SavedAdd your journal

Journals / Doğal Afetler ve Çevre Dergisi / 2026 / Cilt: 12 Sayı: 1

Evaluation of Simulated Rainfall Patterns in Control Plot Subsections

Simüle Edilmiş Yağış Desenlerinin Ölçüm Alt Alanlarında Değerlendirilmesi

Abdullah Emin Demircioğlu(MARMARA ÜNİVERSİTESİ)0009-0003-0541-0295
Erdal Kesgin(İSTANBUL TEKNİK ÜNİVERSİTESİ)0000-0002-9441-5359
Kadir Gezici(ATATÜRK ÜNİVERSİTESİ)0000-0001-6349-8262
Selim Şengül(ATATÜRK ÜNİVERSİTESİ)0000-0002-0041-1454
Remziye İlayda Tan Kesgin(FATİH SULTAN MEHMET VAKIF ÜNİVERSİTESİ)0000-0001-9135-1698
Pages
159–168
Publication Date
2026-01-25
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These results contradict the common assumption of uniform rainfall intensity within the channel area and highlight the necessity of sub-area-based analysis for the accurate interpretation of simulated rainfall experiments.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Rainfall simulators have been used for many years in laboratory settings to simulate natural rainfall.
📊
Key Findings & Data:To observe how the distribution patterns change depending on rainfall intensity within the simulator's operating range of 30-140 mmh⁻¹, we conducted simulations at four different intensities (40, 70, 80, and 100 mmh⁻¹).
💡
Conclusion & Impact:These results contradict the common assumption of uniform rainfall intensity within the channel area and highlight the necessity of sub-area-based analysis for the accurate interpretation of simulated rainfall experiments.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Yağmur Simülatörü · Christiansen Uniformluk Katsayısı · Damla Boyut Dağılımı

Abstract

Rainfall simulators have been used for many years in laboratory settings to simulate natural rainfall. This natural precipitation produced in a laboratory environment is particularly important for hydrological research in controlled laboratory environments where its natural variability can be examined in detail. This study examines the spatial variability of rainfall's fundamental parameters, intensity, uniformity, and drop diameter, in a nine-subarea arrangement within a single-channel rainfall simulator. To observe how the distribution patterns change depending on rainfall intensity within the simulator's operating range of 30-140 mmh⁻¹, we conducted simulations at four different intensities (40, 70, 80, and 100 mmh⁻¹). Within the channel area, I (rainfall intensity) showed local variations. Similarly, Christiansen's uniformity coefficients (CU) ranged from 69% to 95%. However, local CU values in some sub-regions were significantly lower than these averages. D50 (median drop diameter) varied between 1.32 and 1.77 mm for different densities and sub-areas. Generally, it was observed that homogeneity improved as rainfall intensity increased, but there were still significant differences within the area. The size of the raindrops varies depending on where they fall, with larger drops generally observed in the middle of the area (A3, A4, A5). These results contradict the common assumption of uniform rainfall intensity within the channel area and highlight the necessity of sub-area-based analysis for the accurate interpretation of simulated rainfall experiments.

Özet

Yağış simülatörleri laboratuvar ortamlarında doğal yağışı simüle etmek için uzun yıllardır kullanılan cihazlardır. Bu laboratuvar ortamında üretilen doğal yağışın özellikle doğal değişkenliği ayrıntılı olarak incelenebildiği kontrollü laboratuvar ortamlarında, hidrolojik araştırmalar için önemli olmaktadır. Bu çalışma, bir kanallı yağış simülatörü içinde dokuz alt alana ayrılmış bir düzende yağışın temel parametreleri olan şiddet, düzgünlük ve damla çapının mekânsal değişkenliğini incelemektedir. Simülatörün 30-140 mmh-¹’lik çalışma aralığında, yağış şiddetine bağlı olarak dağılım desenlerinin nasıl değiştiğini görmek amacıyla dört farklı yoğunlukta (40, 70, 80 ve 100 mmh-¹) simülasyonlar gerçekleştirdik. Kanal alanı içerisinde I (yağış şiddeti) lokal olarak farklılıklar göstermiştir. Aynı şekilde Christiansen uniformluk katsayılarıda (CU) %69 ile %95 arasında değişmiştir. Fakat bazı alt bölgelerdeki lokal CU değerleri bu ortalamaların çok daha altında kalmıştır. D50 (medyan damla çapı), farklı yoğunluklar ve alt alanlarda 1,32 ile 1,77 mm arasında değişiklik göstermiştir. Genel olarak, yağış şiddeti arttıkça homojenlik iyileştiği fakat alan içinde hala önemli farklılıklar olduğu gözlemlenmiştir. Yağmur damlalarının boyutu düştükleri yere göre değişmektedir; genellikle alanın ortasında daha büyük damlalar gözlemlendi (A3, A4, A5). Bu sonuçlar, kanal alanı içinde aynı şiddette ve tekdüze bir yağış olduğu şeklindeki yaygın varsayımıyla çelişmekte ve simüle edilmiş yağış deneylerinin doğru şekilde yorumlanması için alt alan bazlı analizin gerekliliğini vurgulamaktadır.

🔖

Cite This Article

Demircioğlu, A. E., Kesgin, E., Gezici, K., Şengül, S., Kesgin, R. İ. T. (2026). Evaluation of Simulated Rainfall Patterns in Control Plot Subsections. Doğal Afetler ve Çevre Dergisi, Cilt: 12 Sayı: 1, 159–168. https://doi.org/10.21324/dacd.1764600

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (44)

  1. Abdollahi, Z. (2011). Designing nozzles and testing rainfall characteristic in large soil erosion and sediment yield simulator [M.Sc. thesis, Tarbiat Modares University].
  2. Abudi, I., Carmi, G., & Berliner, P. (2012). Rainfall simulator for field runoff studies. Journal of Hydrology, 454, 76–81. https://doi.org/10.1016/j.jhydrol.2012.05.056
  3. Bentley, W. A. (1904). Studies of raindrops and raindrop phenomena. Monthly Weather Review, 32, 450–456.
  4. Christiansen, J. E. (1941). The uniformity of application of water by sprinkler systems. Agricultural Engineering, 22(2), 89–92.
  5. Clarke, M. A., & Walsh, R. P. D. (2007). A portable rainfall simulator for field assessment of splash and slopewash in remote locations. Earth Surface Processes and Landforms, 32(13), 2052–2069. https://doi.org/10.1002/esp.1593
  6. Confesor, J. G., & Rodrigues, S. C. (2018). Método para calibração, validação e utilização de simuladores de chuvas aplicados a estudos hidrogeomorfológicos em parcelas de erosão. Revista Brasileira de Geomorfologia, 19(1), 25–38.
  7. Demircioğlu, A. E., Kesgin, E., Gezici, K., & Şengül, S. (2024, 16–19 Ekim). Farklı eğim koşullarına sahip yağış simülatörlerinde yağış şiddetinin alansal dağılımın incelenmesi [Bildiri sunumu]. XII. Ulusal Hidroloji Kongresi, Samsun, Türkiye.
  8. Fernández-Raga, M., Rodríguez, I., Caldevilla, P., Búrdalo, G., Ortiz, A., & Martínez-García, R. (2022). Optimization of a laboratory rainfall simulator to be representative of natural rainfall. Water, 14(23), Article 3831. https://doi.org/10.3390/w14233831
  9. Fornis, R. L., Vermeulen, H. R., & Nieuwenhuis, J. D. (2005). Kinetic energy–rainfall intensity relationship for Central Cebu, Philippines for soil erosion studies. Journal of Hydrology, 300, 20–32. https://doi.org/10.1016/j.jhydrol.2004.04.027
  10. Gezici, K., Kesgin, E., & Ağacıoğlu, H. (2021). Hydrological assessment of experimental behaviors for different drainage methods in sports fields. Journal of Irrigation and Drainage Engineering, 147(6), Article 04021034. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001512
  11. Gezici, K., Şengül, S., & Kesgin, E. (2025). Advances in sheet erosion and rainfall simulator performance: A comprehensive review. Catena, 248, Article 108601. https://doi.org/10.1016/j.catena.2025.108601
  12. Green, D., & Pattison, I. (2022). Christiansen uniformity revisited: Re-thinking uniformity assessment in rainfall simulator studies. Catena, 217, Article 106424. https://doi.org/10.1016/j.catena.2022.106424
  13. Henorman, V., Tholibon, A., Nujid, M., Mokhtar, M., Abd Rahim, E., & Saadon, S. (2022). The functional relationship of sediment transport under various simulated rainfall conditions. Fluids, 7(3), Article 107. https://doi.org/10.3390/fluids7030107
  14. Iserloh, T., Fister, W., Seeger, M., Willger, H., & Ries, J. B. (2012). A small portable rainfall simulator for reproducible experiments on soil erosion. Soil and Tillage Research, 124, 131–137. https://doi.org/10.1016/j.still.2012.05.016
  15. Kathiravelu, G., Lucke, T., & Nichols, P. (2016). Rain drop measurement techniques: A review. Water, 8(1), Article 29. https://doi.org/10.3390/w8010029
  16. Kavian, A., Mohammadi, M., Cerda, A., Fallah, M., & Abdollahi, Z. (2018). Simulated raindrop’s characteristic measurements: A new approach of image processing tested under laboratory rainfall simulation. Catena, 167, 190–197. https://doi.org/10.1016/j.catena.2018.04.034
  17. Kesgin, E., Ağacıoğlu, H., & Doğan, A. (2020a). Experimental and numerical investigation of drainage mechanisms at sports fields under simulated rainfall. Journal of Hydrology, 580, Article 124251. https://doi.org/10.1016/j.jhydrol.2019.124251
  18. Kesgin, E., Doğan, A., & Ağacıoğlu, H. (2018). Rainfall simulator for investigating sports field drainage processes. Measurement, 125, 360–370. https://doi.org/10.1016/j.measurement.2018.04.064
  19. Kesgin, E., Gezici, K., & Ağacıoğlu, H. (2020b, 13–15 November). Hydrological evaluation of sports field drainage [Conference Paper] In ISPEC 9th International Conference on Engineering & Natural Sciences (pp. 182–191). Ankara, Turkey.
  20. Kesgin, E., Gezici, K., & Ağacıoğlu, H. (2023). Spor sahaları drenajına genel bakış: Deneysel çalışma sistematiğinin oluşturulması. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 38(4), 2495–2504. https://doi.org/10.17341/gazimmfd.1253839
  21. Khaledian, H., & Shahoe, S. (2007, 21–23 August). Assessment of raindrops size distribution to natural precipitation in Kurdistan Province, Iran [Conference Paper]. Rainwater and Urban Design 2007, Sydney, Australia.
  22. Koch, T., Chifflard, P., Aartsma, P., & Panten, K. (2024). A review of the characteristics of rainfall simulators in soil erosion research studies. MethodsX, 12, Article 102506. https://doi.org/10.1016/j.mex.2023.102506
  23. Koşucu, M. E., Sarı, M., Demirel, M. C., Kıran, A., Yılmaz, G., Aybakan, Z., Albay, G. M., & Kırca, M. (2021). Gerçek zamanlı basınç yönetimiyle su dağıtım şebekesinde su kaybının azaltılması. Teknik Dergi, 32(2), 10541–10564.
  24. Küçükerdem Öztürk, T. S., Saplıoğlu, K., & Güçlü, Y. S. (2025). Median ratio test on graphical representation for trend analysis by comparison with Mann–Kendall and Wilcoxon tests. Hydrological Sciences Journal, 70(14), 2530–2542. https://doi.org/10.1080/02626667.2025.2543943
  25. Küçükerdem, T. S., Saplıoğlu, K., & Güçlü, Y. S. (2019). Bulanık çıkarım sistemlerinde kullanılan küme sayılarının K-ortalamalar ile belirlenmesi ve baraj hacmi modellenmesi: Kestel Barajı örneği. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 25(8), 962–967. https://doi.org/10.5505/pajes.2019.99223
  26. Lasisi, K. H., Akinola, A. O., & Ogunjimi, L. A. O. (2022). Modification and performance evaluation of a small-scale rainfall simulator. International Journal of Agriculture, Environment and Bioresearch, 7(3), 273–285. https://doi.org/10.35410/IJAEB.2022.5736
  27. Luk, S. H., Abrahams, A. D., & Parsons, A. J. (1993). Sediment sources and sediment transport by rill flow and interrill flow on a semi-arid piedmont slope, southern Arizona. Catena, 20(1–2), 93–111.
  28. Luza, J. R., Almeida, W. S., Souza, A. G. S., Schultz, N., Anache, J. A. A., & Carvalho, D. F. (2024). Simulated rainfall in Brazil: An alternative for assessment of soil surface processes and an opportunity for technological development. International Soil and Water Conservation Research, 12(1), 29–42. https://doi.org/10.1016/j.iswcr.2023.05.002
  29. Ma, Z., Liu, Y., Tian, X., Yang, J., Long, Y., Lei, T., Zhang, X., Li, Z., & Zhu, B. (2023). Effects of rainfall pattern and soil surface roughness on surface–subsurface hydrological response and particle size distribution of red soil slope. Catena, 232, Article 107422. https://doi.org/10.1016/j.catena.2023.107422
  30. Meshesha, D. T., Tsunekawa, A., Tsubo, M., Haregeweyn, N., & Adgo, E. (2013). Drop size distribution and kinetic energy load of rainfall events in the highlands of the Central Rift Valley, Ethiopia. Hydrological Sciences Journal, 59(12), 2203–2215. https://doi.org/10.1080/02626667.2013.867371
  31. Meshesha, D. T., Tsunekawa, A., Tsubo, M., Haregeweyn, N., & Tegegne, F. (2016). Evaluation of kinetic energy and erosivity potential of simulated rainfall using Laser Precipitation Monitor. Catena, 137, 237–243. https://doi.org/10.1016/j.catena.2015.09.017
  32. Mhaske, S. N., Pathak, K., & Basak, A. (2019). A comprehensive design of rainfall simulator for the assessment of soil erosion in the laboratory. Catena, 172, 408–420. https://doi.org/10.1016/j.catena.2018.08.039
  33. Moazed, H., Bavi, A., Boroomand-Nasab, S., Naseri, A., & Albaji, M. (2010). Effects of climatic and hydraulic parameters on water uniformity coefficient in solid set systems. Journal of Applied Sciences, 10(16), 1792–1796. https://doi.org/10.3923/jas.2010.1792.1796
  34. Pérez-Latorre, F. J., de Castro, L., & Delgado, A. (2010). A comparison of two variable intensity rainfall simulators for runoff studies. Soil and Tillage Research, 107(1), 11–18. https://doi.org/10.1016/j.still.2010.01.006
  35. Renner, C., Conroy, N., Thaler, E., Collins, A., Thomas, L., Dillard, S., Rowland, J., & Bennett, K. (2024). The next-generation ecosystem experiment arctic rainfall simulator: A tool to understand the effects of changing rainfall patterns in the Arctic. Hydrology Research, 55(1), 67–82. https://doi.org/10.2166/nh.2023.146
  36. Rončević, T., Živanović, M., Radulović, M., Ristić, V., & Sadeghi, S. H. (2025). Design, calibration, and performance evaluation of a high-fidelity spraying rainfall simulator for soil erosion research. Water, 17(12), Article 1863. https://doi.org/10.3390/w17131863
  37. Saplıoğlu, K., & Küçükerdem Öztürk, T. S. (2024). Effect of decision tree in the ANFIS models: An example of completing missing data. Water Resources, 51(5), 435–445.
  38. Saplıoğlu, K., & Küçükerdem, T. S. (2018). Estimation of missing streamflow data using ANFIS models and determination of the number of datasets for ANFIS: The case of Yeşilırmak River. Applied Ecology and Environmental Research, 16(3), 3583–3594. https://doi.org/ 10.15666/aeer/1603_35833594
  39. Saplioglu, K., Kucukerdem, T. S., & Şenel, F. A. (2019). Determining rainwater harvesting storage capacity with particle swarm optimization. Water Resources Management, 33(14), 4749–4766. https://doi.org/10.1007/s11269-019-02389-3
  40. Şenel, F. A., Öztürk, T. S. K., & Saplıoğlu, K. (2020). Yeşilırmak nehri akış verisi tahmininin yapay sinir ağları kullanılarak karınca aslanı algoritması ile zaman gecikmesi boyutunun optimizasyonu. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 20(2), 310–318. https://doi.org/10.35414/akufemubid.669602
  41. Sousa, S. F. D., Mendes, T. A., & Siqueira, E. Q. D. (2017). Development and calibration of a rainfall simulator for hydrological studies. Revista Brasileira de Recursos Hídricos, 22, Article e59. https://doi.org/10.1590/2318-0331.011716018
  42. Tan Kesgin, R. İ. (2025). Revisiting trend stability using Mann-Kendall and Wilcoxon Signed-Rank tests through innovative method comparisons. Sustainability, 17(23), Article 10454. https://doi.org/10.3390/su172310454
  43. Van Dijk, A. I. J. M., Bruijnzeel, L. A., & Rosewell, C. J. (2002). Rainfall intensity–kinetic energy relationships: A critical literature appraisal. Journal of Hydrology, 261(1–4), 1–23. https://doi.org/10.1016/S0022-1694(01)00511-8
  44. Zhang, X., Yu, G. Q., Li, Z. B., & Li, P. (2014). Experimental study on slope runoff, erosion and sediment under different vegetation types. Water Resources Management, 28(8), 2415–2433. https://doi.org/10.1007/s11269-014-0603-5