Study the landuse change and its effects on the hydrologic regime in main catchments of Binalood county

Subject Areas : Natural resources and environmental management

Sayyad Asghari Saraskanrood ¹ , Fahimeh Pourfarrash Zadeh ²

1 - Associate Professor, Department of natural geography, Faculty of Humanities, University of Mohaghegh Ardabili, Iran
2 - PhD. Student in Geomorphology, Faculty of Social Sciences, Mohaghegh Ardabili University, Ardabil, Iran

Received: 2021-05-08 Accepted : 2021-08-11 Published : 2022-05-22

Keywords: Sarasyab, Correlation, discharge, Zirband, Landuse change,

Abstract :

Background and Objective Land use/cover changes have been considered to be one of the most important parts of global environmental changes. These changes are complex and dynamic in relation to other environmental changes (global warming, drought, erosion, and ecosystem degradation). In this context, the impacts of land use/cover changes on hydrologic processes are one of the most important environmental issues and challenges, so the extent of dependency on agriculture and other water-related activities on streams has become a major concern in watershed management. So, Assessing long-term hydrological impacts of land use/land cover  (LULC)  change is of critical importance for land use planning and water resource management. For example, Increased runoff due to the conversion of forests to other land covers, especially agriculture, as well as increased runoff and flood discharge resulting from the expansion of urban and residential use has been repeatedly reported by various researchers. The present study was aimed at identifying and determining the quantity and quality of land use changes and their relationship with flow discharge changes in catchments of Binalud county in order to guide water resources management and conservation of natural resources at the catchment scale, considering the evidence of land use changes as well as the hydrological regime variations in the catchments.Materials and Methods The data used in this study were as follows: the average monthly discharge of hydrometric stations, including 3 stations of ZirbandGolestan, Hesar, and SarasyabShandiz that were collected during 1990, 2000, 2010, and 2018, and the Landsat satellite images, including 4 satellite images for the years 1990, 2000, 2010 and 2020, acquired in the spring (May). The monthly discharge values of two seasons, winter and spring, were selected to study hydrological regime changes, considering the low and close to zero values of the average monthly discharge during summer and autumn and very small variance in the relevant values. The data were tested for normality at the significance level of 0.05 before entering the correlation test based on the Smirnov-Kolmograph method.   In regard to satellite images, the processing steps were as follows: firstly, the atmospheric correction of the images was performed based on the conventional FLAASH method in the ENVI software environment. Then, the combination of visible green, red, and near-infrared bands in false color (4-3-2 in Landsat 5 and 7; 5-4-3 in Landsat 8) was used for classification based on the maximum likelihood algorithm. The land use classes were as follows: 1-garden, 2-residential, 3-water area, 4-rock outcrop, 5-moderate range, 6-poor range, and 7-barren land. The selection of training samples for classification was based on Google Earth images, visual interpretation of satellite images, and of course familiarity with the study area. After classification, the maps were validated based on general accuracy statistics and the Kappa coefficient. However, in order to know the relationship between land use changes and the hydrological regime of the catchments, Pearson two-way correlation test was used in the SPSS software environment. This test was performed at a significance level of 0.05 and between the percentages of the area of each land use and the monthly discharge values (6 months) of hydrometric stations during 4 year.Results and Discussion Preliminary results showed good accuracy of the classification method of the images so that kappa coefficients ranged from 0.78 to 0.95. According to the maps, it is characterized that most area of the catchments belongs to rangelands and barren lands so the changes and conversions of land use occurred mainly between these two land uses. The minimum area percentage of the catchments belonged to the water areas, which at its highest proportion occupied 0.16% and 0.1% of the area of ZirbandGolestan and SarasyabShandiz catchments, respectively. Reagards to land use changes, a decrease in rangelands and the increase of barren lands during the first (1990-2000) and the third (2010-2020) decades have been very considerable, so that 38% and 13% of the moderate rangelands of the Zirband catchment have decreased during the two decades, respectively. In contrast, barren lands have grown by 31% and 15 % over the two decades. Along with these changes, the 8% increase in the area of settlements has been proposed as the most prominent land use change during the second decade (2000-2010) in the catchments. In addition to land use changes, a review of the monthly discharge variations in the catchments showed that the winter months have been experiencing a decreasing trend and, in contrast, the spring months have been experiencing an increasing trend of discharge over the last two decades. The results of the correlation test showed that there are significant relationships between changes in areas of rock outcrop, moderate range, poor range, and discharge variations in the Zirband catchment. In contrast, no significant relationships were found between land uses and monthly discharges in the Sarasyab catchment. In regard to the quality of relationships, positive correlation between the areas of 3 land uses, including residential, rock outcrop, and barren land, and discharges in April and May, and in contrast, a negative correlation between rangeland areas and discharge of the mentioned months was another important result of the study. In general, the increase in human encroachment and occupation in the form of residential and barren land uses has increased the risks of the occurrence of flooding runoff. On the contrary, the rangeland expansion with its protective and moderating effect has reduced the occurrence of spring floods in the studied catchments.Conclusion The results indicate that an important focus of land use change in the catchments has been on rangeland and barren land, so in the last decades, the area of rangelands, which play an effective role in protecting water and soil resources, has been much larger than today. However, due to the lack of protection of pastures and human encroachment on the environment, as well as overgrazing of livestock, the rangelands have gradually retreated to the upstream areas and were replaced by barren lands and residential areas. The existence of a positive correlation between the areas of the residential, rock outcrop, and barren land and discharges in April and May is indicative of acceleration and intensification of the rainfall-runoff process due to the increase in the areas of the land uses. Therefore, the irregular and sprawling growth and expansion of residential areas, as well as barren and abandoned lands, must be prevented. On the other hand, the negative correlation between the percentage area of rangeland and monthly discharge refers to the positive effect of rangelands on the environmental conditions of the catchments in the context of accelerated runoff and erosion processes, which ultimately requires the protection and preservation of natural areas. In general, more attention and focus on the effects of land use change on discharge variations in wet seasons due to the semi-arid climate of the region is necessary.

References:

Aguirre-Gutiérrez J, Seijmonsbergen AC, Duivenvoorden JF. 2012. Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico. Applied Geography, 34: 29-37. doi:https://doi.org/10.1016/j.apgeog.2011.10.010.

Belihu M, Tekleab S, Abate B, Bewket W. 2020. Hydrologic response to land use land cover change in the Upper Gidabo Watershed, Rift Valley Lakes Basin, Ethiopia. HydroResearch, 3: 85-94. doi:https://doi.org/10.1016/j.hydres.2020.07.001.

Cohen WB, Fiorella M, Gray J, Helmer E, Anderson K. 1998. An efficient and accurate method for mapping forest clearcuts in the Pacific Northwest using Landsat imagery. Photogrammetric Engineering and Remote Sensing, 64(4): 293-299.

Cohen WB, Goward SN. 2004. Landsat's Role in Ecological Applications of Remote Sensing. Bioscience, 54(6): 535-545. doi:https://doi.org/10.1641/0006-3568(2004)054[0535:LRIEAO]2.0.CO;2.

Du J, Qian L, Rui H, Zuo T, Zheng D, Xu Y, Xu CY. 2012. Assessing the effects of urbanization on annual runoff and flood events using an integrated hydrological modeling system for Qinhuai River basin, China. Journal of Hydrology, 464-465: 127-139. doi:https://doi.org/10.1016/j.jhydrol.2012.06.057.

Esfandiary Darabad F, Beheshti Javid E, Fathi MH. 2015. Hydrological Impact Assessment of Land Use Change on Annual Surface Runoff at the Gharasoo Catchment by Using L-THIA Model. Hydrogeomorphology, 1(1): 59-73. doi:https://doi.org/20.1001.1.23833254.1393.1.1.4.4. (In Persian).

Ewane BE, Lee HH. 2020. Assessing land use/land cover change impacts on the hydrology of Nyong River Basin, Cameroon. Journal of Mountain Science, 17(1): 50-67. doi:https://doi.org/10.1007/s11629-019-5611-8.

Ghasemiamin N, Arman N, Zeinivand H. 2018. Investigation of land use changes effects on daily stream flow in Nojian Watershed by Clue-s and WetSpa models. Watershed Engineering and Management, 10(1): 14-27. doi:https://doi.org/10.22092/ijwmse.2017.109329.1267. (In Persian).

Gómez C, White JC, Wulder MA. 2016. Optical remotely sensed time series data for land cover classification: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 116: 55-72. doi:https://doi.org/10.1016/j.isprsjprs.2016.03.008.

Huang Hj, Cheng Sj, Wen Jc, Lee Jh. 2008. Effect of growing watershed imperviousness on hydrograph parameters and peak discharge. Hydrological Processes: An International Journal, 22(13): 2075-2085. doi:https://doi.org/10.1002/hyp.6807.

Jensen JR. 1996. Introductory digital image processing: a remote sensing perspective. vol Ed. 2. Prentice-Hall Inc. 318 p.

Kennedy RE, Townsend PA, Gross JE, Cohen WB, Bolstad P, Wang YQ, Adams P. 2009. Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sensing of Environment, 113(7): 1382-1396. doi:https://doi.org/10.1016/j.rse.2008.07.018.

Khodabandehlou B, Khavarian Nehzak H, Ghorbani A. 2019. Change detection of land use /land cover using object oriented classification of satellite images (Case study: Ghare Sou basin, Ardabil province). Journal of RS and GIS for Natural Resources, 10(3): 76-92. (In Persian).

Kiprotich P, Wei X, Zhang Z, Ngigi T, Qiu F, Wang L. 2021. Assessing the impact of land use and climate change on surface runoff response using gridded observations and swat+. Hydrology, 8(1): 48. doi:https://doi.org/10.3390/hydrology8010048.

Li KY, Coe MT, Ramankutty N, Jong RD. 2007. Modeling the hydrological impact of land-use change in West Africa. Journal of Hydrology, 337(3): 258-268. doi:https://doi.org/10.1016/j.jhydrol.2007.01.038.

Lyon SW, Laudon H, Seibert J, Mörth M, Tetzlaff D, Bishop KH. 2010. Controls on snowmelt water mean transit times in northern boreal catchments. Hydrological Processes, 24(12): 1672-1684. doi:https://doi.org/10.1002/hyp.7577.

Olson JM, Alagarswamy G, Andresen JA, Campbell DJ, Davis AY, Ge J, Huebner M, Lofgren BM, Lusch DP, Moore NJ, Pijanowski BC, Qi J, Thornton PK, Torbick NM, Wang J. 2008. Integrating diverse methods to understand climate–land interactions in East Africa. Geoforum, 39(2): 898-911. doi:https://doi.org/10.1016/j.geoforum.2007.03.011.

Öztürk M, Copty NK, Saysel AK. 2013. Modeling the impact of land use change on the hydrology of a rural watershed. Journal of Hydrology, 497: 97-109. doi:https://doi.org/10.1016/j.jhydrol.2013.05.022.

Palamuleni LG, Ndomba PM, Annegarn HJ. 2011. Evaluating land cover change and its impact on hydrological regime in Upper Shire river catchment, Malawi. Regional Environmental Change, 11(4): 845-855. doi:https://doi.org/10.1007/s10113-011-0220-2.

Roy DP, Wulder MA, Loveland TR, C.E W, Allen RG, Anderson MC, Helder D, Irons JR, Johnson DM, Kennedy R, Scambos TA, Schaaf CB, Schott JR, Sheng Y, Vermote EF, Belward AS, Bindschadler R, Cohen WB, Gao F, Hipple JD, Hostert P, Huntington J, Justice CO, Kilic A, Kovalskyy V, Lee ZP, Lymburner L, Masek JG, McCorkel J, Shuai Y, Trezza R, Vogelmann J, Wynne RH, Zhu Z. 2014. Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145: 154-172. doi:https://doi.org/10.1016/j.rse.2014.02.001.

Sanyal J, Densmore AL, Carbonneau P. 2014. Analysing the effect of land-use/cover changes at sub-catchment levels on downstream flood peaks: A semi-distributed modelling approach with sparse data. CATENA, 118: 28-40. doi:https://doi.org/10.1016/j.catena.2014.01.015.

Sheng J, Wilson JP. 2009. Watershed urbanization and changing flood behavior across the Los Angeles metropolitan region. Natural Hazards, 48(1): 41-57. doi:https://doi.org/10.1007/s11069-008-9241-7.

Sinha RK, Eldho T, Subimal G. 2020. Assessing the impacts of land use/land cover and climate change on surface runoff of a humid tropical river basin in Western Ghats, India. International Journal of River Basin Management: 1-12. doi:https://doi.org/10.1080/15715124.2020.1809434.

Sriwongsitanon N, Taesombat W. 2011. Effects of land cover on runoff coefficient. Journal of Hydrology, 410(3): 226-238. doi:https://doi.org/10.1016/j.jhydrol.2011.09.021.

Wang D, Gong J, Chen L, Zhang L, Song Y, Yue Y. 2012. Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed. International Journal of Applied Earth Observation and Geoinformation, 14(1): 12-21. doi:https://doi.org/10.1016/j.jag.2011.08.007.

Welde K, Gebremariam B. 2017. Effect of land use land cover dynamics on hydrological response of watershed: Case study of Tekeze Dam watershed, northern Ethiopia. International Soil and Water Conservation Research, 5(1): 1-16. doi:https://doi.org/10.1016/j.iswcr.2017.03.002.

Woltemade CJ, Hawkins TW, Jantz C, Drzyzga S. 2020. impact of changing climate and land cover on flood magnitudes in the Delaware River Basin, USA. JAWRA Journal of the American Water Resources Association, 56(3): 507-527. doi:https://doi.org/10.1111/1752-1688.12835.

Wu W, Zucca C, Karam F, Liu G. 2016. Enhancing the performance of regional land cover mapping. International Journal of Applied Earth Observation and Geoinformation, 52: 422-432. doi:https://doi.org/10.1016/j.jag.2016.07.014.

Wulder MA, White JC, Cranny M, Hall RJ, Luther JE, Beaudoin A, Goodenough DG, Dechka JA. 2008. Monitoring Canada’s forests. Part 1: Completion of the EOSD land cover project. Canadian Journal of Remote Sensing, 34(6): 549-562. doi:https://doi.org/10.5589/m08-066.

Zhu C, Li Y. 2014. Long-Term Hydrological Impacts of Land Use/Land Cover Change From 1984 to 2010 in the Little River Watershed, Tennessee. International Soil and Water Conservation Research, 2(2): 11-21. doi:https://doi.org/10.1016/S2095-6339(15)30002-2.