Zhandong Sun

Using SPOT-VGT NDVI as a successive ecological indicator for understanding the environmental implications in the Tarim River Basin, China

The resilience and vulnerability of terrestrial ecosystem in the Tarim River Basin, Xinjiang is critical in sustainable development of the northwest region in China. To learn more about causes of the ecosystem evolution in this wide region, vegetation dynamics can be a surrogate indicator of environmental responses and human perturbations. This paper aims to use the inter-annual and intra-annual coefficient of variation (CoV) derived by the SPOT-VGT Normalized Difference Vegetation Index (NDVI) as an integrated measure of vegetation dynamics to address the environmental implications in response to climate change. To finally pin down the vegetation dynamics, the intra-annual CoV based on monthly NDVI values and the inter-annual CoV based on seasonally accumulated NDVI values were respectively calculated. Such vegetation dynamics can then be associated with precipitation patterns extracted from the Tropical Rainfall Measuring Mission (TRMM) data and irrigation efforts reflecting the cross-linkages between human society and natural systems. Such a remote sensing analysis enables us to explore the complex vegetation dynamics in terms of distribution and evolution of the collective features of heterogeneity over local soil characteristics, climate change impacts, and anthropogenic activities at differing space and time scales. Findings clearly indicate that the vegetation changes had an obvious trend in some high mountainous areas as a result of climate change whereas the vegetation changes in fluvial plains reflected the increasing evidence of human perturbations due to anthropogenic activities. Some possible environmental implications were finally elaborated from those cross-linkages between economic development and resources depletion in the context of sustainable development.

Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis

Abstract A decadal-scale study to retrieve the spatio-temporal precipitation patterns of the Yangtze River basin, China, using the Tropical Rain Mapping Mission, Precipitation Radar (TRMM/PR) data is presented. The empirical orthogonal function (EOF) based on monthly TRMM/PR data extracts several leading precipitation patterns, which are largely connected with physical implications at the basin scale. With the aid of gauge station data, the amplitudes of major principal components (PCs) were used to examine the generic relationships between precipitation variations and hydrological extremes (e.g. floods and droughts) during summer seasons over the past decade. The emergence of such major precipitation patterns clearly reveals the possible linkages with hydrological processes, and the oscillations in relation to the amplitude of major PCs are consistent with these observed hydrological extremes. Although the floods in some sections of the Yangtze River were, to some extent, tied to human activities, such as the removal of wetlands, the variations in major precipitation patterns are recognized as the primary driving force of the flow extremes associated with floods and droughts. The research findings indicate that long-distance hydro-meteorological signals of large-scale precipitation variations over such a large river basin can be successfully identified with the aid of EOF analysis. The retrieved precipitation patterns and their low-frequency jumps of amplitude in relation to PCs are valuable tools to help understand the association between the precipitation variations and the occurrence of hydrological extremes. Such a study can certainly aid in disaster mitigation and decision-making in water resource management. Editor Z.W. Kundzewicz; Associate editor A. Montanari Citation Sun, Z., Chang, N.-B., Huang, Q., and Opp, C., 2013. Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis. Hydrological Sciences Journal, 57 (7), 1315–1324.

Assessing the long-term effects of land use changes on runoff patterns and food production in a large lake watershed with policy implications

Effects of land use development on runoff patterns are salient at a hydrological response unit scale. However, quantitative analysis at the watershed scale is still a challenge due to the complex spatial heterogeneity of the upstream and downstream hydrological relationships and the inherent structure of drainage systems. This study aims to use the well-calibrated Soil and Water Assessment Tool (SWAT) to assess the response of hydrological processes under different land use scenarios in a large lake watershed (Lake Dongting) in the middle Yangtze River basin in China. Based on possible land use changes, scale-dependent land use scenarios were developed and parameters embedded in SWAT were calibrated and validated for hydrological systems analysis. This approach leads to the simulation of the land use change impacts on the hydrological cycle. Results indicated that evapotranspiration, surface runoff, groundwater flow, and water yield were affected by the land use change scenarios in different magnitudes. Overall, changes of land use and land cover have significant impacts on runoff patterns at the watershed scale in terms of both the total water yield (i.e., groundwater flow, surface runoff, and interflow, minus transmission losses) and the spatial distribution of runoff. The changes in runoff distribution were resulted in opposite impacts within the two land use scenarios including forest and agriculture. Water yield has a decrease of 1.8 percent in the forest-prone landscape scenario and an increase of 4.2 percent in the agriculture-rich scenario during the simulated period. Surface runoff was the most affected component in the hydrological cycle. Whereas surface runoff as part of water yield has a decrease of 8.2 percent in the forest- prone landscape scenario, there is an increase of 8.6 percent in the agriculture-rich landscape scenario. Different runoff patterns associated with each land use scenario imply the potential effect on flood or drought mitigation policy. Based on the results, key areas were identified to show that hydrological extreme mitigation and flood control can be coordinated by some land use regulations.

Modelling the stream flow change in a poorly gauged mountainous watershed, southern Tianshan Mountain, using multi-source remote sensing data

Hydrological predictions in ungauged or poorly gauged basin are crucial for sustainable water management and environmental changes study induced by climate change. Application of remote sensing technology has retrieved lots of spatio-temporal dataset during the past decades for references. In this study, TRMM/PR and MODIS LST data were introduced to get spatial patterns of precipitation and temperature changes by Empirical Orthogonal Function (EOF) technique in a mountainous watershed, southern Tianshan. An input variable group was attempted to be constructed for the Artificial Neural Networks (ANN) to model the stream flow change based on the patterns achieved above. The results indicate that the spatial variability patterns of meteorology can be well recognized from the remote sensing data by EOF analysis. The stream flow process can be satisfyingly simulated with input variables captured from the leading modes during the study period. While, since the probabilistic model was not based on full physical mechanisms, and often times, also limited by the amount of input data, uncertainties often implicated in the output. As an example, it is discussed through the rapidly glaciers melting phenomena induced by climate warming, which is expected to cause change in the flow generation mechanism.

Dynamics of Land Surface Temperature in the Central Tien Shan Mountains

Permafrost conditions in mountain ranges are sensitive to regional land surface temperature (LST), among other factors. To explore that relationship, this study carried out 3 steps: (1) validated Moderate Resolution Imaging Spectroradiometer 1-km daily LST data using data measured in situ, (2) used the Harmonic Analysis of Time Series (HANTS) algorithm for fitting and removing the influence of clouds, and (3) analyzed the spatial and temporal characteristics of LST dynamics in the central Tien Shan mountain range based on remote-sensing data improved by covariance and empirical orthogonal function analysis. The results indicate that the in situ data present a basic reference for rebuilding invalid values in the retrieved data, and the data gap in daily LST products can be logically reconstructed with the HANTS algorithm. Major long-term and large-scale patterns can be well extracted with the reconstructed LST data. The most dynamic and sensitive LST areas occurred in the buffers around the periglacial areas. Areas above the periglacial line mainly exhibited a decrease in LST, while areas below it showed an increase. This suggests that the periglacial line of the central Tien Shan region has risen during the past decade. These findings can provide a reference for how periglacial areas respond to climate change and how this may affect hydrological and ecological processes.

Analyzing the Patterns and Variation of Precipitation in the Yangtze River Basin Using TRMM/PR Data

An empirical orthogonal function (EOF) analysis of monthly TRMM/PR(precipitation radar) data set during 1998-2008 was used to examine dominant patterns of precipitation variability in the Yangtze River Basin attempting to explain variation revealed by standard deviation(Std) and coefficient of variation(CoV). The Std and CoV results have represented precipitation variation in different emphasis. The EOF analysis based on the TRMM/PR anomaly data shows that patterns of large scale precipitation variation can be well identified. A primary analysis reveals that the physical meanings of the first several leading EOFs are the general circulation of atmosphere and the prevailing winds, which account for the majority variance in precipitation. The leading EOFs explain the Std characters satisfyingly, but have not provided an interpretation for CoV analysis due to input data selection.

Characterizing snow cover interannual variability with Empirical Orthogonal Function (EOF) analysis and its climate effect in the inland region, Northwest China

Satellite images and field temperature data have been used to derive the winter snow cover change in the northwest inland regions for the period 1978-2005. Decomposition of the satellite-derived snow depth field yields several statistically-significant EOFs (modes) and spectrums of variability according to the selection rule. The first three leading EOF modes account for 63%, 5%, and 4% of the total variance respectively. Spatially, their sensitive regions are characterized significantly with slope orientation, EOF1 towards northwest, EOF2 towards south and EOF3 towards southeast. A primary analysis shows the three modes can be explained by the precipitation events induced by the water vapor conveyed by atmospheric circulation originated from northwest, south and southeast oceans accordingly. As for the temporal dimension, EOF1 shows evidently different from EOF2 and EOF3, and services as a stable process during the 27 years. Their temporal processes correlate temperature in a complicated way. On the whole, the temperature correlates EOF1, EOF2 and EOF3 more significantly, which indicates the impact of climate warming to the snow cover is, to some extent, acted with circulation originated from different orientations, or as a result of their interactions.