The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the c... more The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the crucial hydrological variables [run-off and actual evapotranspiration (AET)] of the water balance across China for the period 1951-2006 including a precipitation analysis. Results suggest three major findings. First, simulated run-off captured 85% of the spatial variability and 80% of the temporal variability for 85 hydrological gauges across China. The mean relative errors were within 20% for 66% of the studied stations and within 30% for 86% of the stations. The Nash-Sutcliffe coefficients indicated that the quantity pattern of run-off was also captured acceptably except for some watersheds in southwestern and northwestern China. The possible reasons for underestimation of run-off in the Tibetan plateau include underestimation of precipitation and uncertainties in other meteorological data due to complex topography, and simplified representations of the soil depth attribute and snow processes in the model. Second, simulated AET matched reasonably with estimated values calculated as the residual of precipitation and run-off for watersheds controlled by the hydrological gauges. Finally, trend analysis based on the Mann-Kendall method indicated that significant increasing and decreasing patterns in precipitation appeared in the northwest part of China and the Yellow River region, respectively. Significant increasing and decreasing trends in AET were detected in the Southwest region and the Yangtze River region, respectively. In addition, the Southwest region, northern China (including the Heilongjiang, Liaohe, and Haihe Basins), and the Yellow River Basin showed significant decreasing trends in run-off, and the Zhemin hydrological region showed a significant increasing trend. Figure 7. Comparison of simulated AET and the evaluated AET (calculated as the residual of precipitation and run-off) and each point for each hydrological gauge in each year Figure 8. Anomaly graphs of precipitation, AET, and run-off for each hydrological region from 1960 to 2006. A simple linear regression was calculated for each graph with the slope value (k) marked (dash line) Figure 9. Z values and confidence level of Mann-Kendall trend analysis for precipitation, AET, and run-off from 1960 to 2006 in each hydrological region Figure 10. Countrywide maps of Mann-Kendall trend analysis confidence level for run-off (a), precipitation (b), AET (c) and temperature (d) from 1960 to 2006. The negative and positive values indicate decreasing and increasing trends, respectively, and the confidence levels are described as 0: no trend, 1: trend happened with no statistical confidence, 90: confidence level at 90%, 95: confidence level at 95%, 99: confidence level at 99%, 999: confidence level at 99Ð9%. The hydrological regions are showed on each map
The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the c... more The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the crucial hydrological variables [run-off and actual evapotranspiration (AET)] of the water balance across China for the period 1951-2006 including a precipitation analysis. Results suggest three major findings. First, simulated run-off captured 85% of the spatial variability and 80% of the temporal variability for 85 hydrological gauges across China. The mean relative errors were within 20% for 66% of the studied stations and within 30% for 86% of the stations. The Nash-Sutcliffe coefficients indicated that the quantity pattern of run-off was also captured acceptably except for some watersheds in southwestern and northwestern China. The possible reasons for underestimation of run-off in the Tibetan plateau include underestimation of precipitation and uncertainties in other meteorological data due to complex topography, and simplified representations of the soil depth attribute and snow processes in the model. Second, simulated AET matched reasonably with estimated values calculated as the residual of precipitation and run-off for watersheds controlled by the hydrological gauges. Finally, trend analysis based on the Mann-Kendall method indicated that significant increasing and decreasing patterns in precipitation appeared in the northwest part of China and the Yellow River region, respectively. Significant increasing and decreasing trends in AET were detected in the Southwest region and the Yangtze River region, respectively. In addition, the Southwest region, northern China (including the Heilongjiang, Liaohe, and Haihe Basins), and the Yellow River Basin showed significant decreasing trends in run-off, and the Zhemin hydrological region showed a significant increasing trend. Figure 7. Comparison of simulated AET and the evaluated AET (calculated as the residual of precipitation and run-off) and each point for each hydrological gauge in each year Figure 8. Anomaly graphs of precipitation, AET, and run-off for each hydrological region from 1960 to 2006. A simple linear regression was calculated for each graph with the slope value (k) marked (dash line) Figure 9. Z values and confidence level of Mann-Kendall trend analysis for precipitation, AET, and run-off from 1960 to 2006 in each hydrological region Figure 10. Countrywide maps of Mann-Kendall trend analysis confidence level for run-off (a), precipitation (b), AET (c) and temperature (d) from 1960 to 2006. The negative and positive values indicate decreasing and increasing trends, respectively, and the confidence levels are described as 0: no trend, 1: trend happened with no statistical confidence, 90: confidence level at 90%, 95: confidence level at 95%, 99: confidence level at 99%, 999: confidence level at 99Ð9%. The hydrological regions are showed on each map
Uploads
Papers by Weiming Ju