Qinghan Dong

Climate change impact on water resource extremes in a headwater region of the Tarim basin in China

The Tarim river basin in China is a huge inland arid basin, which is expected to be highly vulnerable to climatic changes, given that most water resources originate from the upper mountainous headwater regions. This paper focuses on one of these headwaters: the Kaidu river subbasin. The climate change impact on the surface and ground water resources of that basin and more specifically on the hydrological extremes were studied by using both lumped and spatially distributed hydrological models, after simulation of the IPCC SRES greenhouse gas scenarios till the 2050s. The models include processes of snow and glacier melting. The climate change signals were extracted from the grid-based results of general circulation models (GCMs) and applied on the station-based, observed historical data using a perturbation approach. For precipitation, the time series perturbation involves both a wet-day frequency perturbation and a quantile perturbation to the wet-day rainfall intensities. For temperature and potential evapotranspiration, the climate change signals only involve quantile based changes. The perturbed series were input into the hydrological models and the impacts on the surface and ground water resources studied. The range of impact results (after considering 36 GCM runs) were summarized in high, mean, and low results. It was found that due to increasing precipitation in winter, snow accumulation increases in the upper mountainous areas. Due to temperature rise, snow melting rates increase and the snow melting periods are pushed forward in time. Correspondence to: P. Willems (patrick.willems@bwk.kuleuven.be) Although the qualitive impact results are highly consistent among the different GCM runs considered, the precise quantitative impact results varied significantly depending on the GCM run and the hydrological model.

Investigating the relationship between ground‐measured LAI and vegetation indices in an alpine meadow, north‐west China

A field campaign was carried out in the alpine meadow of Heihe River Basin, north‐west China on 11–15 July 2002. Several bio‐geophysical parameters such as leaf area index (LAI) were measured according to VALERI sampling procedures within 38 elementary sampling units (ESUs) in the 3 km×3 km ‘VALERI’ site. A quarter scene of Landsat 7 ETM+ with acquisition times close to the field campaign time was atmospherically and geographically corrected. Three kinds of spectral vegetation index maps including NDVI, SR and MSAVI in the sampling area were derived from the corrected ETM+ image. The two sets of LAI data measured with LAI‐2000 and TRAC instrument at the same site were inter‐compared. This is particularly meaningful for assessing the accuracy of LAI measurements. The relationships between the measured LAI and the three kinds of vegetation indices were also investigated. These comparisons found good relationships between the measured LAI and the different vegetation indices in most cases. Among them, NDVI seems the most promising estimator for extraction of LAI for the alpine meadow. In addition, the LAI‐2000 seems to perform better for LAI measurement in the alpine meadow than the TRAC instrument.

Soil moisture content retrieval based on apparent thermal inertia for Xinjiang province in China

In the arid to semi-arid regions of north-western China, soil moisture is the main hydrological driver for vegetation growth. With the launch of the Moderate Resolution Imaging Spectroradiometer (MODIS), the local MODIS reception capacity and the strong pressure on water resources in the province, the detection and mapping of soil moisture content (SMC) has become a major issue for the regional water management authorities of the province. In this article, we apply the apparent thermal inertia approach to quantify SMC in the soils of the province of Xinjiang using locally received MODIS data. We report on SMC mapping for the entire province for the year 2005. For the estimation, diurnal land surface temperature (LST (Tσ)), LST difference (ΔTσ) and broadband albedo (α0) were applied to determine the space–time variability of SMC. The retrieval of SMC was based on the rationale that high apparent thermal inertia (Iτ) values correspond to high SMCs and low Iτ values correspond to the minimal ones. To enable the application of the technique, a new classification of soil texture was established based on an existing Chinese soil type classification. Typically only topsoil surface moisture content is retrieved with thermal remote sensing (RS). However, SMC retrieval for a 1 m soil profile was performed by applying a semi-empirical modelling approach. The model uses a two-layer water balance equation, and its SMC (θg) input is based on its linear relationship with the soil moisture saturation index (θsi) at time t. For validation purposes, the automatic weather station and time domain reflectometry (TDR) monitoring network included eight sites in the province, including the Mosuowan and Tianshan snow sites and the Turpan, Bayangburk, Kuerle, Yinsu, Alagan and Yiganbujima TDR sites for which data for the year of 2005 were acquired by the Xinjiang Meteorological Bureau (XMB), the Tarim Management Bureau (TMB) and the Xinjiang Institute for Ecology and Geography (XIEG). When time series of SMC determined by using Iτ are compared with the measurements at the different validation sites, regression curve slopes of the validation relationships vary between 0.499 and 0.922. The R2 values vary between 0.25 and 0.83. The minimum and maximum root mean square errors (RMSEs) are 0.001 and 0.028, respectively. Results suggest that apparent thermal inertia application is quite suitable for θg retrieval of a 1 m soil moisture profile in an arid to semi-arid region. The Aqua MODIS 10-day mean soil moisture product is proven to deliver quantitatively correct SMC imagery representing seasonal changes quite realistically.

Investigating relationship between Landsat ETM+ data and LAI in a semi-arid grassland of Northwest China

A field campaign was executed in a semi-arid grassland of northwest China from July 11th-July 15th, 2002. According to the VALERI (Validation of Land European Remote Sensing Instruments) sampling procedures, the leaf area index (LAI) were intensively measured within a homogenous 3times3 km2 square by using LAI-2000 and TRAC instrument. A quarter scene of Landsat7 ETM+ with acquisition times close to the field campaign time was processed by proper geo-registration and atmospheric correction. Three kinds of spectral vegetation index including NDVI, SR and MSAVI in the sampling area were derived from the corrected ETM+ image. The two sets of LAI data measured with LAI-2000 and TRAC instrument at the same site were inter-compared. The relationships between the measured LAI and vegetation indices were investigated as well. The results elicit that the statistical relationships between measured LAI and the different vegetation indices are consistent. Among them, NDVI seems the most promising estimator for the extraction of LAI. In addition, the LAI-2000 seems to perform better for LAI measurement in the semi-arid grassland than the TRAC instrument

The AMSL LST algorithm validated for the Xinjiang Autonomous Region in China

The split-window land surface brightness temperature (LSTb) algorithm of Coll and Caselles (1994) is one of the first approaches to estimate LSTb applied for large surface areas. In this article, we describe a calibrated and validated version of the Coll and Caselles (1994) algorithm applied for the retrieval of land surface air temperature (LSTa) – equivalent to standard WMO (World Meteorological Organization) temperature measurements – for the province of Xinjiang (PR of China). Locally received MODIS (Moderate Resolution Imaging Spectroradiometer) imagery (Fukang receiving station) is used as the input data stream for the so-called AMSL (Aqua MODIS SWA LSTa) algorithm. The objective to develop this algorithm is that it is an input for a distributed hydrological model as well as a soil moisture content retrieval algorithm. In the Xinjiang province with an abundance of arid to semi-arid regions, a highly continental climate, irrigated crop fields and mountain ranges of 6000 m and higher, one typically deals with the spatio-temporally complex conditions, making a high-accuracy retrieval of LSTa quite a challenge. The calibration and validation of the AMSL LSTa product (LSTa,amsl) – using the Jackknife method – is performed using LSTa measurements (LSTa,tmb) from 49 meteorological stations managed by the Tarim Meteorological Bureau (TMB). These stations are distributed relatively homogeneously over the province. The TMB stations’ temperature data are split into 40 calibration LSTa,tmb data sets and 9 validation LSTa,tmb data sets. We can observe that when validated, the LSTa,amsl versus LSTa,tmb validation relationship elicits a high correlation, a slope very close to 1 and an intercept very close to 0. The validated LSTa,amsl estimates demonstrate an estimation accuracy of 0.5 K. The results presented in this article suggest that the LSTa,amsl product is suitable to estimate the land surface air temperature spatio-temporal fields for the arid and semi-arid regions of the Xinjiang province accurately.

Estimation of NPP in Western China using remote sensing and the C-Fix model

Net primary productivity (NPP) is a key component of the terrestrial carbon cycle. The accurate estimation of NPP on regional and global scale is crucial for the studies of global change. In this paper, the Monteith type parametric model-C-Fix, the 1 km SPOT4/VEGETATION data as well as the global meteorological data provided by Meteo France were used to estimate NPP of the terrestrial ecosystems in Western China (73/spl deg/-112/spl deg/E, 26/spl deg/-50/spl deg/N) for the year of 2002. The total yearly NPP of Western China was estimated at 0.96 P (=10/sup 15/)g C in 2002, but the total mean NPP was only equal to 168 g C/m/sup 2//year over the study area of 4.5 million km/sup 2/. The spatial pattern of the annual accumulated NPP as well as the monthly dynamics of NPP in Western China were illustrated and descript in detail. In addition, the NPP-values in the annual accumulated level and the mean level for the different ecosystems were evaluated by using the newest 1:1M land-use map of Western China. The results showed that the spatial and temporal patterns of NPP in Western China are attributable to the complex interaction between natural environment, various climates and human activities. Although Western China has a large area of land, the total mean NPP level is very low due to the hard natural conditions. Among them, the restricted water resource is the main element to control the NPP of Western China.

Land cover mapping and its validation for the northwest of China using SPOT Vegetation data

An accurate land cover mapping is a prerequisite to run all biospheric models. In this paper, NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) time-series of data sets derived from 1-km SPOT/VEGETATION products were used to compile the land cover map of northwest China. The unsupervised classification technique of ISODATA was applied to classify the land cover classification system. With the assumption of the 1:100000 land use map of northwest China interpreted from TM images as the truth, the accuracy of the SPOT/VEGETATION land cover map was evaluated by validating 47 sampling units randomly selected in the whole mapping region. Each sample is a square unit of 25km´25km. The validation results showed an approving accuracy of the land cover map of northwest China. In addition, the combination of NDVI and NDWI vegetation indexes is an effective method on large regional land cover mapping. Meanwhile, three major problems are addressed for explaining the reasons that influence the accuracy of land cover mapping in this region

Estimation of Evaporative Fraction from Remotely Sensed in Arid/Semi-arid Regions

Evaporative Fraction is an intermediary step to assess evapotranspiration and is also a primary component in many water balance models. The paper uses the Land surface temperature and albedo to assess the space-time variability of EF. By analyzing, the results show the precise inversion of EF characteristics in Arid/Semi-arid regions and suggest scientifically available.

Monitoring of land cover changes in Northwest China during the past decade using AVHRR data

For the months July and August, 144 AVHRR images were pre-processed for 1990, 1992, 1994, 1996 and 1999 with a NOAA pre-processing chain (NOAA-CHAIN). A differencing method was applied to estimate the change of the NDVI between different years. The trend lines for six typical region’s NDVI average values in each year were subsequently analyzed. The vegetation condition of most of the regions in the Northwest of China is poor. From 1990 to 1999, most regions have negative NDVI difference values. Concomittantly, locally, some regions show positive NDVI differences, indicating that the vegetation conditions in the regions where an increase occurs, more or less improve. The most largely increasing region with regards to vegetation growth conditions mainly include the North and West of the Xingjiang Province, e.g., the Aertai Mountains, Tacheng, Kelamayi, north of Shihezi, the region between Shihezi and Kuerle, Yining, Akesu, Lanzhou and Dingxi of the Gansu Province. The trend lines of the first three typical regions show an upward path while those of the last three regions a downward one. Comparing the slopes of the six trend lines, it is indicated that the decrease in NDVI range is larger than the NDVI increase for the Northwest of China.