Christian Opp

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.

Load on differently used soils by heavy metals within the highly contaminated area of Bitterfeld (FRG)

Abstract A large number of emission sources contribute to the contamination of ecosystems in the Bitterfeld area. Flood-plains are a special sink of anthropogenic emmissions because they are able to store substances stemming from different sources and matter flows for, at least, a while. In the flood-plain of the river Mulde, at positions both near and far from the chemical industrial complex of Bitterfeld-Wolfen, soil profiles under wood, meadow and arable land were investigated. The differently used soils are located only some metres apart from each other and the soil-genetic features of the test sites are comparable with one another. Both near the emitters and far from them, the highest heavy-metal concentrations (Cu, Zn, Pb) were observed in the wood profile and the lowest values in the arable land. In some cases, limit values of the German sewage sludge regulation (Klarschlammverordnung) were exceeded. The topsoil of the wood profile taken near the emitters contained the highest copper concentrations observed. The highest zinc and lead contents, however, were observed in the topsoil of the wood profile far from the emitters. Because of the better sorption features of the subsoils situated far from the emitters, Cu, Zn and Pb values are higher here than at positions near the emitters.

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.

Impacts of dam draining on the mobility of heavy metals and arsenic in water and basin bottom sediments of three studied dams in Germany

The draining of a dam is a relatively rare event, however, it can have severe consequences for a watercourse connected to that reservoir. In order to understand the effects of the draining on the mobility of pollutants stored in the bottom sediments, the concentrations of heavy metals and arsenic were measured in pore water, river water, and sediments sampled from three emptied reservoirs in Germany. Two of these sites were analyzed immediately after the draining, while the third reservoir was studied one and a half years after the complete discharge of the stored water. Heavy metal and arsenic concentrations within the sediments varied among the studied dams as a result of different geological characteristics and the degree of anthropogenic impacts. Based on the analysis of pore water samples, the concentrations of heavy metals and arsenic were not significantly altered shortly after the draining. However, increased concentrations of As, Fe, Cd, Ni, and Zn were measured in pore water samples after a longer duration of sediment exposure, which altered the redox conditions and sediment properties. The changes in Cu, Cr, Mn, and Pb concentrations in pore water samples were less pronounced. As a result of the pore water drainage increased dissolved heavy metal concentrations were found in the discharge water immediately after draining. At the third site, which had been emptied for one and a half years, only for Mn, a concentration increase was detected in the reservoir discharge water, which emphasizes the strong temporal dynamic of the mobilization of the analyzed elements.

Regime dynamics of hydrochemical and toxicological parameters of the Irtysh River in Kazakhstan

Since the Irtysh River flows through the important economic, ecological and social territories of China, Kazakhstan and Russia, the water quality issues growingly draw the attention of the water authorities from these countries. Therefore, a detailed study of the hydrochemical regime and toxicological indicators in Kazakhstan was carried out for understanding the regime dynamics of water quality and its affect factors. The combined assessment of maximum permissible concentration (MPC) of chemical components and biotesting method were proposed and performed for the study area. The results clearly showed that the concentrations of single chemical component at different locations are mostly under MPC standard in a basin scale. However, the watershed surface runoff and tributary stream flow from mining industry areas had high concentration of heavy metals and had significant impact on the water quality near Ust-Kamenogorsk. Furthermore, even the stream water generally meet MPC standard, the results of biotesting method show the toxicity level of water sample is lethal for the test objects of phytoplankton and Daphnia. The survival rates of most water samples are lower than 46.7%. Hereby, this study strongly suggests using combined water assessment methods to evaluate the water quality.

Long-term trends in flood discharges of the Ulster and Upper Fulda (Germany): a statistical review

Intensifying processes in the hydrological cycle, induced by global warming, involve the danger of increasing flood discharges. Therefore, in the more recent past several large-scale studies on long-term trends within flood discharge datasets were conducted in Germany. The aim of this work is to supplement the existing findings with a focused, more detailed view on a region within the Central German Uplands as one of the flood generation areas. For this purpose, the catchments of Ulster and Upper Fulda in Eastern Hesse were chosen as study area. Datasets of three gauges, covering the period from 1961 to 2010 as well as datasets of five gauges from 1972 to 2010 were analyzed with statistical methods. Linear trends were calculated, verified and screened for change points. For selected time series, differences in long-term mean maximum discharges before and after these change points were examined with annual, semi-annual and monthly resolution. Results mainly showed upward, but non-significant trends. Most distinctive upward linear trends were detected in time series of the Ulster’s gauges. Change point analysis yielded a characteristic clustering around 1977. The examination of the long-term flood regimes’ dynamics, before and after a harmonized break between 1977 and 1978, revealed higher discharges for the sub-series after 1977, primarily during the winter half year. The results coincide with the findings of large-scale studies for Central, Western and Southern Germany in many ways. In particular long-term flow patterns in contiguous catchments bear a close resemblance to those of the Ulster and Fulda.

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.