Document Type: ORIGINAL RESEARCH PAPER

Authors

GeoSafer Northern Mindanao/ Cotabato Project, College of Forestry and Environmental Science, Central Mindanao University, Musuan, Maramag 8710, Bukidnon, Philippines

Abstract

Predicting the impact of land cover and climate change on hydrologic responses using modeling tools are essential in understanding the movement and pattern of hydrologic processes within the watershed. The paper provided potential implications of land conversions and climate change scenarios on the hydrologic processes of Muleta watershed using soil and water assessment tool model. Model inputs used include interferometric synthetic aperture radar-digital elevation model, 2016 land cover map, soil map, meteorological and hydrologic data. The model was calibrated using appropriate statistical parameters (R2=0.80, NS=0.80 and RSR=0.45). Model validation using observed streamflow with the same statistical parameters (R2 = 0.79, NS = 0.67 and RSR = 0.57) showed that the result was statistically acceptable. The model provided potential implications of land conversions and climate change adversely affecting hydrologic processes of critical watersheds. Climate change projections with a 13% decrease in rainfall directly influenced the decrease in hydrologic processes. Meanwhile, urbanization had influenced the increase in surface runoff, evapotranspiration, and baseflow. The increase of forest vegetation resulted in a minimal decrease in baseflow and surface runoff. The watershed hydrologic processes were influenced by changes in land cover and climate. Results of this study are useful by the localities and policy makers in coming up with a more informed decision relative to the issues and concern on hydrological responses in the uplands.  

Graphical Abstract

Highlights

  • The SWAT model effectively simulate land cover and climate change impacts on hydrologic processes of Muleta watershed
  • The decrease in rainfall projections directly influenced the decrease in hydrologic processes
  • Increase in urban areas influenced the increase in surface runoff, evapotranspiration and baseflow
  • Increased forest vegetation decreases surface runoff.

Keywords

Main Subjects

Addabbo, P.; Focareta, M.; Marcuccio, S.; Votto, C.; Ullo, S. L., (2016). Contribution of sentinel‐2 data for applications in vegetation monitoring. Acta Imeko, 5(2): 44–54 (11 pages).

Al-Bakri, J.; Salahat, M..; Suleiman, A.; Suifan, M.; Hamdan, M.; Khresat, S.; Kandakji, T., (2013). Impact of climate and land use changes on water and food security in Jordan: Implications for transcending “the tragedy of the commons.” Sustainability, 5(2): 724–748 (25 pages).

Alibuyog, N.R.; Ella, V.B.; Reyes, M.R.; Srinivasan, R.; Heatwole, C.; Dillaha, T., (2009). Predicting the effects of land use on runoff and sediment yield in selected sub-watersheds of the Manupali river using the ArcSWAT model. Int. Agric. Eng. J., 18(1-2): 15–25 (11 pages).

Boggs, J.L.; Sun, G., (2011). Urbanization alters watershed hydrology in the Piedmont of North Carolina. Ecohydrology, 4(2): 256-264 (9 pages).

Briones, R.U.; Ella, V.B.; Bantayan, N.C., (2016). Hydrologic impact evaluation of land use and land cover change in Palico watershed, Batangas, Philippines, using the SWAT model. J. Environ. Sci. Manage., 19(1): 96–107 (12 pages).

Can, T.; Xiaoling, C.; Jianzhong, L.; Gassman, P.W.; Sabine, S.; José-miguel, S.P., (2015). Assessing impacts of different land use scenarios on water budget of Fuhe River, China using SWAT model. Int. J. Agric. Biol. Eng., 8(3): 95–108 (15 pages).

Chithra, S.V.; Nair, M.V.H.; Amarnath, A.; Anjana, N.S., (2015). Impacts of impervious surfaces on the environment. Int. J. Eng. Sci. Invention, 4(5): 27-31 (5 pages).

Combalicer, E.A.; Cruz, R.V.O.; Lee, S.H.; Im, S., (2010). Modelling hydrologic processes distribution in a tropical forest watershed in the Philippines. J. Trop. For. Sci., 22(2): 155–169 (15 pages).

Coutu, G.W.; Vega, C., (2007). Impacts of land use changes on runoff generation in the east branch of the Brandywine Creek watershed using a GIS-based hydrologic model. Middle States Geogr., 40: 142–149 (8 pages).

da Silva, M. G.; de Oliveira de Aguiar Netto, A.; de Jesus Neves, R. J.; do Vasco, A. N.; Almeida, C., A.; Fsccioli, G. G., (2015). Sensitivity analysis and calibration of hydrological modeling of the watershed northeast Brazil. J. Environ. Prot., 6: 837–850 (14 pages).

Djamai, N.; Fernandes, R., (2018). Comparison of SNAP-derived Sentinel-2A L2A product to ESA product over Europe. Remote Sens., 10(6): 1-17 (17 pages).

Dumago, S.W.; Puno, G.R.; Ingotan, S., (2018). Water quality assessment in various land use and land cover of Muleta watershed Bukidnon, Philippines. J. Biodivers. Environ. Sci., 12(3): 201-209 (9 pages).

Githui, F.; Mutua, F.; Bauwens, W., (2009). Estimating the impacts of land-cover change on runoff using the soil and water assessment tool (SWAT): Case study of Nzoia catchment, Kenya. Hydrol. Sci. J., 54(5): 899–908 (11 pages).

Gyamfi, C.; Ndambuki, J.M.; Salim, R.W., (2016). Hydrological responses to land use/cover changes in the Olifants basin, South Africa. Water. 8(12): 1-16 (16 pages).

Hermassi, T.; Khadhraoui, M., (2017). Hydrological modelling of stream flows in the Rmel watershed using SWAT model. J. New Sci., 12: 2684–2692 (9 pages).

Huang, T.; Lo, K., (2015). Effects of land use change on sediment and water yields in Yang Ming Shan national park, Taiwan. Environments, 2(1): 32–42 (11 pages).

Huang, X.D., Shi, Z.H., Fang, N.F., Li, X., (2016). Influences of land use change on baseflow in mountainous watersheds. Forests, 7(1): 1–15 (15 pages).

Khoi, D.N.; Suetsugi, T., (2014). Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be river catchment, Vietnam. Hydrol. Sci. J., 59(5): 1095–1108 (14 pages).

Kim, H.W.; Li, M.-H.; Kim, J.-H.; Jaber, F., (2016). Examining the Impact of suburbanization on surface runoff using the SWAT. Int. J. Environ. Res., 10(3): 379–390 (12 pages).

Li, Y.; Wang, C., (2009). Impacts of urbanization on surface runoff of the Dardenne Creek watershed, St. Charles County, Missouri. Phys. Geogr., 30(6): 556–573 (18 pages).

Li, Z.; Deng, X.; Wu, F.; Hasan, S.S., (2015). Scenario analysis for water resources in response to land use change in the middle and upper reaches of the Heihe river basin. Sustainability, 7(3): 3086–3108 (23 pages).

Li, Z.; Liu, W.-Z; Zhang, X.-C; Zheng, F.-Li., (2009). Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China. J. Hydrol., 377(1-2): 35–42 (8 pages).

Louis, J.; Debaecker, V.; Pflug, B.; Main-Knorn, M.; Bieniarz, J.; Mueller-Wilm, U.; Cadau, E.; Gascon, F., (2016). Sentinel-2 SEN2COR: L2A processor for users. Conference Proceedings “Living Planet Symposium 2016". Prague, Czech Republic 9-13 May.

Michaud, A.R.; Beaudin, I.; Deslandes, J.; Bonn, F.; Madramootoo, C.A., (2007). SWAT-predicted influence of different landscape and cropping system alterations on phosphorus mobility within the Pike river watershed of south-western Quebec. Can. J. Soil. Sci., 87(3): 329-344 (16 page).

Moriasi, D. N.; Arnold, J. G.; Van Liew, M. W.; Bingner, R. L.; Harmel, R. D.; Veith, T. L., (2017). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Am. Soc. Agric. Biol. Eng., 50(3): 885–900 (16 pages).

Narsimlu, B.; Gosain, A.K.; Chahar, B.R.; Singh, S.K.; Srivastava, P.K., (2015). SWAT model calibration and uncertainty analysis for streamflow prediction in the Kunwari river basin, India, using sequential uncertainty fitting. Environ. Process., 2(1): 79–95 (17 pages).

Palao, L.K.M.; Dorado, M.M.; Anit, K. P.A.; Lasco, R.D., (2013). Using the soil and water assessment tool (SWAT) to assess material transfer in the Layawan watershed, Mindanao, Philippines and its implications on payment for ecosystem services. Int. J. Sustainable Dev., 6(6): 73–88 (16 pages).

Pan, S.; Liu, D.; Wang, Z.; Zhao, Q.; Zou, H.; Hou, Y.; Lui, P.; Xiong, L., (2017). Runoff responses to climate and land use/cover changes under future scenarios. Water, 9(475): 1–23 (23 pages).

Petchprayoon, P.; Blanken, P.D.; Ekkawatpanit, C.; Hussein, K., (2010). Hydrological impacts of land use/land cover change in a large river basin in central-northern Thailand. Int. J. Climatol., 30(13): 1917–1930 (14 pages).

Price, K., (2011). Effects of watershed topography, soils, land use, and climate on baseflow hydrology in humid regions: A review. Prog. Phys. Geogr., 35(4): 465–492 (29 pages).

Puno, G. R., (2017). Runoff and sediment yield modeling using GeoWEPP in Mapawa Catchment. CMU J. Sci., 18: 49-70 (22 pages).

Rumsey, C.A.; Miller, M.P.; Susong, D.D.; Tillman, F.D.; Anning, D.W., (2015). Regional scale estimates of baseflow and factors influencing baseflow in the upper Colorado river basin. J. Hydrol.: Reg. Stud., 4(B): 91–107 (17 pages).

Salsabilla, A.; Kusratmoko, E., (2017). Assessment of soil erosion risk in Komering watershed, South Sumatera, using SWAT model. AIP Conference Proceedings, 030192 (2017) -1-030192-7 (7 pages).

Santillan, J.; Makinano, M..; Paringit, E., (2011). Integrated landsat image analysis and hydrologic modeling to detect impacts of 25-year land-cover change on surface runoff in a Philippine watershed. Remote Sens., 3(6): 1067–1087 (21 pages).

Smarzyńska, K.; Miatkowski, Z., (2016). Calibration and validation of SWAT model for estimating water balance and nitrogen losses in a small agricultural watershed in central Poland. J. Water Land Dev., 29(1): 31–47 (17 pages).

Teshager, A.D.; Gassman, P.W.; Schoof, J.T.; Secchi, S., (2016). Assessment of impacts of agricultural and climate change scenarios on watershed water quantity and quality, and crop production. Hydrol. Earth Syst. Sci., 20(8): 3325–3342 (18 pages).

Trinh, D.H.; Chui, T.F.M., (2013). Assessing the hydrologic restoration of an urbanized area via an integrated distributed hydrological model. Hydrol. Earth Syst. Sci., 17(12): 4789–4801 (13 pages).

Wessel, M.; Brandmeier, M.; Tiede, D., (2018). Evaluation of different machine learning algorithms for scalable classification of tree types and tree species based on Sentinel-2 data. Remote Sens., 10(9): 1-21 (21 pages).

Zhou, Y.; Xu, Y. J.; Xiao, W.; Wang, J.; Huang, Y.; Yang, H., (2017). Climate change impacts on flow and suspended sediment yield in headwaters of high-latitude regions-a case study in China’s far northeast. Water, 9(12): 1-17 (17 pages).

 

HOW TO CITE THIS ARTICLE     

Puno, R.C.C.; Puno, G.R.; Talisay, B.A.M., (2019). Hydrologic responses of watershed to land cover and climate change using soil and water assessment tool model. Global. J. Environ. Sci. Manage., 4(1): …, …


Letters to Editor


GJESM Journal welcomes letters to the editor for the post-publication discussions and corrections which allows debate post publication on its site, through the Letters to Editor. Letters pertaining to manuscript published in GJESM should be sent to the editorial office of GJESM within three months of either online publication or before printed publication, except for critiques of original research. Following points are to be considering before sending the letters (comments) to the editor.

[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.
[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.
[3] Letters can be no more than 300 words in length.
[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.
[5] Anonymous letters will not be considered.
[6] Letter writers must include their city and state of residence or work.
[7] Letters will be edited for clarity and length.

CAPTCHA Image