With the development of population and economy, the problems of deficit in water resources and degradation in water environment are increasingly serious in the Taihu watershed of China. The information on spatial and temporal availabilities of water will be helpful for the optimum utilization of water resources. In this study, we apply precipitation (P) from the Tropical Rainfall Measuring Mission (TRMM) products, evapotranspiration (ET) derived from MODIS data, and ground-observed runoff. Then annual water budgets in the Taihu watershed from 2005 to 2007 and the variation of water budget components in spatial and temporal (monthly and annually) scales were evaluated. The results indicated that ET was the most notable component of water consumption in the watershed. The annual mean ratio of the ET to the precipitation was 0.73 to 0.89 in the watershed and 1.1 to 1.3 in Lake Taihu area from 2005 to 2007. The analysis of water balance in the watershed indicated that the amount of water input and output were approximately equal for the watershed and the lake areas with imbalance percentages of 1.4% to 4.4% and 0.1% to 4.0%, respectively.
Taihu Basin is located in the lower reach of the Yangtze River basin. Recent years, severe pollution in Lake Taihu was
frequently occurred, which need to evaluate overall water balance of the basin. Evapotranspiration (ET) and precipitation
are the key elements in water balance estimation that give scientifically sound information on water availability.
Currently, satellite remote sensing is widely used for estimation of these two parameters. In this study, precipitation and
ET from remote sensing and observing runoff are used to estimate annual variations in the water budget of the Taihu
Lake Basin from 2005 to 2007. The Global Satellite Mapping of Precipitation (GSMaP) data was applied to estimate
precipitation in spatial and temporal variability of the Taihu Basin. The surface temperature-normalized difference
vegetation index (Ts-NDVI) triangle method with topographic correction was used to estimate ET from MODIS datasets
in this study. Runoff was observed from hydrological station. The ET is the largest consumption in water budget
components over Taihu Basin. For the whole basin, the ratio of ET/Rainfall is about 0.85-0.95 from 2005 to 2007, and it
is about 1.2-1.4 for Lake Taihu. In general, the income terms of water balance in the basin including precipitation and
inflow from Yangtze River should be equal to outgo terms including ET, outflow and water storage. But the income
terms is mostly larger than outgo terms in Taihu Basin, the imbalance percentage is about 0.4-9.6% for the whole basin,
and 0.5-3.7% for Lake Taihu.
Poyang Lake is the largest shallow lake wetlands in China, and which vegetation succession is rapid under high
changeable hydrological regimes. This study measured the fluxes of carbon dioxide and methane simultaneously by
opaque static chamber-gas chromatography technique for typical wetland vegetation ecosystems in the growing season.
In view of the advantages both in temporal and spatial, HJ-1 satellite images were chosen as the data source for
vegetation cover classification and area estimates. And based on the areas in different vegetation, carbon flux for the
entire study area was estimated during the growing season. Results indicated that carbon dioxide flux has closer
relationship with vegetation change than methane flux does.
Methane (CH4), a significant atmospheric trace-gas, controls numerous chemical processes and species in the
troposphere and stratosphere and is also a strong greenhouse gas with significantly adverse environmental impacts. Since
the SCIAMACHY on the Envisat was in orbit since 2002, CH4 measurements at a regional scale became available. This
study (1) firstly improved the spatial resolution of 0.5°×0.5° lat/lon grid data provided by University of Bremen IUP/IFE
SCIAMACHY near-infrared nadir measurements using the scientific retrieval algorithm WFM-DOAS to 0.1°×0.1°
lat/lon with the ordinary Kriging method, (2) then analyzed the spatial-temporal characteristics of atmospheric CH4
concentration in the Yangtze River basin (YRB), China from 2003 to 2005, (3) finally analyzed the relations with the
main environmental factors: the precipitation from GSMaP MVK+ 0.1x 0.1 lat/lon degree grid data and the temperature
from 147 meteorological stations in the YRB. The analysis shows that atmospheric methane concentration has significant
and obvious characteristics of the spatial distribution of the inter-annual cycle fluctuations and seasonal characteristics
during the year, and points out that the temperature is the main impact factor.
Normalized difference vegetation index (NDVI) is defined as a ratio of the difference of the infrared and red bands to
the sum of the two bands. It can be estimated directly from satellite data, and has been widely used in numerous
environmental studies. Yet the satellite-based NDVI was criticized for its variations with temporal factors (e.g.
sun-surface-satellite geometry, atmospheric variations). Such variations may result in false change of vegetation over
surface. However, the uncertainties relevant to the false change are generally unquantified in the studies. It is therefore
unclear to what extent the satellite-based NDVI would be reliable. In this study, we used a derived relationship between
the digital number (DN) with and without temporal influences for the same area. Using the derived relationship, NDVI
can be expressed as a function of atmospheric optical thickness (AOT), view angle, and DN without temporal
influences. As a result, the uncertainties relevant to the temporal factors were quantified with a mathematical
expression. We found that satellite-based NDVI was a function of AOT, day of year, latitude, and NDVI without
temporal influences. We made simulations in the case of Landsat TM data. Simulations showed that atmospheric effect
was most influential to a satellite-based NDVI, and the NDVI would suffer more serious influences at higher latitude
than at lower latitude. In general, the temporal influences on NDVI cannot be ignored for a reliable monitoring of
surface phenological processes.
Land surface temperature (LST) is of importance in controlling most physical, chemical, and biological processes of the Earth system. Satellite-derive LST provides large-scale observation and is very useful to environmental studies. Among numerous satellite sensors, the MODerate resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) are onboard the same satellite platform TERRA. MODIS MOD11_L2 and ASTER AST_08 LST products have a spatial resolution of 1-km and 90-m, respectively. Our previous scaling study revealed 2.2K on-average differences between the MODIS and the upscaled ASTER LST over a heterogeneous semiarid area in the Loess Plateau of China (SPIE Proc., 5967: 58670O-1-8). Because the retrieval algorithm for MODIS 1-km LST product is subject to uncertainty in emissivity estimate over semiarid and arid areas, this paper uses ASTER emissivity data to reduce the LST inconsistency. Based on the MODIS LST retrieval algorithm, a new algorithm is derived. The algorithm does not rely on the coefficients used in the MODIS algorithm such that it can be implemented without acquisition of the raw MODIS datasets. The MODIS LST and band-31 emissivity as well as the upscaled ASTER emissivity are the necessary inputs to the proposed algorithm. Using the new approach, the rectified MODIS LST achieved the satisfied agreement with the upscaled ASTER LST. This study also suggested that the uncertainty in LST induced by retrieval algorithm could be larger than the scale induced uncertainty.
Evapotranspiration (ET) is an important component of hydrological cycle and large-scale ET is of great concern in numerous studies of global environmental change. The large-scale ET can be estimated using remotely sensed data and the energy balance based approach, in which the homogeneous land surface is assumed. The difficulty in application of the approach with the homogeneity assumption to the heterogeneous land surface can be released by spatial scaling approach. On the other hand, measurement error always exists even over the homogeneous surfaces, and the error unavoidably propagates into the scaled ET. However, error propagation in scaling received rare attention. To this issue, this paper describes the energy balance based approach and the physics-based scaling functions for expanding the application to heterogeneous surface. Surfaces at a fine-scale are assumed to be homogeneous enough so as to represent a heterogeneous surface at a coarse-scale. From error analysis, a general form of error propagation in ET is derived and then applied to ET at the two scales. Multi-scale analysis results suggest that error in ET estimate, introduced by measurement errors in the relevant variables at the fine-scale, would decline rather than be enhanced, when the variables are scaled up into the coarse-scale using the scaling functions. Therefore, the coarse-scale value would be more accurate with the proper scaling approach adopted.
Accurate representation of land surface temperature (LST) at a large-scale is of great concern in numerous environmental studies. Simply averaging of LST measured at a small-scale into the large-scale may lead to misrepresentation due to spatial variability in LST and uncertainty in surface heterogeneity. The satellite-derived LST may be more comprehensive in large-scale observation, yet it often has the satellite-view biases, which is especially true to terrain area. To account for these factors, an approach for LST scaling was proposed, based on the Stefan-Boltzmann law and terrain correction approach used in remote sensing. It was further modified oriented to satellite-derived LST. A terrain area over the Loss Plateau of China was selected for examination. The Lipton-Ward (L-W) approach, which was originally developed for addressing the satellite-view biases in retrieved LST in mountain area, was also adopted in the examination from the perspective of scaling. Incorporated with 90-m topographical data, 90-m LST and emissivity products from The Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) were scaled up to 900-m using the two approaches. Results showed that the proposed approach smoothed the LST difference and reduced the standard deviation of LST but the L-W approach did not. This was further confirmed from the comparison with the terrain corrected 900-m LST, which was produced from the LST products of The MODerate resolution Imaging Spectroradiometer (MODIS) onboard the same satellite platform with ASTER sensor.