Water Yield Estimation in a Tropical Watershed using Remote Sensing and SEBAL Model
Keywords:
Water yield, Evapotranspiration, Remote Sensing, TRMM, Hydrology.Abstract
Water yield information helps in determining water surplus or water deficit on certain duration of time. The use of remote sensing techniques to estimate water yield is getting popular, particularly in developing countries. This gives a new injection to the management of water resources by knowing the amount of water in a watershed area. The objective of this study is to measure the daily and monthly water yield in Triang watershed. The Surface Energy Balance Algorithm for Land Model (SEBAL) is integrated with remote sensing data to estimate water yield in Triang watershed, Malaysia. Actual rainfall and evapotranspiration parameters are used in the water yield estimations. Rainfall data is collected from the Department of Meteorological Services and Tropical Rain Measuring Mission (TRMM 2A25). While, actual evapotranspiration is extracted from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite data using SEBAL model. The highest potential evaporation value of the SEBAL Model is 7.04 mm/day. Results show that the highest daily water yield was recorded was 6.56 mm, while the lowest was 1.42 mm. On the other hand, the highest and lowest monthly water yield were 38.59 mm and 33.44 mm, respectively. The research results can help the local water agency and government department in handling water resources in Malaysia.
References
[1] ML. Tan, AL. Ibrahim, Z. Yusop, VP. Chua, & NW. Chan. (2017, June). “Climate Change Impacts under CMIP5 RCP Scenarios on Water Resources of the Kelantan River Basin, Malaysia.” Atmospheric Research. [On-line]. vol. 189, pp. 1-10.
[2] M. Tani, AR. Nik, Y. Ohtani, Y. Yasuda, MM. Sahat, B. Kasran, S. Takanashi, S. Noguchi, Z. Yusop & T. Watanabe. T. (2003). Pasoh Ecology of Lowland Rain Forest in Southeast Asia. Springer-Tokyo. 73-88.
[3] ML. Tan, AL. Ibrahim, Z. Duan, AP. Cracknell, & V. Chaplot. (2015, January). “Evaluation of Six High-Resolution Satellite and Gound-Based Precipitation Products Over Malaysia.” Remote Sensing. [On-line]. vol. 7(2), pp. 1504-1528.
[4] J. Wu, D. Wang, & ME. Bauer. (2005, November). “Imaged-based Atmospheric Correction of Quickbird Imagery of Minnesota Cropland.” Remote Sensing of Environment. [On-line]. vol. 99 (3), pp. 315-325.
[5] T. Kumagai, TM. Saitoh, Y. Sato, H. Takahashi, OJ. Manfros, T. Morooka, K. Kuraji, M. Suzuki, T. Yasunari, & H. Komatsu, H. (2015, January) “Annual Water Balance and Seasonality of Evapotranspiration in a Borneo Tropical Rainforest.” Agricultural and Forest Meteorology, vol. 128(1-2), pp. 81-92.
[6] SNM. Santos, & MH. Costa. (2004, September) “A Simple Tropical Ecosystem model of carbon, water and energy fluxes.” Ecological Modeling, vol. 176(3-4), pp. 291-312.
[7] AR. Huete, HQ, Liu, K. Batchily, W. Van Leeuwen. (1997, March) “A Comparison of Vegetation Indices Over a Global Set of TM Images for EOS-MODIS.” Remote Sensing of Environment, vol. 59 (3), pp. 440-451.
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