<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

Model of Eco-Water Driving Force Affecting the Evolvement of Runoff in the Upper Minjiang River Basin

Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources of the China, Chengdu University of Technology, Chengdu, Sichuan, 610059 China

Faculty of Science and Natural Resources, University Malaysia,

Polish Maritime Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The amount of eco-water resources reflects the land surface water conservation capability, and the underlying surface condition in the hydrologic cycle. In the...

Model of Eco-Water Driving Force Affecting the Evolvement of Runoff in the Upper Minjiang River Basin

Publié en ligne: 16 nov. 2016

Pages: 91 - 96

DOI: https://doi.org/10.1515/pomr-2016-0051

Mots clés
Eco-water, Remote Sensing Quantitative Retrieval, Upper Minjiang River, Runoff Prediction

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Model of Eco-Water Driving Force Affecting the Evolvement of Runoff in the Upper Minjiang River Basin

Publié en ligne: 16 nov. 2016

Pages: 91 - 96

DOI: https://doi.org/10.1515/pomr-2016-0051

Mots clésEco-water, Remote Sensing Quantitative Retrieval, Upper Minjiang River, Runoff Prediction

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Mots clés
Eco-water, Remote Sensing Quantitative Retrieval, Upper Minjiang River, Runoff Prediction