 65-75
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هم رسانی
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