Evaluation of desertification intensity based on quantitative and qualitative changes in groundwater and soil criteria using Madalus model and geostatistical methods

Document Type : Original Article

Authors

1 Department of Arid Zone Management, Faculty of Rangeland and watershed management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Department of Environmental Assessment, Faculty of Fisheries and Environment, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

3 Department of Geosciences and Geography, Faculty of Earth Sciences, The University of Helsinki, Finland

Abstract

Introduction: Desertification involves processes that are both the product of natural factors and the mismanagement of human beings. Adafic parameters and processes affecting soil condition, climate, groundwater, vegetation and management are the most important factors affecting the phenomenon of desertification in many arid and semi-arid regions. These parameters are investigated using different models in different regions.Therefore, this study was conducted to evaluate the desertification intensity based on groundwater and soil criteria in the west of Golestan province.
Material and methods: To determine the work unit map, topographic, geological, aerial photo interpretation, panchromatic band and multispectral Landsat satellite images and field visits were used. In this study, the Madalus method was used to prepare a map and evaluate the desertification situation. The geostatistical methods used in this research include kriging method, local estimator method (GPI), radial function method (RBF) and distance distance method (IDW). in Madalus model, 6 criteria and 20 indicators were used to evaluate the intensity of desertification. The scoring of each of the indicators was determined at the unit level in the region. The map of each criterion is also obtained through the geometric mean relationship between the indicators. To evaluate the accuracy of the model results, the desertification class in each of the work units according to the field evidence, observational and visual evaluation was performed and then the statistical comparison of the model desertification class with an expert opinion was performed. SPSS software and Mann-Whitney non-parametric test were used to validate the model results.
Results and discussion: In this study, according to the histogram of the data, the normality of the parameters was investigated. The mean square squared error (RMSE) was used to determine the most appropriate interpolation method. The weighted average score of desertification intensity of area 135 was obtained, which indicates the middle class. In terms of zoning of desertification intensity, the region was classified into three classes: low and insignificant with a frequency of 27 and medium with a frequency of 60 and severe with a frequency of 13. Among the criteria of desertification, the criterion of management and policy with an average weight of 148 points is the dominant and effective criterion of desertification, followed by the criterion of vegetation (145), the criterion of soil (141), the criterion of erosion (138), the criterion of climate. (122) and groundwater criteria (121) were in the next rank of effective desertification criteria in the region. Also, the most important indicators of desertification are the indicators of drought resistance, conservation operations and soil salinity, respectively. These indicators have increased the trend of desertification in the work units of abandoned lands, saline and wetland lands and saline lands located in the northeastern parts of the region.
Based on the spatial distribution of classes with low and insignificant desertification intensity in the southern and eastern part of the region, the middle class in the western, central and northern parts and finally the severe desertification class are located in the northeastern parts of the region.
Conclusion: According to the obtained results, which indicate high evapotranspiration of the region, expansion of land salinity, unprincipled road construction and incomplete drainage.it seems that the management of desertification in the west of Golestan province, as one of the agricultural hubs, should be in the managerial priority of the officials and experts of the executive departments.Accordingly, it is proposed in order to control the process of desertification and achieve sustainable development in the region .treatment of industrial and domestic effluents for reuse for various purposes, Use of modern irrigation systems for agricultural lands, Placing low-yield crops in terms of water consumption in the region's crop rotation and As well as the necessary training to justify farmers to use pesticides and chemical fertilizers in the area.

Keywords

References

Akbari, M., 2016. Proposing an early warning system for desertification hazard (Case study: Semi desert region of the Gorgan Plain, Golestan Province, Iran). Ph.D. Thesis. Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
Arami, A.H., 2012. Assessment of risk, damage and development of desert management program in semi-arid region of Aqband, Golestan province. MS.c. Thesis. Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
Ardakani, S., Rcban, SH. and Mani, J., 2014. Evaluation of concentration of some heavy metals in groundwater resources of Ghahavand plain of Hamadan. Monthly Journal of Kermanshah University of Medical Sciences 18(6), 348-339. (In Persian with English abstract).
Azareh, A., Rafiei Sardoii, E., Nazari Samani, A., Masoudi, R. and Khosravi, H., 2014. Study on spatial and temporal variations of groundwater level in garmsar plain. Journal of Desert Management 3(2):11-20. (In Persian with English
abstrac).
Boali, A., Bashari, H., Jafari, R. and Soleimani, M., 2017. Investigating the effect of groundwater quality on desertification of land in Segzi plain of Isfahan using Bayesian Belief networks . Journal of Science and Technology of Agriculture and Natural Resources, Soil and Water Sciences. 21 (2), 15 - 28. (In Persian with English abstract).
Boali, A., Bashari, H. and Jafari, R., 2018. Evaluating the potential of bayesian networks for desertification assessment in arid areas of Iran. Land Degrad. Dev. 30, 371-390. https://doi.org/10.1002/ldr.3224 .
Boali, A. and Mohahadian, A., 2019. Assessing the severity and risk of desertification and presenting a management plan (Study area: Segzi plain of Isfahan). Geography and development. 63, 227-244. https://doi.org/10.1002/ldr.3224.
Bakhshi, M., Komaki, Ch.B. and Ownegh, M., 2015. The assessment hazard desertification using desertification indicator system for Mediterranean Europe (DIS4ME) (Case study: Atrak watershed in Golestan province). Journal of Water and Soil Conservation. 22(4), 243 - 251. (In Persian with English abstract).
Bajjali, W., 2005. "Model the Effect of Four Artificial Recharge Dams on the Quality of
Groundwater Using Geostatistical Methods in GIS Environment, Oman". Journal of Spatial
Hydrology. 5 (2), 67-80
Castellano, M.J. and Valone, T.J., 2007. Livestock, soil compaction and water infiltration rate: Evaluating a potential desertification recovery mechanism. Journal of Arid Environ. 71, 97-108.
Delbari, M., Afrasiab, P. and Miremadi, S R., 2011. Spatio-temporal variability analysis of groundwater salinity and depth (Case study: Mazandaran province). Iranian Journal of irrigation and drainage. 3(4), 359- 374. (In Persian with English abstract).
Davari, S., Rashaki, A., Akbari, M. and Talibanfard, A., 2017. Assessment of severity and risk of desertification and presentation of management plans in the study area: Qasem Abad Plain, Razavi Khorasan Province, Iran. Journal of Desert Management. 9(7), 106 - 91. (In Persian with English abstract).
Azar, Kh., 2002. Modification of Saline and Sodium Soils (Soil and Water Management). Jahad University Press, Tehran.
Honardost, F., Onaq, M. and Sheikh V, 2011 Assessing the current situation of desertification of Sufikam-Mangali plain in the northwest of Golestan province, Water and Soil Conservation Research. 3(18), 213-219. (In Persian with English
abstract).
Hosseinalizadeh, M. and Yaghubi, A., 2010. Spatiotemporal variability of ground water using geostatistic. Iran Watershed Management Science and Engineering. 4(10), 63-68. (In Persian with English abstract).
Khodai, K., Shahsavari, A. and Etebari, B., 2006. Evaluation of jowin groundwater changes using drastic and gods’ methods. Geological Journal of Iran. 2(4), 73-87. (In Persian with English
abstract).
Masoudi, R., Zehtabian, G.R., Ahmadi, H. and
Malkian, A., 2015. Evaluation of the quantitative and qualitative changes of groundwater in Kashan Plain Desert Management Journal. 5(3), 80-67. (In Persian with English abstract).
Mei, K., Liao, L., Zhu, Y., Lu, P., Wang, Z.,
Dahlgren, R.A. and Zhang, M., 2014. Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface. Environmental Science and Pollution
Research. 21(13), 8036-8051.
Naderianfar, M., Ansari, H., Ziaie, A. and Davary, K., 2011. Evaluating the groundwater level fluctuations under different climatic conditions in the basin Neyshabour. Iranian of Irrigation & Water Engineering. 1(3), 22-37. (In Persian with English abstract).
Nas, B., 2009. Geostatistical approach to
assessment of spatial distribution of groundwater quality. Polish Journal of Environment Study. 6(12), 1073-1082.
Nafar, F., 2019. Evaluation and comparison of Madalus model and remote sensing in estimating desertification of Sefiddasht-Borujen watershed. MS.c. Thesis. Shahrekord University, Shahrekord, Iran.
Salunkhe, S.S., Bera, A.K., Rao, S.S., Venkataraman, V.R., Raj, U. and Murthy, Y.V.N.K., 2018. Evaluation of indicators for desertification risk assessment in part of Thar Desert Region of Rajasthan using geospatial techniques. Journal of Earth System Science. 127 (8), 116-140.
Shabani, M., 2011. Estimation of groundbased
methods in the preparation of groundwater quality maps and their zoning, Case study: Neyriz plain. Fars’s province. Journal of natural geography Lar. 13, 83-96.
Sun, Y., Kang, S., Li, F. and Zhang, L., 2019. Comparison of interpolation methods for depth to groundwater and its temporal and spatial variations in the minqin oasis of northwest China. Environmental Modelling and Software. 24(10), 1163-1170.
Safari, F., Shahbazi, A. and Ketabchi, H., 2019. Analysis of quality and nitrate zoning of groundwater resources in Alborz province (Hashtgerd plain). Water and Soil Conservation Research. 5(26), 113-130. (In Persian with English abstract).
Sepehr, A., 2008. A Study of the application of the MEDALUS method for presenting a regional model for evaluating and preparing desertification maps. Journal of the Faculty of Natural Resources. 61(3), 554-537. (In Persian with English abstract).
UNEP., 2004. UNEP’s Strategy on Land Use Management and Soil Conservation. Available online at: https://www.un.org/press/en /2004/ unep245.doc.htm .
Yazdanpanahi, A., Akabri, M. and Behrangmanesh, M., 2018. Spatio-temporal variable of groundwater parameters using Geo-statistical methods in Mashhad plain. Extension and Development of Watershed
Management. 6(20), 25-34. (In Persian with English
abstract).
Zehtabian, G.R., Khosravi, H. and Masoudi, R., 2014. Desertification evaluation models (Criteria and Indicators). Tehran University Press, Tehran, Iran.
Zehtabian, G.R., Ahmadi, H. and Azadnea, F., 2008. Investigation of soil and water criteria in desertification of Ein Khosh Dehloran region. Research and Construction in Natural Resources. 6(86), 1-8. (In Persian with English abstract).
Environmental Sciences
Volume 19, Issue 4
January 2022
Pages 85-106

Files

Share

How to cite

Statistics