Model of eco-water driving force affecting the evolvement of runoff in the upper Minjiang river basin

• Autorzy: Huang J. , Yang W. , Peng L. , Ashraf M.A.
• Języki publikacji: EN

Abstrakty

EN

The amount of eco-water resources reflects the land surface water conservation capability, and the underlying surface condition in the hydrologic cycle. In the upper Minjiang River Basin, the amounts of eco-water resources were retrieved from remotely sensed data during 1992 to 2005. Through regression analysis between the retrieved eco-water data and the climate hydrological data mainly including the temperature, the precipitation, and the runoff in the same period, the model of eco-water driving force affecting the evolvement of runoff was established. The accuracy analysis indicates that the model can well describe the relationship between dry season runoff and its driven factors, the measured data validation proves that the model has high precision and good practicability. The eco-water remote sensing inversion provides a valid method to quantify the land surface water conservation capability, and suggests an interesting approach for the driving function quantitative researches of underlying surface factor in the hydrologic cycle

• Wydawca: -
• Czasopismo: Polish Maritime Research
• Rocznik: 2016
• Tom: 23
• Numer: Special Issue S1
• Opis fizyczny: p.91-96,fig.,ref.

Twórcy

autor

Huang J.

• Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu, P.R.China

autor

Yang W.

• Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu, P.R.China

autor

Peng L.

• Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu, P.R.China

autor

Ashraf M.A.

• Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu, P.R.China
• Faculty of Science and Natural Resources, University Malaysia, Malaysia

Bibliografia

• 1. Liu, X. D., Wu, Q. X., &Su, N. H.1989 Studies on rainfall interception in canopy, litter and soil hydrological characteristics of forests in Liupanshan mountains. Scientia Silvae Sinicae, 25(3), 220-227.
• 2. Kyziol, L. 2013 Stress-corrosion resistance of the EN AW-AlZn5Mg1,5CuZr alloy in different heat treatment states. Polish Maritime Research, 20(4), 39-44.
• 3. Ogee, J. & Brunet, Y. 2002 A forest floor model for heat and moisture including a litter layer.Journal of Hydrology, 255(1), 212-233.
• 4. Rao, L.Y., Zhu, J. Z. &BI, H. X. 2005 Hydrological effects of forest litters and soil in the Simian mountain of Chongqing city.Journal of Beijing Forestry University.27(1), 33-37.
• 5. Hu, X. Y., YUu, X. Y. 2014 Hydrological characteristics of litters and soil in restoration and succession of Karst forest. Guangdong Agricultural Sciences, (23), 150-154.
• 6. Yang, W. N., Yuan,P.X. &Wan, X. N.2001 The study report: the ecological environment integrative survey and evaluation in the Minjiang upper river based on remote sensing, 863-308-21(6). Chengdu: Chengdu University of Technology Archives.
• 7. Wan, X. N., Yang, W. N., Wu, B F., Sun, W. D. & Huang, Q. 2004 Conception of Eco-water sphere and its application. Adv. Earth Sci, 6(19), 117–121.
• 8. Li, Y. X.,Yang, W. N., Tong, L., Jian, J.&Gu, X. F. 2009 Remote sensing quantitative monitoring and analysis fuel moisture content based on spectral index. Acta Optica Sinica, 29(5), 1403-1407.
• 9. Jian, J., Yang, W. N., Jiang, H., Wan, X. N., Li, Y. X. & Peng, L. 2012 A model for retrieving soil moisture saturation with Landsat remotely sensed data. International Journal of Remote Sensing, 33(14), 4553-4566.
• 10. Sun, B; Wei, M; Du, J; Ji, W; Wen, MQ. 2015 Multi-attribute Group Decision Making Method of Ecological Water Compensation Program Based on Preference of Decision Makers. Journal of Coastal Research, 73, 606-610.
• 11. Zhang, R. H., Tian J., Li Z. L., Su H. B., Chen S. H.& Tang X. Z. 2010(a) Principles and methods for the validation of quantitative remote sensing products.Science China(Earth Sciences), 53(5), 741-751.
• 12. Zhang, J. H., Xu, Y., Yao, F. M., Wang, P. J., Guo, W. J., Li, L. & Yang, L. M. 2010(b) Advances in estimation methods of vegetation water content based on optical remote sensing techniques. Science China Technological Sciences, 53(5), 1159-1167.
• 13. Wang, L. T., Wang, S. X., Zhou, Y., Liu, W. L. & Wang, F. 2011 Vegetation water content retrieval and application of drought monitoring using multispectral remote sensing. Spectroscopy and Spectral Analysis, 31(10), 2804-2808.
• 14. Yi, Q. X., Bao, A. M., Luo, Y. & Zhao, J. 2012 Measuring cotton water status using water-related vegetation indices at leaf and canopy levels. Journal of Arid Land, 4(3), 310-319.
• 15. Zhan, Z. M., Qin, Q. M., Ghulan, A. & Wang, D. D. 2007 NIR-red spectral space based new method for soil moisture monitoring. Science in China(Series D:Earth Sciences), 50(02), 283-289.
• 16. Qin, Q. M., You, L., Zhao, Y., Zhao, S. H. & Yao, Y. J. 2012 Soil line automatic identification algorithm based on two-dimensional feature space. Transactions of the CSAE, 28(3), 167-171.
• 17. Wu, Y., Su, Z. X. & Fang, J. Y. 2003 Study on causes and ecological renewal of arid and warm valley of upper Minjiang river. Journal of China West Normal University(Natural Sciences), 24(3), 276-281.
• 18. Sansom, A. L. 1999 Upland vegetation management: the impacts of overstocking. Water Science and Technology, 39(12), 85-92.

Identyfikatory

DOI

10.1515/pomr-2016-0051