Abstract
Climate change can alter soil moisture with subsequent effects on water resources and vegetation growth. This study aims to understand the interactions and quantify the impact of climate change on soil moisture and vegetation in the Urmia Lake basin, Iran. The ERA-5 precipitation and temperature, GLDAS soil moisture, and MODIS NDVI monthly time series were used for 2001–2018. The MK test and Pearson correlation revealed the seasonal and monthly precipitation, and NDVI displayed insignificant trends, but the positive trend of temperature was observed in the cold season. At a depth of 0–10 cm, the monthly soil moisture trend indicated the highest negative trends occurring during April–May, while the lowest negative trends were in winter between December and January. Also, time-lagged (0, 1, and 2 months) correlation analysis showed soil moisture and climatic parameters of each month with short time-lagged (0 and 1 month) mostly presented significant correlations, but mid-time-lagged (2-months) correlations were not found significant with precipitation. Results showed that temperature played a more critical role than precipitation in soil moisture distribution within the study area. Investigating the impact of climate change on soil moisture by ensembles of AOGCM models under the different RCPs showed that soil moisture is influenced by temperature increasing.
Similar content being viewed by others
Data Availability
The datasets analyzed during the current study are available in the ERA-5-ECMWF dataset repository (ERA-5|ECMWF), and stationary data are available in IRIMO and NASA Global Land Data Assimilation System (GLDAS).
Code availability
The software was used in this study was R, which has been using as a programming language and free software for statistical computing and graphics.
References
Ahmad, I., Tang, D., Wang, T., Wang, M., & Wagan, B. (2015). Precipitation trends over time using Mann-Kendall and spearman’s rho tests in swat river basin, Pakistan. Advances in Meteorology, 2015.
Akbari M, Torabi Haghighi A, Aghayi MM, Javadian M, Tajrishy M, Kløve B (2019) Assimilation of satellite-based data for hydrological mapping of precipitation and direct runoff coefficient for the Lake Urmia Basin in Iran. Water 11(8):1624
Al-Doski J, Mansor SB, Shafri HZM (2013) NDVI differencing and post-classification to detect vegetation changes in Halabja City, Iraq. IOSR Journal of Applied Geology and Geophysics (IOSR-JAGG) 1(2):01–10
Barlow M, Zaitchik B, Paz S, Black E, Evans J, Hoell A (2016) A review of drought in the Middle East and southwest Asia. Journal of Climate, 29(23):8547–8574
Boke-Olén N, Ardö J, Eklundh L, Holst T, Lehsten V (2018) Remotely sensed soil moisture to estimate savannah NDVI. PLoS One 13(7):e0200328
Bonfils, S., 2012. Trend analysis of the mean annual temperature in Rwanda during the last fifty two years. Journal of Environmental Protection, 2012.
Cai J, Zhang Y, Li Y, Liang XS, Jiang T (2017) Analyzing the characteristics of soil moisture using gldas data: a case study in eastern China. Appl Sci 7(6):566
Chen T, De Jeu RAM, Liu YY, Van der Werf GR, Dolman AJ (2014) Using satellite-based soil moisture to quantify the water driven variability in NDVI: a case study over mainland Australia. Remote Sens Environ 140:330–338
Didan K, Munoz AB, Solano R, Huete A (2015) MODIS vegetation index user’s guide (MOD13 series). The University of Arizona, Vegetation Index and Phenology Lab, pp 1–38
Dirmeyer PA, Jin Y, Singh B, Yan X (2013) Trends in land–atmosphere interactions from CMIP5 simulations. J Hydrometeorol 14(3):829–849
D'Odorico P, Ridolfi L, Porporato A, Rodriguez-Iturbe I (2000) Preferential states of seasonal soil moisture: the impact of climate fluctuations. Water Resour Res 36(8):2209–2219
Engstrom R, Hope A, Kwon H, Stow D (2008) The relationship between soil moisture and NDVI near Barrow, Alaska. Phys Geogr 29(1):38–53
Feng H, Liu Y (2015) Combined effects of precipitation and air temperature on soil moisture in different land covers in a humid basin. J Hydrol 531:1129–1140
Alizade Govarchin Ghale, Y., Baykara, M. and Unal, A., 2017. Analysis of decadal land cover changes and salinization in Urmia Lake Basin using remote sensing techniques. Natural Hazards and Earth System Sciences Discussions, pp. 1–15.
Javadian M, Behrangi A, Gholizadeh M, Tajrishy M (2019) METRIC and WaPOR estimates of evapotranspiration over the Lake Urmia Basin: comparative analysis and composite assessment. Water 11(8):1647
Katiraie-Boroujerdy PS, Akbari Asanjan A, Chavoshian A, Hsu KL, Sorooshian S (2019) Assessment of seven CMIP5 model precipitation extremes over Iran based on a satellite-based climate data set. Int J Climatol 39(8):3505–3522
Khazaei, B., Khatami, S., Rashidi, L. and Madani, K., 2016, December. Hydro-climatic investigation of Lake Urmia shrinkage using remote sensing. In Abstract [H51H-1629] presented at 2016 Fall Meeting, AGU, San Francisco, Calif (pp. 12–16).
Kim H, Choi M (2015) An Inter-comparison of active and passive satellite soil moisture products in East Asia for dust-outbreak prediction. J Korean Soc Hazard Mitig 15(4):53–58
Legates DR (2000) Real-time calibration of radar precipitation estimates. Prof Geogr 52(2):235–246
Li D, Zhao T, Shi J, Bindlish R, Jackson TJ, Peng B, An M, Han B (2015) First evaluation of aquarius soil moisture products using in situ observations and GLDAS Model Simulations. IEEE J Sel Topics Appl Earth Observ Remote Sens 8(12):5511–5525
Maleki KH, Vaezi AR, Sarmadian F, Crow WT (2019) Validation of satellite-based soil moisture retrievals from SMAP with in situ observation in the Simineh-Zarrineh (Bokan) Catchment, NW of Iran. Eur J Soil Sci 8(4):340–350
Malekian A, Kazemzadeh M (2016) Spatio-temporal analysis of regional trends and shift changes of autocorrelated temperature series in Urmia Lake basin. Water Resour Manag 30(2):785–803
McBean, E. and Motiee, H., 2008. Assessment of impact of climate change on water resources: a long term analysis of the Great Lakes of North America. Hydrology and Earth System Sciences, 12(1), pp. 239–255.
Meng X, Li R, Luan L, Lyu S, Zhang T, Ao Y, Han B, Zhao L, Ma Y (2018) Detecting hydrological consistency between soil moisture and precipitation and changes of soil moisture in summer over the Tibetan Plateau. Clim Dyn 51(11-12):4157–4168
Niu CY, Musa A, Liu Y (2015) Analysis of soil moisture conditions under different land uses in the arid region of Horqin sandy land, northern China. Solid Earth 6(4):1157–1167
Ouyang W, Wu Y, Hao Z, Zhang Q, Bu Q, Gao X (2018) Combined impacts of land use and soil property changes on soil erosion in a mollisol area under long-term agricultural development. Sci Total Environ 613:798–809
Park S, Park S, Im J, Rhee J, Shin J, Park J (2017) Downscaling gldas soil moisture data in east, Asia, through the fusion of multi-sensors by optimizing modified regression trees. Water 9(5):332
Potić I, Bugarski M, Matić-Varenica J (2017) Soil moisture determination using remote sensing data for property protection and increase of agriculture production. In: Worldbank conference on land and poverty. The World Bank, Washington DC
Raziei, T. and Sotoudeh, F., 2017. Investigation of the accuracy of the European Center for Medium Range Weather Forecast (ECMWF) in forecasting observed precipitation in different climates of Iran. Journal of the earth and space physics, 43(1), pp. 133–147.
Rouse, J. W., Haas, R. H., Schell, J. A., Deering, D. W., & Harlan, J. C. (1974). Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. NASA/GSFC Type III Final Report, Greenbelt, Md, 371.
Rui, H., Beaudoing, H., & Loeser, C. (2018). README document for NASA GLDAS version 2 data products. Goddart Earth Sciences Data and Information Services Center (GES DISC): Greenbelt, MD, USA.
Saha A, Patil M, Goyal VC, Rathore DS (2018) Assessment and impact of soil moisture index in agricultural drought estimation using remote sensing and GIS techniques. MDPI (Multidisciplinary Digital Publishing Institute) 7(1):2
Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture–climate interactions in a changing climate: A review. Earth Sci Rev 99(3-4):125–161
Shen J, Chang Q, Li F, Wang L (2017) Extraction of winter wheat information based on time-series NDVI in the Guanzhong area. Trans Chin Soc Agric Mach 48(3):215–220
Shokoohi A, Morovati R (2015) Basinwide comparison of RDI and SPI within an IWRM framework. Water Resour Manag 29(6):2011–2026
Sneyers, R. (1990). Technical note No 143 on the statistical analysis of series of observations. World Meteorological Organization, Geneva, Switzerland.
Tootoonchi, R., Nourani, V., Andaryani, S., & Tootoonchi, F. (2020, March). Application of Mann-Kendall trend test and Normalized Difference Vegetation Index (NDVI) in hydroclimatological change detection–A Case Study of Urmia Lake watershed, Iran. In EGU General Assembly Conference Abstracts (p. 6904).
Wang L, Qu JJ (2009) Satellite remote sensing applications for surface soil moisture monitoring: A review. Front Earth Sci China 3(2):237–247
Wang Y, Yang J, Chen Y, Wang A, De Maeyer P (2018) The spatiotemporal response of soil moisture to precipitation and temperature changes in an arid region, China. Remote Sens 10(3):468
Wang Y, Yang J, Chen Y, Fang G, Duan W, Li Y, De Maeyer P (2019) Quantifying the effects of climate and vegetation on soil moisture in an arid area, China. Water 11(4):767
Wang N, Liu W, Sun F, Yao Z, Wang H, Liu W (2020) Evaluating satellite-based and reanalysis precipitation datasets with gauge-observed data and hydrological modeling in the Xihe River Basin, China. Atmos Res 234:104746
West H, Quinn N, Horswell M, White P (2018) Assessing vegetation response to soil moisture fluctuation under extreme drought using Sentinel-2. Water 10(7):838
Wilson DJ, Western AW, Grayson RB, Berg AA, Lear MS, Rodell M, Famiglietti JS, Woods RA, McMahon TA (2003) Spatial distribution of soil moisture over 6 and 30 cm depth, Mahurangi River catchment, New Zealand. J Hydrol 276(1-4):254–274
Yang, L., Sun, G., Zhi, L., & Zhao, J. (2018). Negative soil moisture-precipitation feedback in dry and wet regions. Scientific reports, 8(1), 1–9.
Zaman, M., Fang, G., Mehmood, K., & Saifullah, M. (2015). Trend change study of climate variables in Xin’anjiang-Fuchunjiang Watershed, China. Advances in Meteorology, 2015.
Zeng J, Li Z, Chen Q, Bi H, Qiu J, Zou P (2015) Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations. Remote Sens Environ 163:91–110
ZHANG Q, WANG S, WEI G (2003) A study on physical parameters of local land-surface processes on the Gobi in Northwest China. Chin J Geophys 46(5):883–895
Zhang, G., Su, X., Singh, V. P., & Ayantobo, O. O. (2017). Modeling NDVI using Joint Entropy method considering hydro-meteorological driving factors in the middle reaches of Hei river basin. Entropy, 19(9), 502.
Zhu Q, Lan H, Shen T (1996) Numerical study of the influence of soil moisture and surface albedo on the climate of the north part of China. Acta Meteoro-Log Sin 54:493–500
Zucco G, Brocca L, Moramarco T, Morbidelli R (2014) Influence of land use on soil moisture spatial-temporal variability and monitoring. J Hydrol 516:193–199
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethics approval
1) This material is the authors’ original work, which has not been previously published elsewhere.
2) The paper is not currently being considered for publication elsewhere.
3) The paper reflects the authors’ research and analysis wholly and truthfully.
4) The paper properly credits the meaningful contributions of co-authors and co-researchers.
5) The results are appropriately placed in the context of prior and existing research.
6) All sources used are correctly disclosed (correct citation). Copying of text must be indicated as such by using quotation marks and giving proper reference.
(Chen et al. 2014) All authors have been personally and actively involved in substantial work leading to the paper and will take public responsibility for its content.
The violation of the ethical statement rules may result in severe consequences.
I agree with the above statements and declare that this submission follows Solid-State Ionics’ policies outlined in the guide for authors and the ethical statement.
Consent to participate
I am a corresponding author; on behalf of the other authors, I declare that we are satisfied with participating in the research.
Consent for publication
I am a corresponding author; on behalf of the other authors, I declare that we are pleased to publish this valuable journal research.
Conflict of interest
The authors declare no competing interests.
Additional information
Responsible Editor: Zhihua Zhang
Rights and permissions
About this article
Cite this article
Saadatabadi, A.R., Izadi, N., Karakani, E.G. et al. Investigating relationship between soil moisture, hydro-climatic parameters, vegetation, and climate change impacts in a semi-arid basin in Iran. Arab J Geosci 14, 1796 (2021). https://doi.org/10.1007/s12517-021-07831-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-021-07831-8