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Health variability based on SPI and estimating median and mean health indices in watersheds and townships of Kermanshah Province, Iran

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Abstract

The watershed health assessment provides a vital roadmap for managers to appropriately focus on hotspots and work on controlling factors threatening soil and water resources and the livelihood of the beneficiary communities. However, the spatial mapping of drought-based watershed health at various managerial scales and using different procedures have to be studied. Therefore, using two manners of average calculation, this study zoned Kermanshah Province in Western Iran at watershed and township scales based on normalized precipitation index (SPI). Towards that, the monthly SPI drought index was calculated using rainfall data from 1993 to 2020 collected for the selected stations governing the study area. Arithmetic mean and median SPI thresholds for each station were then used to determine failure and satisfactory incidents. Finally, the reliability-resilience-vulnerability (RelResVul) framework was employed using thresholds found based on mean and median SPI for the health zoning of the study province. The results showed that Rel, Res, Vul, and weighted health indices based on the arithmetic mean varied between 0.51 and 0.54, 0.36 to 0.50, 0.46 to 0.72, and 0.47 to 0.52, respectively. On the other hand, based on the median, they ranged from 0.50 to 0.51, 0.37 to 0.46, 0.39 to 0.67, and 0.43 to 0.49, respectively. Due to the internal differences in the results of health indices obtained from the arithmetic mean and median, the lowest and highest health indices in the arithmetic mean belonged to watersheds 3 and 12, and those of the median were associated with watersheds 8 and 4. Likewise, on the Townships basis, the lowest and highest health indices, based on the arithmetic mean, belonged to Harsin and Kangavar, whereas, based on the median, Sahaneh and Eslamabad Gharb had the lowest and highest levels of health, respectively. According to the current study’s findings, median-based health assessment would produce a better health zoning to be utilized by decision-makers and local managers by validating disparities between data used for assessing health indices at two study scales. In addition, the current research results can provide managers and planners with a correct understanding of the governing conditions of the province from the viewpoint of drought, based on which the necessary priorities for allocating credit and carrying out executive actions can be correctly accomplished.

Highlights

Health status at watershed and township scales was assessed in Kermanshah Province.

Health index (HI) was assessed by reliability-resilience-vulnerability (RelResVul).

RelResVul indicators were calculated using standardized precipitation index (SPI).

Rel, Res, Vul and HI were comparatively obtained using arithmetic mean and median.

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Data availability

The data supporting this study’s findings are from Iran Meteorological Organization (https://www.irimo.ir/). Further data are available from the authors on request.

References

  • Abbaspour, K. C., Faramarzi, M., Ghasemi, S. S., & Yang, H. (2009). Assessing the impact of climate change on water resources in Iran. Water Resources Research, 45(10), 10434.

    Article  Google Scholar 

  • Andrews, S. S., Karlen, D. L., & Mitchell, J. P. (2002). A comparison of soil quality indexing methods for vegetable production systems in Northern California. Agriculture Ecosystems & Environment, 90(1), 25–45.

    Article  Google Scholar 

  • Anghel, C. G., & Ilinca, C. (2023). Hydrological Drought Frequency Analysis in Water Management using Univariate distributions. Applied Sciences, 13(5), 3055.

    Article  CAS  Google Scholar 

  • Ben Othman, D., & Abida, H. (2022). Monitoring and mapping drought in a semi-arid region: Case of the Merguellil watershed, central Tunisia. Environmental Monitoring and Assessment, 194(4), 287.

    Article  Google Scholar 

  • Cerpa Reyes, L. J., Ávila Rangel, H., & Herazo, L. C. S. (2022). Adjustment of the normalized precipitation index (SPI) for the evaluation of drought in the Arroyo pechelín basin, Colombia, under zero monthly precipitation conditions. Atmosphere, 13(2), 236.

    Article  Google Scholar 

  • Chamani, R., Sadeghi, S. H. R., Vafakhah, M., & Naghdi, M. (2022). Reliability, resilience, and vulnerability of Chalous Watershed based on drought index. Watershed Engineering and Management, 14(1), 65–75.

    Google Scholar 

  • Chamani, R., Sadeghi, S. H. R., Zare, S., Shekohideh, H., Mumzaei, A., Amini, H., Hemmati, L., & Zarei, R. (2023a). Flood-oriented watershed health and ecological security conceptual modeling using pressure, state, and response (PSR) approach for the Sharghonj Watershed. Natural Resource Modeling. e12385.

  • Chamani, R., Vafakhah, M., & Sadeghi, S. H. R. (2023b). Effect of drought on temporal-spatial changes of the Efin Watershed health. Watershed Engineering and Management, 15(1), 1–12.

    Google Scholar 

  • Chang, W., Li, W., Ma, H., Wang, D., Bandala, E. R., Yu, Y., & Rodrigo-Comino, J. (2022). An integrated approach for shaping drought characteristics at the watershed scale. Journal of Hydrology, 604, 127248.

    Article  Google Scholar 

  • Dąbrowska, J., Orellana, A. E. M., Kilian, W., Moryl, A., Cielecka, N., Michałowska, K., & Włóka, A. (2023). Between flood and drought: How cities are facing water surplus and scarcity. Journal of Environmental Management, 345, 118557.

    Article  Google Scholar 

  • Davari, M., Gholami, L., Nabiollahi, K., Homaee, M., & Jafari, H. J. (2020). Deforestation and cultivation of sparse forest impacts soil quality (case study: West Iran, Baneh). Soil and Tillage Research, 198, 104504.

    Article  Google Scholar 

  • Duan, T., Feng, J., Chang, X., & Li, Y. (2022). Watershed health assessment using the coupled integrated multistatistic analyses and PSIR framework. Science of the Total Environment, 847, 157523.

    Article  CAS  Google Scholar 

  • Duez, P., Dehon, G., Kumps, A., & Dubois, J. (2003). Statistics of the Comet assay: A key to discriminate between genotoxic effects. Mutagenesis, 18(2), 159–166.

    Article  CAS  Google Scholar 

  • Ervinia, A., Huang, J. L., Huang, Y. L., & Lin, J. Y. (2019). Coupled effects of climate variability and land use pattern on surface water quality: An elasticity perspective and watershed health indexes. Science of the Total Environment, 693, 133592.

    Article  CAS  Google Scholar 

  • Fekete, A., Hufschmidt, G., & Kruse, S. (2014). Benefits and challenges of resilience and vulnerability for disaster risk management. International Journal of Disaster Risk Science, 5(1), 3–20.

    Article  Google Scholar 

  • Fernández-de‐Uña, L., Martínez‐Vilalta, J., Poyatos, R., Mencuccini, M., & McDowell, N. G. (2023). The role of height‐driven constraints and compensations on tree vulnerability to drought. New Phytologist, 239(6), 2083–2098.

    Article  Google Scholar 

  • Gari, S. R., Guerrero, C. E. O., Uribe, B., Icely, J. D., & Newton, A. (2018). A DPSIR-analysis of water uses and related water quality issues in the Colombian Alto and Medio Dagua Community Council. Water Science, 32, 318–337.

    Article  Google Scholar 

  • Geissen, V., Sánchez-Hernández, R., Kampichler, C., Ramos-Reyes, R., Sepulveda-Lozada, A., Ochoa- Goana, S., de Jong, B. H. J., Huerta-Lwanga, E., & Hernández-Daumas, S. (2009). Effects of land-use change on some properties of tropical soils- An example from Southeast Mexico. Geoderma, 151, 87–97.

    Article  CAS  Google Scholar 

  • Ghasemi-Mobtaker, H., Kaab, A., & Rafiee, S. (2020). Application of life cycle analysis to assess environmental sustainability of wheat cultivation in the west of Iran. Energy, 193, 116768.

    Article  CAS  Google Scholar 

  • Hadi Pour, S., Abd Wahab, A. K., & Shahid, S. (2020). Spatiotemporal changes in aridity and the shift of drylands in Iran. Atmospheric Research, 233, 104704.

    Article  Google Scholar 

  • Hansen, M. K., Sharma, A. K., Dybdahl, M., Boberg, J., & Kulahci, M. (2014). In vivo Comet assay–statistical analysis and power calculations of mice testicular cells (Vol. 774, pp. 29–40). Mutation Research/Genetic Toxicology and Environmental Mutagenesis.

  • Hashimoto, T., Stedinger, J. R., & Loucks, D. P. (1982). Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), 14–20.

    Article  Google Scholar 

  • Hazbavi, Z., & Kalehhouei, M. (2020). Watershed management sciences and engineering conference in Iran: History and highlights. ECOPERSIA, 8(4), 231–245.

    Google Scholar 

  • Hazbavi, Z., & Sadeghi, S. H. R. (2017). Watershed health characterization using reliability–resilience–vulnerability conceptual framework based on hydrological responses. Land Degradation & Development, 28(5), 1528–1537.

    Article  Google Scholar 

  • Hazbavi, Z., Baartman, J. E. M., Nunes, J. P., Keesstra, S. D., & Sadeghi, S. H. R. (2018). Changeability of reliability, resilience, and vulnerability indexs with respect to drought patterns. Ecological Indexs, 87, 196–208.

    Article  Google Scholar 

  • Hazbavi, Z., Sadeghi, S. H. R., Gholamalifard, M., & Davudirad, A. A. (2019). Watershed health assessment using the pressure–state–response (PSR) framework. Land Degradation & Development, 31(1), 3–19.

    Article  Google Scholar 

  • Hoque, Y. M., Tripathi, S., Hantush, M. M., & Govindaraju, R. S. (2012). Watershed reliability, resilience, and vulnerability analysis under uncertainty using water quality data. Journal of Environmental Management, 109, 101–112.

    Article  CAS  Google Scholar 

  • Hoque, Y. M., Raj, C., Hantush, M. M., Chaubey, I., & Govindaraju, R. S. (2014). How do land-use and climate change affect watershed health? A scenario-based analysis. Water Quality Exposure and Health, 6(1), 19–33.

    Article  Google Scholar 

  • Hoque, Y. M., Tripathi, S., Hantush, M. M., & Govindaraju, R. S. (2016). Aggregate measures of watershed health from reconstructed water quality data with uncertainty. Journal of Environmental Quality, 45(2), 709–719.

    Article  CAS  Google Scholar 

  • Hu, J., Yang, Z., Hou, C., & Ouyang, W. (2023). Compound risk dynamics of drought by extreme precipitation and temperature events in a semi-arid watershed. Atmospheric Research, 281, 106474.

    Article  Google Scholar 

  • Jamshidi, R. (2016). Continuity of a decade of drought in stone and water land, HamshahriNewspaper, 17 May 2016.

  • Kalehhouei, M., Hazbavi, Z., Spalevic, V., Mincato, R. L., & Sestras, P. (2021). What is smart watershed management? Poljoprivreda i Sumarstvo, 67(2), 195–209.

    Google Scholar 

  • Khanian, M., Marshall, N., Zakerhaghighi, K., Salimi, M., & Naghdi, A. (2018). Transforming agriculture to climate change in Famenin County, West Iran, through a focus on environmental, economic, and social factors. Weather and Climate Extremes, 21, 52–64.

    Article  Google Scholar 

  • Khosravi, K., Panahi, M., Golkarian, A., Keesstra, S. D., Saco, P. M., Bui, D. T., & Lee, S. (2020). Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran. Journal of Hydrology, 591, 125552.

    Article  Google Scholar 

  • Koley, S., & Jeganathan, C. (2023). Evaluating the climatic and socio-economic influences on the agricultural drought vulnerability in Jharkhand. Environmental Monitoring and Assessment, 195(1), 8.

    Article  Google Scholar 

  • Koochaki, E., Nasiri Mahdi, M., & Kamali, G. (2007). Iran meteorological indexes in climate change conditions. Agronomy Research, 5(1), 133–142.

    Google Scholar 

  • Kousari, M. R., Ahani, H., & Hendi-zadeh, R. (2013). Temporal and spatial trend detection of maximum air temperature in Iran during 1960–2005. Global and Planetary Change, 111, 97–110.

    Article  Google Scholar 

  • Kumar, N. M., Murthy, C. S., Sesha Sai, M. V. R., & Roy, P. S. (2009). On the use of normalized Precipitation Index (SPI) for drought intensity assessment. Meteorological Applications: A Journal of Forecasting Practical Applications Training Techniques and Modelling, 16(3), 381–389.

    Article  Google Scholar 

  • Lankford, B., Pringle, C., McCosh, J., Shabalala, M., Hess, T., & Knox, J. W. (2023). Irrigation area, efficiency, and water storage mediate the drought resilience of irrigated agriculture in a semi-arid catchment. Science of the Total Environment, 859, 160263.

    Article  CAS  Google Scholar 

  • Li, Y., Lu, H., Yang, K., Wang, W., Tang, Q., Khem, S., Yang, F., & Huang, Y. (2021). Meteorological and hydrological droughts in Mekong River Basin and surrounding areas under climate change. Journal of Hydrology: Regional Studies, 36, 100873.

    Google Scholar 

  • Li, H., Zhang, S., Zhang, J., Zhang, W., Song, Z., Yu, P., & Xie, C. (2023). A framework for identifying priority areas through integrated eco-environmental risk assessment for a holistic watershed management approach. Ecological Indexs, 146, 109919.

    Article  Google Scholar 

  • Lotfirad, M., Esmaeili-Gisavandani, H., & Adib, A. (2022). Drought monitoring and prediction using SPI, SPEI, and random forest models in various climates of Iran. Journal of Water and Climate Change, 13(2), 383–406.

    Article  Google Scholar 

  • Mahmoodi, S., Heydari, M., Ahmadi, K., Khwarahm, N. R., Karami, O., Almasieh, K., Naderi, B., Bernard, P., & Mousavi, A. (2022). The current and future potential geographical distribution of Nepeta Crispa Willd., an endemic, rare and threatened aromatic plant of Iran: Implications for ecological conservation and restoration. Ecological Indexs, 137, 108752.

    Article  Google Scholar 

  • Mallya, G., Hantush, M., & Govindaraju, R. S. (2018). Composite measures of watershed health from a water quality perspective. Journal of Environmental Management, 214, 104–124.

    Article  CAS  Google Scholar 

  • McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, 17 (22), 179–183.

  • Mehravar, S., Amani, M., Moghimi, A., Javan, F. D., Samadzadegan, F., Ghorbanian, A., & Stein A., Mell, I. (2020). The impact of austerity on funding green infrastructure: A DPSIR evaluation of the Liverpool Green & Open Space Review (LG&OSR), UK. Land Use Policy, 91, 104284.

  • Moghim, S. (2018). Impact of climate variation on hydrometeorology in Iran. Global and Planetary Change, 170, 93–105.

    Article  Google Scholar 

  • Mokarram, M., & Pham, T. M. (2023). Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data. Natural Hazards, 116(1), 1291–1314.

    Article  Google Scholar 

  • Montes-Vega, M. J., Guardiola-Albert, C., & Rodríguez-Rodríguez, M. (2023). Calculation of the SPI, SPEI, and GRDI Indices for Historical Climatic Data from Doñana National Park: Forecasting climatic series (2030–2059) using two climatic scenarios RCP 4.5 and RCP 8.5 by IPCC. Water, 15(13), 2369.

    Article  Google Scholar 

  • Moradi, S., & Limaei, S. M. (2018). Multi-objective game theory model and fuzzy programming approach for sustainable watershed management. Land Use Policy, 71, 363–371.

    Article  Google Scholar 

  • Morid, S., Moghaddasi, M., Arshad, S., & Omid, M. (2005). Drought index package (version 2). Tarbiat Modarres University.

  • Mosaffaie, J., Jam, A. S., Tabatabaei, M. R., & Kousari, M. R. (2021). Trend assessment of the watershed health based on DPSIR framework. Land Use Policy, 100, 104911.

    Article  Google Scholar 

  • Movahedi, R., Jawanmardi, S., Azadi, H., Goli, I., Viira, A. H., & Witlox, F. (2021). Why do farmers abandon agricultural lands? The case of western Iran. Land Use Policy, 108, 105588.

    Article  Google Scholar 

  • Penny, J., Khadka, D., Alves, P. B., Chen, A. S., & Djordjević, S. (2023). Using Multi Criteria Decision Analysis in a geographical information system framework to assess Drought Risk. Water Research X, 100190.

  • Rahmani, F., & Fattahi, M. H. (2023). Long-term evaluation of land use/land cover and hydrological drought patterns alteration consequences on river water quality (pp. 1–18). Environment, Development and Sustainability.

  • Rashki, A., Middleton, N. J., & Goudie, A. S. (2021). Dust storms in Iran–Distribution, causes, frequencies and impacts. Aeolian Research, 48, 100655.

    Article  Google Scholar 

  • Ren, J., Wang, W., Wei, J., Li, H., Li, X., Liu, G., & Ye, S. (2023). Evolution and prediction of drought-flood abrupt alternation events in Huang-Huai-Hai River Basin, China. Science of the Total Environment, 869, 161707.

    Article  CAS  Google Scholar 

  • Rietveld, T., & Van Hout, R. (2017). The paired t-test and beyond recommendations for testing the central tendencies of two paired samples in research on speech, language, and hearing pathology. Journal of Communication Disorders, 69, 44–57.

    Article  Google Scholar 

  • Sadeghi, S. H. R., Hazbavi, Z., & Gholamalifard, M. (2019). Interactive impacts of climatic, hydrologic, and anthropogenic activities on watershed health. Science of the Total Environment, 648, 880–893.

    Article  CAS  Google Scholar 

  • Sadeghi, S. H. R., Chamani, R., Zabihi Silabi, M., Tavosi, M., Katebikord, A., Khaledi Darvishan, A., Moosavi, V., Sadeghi, P. S., Vafakhah, M., & Moradi Rekabdarkolaei, H. (2023). Watershed health and ecological security zoning throughout Iran. Science of the Total Environment, 20, 905167123.

    Google Scholar 

  • Sadoddin, A., Ownegh, M., Najafi Nejad, A., & Sadeghi, S. H. R. (2016). Development of a National Mega Research Project on the integrated watershed management for Iran. Environmental Resources Research, 4(2), 231–238.

    Google Scholar 

  • Salimi, H., Asadi, E., & Darbandi, S. (2021). Meteorological and hydrological drought monitoring using several drought indices. Applied Water Science, 11(2), 1–10.

    Article  Google Scholar 

  • Shahbazi, K., Khosroshahi, M., Heshmati, M., & Saieedifar, Z. (2022). Effects of climate change on dust storm occurrence in Kermanshah Province. Iran ECOPERSIA, 10(2), 121–131.

    Google Scholar 

  • Sharafi, L., Zarafshani, K., Keshavarz, M., Azadi, H., & Van Passel, S. (2020). Drought risk assessment: Towards drought early warning system and sustainable environment in western Iran. Ecological Indexs, 114, 106276.

    Article  Google Scholar 

  • Shen, Y., & Jiang, C. (2023). A comprehensive review of watershed flood simulation model. Natural Hazards, 1–28.

  • Smirnov, O., Lahav, G., Orbell, J., Zhang, M., & Xiao, T. (2023). Climate change, drought, and potential environmental migration flow under different policy scenarios. International Migration Review, 57(1), 36–67.

    Article  Google Scholar 

  • Spiegel, J. M., Bonet, M., Yassi, A., Molina, E., Concepcion, M., & Mast, P. (2001). Developing ecosystem health indexes in Centro Habana: A community-based approach. Ecosystem Health, 7(1), 15–26.

    Article  Google Scholar 

  • Tabari, H., AghaKouchak, A., & Willems, P. (2014). A perturbation approach for assessing trends in precipitation extremes across Iran. Journal of Hydrology, 519, 1420–1427.

    Article  Google Scholar 

  • Taiwo, B. E., Kafy, A. A., Samuel, A. A., Rahaman, Z. A., Ayowole, O. E., Shahrier, M., Duti, B. M., Rahman, M. T., Peter, O. T., & Abosede, O. O. (2023). Monitoring and predicting the influences of land use/land cover change on cropland characteristics and drought severity using remote sensing techniques. Environmental and Sustainability Indexs, 18, 100248.

    Article  Google Scholar 

  • Tran, D. D., Nguyen, T. D., Park, E., Nguyen, T. D., Ngoc, P. T. A., Vo, T. T., & Nguyen, A. H. (2023a). Rural out-migration and the livelihood vulnerability under the intensifying drought and salinity intrusion impacts in the Mekong Delta. International Journal of Disaster Risk Reduction, 93, 103762.

    Article  Google Scholar 

  • Tran, T. V., Bruce, D., Huang, C. Y., Tran, D. X., Myint, S. W., & Nguyen, D. B. (2023b). Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data. GIScience & Remote Sensing, 60(1), 2163070.

    Article  Google Scholar 

  • Tsakiris, G., & Vangelis, H. (2004). Towards a drought watch system based on spatial SPI. Water Resources Management, 18, 1–12.

    Article  Google Scholar 

  • Upadhyay, M., & Sherly, M. A. (2023). Multivariate framework for integrated drought vulnerability assessment–An application to India. International Journal of Disaster Risk Reduction, 85, 103515.

    Article  Google Scholar 

  • Veuillen, L., Prévosto, B., Alfaro-Sánchez, R., Badeau, V., Battipaglia, G., Beguería, S., & Cailleret, M. (2023). Pre-and post-drought conditions drive resilience of Pinus halepensis across its distribution range. Agricultural and Forest Meteorology, 339, 109577.

    Article  Google Scholar 

  • Visockiene, J. S., Tumeliene, E., & Maliene, V. (2019). Analysis and identification of abandoned agricultural land using remote sensing methodology. Land Use Policy, 82, 709–715.

    Article  Google Scholar 

  • Wang, M., Xu, B., Zhang, C., Peng, Y., Li, Y., Yu, B., & Du, X. (2023a). Evaluating the sustainability of groundwater resources: A framework incorporating the ecological groundwater depth and reliability, resilience, and vulnerability indexes. Water Resources Research, 1–45.

  • Wang, R., Li, X., Zhang, Q., Cheng, J., Li, J., Zhang, D., & Liu, Y. (2023b). Projection of drought-flood abrupt alternation in a humid subtropical region under changing climate. Journal of Hydrology, 624, 129875.

    Article  Google Scholar 

  • Xu, C., Zhou, Y. K. W., Luo, W., Ma, W., Song, L., Smith, M. D., Hoover, D. L., Wilcox, K. R., Fu, W., Zhang, W., Zeng, P., Sun, F., Liu, Y., & Che, Y. (2020). Future river basin health assessment through reliability-resilience-vulnerability: Thresholds of multiple dryness conditions. Science of the Total Environment, 741, 140395.

    Article  Google Scholar 

  • Xu, Y., Jiang, Z., Liu, Y., Zhang, L., Yang, J., & Shu, H. (2023). An adaptive ensemble framework for flood forecasting and its application in a small watershed using distinct rainfall interpolation methods. Water Resources Management, 37(5), 2195–2219.

    Article  Google Scholar 

  • Yerdelen, C., Abdelkader, M., & Eris, E. (2021). Assessment of drought in SPI series using continuous wavelet analysis for Gediz Basin, Turkey. Atmospheric Research, 260, 105687.

    Article  Google Scholar 

  • You, Q., Fang, N., Jian, M., Hu, Q., Yao, B., Liu, D., & Yang, W. (2022). A reliability-resilience-vulnerability framework for measuring the influence of changes in water level fluctuations on lake conditions. Ecological Indexs, 134, 108468.

    Article  Google Scholar 

  • Zhang, Y., You, Q., Ullah, S., Chen, C., Shen, L., & Liu, Z. (2023). Substantial increase in abrupt shifts between drought and flood events in China based on observations and model simulations. Science of the Total Environment, 876, 162822.

    Article  CAS  Google Scholar 

  • Zohrevandi, A. A., & Sagheb Talebi, K. (2021). Distribution pattern of wild pear (Pyrus spp.) in the forests of Kermanshah Province of Iran. Applied Biology, 33(4), 165–178.

    Google Scholar 

  • Zolfaghari, H., Sahrai, J., Sahaghobadi, F., & Jalilian, A. (2014). Analysis of synoptic and dynamic aspects of air pollution in Kermanshah city. Journal of Geography and Environmental Hazards, 3(1), 75–96.

    Google Scholar 

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  1. Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Noor, 46417-76489, Iran

    Seyed Hamidreza Sadeghi

  2. Agrohydrology Research Group, Tarbiat Modares University, Tehran, Iran

    Reza Chamani, Mahin Kalehhouei & Khadijeh Haji

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  1. Seyed Hamidreza Sadeghi
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Sadeghi, S.H., Chamani, R., Kalehhouei, M. et al. Health variability based on SPI and estimating median and mean health indices in watersheds and townships of Kermanshah Province, Iran. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04911-z

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