تخمین هدایت هیدرولیکی اشباع لایه سطحی خاک به روش تلفیق توابع انتقالی و سنجش از دور (مطالعه موردی: اراضی جنوب اهواز)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه آبیاری و زهکشی، دانشکده مهندسی آب و محیط‌زیست، دانشگاه شهید چمران اهواز، ایران

2 گروه آبیاری و زهکشی، دانشکده مهندسی آب و محیط زیست، دانشگاه شهید چمران اهواز، ایران

چکیده

هدایت هیدرولیکی خاک یکی از مهم‌ترین ویژگی‌های فیزیکی خاک می‌باشد که شناخت آن، نقش مهمی در بررسی انتقال املاح و آلاینده‌ها در خاک دارد. بنابراین، هدف از این پژوهش به دست آوردن توابع انتقالی هدایت هیدرولیکی اشباع با استفاده از ترکیب ویژگی‌های زود یافت خاک و تصاویر ماهواره‌ای بود. بنابراین، هدایت هیدرولیکی اشباع خاک با استفاده از روش چاهک معکوس در بخشی از اراضی جنوب غربی استان خوزستان در 50 نقطه انجام شد. سپس، در این نقاط، نمونه‌های سطحی از خاک برداشت شد و ویژگی‌های زود یافت خاک مانند بافت خاک، هدایت الکتریکی، کربن آلی خاک و رطوبت اشباع خاک اندازه‌گیری شد. در مرحله بعد، شاخص‌های بازتابشی خاک، پوشش گیاهی و رطویتی خاک با استفاده از تصاویر ماهواره سنتینل – 2 تهیه شدند و یازده تابع انتقالی (PTF1-PTF11) برای هدایت هیدرولیکی اشباع طی چهار مرحله با ترکیب ویژگی‌های زود یافت خاک و این شاخص‌ها به دست آمد. در نهایت، با استفاده از مدل جنگل تصادفی پهنه‌بندی هدایت هیدرولیکی اشباع خاک به دست آمد. نتایج مدل‌سازی توابع انتقالی هدایت هیدرولیکی اشباع خاک نشان داد که از بین یازده مدلی که توابع انتقالی هدایت هیدرولیکی اشباع خاک با استفاده از آن‌ها تهیه شده بود، ترکیب شاخص‌های پوشش گیاهی با ویژگی‌های زود یافت خاک بیشترین کارایی را برای تخمین هدایت هیدرولیکی اشباع داشت (PTF7). مقادیر R2 ،RMSE و MAE برای این حالت به ترتیب برابر با 83/0، 40/0 و 16/0 بود. همچنین، پهنه‌بندی هدایت هیدرولیکی اشباع با استفاده از مدل جنگل تصادفی نشان داد که این مدل توزیع مکانی هدایت هیدرولیکی اشباع خاک را با دقت بالایی پیش‌بینی می‌کند. بر اساس نتایج به دست آمده می‌توان گفت که ترکیب ویژگی‌های زود یافت خاک با شاخص‌های به دست آمده از تصاویر ماهواره سنتینل-2، باعث ایجاد توابع انتقالی هدایت هیدرولیکی اشباع خاک با دقت بسیار بالا می‌شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Estimation of saturated hydraulic conductivity of the soil surface layer by combining transfer functions and remote sensing (Case Study: South of Ahwaz Lands)

نویسندگان [English]

  • Mansour Sorkheh Nejad 1
  • Mohammad Albaji 1
  • Abd Ali Naseri 2
  • Saeed Boroomand Nasab 1
1 Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
چکیده [English]

Hydraulic conductivity is one of the most important physical properties of soil, and knowing it plays a vital role in investigating the transport of solutes and pollutants in porous environments such as soil. This study aims to obtain saturated hydraulic conductivity pedotransfer functions (PTFs) using soil properties and satellite images. In this regard, the hydraulic conductivity of soil saturation was performed using the Inversed augerhole method in a part of the southwestern lands of Khuzestan province at 50 points. Then, at these points, surface samples of the soil were taken and soil properties such as soil texture, electrical conductivity, soil organic carbon, and saturated moisture were determined in the laboratory. In the next step, the indices of Sentinel-2 satellite images were calculated in three categories of soil, vegetation, and moisture indices and 11 PTFs, (PTF1-PTF11) for saturated hydraulic conductivity were obtained in four stages by combining soil properties and these indices. Finally, the spatial distribution of saturated soil hydraulic conductivity was obtained using the random forest model. The results of the modeling of PTFs of saturated hydraulic conductivity showed that among the 11 models with which PTFs of hydraulic conductivity were performed, the combination of three vegetation indices with soil-found early properties was the most effective for estimating the saturated hydraulic conductivity (PTF7). The values of R2, RMSE and MAE for this case were equal to 0.83, 0.40 and 0.166 respectively. Finally, the spatial distribution of saturated hydraulic conductivity using the Random Forest model showed that this model performs the spatial distribution of saturated soil hydraulic conductivity of soil well. Based on the obtained results, it can be found that the combination of soil properties with the indices obtained from the Sentinel-2 satellite images, creates PTFs of saturated hydraulic conductivity of the soil with very high accuracy.

کلیدواژه‌ها [English]

  • Sentinel-2
  • Soil properties
  • Soil texture
  • Vegetation index

EXTENDED ABSTRACT

Introduction:

 In order to absorb water, the plant needs a suitable environment. During the irrigation, the environment becomes saturated. After depletion of gravity water from the plant root zone, unsaturated state in the soil occured. Based on this, the study and measurement of soil hydraulic conductivity and penetration are the essential parameters of the soil and water resources management. Hydraulic conductivity is one of the most important physical properties of the soil, which plays a vital role in solute and pollutant transport in the porous environments such as soil.

 

Objective:

 This study aims to obtain pedotransfer functions (PTFs) for saturated and unsaturated hydraulic conductivity using soil properties and satellite images.

 

Materials and methods:

 In this regard, soil sampling was performed in some parts of the southwest of Khuzestan province at 50 points. After that, soil samples were passed through a 2 mm sieve for homogenizing, and soil properties such as soil texture, electrical conductivity, soil organic carbon, and saturated moisture were determined in the laboratory. Then, saturated hydraulic conductivity was determined at the same sampling points in the field. Then after, indicators of Sentinel-2 satellite images were obtained. For this purpose, visible, infrared, mid-infrared, and short-infrared satellite images were prepared with a spatial resolution of 20 m2, and the indices of Sentinel-2 satellite images were calculated in three categories of soil, vegetation, and moisture. Finally, 11 PTFs, (PTF1-PTF11) for saturated hydraulic conductivity were obtained in four stages by combining soil properties and the aformentioned indices.

 

Results and discussion:

 The results of the PTFs models for saturated hydraulic conductivity showed that among the 11 models, the combination of three vegetation indices with easily measured soil properties was the most effective PTF model for estimating the saturated hydraulic conductivity (with R2 = 0.57, RMSE = 0.63 and MAE = 0.40). While the PTF7 model obtained by combination of the vegetation cover index and soil properties had R2 = 0.83, RMSE = 0.4 and MAE = 0.166. Finally, the spatial distribution of saturated hydraulic conductivity using the Random Forest model showed a better performance, as compared to the others.

 

Conclusion:

Based on the obtained results, it was found that PTFs obtained from soil properties alone cannot estimate the soil hydraulic conductivity with appropriate accuracy. Therefore, it is suggested in addition of soil properties, satellite images indices are used for modeling PTFs, in order to improve estimation of saturated hydraulic conductivity in the soil.

 

 Keywords: Sentinel-2,  Soil properties,  Soil texture,  Vegetation index.

مراجع

Babaian, a., Homai, m., & Nowrozi, a. a. (2014). Examining different scenarios of spectral resolution in estimating soil hydraulic properties. Iran water and soil research, 46(3), pp. 529-544 (In Persian).
Biau, G., & Scornet, E. (2016). A random forest guided tour. Test, 25, 197-227.
Brom, J., Duffková, R., Haberle, J., Zajíček, A., Nedbal, V., Bernasová, T., & Křováková, K. (2021). Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data. Remote Sensing, 13(20), 4127.
De amorim, b., Baldassarre, d., Bevacqua, g., Sierra, p., & Loon, v. (2019). Twenty-three unsolved problems in hydrology (uph)–a community perspective. Hydrological sciences journal, 64(10), 1141-1158.
Elmqvist, T., Andersson, E., Frantzeskaki, N., McPhearson, T., Olsson, P., Gaffney, O., . . . Folke, C. (2019). Sustainability and resilience for transformation in the urban century. Nature sustainability, 2(4), 267-273.
Hao, M., Zhang, J., Meng, M., Chen, H. Y., Guo, X., Liu, S., & Ye, L. (2019). Impacts of changes in vegetation on saturated hydraulic conductivity of soil in subtropical forests. Scientific reports, 9(1), 8372.
Hazelton, P., & Murphy, B. (2016). Interpreting soil test results: What do all the numbers mean? CSIRO publishing.
Herrick, J. E., & Wander, M. M. (2018). Relationships between soil organic carbon and soil quality in cropped and rangeland soils: the importance of distribution, composition, and soil biological activity. In Soil processes and the carbon cycle (pp. 405-425). CRC Press.
Honarbakhsh, A., Tahmoures, M., Afzali, S. F., Khajehzadeh, M., & Ali, M. S. (2022). Remote sensing and relief data to predict soil saturated hydraulic conductivity in a calcareous watershed, Iran. CATENA, 212, 106046.
Jansen, W., & Kleukers, R. (2001). Project rosse sprinkhaan: monitoringverslag 2000.
Khodaverdiloo, H., Homaee, M., van Genuchten, M. T., & Dashtaki, S. G. (2011). Deriving and validating pedotransfer functions for some calcareous soils. Journal of Hydrology, 399(1-2), 93-99.
Khosravi Aqdam, K., Miran, N., Mohammadi Khajelou, Y., Khosravi Aqdam, M., Asadzadeh, F., & Mosleh, Z. (2021). Predicting the spatial distribution of soil mineral particles using OLI sensor in northwest of Iran. Environmental Monitoring and Assessment, 193(6), 377.
Khosravi, N., Zolfaghari, A., Kabol, H., & Ghafar, H. (2022). Application of Digital Soil Mapping in Soil Particle Size Zonation and Estimation of Saturated Soil Hydraulic Conductivity for Optimal Management of Watersheds (Case Study: Damghanrood Watershed). Iranian Journal of Soil and Water Research, 53(2), 245-261. (In Persian).
Ließ, M., Glaser, B., & Huwe, B. (2012). Uncertainty in the spatial prediction of soil texture: comparison of regression tree and Random Forest models. Geoderma, 170, 70-79.
Lohan, S. K., Jat, H., Yadav, A. K., Sidhu, H., Jat, M., Choudhary, M., . . . Sharma, P. (2018). Burning issues of paddy residue management in north-west states of India. Renewable and Sustainable Energy Reviews, 81, 693-706.
Malone, B. P., Minasny, B., & McBratney, A. B. (2017). Using R for digital soil mapping (Vol. 35). Springer.
Miran, N., Rasouli Sadaghiani, M. H., Feiziasl, V., Sepehr, E., Rahmati, M., & Mirzaee, S. (2021). Predicting soil nutrient contents using Landsat OLI satellite images in rain-fed agricultural lands, northwest of Iran. Environmental Monitoring and Assessment, 193(9), 607.
Peer, S., & Bodner, G. (2008). High-resolution sonography of the peripheral nervous system. Springer.
Roy, D., Datta, A., Jat, H., Choudhary, M., Sharma, P. C., Singh, P. K., & Jat, M. L. (2022). Impact of long term conservation agriculture on soil quality under cereal based systems of North West India. Geoderma, 405, 115391.
Sedaghat, A., Shahrestani, M. S., Noroozi, A. A., Nosratabad, A. F., & Bayat, H. (2022). Developing pedotransfer functions using Sentinel-2 satellite spectral indices and Machine learning for estimating the surface soil moisture. Journal of Hydrology, 606, 127423.
USDA, N. (1999). United States department of agriculture. Natural Resources Conservation Service. Plants Database. http://plants. usda. gov (accessed in 2000).
Vinhal-Freitas, I. C., Corrêa, G. F., Wendling, B., Bobuľská, L., & Ferreira, A. S. (2017). Soil textural class plays a major role in evaluating the effects of land use on soil quality indicators. Ecological indicators, 74, 182-190.
Wadoux, A., Malone, B., Minasny, B., Fajardo, M., & McBratney, A. B. (2021). Soil Spectral Inference with R. Springer.
Zhang, L., & Wang, J. (2023). Prediction of the soil saturated hydraulic conductivity in a mining area based on CT scanning technology. Journal of Cleaner Production, 383, 135364.
Zhang, Y., & Schaap, M. G. (2019). Estimation of saturated hydraulic conductivity with pedotransfer functions: A review. Journal of Hydrology, 575, 1011-1030.
تحقیقات آب و خاک ایران
دوره 54، شماره 1
فروردین 1402
صفحه 105-122

فایل ها

هم رسانی

ارجاع به این مقاله

آمار