Relationship Between Cloud Seeding and Variation in Precipitation Levels in Agricultural Areas of the Arequipa Region, 2024
DOI:
https://doi.org/10.47840/ReInA.7.1.2335Keywords:
cloud seeding, precipitation, correlation, Arequipa, water resources.Abstract
This study examines the relationship between cloud seeding and precipitation levels in agricultural areas of the Arequipa region, Peru, during 2024. Employing a quantitative approach with a non-experimental cross-sectional design and correlational scope, precipitation data were collected from both seeded and control zones. Results showed a 25.3% average increase in precipitation levels in seeded areas, with a high positive correlation (r > 0.8) between seeding frequency and observed increases. Statistical tests revealed significant differences (p < 0.005), validating the effectiveness of cloud seeding as a tool to alleviate water scarcity in semi-arid regions. Numerical simulations predicted outcomes with less than 3% deviation, underscoring the reliability of the applied models. However, the study highlights the need for long-term monitoring of environmental impacts. This research offers a robust scientific foundation for the strategic management of water resources in areas vulnerable to climate change.
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Azeez, H. M., Ibraheem, N. T., & Hussain, H. H. (2024). Alternate chemical compounds as a condensation nucleus in cloud seeding. Nature Environment and Pollution Technology, 23(3), 1795–1799. https://doi.org/10.46488/nept.2024.v23i03.052
Meng, L., Tian, Z., Fan, D., Van De Ven, F. H., Sun, L., Ye, Q., Sun, S., Liu, J., Nougues, L., & Rooze, D. (2024). A multi-objective optimization approach for harnessing rainwater in changing climate. Advances in Climate Change Research. https://doi.org/10.1016/j.accre.2024.08.006
Herman, K. S., & Sovacool, B. K. (2024). Applying the multi-level perspective to climate geoengineering: Sociotechnical bottlenecks for negative emissions and cloud seeding technologies. Energy Research & Social Science, 115, 103637. https://doi.org/10.1016/j.erss.2024.103637
Henderson, S., Bernert, M., Brida, D., Derks, G., Elmore, S., Federici, F., Harrison, J., Kirk, A., Kool, B., Lonigro, N., Lovell, J., Moulton, D., Reimerdes, H., Ryan, P., Stobbs, J., Verhaegh, K., Van Den Doel, T., Wijkamp, T., & Bardsley, O. (2024). Validating reduced models for detachment onset and reattachment times on MAST-U. Nuclear Materials and Energy, 101765. https://doi.org/10.1016/j.nme.2024.101765
Huang, J., Huang, J., Cai, J., Sun, S., & Peng, C. (2024). LIGHTWEIGHT DESIGN OF THE SEEDING WHEEL STRUCTURE OF RICE DIRECT SEEDER BASED ON TOPOLOGY OPTIMIZATION. INMATEH Agricultural Engineering, 325–334. https://doi.org/10.35633/inmateh-74-28
Yamashita, K., Kuo, W., Murakami, M., Tajiri, T., Saito, A., Orikasa, N., & Ohtake, H. (2024). Physical properties of background aerosols and cloud condensation nuclei measured in Kochi City in June 2010 and its implication for planned and inadvertent cloud modification. Journal of the Meteorological Society of Japan Ser II, 102(3), 353–363. https://doi.org/10.2151/jmsj.2024-016
Kuo, W., Yamashita, K., Murakami, M., Tajiri, T., & Orikasa, N. (2024). Numerical Simulation on Feasibility of Rain Enhancement by Hygroscopic Seeding over Kochi Area, Shikoku, Japan, in Early Summer. Journal of the Meteorological Society of Japan Ser II, 102(4), 429–443. https://doi.org/10.2151/jmsj.2024-021
Harrison, R. G., Alkamali, A. A., Escobar-Ruiz, V., Nicoll, K. A., & Ambaum, M. H. P. (2024). Providing charge emission for cloud seeding aircraft. AIP Advances, 14(9). https://doi.org/10.1063/5.0227533
Haywood, J. M., Jones, A., Jones, A. C., Halloran, P., & Rasch, P. J. (2023). Climate intervention using marine cloud brightening (MCB) compared with stratospheric aerosol injection (SAI) in the UKESM1 climate model. Atmospheric Chemistry and Physics, 23(24), 15305–15324. https://doi.org/10.5194/acp-23-15305-2023
Beer, C. G., Hendricks, J., & Righi, M. (2024). Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC. Atmospheric Chemistry and Physics, 24(5), 3217–3240. https://doi.org/10.5194/acp-24-3217-2024
Konwar, M., Werden, B., Fortner, E. C., Bera, S., Varghese, M., Chowdhuri, S., Hibert, K., Croteau, P., Jayne, J., Canagaratna, M., Malap, N., Jayakumar, S., Dixit, S. A., Murugavel, P., Axisa, D., Baumgardner, D., DeCarlo, P. F., Worsnop, D. R., & Prabhakaran, T. (2024). Identifying the seeding signature in cloud particles from hydrometeor residuals. Atmospheric Measurement Techniques, 17(8), 2387–2400. https://doi.org/10.5194/amt-17-2387-2024
Zhou, H., Dai, Z., Wu, C., Ma, X., Zhu, L., & Wu, P. (2024). Comparison of different impact factors and spatial scales in PM2.5 variation. Atmosphere, 15(3), 307. https://doi.org/10.3390/atmos15030307
Yan, L., Zhou, Y., Wu, Y., Cai, M., Peng, C., Song, C., Liu, S., & Liu, Y. (2024). FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm. Atmosphere, 15(5), 556. https://doi.org/10.3390/atmos15050556
Cotton, W. R. (2024). Aerosol-Induced Invigoration of Cumulus Clouds—A Review. Atmosphere, 15(8), 924. https://doi.org/10.3390/atmos15080924
Chen, J., Rösch, C., Rösch, M., Shilin, A., & Kanji, Z. A. (2024). Critical size of silver iodide containing glaciogenic cloud seeding particles. Geophysical Research Letters, 51(7). https://doi.org/10.1029/2023gl106680
Chen, C., Richter, J. H., Lee, W. R., MacMartin, D. G., & Kravitz, B. (2024). Rethinking the Susceptibility‐Based Strategy for Marine Cloud Brightening Climate Intervention: Experiment with CESM2 and its implications. Geophysical Research Letters, 51(10). https://doi.org/10.1029/2024gl108860
Lau, K. H., & Toumi, R. (2024). On the Spirality of the Asymmetric Rain Field of Tropical Cyclones Under Vertical Wind Shear. Geophysical Research Letters, 51(18). https://doi.org/10.1029/2024gl109388
Wang, F., Chen, B., Yue, Z., Wang, J., Li, D., Lin, D., Tang, Y., & Luan, T. (2024). A composite approach for evaluating operational cloud seeding effect in stratus clouds. Hydrology, 11(10), 167. https://doi.org/10.3390/hydrology11100167
Kretzschmar, J., Pöhlker, M., Stratmann, F., Wex, H., Wirth, C., & Quaas, J. (2024). From trees to rain: Enhancement of cloud glaciation and precipitation by pollen. Environmental Research Letters, 19(10), 104052. https://doi.org/10.1088/1748-9326/ad747a
Lee, M., Yoo, C., & Chang, K. (2023). Unexpected contribution of cloud seeding to NPP increase during drought. Hydrology Research, 55(1), 17–32. https://doi.org/10.2166/nh.2023.075
Istrate, V., Eremeico, S., Sîrbu, D. A., Popescu, E. V., Sîrbu, E., & Popescu, D. D. (2024). Investigation on radar characteristics of hailstorms seeded with the glaciogenic reagent in Romania. Present Environment and Sustainable Development, 18(1), 21–32. https://doi.org/10.47743/pesd2024181002
Ilie, N., Florea, D., Sârbu, D. A., & Popescu, E. V. (2024). Using light, unmanned helium balloons for rain enhancement. Present Environment and Sustainable Development, 18(1), 169–183. https://doi.org/10.47743/pesd2024181012
Ramelli, F., Henneberger, J., Fuchs, C., Miller, A. J., Omanovic, N., Spirig, R., Zhang, H., David, R. O., Ohneiser, K., Seifert, P., & Lohmann, U. (2024). Repurposing weather modification for cloud research showcased by ice crystal growth. PNAS Nexus, 3(9). https://doi.org/10.1093/pnasnexus/pgae402
Ren, X., & Jin, Y. (2024). Transport pathway of the Ag+ following artificial precipitation enhancement activities. Heliyon, 10(3), e25299. https://doi.org/10.1016/j.heliyon.2024.e25299
Ignaciuk, S., Zarajczyk, J., Różańska-Boczula, M., Borusiewicz, A., Kuboń, M., Barta, D., Choszcz, D. J., & Markowski, P. (2023). Predicting the seeding quality of radish seeds with the use of a family of Nakagami distribution functions. International Agrophysics, 38(1), 21–29. https://doi.org/10.31545/intagr/174994
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