Related Links
Determination of the Potential of Groundwater Resources in the Urmia Plain Using the Morphometric Parameters and Indices | ||
| پژوهش های آبخیزداری | ||
| Article 3, Volume 34, Issue 4 - Serial Number 133, December 2022, Pages 16-33 PDF (2.22 M) | ||
| Document Type: Research | ||
| DOI: 10.22092/wmrj.2021.353111.1382 | ||
| Authors | ||
| Samaneh Dadafarid* 1; Habib Nazarnejad2; Amin Khosravi1 | ||
| 1Ph.D. Candidate, Department of Watershed Management, Faculty of Agriculture and Natural Resources, Urmia University, Urmia, Iran | ||
| 2Associate Professor, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, Urmia University, Urmia, Iran | ||
| Abstract | ||
| Morphometric analyses play an important role in understanding the geo-hydrological conditions of basins such as identification of the and potential management of groundwater resources. A hydrological DEM was prepared to draw the drainage network in four sub-basins of Lake Urmia. Linear, surface, and topographic morphometric parameters were calculated to prioritize the potential of groundwater resources in the sub-basins. The mean values obtained from the rank of the parameters in each sub-basin were close and the sub-basins were prioritized as Nazluchai, Baranduzchai, Shaharchai, and Rouzehchai, respectively. Furthermore, the morphometric indices of TPI, TRI, VRM, surface curvature, and surface ratio were studied to prepare the spatial value map of the groundwater resources. Each map was prepared and classified with the same cell size in seven classes and the morphometric index map was combined with the same weights. The map of potential groundwater areas under the study area was obtained with values of 2.2 to 5.0. The highest value in the map of the spatial value of groundwater resources belonged to the pixels that had the lowest TPI, the lowest TRI, the highest VRM, the lowest surface curvature, and the highest surface ratio. The findings were confirmed by examining the location of springs and yielding wells in the study area. | ||
| Keywords | ||
| Groundwater; Morphometric indices; Morphometric parameters; Prioritization; Spatial value | ||
| References | ||
|
Abdide M, Gharshi M, Rangzan K, Ariyan M. 2011. Relative assessment of active substructure using morphometric analysis (Case study: Dez River Basin, Southwestern Iran). Journal of Earth Sciences. 20 (80):33-46. (In Persian). Ahmadi H, Taheri S. 2009. Importance of morphometric analyzes to obtain areas with groundwater potential by controlling land structure (Case study: Tasuj watershed). 5rd National Conference on Watershed Management Science and Engineering (Sustainable Disaster Management), University of Agricultural Sciences and Natural Resources, Gorgan, Iran. 10 p. (In Persian). Alizadeh A. 2015. Principles of applied hydrology. Imam Reza University Press. 942 p. (In Persian). Allafta H, Opp Ch, Patra S. 2021. Indentification of groundwater potential zones using remote sensing and GIS techniques: A case study of the Shatt Al-Arab basin. Journal of Remote Sensing. 13 (1):112–140. AsadiNalivan A, Saghazadeh N, SalahshurDastgerdi M, Bay M. 2015. Prioritization of sub-basins using morphometric analysis and GIS for watershed management measures (Case study: Maraveh Tappeh Watershed, Golestan Province). Journal of Ecohydrology. 2 (1):91-103. (In Persian). Baboli Moakhar H, Taghiyan A, Shirani K. 2019. Applying morphometric indices in optimizing landslide sensitivity zoning maps using probabilistic models. Journal of Natural Geography Research. 50 (4):747–772. (In Persian). Choubin B, Rahmati O, Soleimani F, Alilou H, Moradi E, Alamdari N. 2019. Regional groundwater potential analysis using classification and regression trees. Spatial modeling in GIS and R for environment sciences, Elsevier Inc. pp:485–498. Das S. 2019. Comparison among influencing factor, frequency ratio and analytical hierarchy process techniques for groundwater potential zonation in Vaitarna basin, Maharashtra, India. Grounds Sustain Dev 8 (1):617–629. Doke A, Pardeshi S, Das S. 2020. Drainage morphometry and groundwaterpotential mapping: application of geoinformatics with frequency ratio and influencing factor approaches. Journal of Environmental Earth Sciences. 79 (16):1–17. Erfanian M, Farajollahi H, Souri M, Shirzadi A. 2015. Comparing efficiency of weight of evidence, logestic regression and frequency ratio methods for mapping groundwater spring potential in Ghelgazi watershed, Kordestan province of Iran. Water and Soil Sci. 20 (75):59-72. (In Persian). FallahSourki M, Kavian A, Omidvar A. 2016. Prioritization of Haraz watershed sub-basins for soil and water conservation operations based on morphometric and land use parameters. Journal of Soil and Water Sciences (Agricultural Science and Technology and Natural Resources). 20 (77):85–99. (In Persian). Fathi F, Negahban S, YeganehKiya Z. 2011. Report on the establishment of drought risk management system in the watershed of Lake Urmia. 155 p. (In Persian). Ghaderi K, FazeliSani A. 2016. Quantitative analysis of morphometric parameters of the watershed (Case study: Manjir, Mazandaran). 4rd International Congress of Civil Engineering, Architecture and Urban Planning, Shahid Beheshti University, Tehran, Iran. 16 p. (In Persian). Hadley RF, Schumm SA. 1961. Sediment source and drainage basin characteristics in upper Cheyenne River Basin. US Geological survey water supply paper 1531. 198 p. Hajam R, Hamid A, Bhat S. 2013. Application of morphometric analysis for geo-hydrological studies using geo-spatial technology (Case study: Vishav drainage basin). Journal of Hydrology Current Research. 4 (157):2–13. Hassan ZU, Kanth TA, Malik MI. 2018. Groundwater potential zonation and prioritization of wular catchment of Kashmir using GIS based multi-criteria evaluation approach. Water and Energy International. 60 (11):49–61. HatefiArdakani A, RezayiRad N. 2011. Use of RS and GIS techniques in proper location of artificial nutrition of groundwater resources in semnan plain. 7rd National Conference on Watershed Management Science and Engineering, University of Technology, Isfahan, Iran. 7 p. (In Persian). Hesari B, Karimzadegan S. 2019. Preparation of hydrological DEM and its application in the production of continuous river flow map (Case study: The basin upstream of Karkheh dam). Iranian Journal of Remote Sensing and GIS. 10 (4):85-98. (In Persian). Horton RE. 1945. Erosional development of streams and their drainage basins: a hydrophysical approach to quantitative morphology. Geol Soc Amer Bulletin. 56 (3):275-370. Ismail A, Clark L. 2016. Using GIS techniques and quantitative morphometric analysis to evaluate the groundwater resources in the central flinders’ ranges, South Australia. 3rd Annual Conference of Research. 6 p. Jenness J. 2013. Manual: Dem surface tools for arcgis, Jenness enterprises. 98 p. Kalantar B, Pradhan B, Naghibi SA, Motevalli A, Mansor S. 2018. Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN). Geomatics Nat Hazards Risk 9 (1):49-69. KarimiAsl S, Hesari B. 2019. Groundwater quality zoning of urmia plain. 1rd International Congress and 4rd National Congress of Irrigation and Drainage, Urmia, Iran. 10 p. (In Persian). Lawal O, Umeuduji J. 2017. Exploration of hydro-geomorphological indices for coastal flood characterization in rivers state, nigeria. Ghana Journal of Geography. 9 (1):67-87. Meshram S, Alvandi E, Singh V, Meshram Ch. 2019. Comparison of AHP and fuzzy AHP models for prioritization of watersheds. Journal of Methodologies and Application. 23 (24):13615-13625. Miller VC. 1953. A quantitative geomorphic study of drainage basin characteristics in Clinch Mountain Area, Virginia and Tennessee. Department of Geology Columbia University, New York. 13 p. Mohammed A, Adugna T, Takala W. 2018. Morphometric analysis and prioritization of watersheds for soil erosion management in upper gibe catchment. Journal of Degraded and Mining Lands Management. 6 (1):1419-1426. Mokaram M, Negahban S. 2014. Classification of landforms using topographic position index (TPI) (Case study: Southern region of Darab city). Scientific Journal of Geographical Information. 23 (92):57- 65. (In Persian). Mosavi A, Sajedi F, Choubin B, Goodarzi M, Dineva AA, Rafiei E. 2020. Ensemble bossting and bagging based machine learning models for groundwater potential prediction. Journal of Water Resources Management. 15 p. NairNithya C, Srinivas Y, Magesh N, Kaliraj S. 2019. Assessment of groundwater potential zones in chittar basin, Southern India using GIS based AHP technique. Journal of Remote Sensing Applications: Society and Environment. 15(1):100248. Parvin M. 2020. Investigating the relationship between basin morphometric conditions and groundwater resources (Case study: Kamyaran basin). Journal of Quantitative Geomorphological Research. 8 (4):18-33. (In Persian). Rahmati O, Yousefi S, Kalantari Z, Uuemaa E, Teimurian T, Keesstra S, Pham T, Bui D. 2019. Multi-hazard exposure mapping using machine learning techniques: a case study from Iran. Journal of Remote Sensing. 11:1943-1963. Riley S, Degloria S, Elliot R. 1999. A terrain ruggedness that quantifies topographic heterogeneity. Intermountain Journal of Science. 5 (1-4):23-27. Rozyka M, Migon P, Michniewicz A. 2017. Topographic wetness index and terrain ruggedness index in geomorphic characterisation of landslide terrains, on examples from the Sudetes, SW Poland. Journal of Zeitschrift fur Geomorphologie. Germany. 61 (2):61-80. Samadi M, Jalali S, Kornejadi A, SamadiGheshlaghchayi M. 2016. Investigation of morphometric indices in chehelchai watershed of golestan province using GIS. Journal of Surveying Engineering and Spatial Information Engineering. 7 (4):67-74. (In Persian). Schumm SA. 1956. Evolution of drainage systems and slopes in Bedlands at Perth Amboy, New Jersey. Geological Society of America Bulletin. 67 (5):597-646. Schumm SA. 1963. Sinuosity of alluvial rivers on the great plains. Geol Soc Am Bulletin. 74:1089-1100 Sharifikia M, Shayan S, Yamani M, ArabAmeri A. 2018. Classification of nekarood watershed sub-basins using multi-criteria decision making models TOPSIS, VIKOR, SAW. Journal of Ecohydrology. 5 (1):69-83. (In Persian). Skentos A, Ourania A. 2017. Landform analysis using terrain attributes. A GIS application on the Island of Ikaria (Aegean Sea, Greece). Annals of Valiha University of Targovishte, Geographical Series. 17 (1):90-97. Strahler AN. 1964. Quantitative geomorphology of drainage basins and channel networks, Section 4-II. Handbook of applied hydrology. McGraw-Hill, New York. pp: 439-476. Weiss A. 2001. Topographic position and landforms analysis, Director: Ecoregional data management team, The nature conservancy, In Poster presentation, ESRI user conference, San Diego. Vol 200. Waikar M, Nilawar A. 2014. Morphometric analysis of a drainage basin using geographical information system: a case study. International Journal of Multidisciplinary and Current Research. 2 (1):179-184. Zhang H, Shi Z, Fang N, Guo M. 2015. Linking watershed geomorphic characteristics to sediment yield: evidence from the loess plateau of China. Journal of Geomorphology. 234 (1):19-27. | ||
|
Statistics Article View: 720 PDF Download: 774 |
||
Journal management system. designed by sinaweb