Based on monitored data from 840 samples, we assessed the spatial and temporal variability of groundwater salinization in the Tarim River lower reaches combining classical statistics and geostatistics. Results show th...Based on monitored data from 840 samples, we assessed the spatial and temporal variability of groundwater salinization in the Tarim River lower reaches combining classical statistics and geostatistics. Results show that total dissolved solids （TDS） is significantly correlated with other related ions, such as Na＋, Mg2＋, Ca2-, C1- and K＋. TDS and underground water level have characteristics of spatial autocorrelation, both of which present the isotropic characteristic and con- form to the spherical model in each year from 2001-2009. TDS is basically greater than 1 g/L but less than 2 g/L in the Tarim River lower reaches, which indicates that salt stagnation pollution is more serious. The most serious salinization （3 g/L 〈 TDS _〈 35 g/L） contaminated area is mainly in the middle and lower part of the study area.展开更多
Using an integrated method combining wavelet analysis and non-parameter Mann-Kendall test, this paper analyzed spatial-temporal variations of vegetation cover in the Yellow River Basin based on SPOT-VEG images from 19...Using an integrated method combining wavelet analysis and non-parameter Mann-Kendall test, this paper analyzed spatial-temporal variations of vegetation cover in the Yellow River Basin based on SPOT-VEG images from 1998 to 2008 The results indicate： （1） Vegetation cover presented marked seasonal variation during the study period, with minima around winter and maxima in summer. The detail component D5 （with semi-period of 240 days） has presented a major contribution to the intra-armual variability. Forest vegetation presents a marked decreasing trend, while alpine shrubs, meadow, typical steppe, desert steppe, and forest （meadow） steppe vegetation all show a marked increasing trend. （2） Mean vegetation amount increased from the upper to lower reaches of the basin. It is low in the Ordos Plateau and Loess Plateau, and high in the southern Loess Plateau and the lower reaches. Amplitude of the annual phenological cycle pre- sents an opposite pattern in spatial distribution with that of the mean vegetation amount. （3） Vegetation cover presented a dominant positive inter-annual change trend, which implies that the eco-environment in the region has steadily improved. Only a few areas show a negative trend, which are located in the upper reaches and the southern Loess Plateau.展开更多
Using the hydrological and meteorological data in the Kaidu River Basin during 1957-2008, we simulated the hydro-climatic process by back-propagation artificial neural network （BPANN） based on wavelet analysis （WA...Using the hydrological and meteorological data in the Kaidu River Basin during 1957-2008, we simulated the hydro-climatic process by back-propagation artificial neural network （BPANN） based on wavelet analysis （WA）, and then compared the simulated results with those from a multiple linear regression （MLR）. The results show that the variation of runoff responded to regional climate change. The annual runoff （AR） was mainly affected by annual average temperature （AAT） and annual precipitation （AP）, which revealed different varia- tion patterns at five time scales. At the time scale of 32-years, AR presented a monotonically increasing trend with the similar trend of AAT and AP. But at the 2-year, 4- year, 8-year, and 16-year time-scale, AR presented non-linear variation with fluctuations of AAT and AP. Both MLR and BPANN successfully simulated the hydro- climatic process based on WA at each time scale, but the simulated effect from BPANN is better than that from MLR.展开更多
基金supported by the National Basic Research Program of China(973 ProgramNo.2010CB951003)
文摘Based on monitored data from 840 samples, we assessed the spatial and temporal variability of groundwater salinization in the Tarim River lower reaches combining classical statistics and geostatistics. Results show that total dissolved solids （TDS） is significantly correlated with other related ions, such as Na＋, Mg2＋, Ca2-, C1- and K＋. TDS and underground water level have characteristics of spatial autocorrelation, both of which present the isotropic characteristic and con- form to the spherical model in each year from 2001-2009. TDS is basically greater than 1 g/L but less than 2 g/L in the Tarim River lower reaches, which indicates that salt stagnation pollution is more serious. The most serious salinization （3 g/L 〈 TDS _〈 35 g/L） contaminated area is mainly in the middle and lower part of the study area.
基金supported by National Natural Science Foundation of China (Grant Nos. 41130525,41040015)
文摘Using an integrated method combining wavelet analysis and non-parameter Mann-Kendall test, this paper analyzed spatial-temporal variations of vegetation cover in the Yellow River Basin based on SPOT-VEG images from 1998 to 2008 The results indicate： （1） Vegetation cover presented marked seasonal variation during the study period, with minima around winter and maxima in summer. The detail component D5 （with semi-period of 240 days） has presented a major contribution to the intra-armual variability. Forest vegetation presents a marked decreasing trend, while alpine shrubs, meadow, typical steppe, desert steppe, and forest （meadow） steppe vegetation all show a marked increasing trend. （2） Mean vegetation amount increased from the upper to lower reaches of the basin. It is low in the Ordos Plateau and Loess Plateau, and high in the southern Loess Plateau and the lower reaches. Amplitude of the annual phenological cycle pre- sents an opposite pattern in spatial distribution with that of the mean vegetation amount. （3） Vegetation cover presented a dominant positive inter-annual change trend, which implies that the eco-environment in the region has steadily improved. Only a few areas show a negative trend, which are located in the upper reaches and the southern Loess Plateau.
文摘Using the hydrological and meteorological data in the Kaidu River Basin during 1957-2008, we simulated the hydro-climatic process by back-propagation artificial neural network （BPANN） based on wavelet analysis （WA）, and then compared the simulated results with those from a multiple linear regression （MLR）. The results show that the variation of runoff responded to regional climate change. The annual runoff （AR） was mainly affected by annual average temperature （AAT） and annual precipitation （AP）, which revealed different varia- tion patterns at five time scales. At the time scale of 32-years, AR presented a monotonically increasing trend with the similar trend of AAT and AP. But at the 2-year, 4- year, 8-year, and 16-year time-scale, AR presented non-linear variation with fluctuations of AAT and AP. Both MLR and BPANN successfully simulated the hydro- climatic process based on WA at each time scale, but the simulated effect from BPANN is better than that from MLR.
