Chinese Cryospheric Information System

3 Modeling Cryospheric Response to Global Change

3.1 A GIS Aided Response Model of High Altitude Permafrost to Global Change

3.1.1 Data and Climatic Scenarios
The original Digital Elevation Model (DEM) of the Qinghai-Tibet Plateau has a high spatial resolution. It was resampled to a coarse resolution of 0.5 degree. The permafrost map complied by Li Shude and Cheng Guodong (1996) was digitized to provide the base data, because it reflects the most up-to-date permafrost observations. The map was transferred to a grid map with a resolution of 0.5° by ARC/INFO, so that it could be spatially registered with the DEM.

The GCM model HADCM2 (Viner, 1996), which was developed at the Hakley Center for Climate Prediction and Research in Britain, was adopted for climate senarios. We only use air temperature scenarios in permafrost response model. In order to preserve the original air temperature forcast results in the HADCM2, the nearest- neighbor method was used to resample the air temperature for the years 2009, 2049 and 2099 into 0.5°*0.5° grids compatible with the DEM. The maps of air temperature change show that, for the above three times, the air temperature would increase by 0.51, 1.10 and 2.91°C, C, respectively, on the Qinghai-Tibet Plateau. The maximum air temperature increases would be 1.62, 2.99 and 5.45°C respectively.

3.1.2 The Altitude Model
We used the altitude model to simulate permafrost distrubution on the Qinghai-Tibet Plateau. Altitude model is based on the three-dimensional zonation in the distribution of high altitude permafrost, namely, vertical, latitudinal and aridity (or longitudinal) zonation (Cheng, 1984; Cheng and Dramis, 1992). By using the method of curve fitting, the empirical corretation between lower limit of high altitude permafrost (H) and latitude (i) has been obtained. It can be expressed as:

H=3650exp[-0.003(i-25.37)²]+1428 (1)
Because the altitude model takes the lower limit as the main criterion of high altitude permafrost distribution, DEM can be used to calculate the lower limit of every grid and compare it with the altitude of the same grid to conclude if there has permafrost on the grid. The judgment function can be expressed as:

where, P is a Boolean variable, P=1, means there exists permafrost, P=0, means there does not exist permafrost; h is the altitude (m) of the grid.

The simulation result shows that the altitude model can describe the permafrost distribution on the Qinghai-Tibet Plateau very well. If the 1800 spatial sample in the mapping area are taken for regression analysis, the correlation is 0.92 and the coefficient of determinacy is larger than 85%. Meanwhile, the permafrost area in simulation result is 1,294,376 km², comparing it with the actual area 1,272,709 km² (after vector to raster processing), the error is only 1.70%.

3.1.3 Permafrost Change on the Qinghai-Tibet Plateau
There are no climate variables in the altitude model, therefore, some assumptions must be given out to forecast the permafrost response to global change. These assumptions are: 1) The function that describes high altitude permafrost distribution will not change according to the climate warming. 2) If air temperature increases 1°C, the vertical zonation will rise a certain height agreeing on the lapse rate, the lower limit of the high-altitude permafrost will rise the same height. 3) Lakes, glaciers, deserts will not change.

Based on the above assumptions, and if only air temperature increase is taken into account, the permafrost distribution in the year of 2009, 2049 and 2099 can be forecasted by using the altitude model.

The results show that the permafrost on the Plateau will not change significantly during 20-50 years, the percentage of the total disappeared area will not over 19%. However, by the year of 2099, if the air temperature increases by an average of 2.91°C on the Plateau, the decrease in the area of permafrost will exceed 58%, almost all the permafrost in the Southern Plateau and in the Eastern Plateau will disappear (Figure 2).

Present permafrost distribution

Permafrost change when air temperature rise 0.51°C

Permafrost change when air tem[erature rises 1.10°C

Permafrost change when air temperature rises 2.91°C

Figure 2. The altitude model simulation result of permafrost change on the Qinghai-Tibet Plateau

3.2 A GIS Aided Evaluation Model of Engineering Properties in Permafrost Regions along the Qinghai-Tibet Highway

3.2.1 GIS of the Qinghai-Tibet Highway
The impacts of global warming on the Qinghai-Tibet Highway are obvious (Tong and Wu, 1996; Zhu et al., 1996). In the case study along the Qinghai-Tibet Highway, we paid particularly attention to the evaluation of permafrost-engineering properties because frozen soil environment was heavily destroyed when the Highway was constructed. The GIS of the Qinghai-Tibet Highway covers the part of the highway from Xidatan to Naqu, which is about 700km long and 20-30km wide. It stores information about digital elevation data, borehole data, ground temperature, the Quaternary geology, and other permafrost data. The scale of the topographic and thematic maps is 1:250,000 and the grid resolution of DTMs (digital terrain model) is 100*100 m. Based on the GIS, two models are developed. They are the permafrost distribution model and the ground temperature zonation model, the two models evaluate permafrost-engineering properties in different stability zones.

3.2.2 Modeling the Permafrost stability
Traditional one-dimensional climate-permafrost model cannot be applied for regional permafrost mapping along the Qinghai-Tibet Highway because of great regional difference in surface characteristics. Modeling permafrost-engineering properties along the Qinghai-Tibet Highway must consider high-altitude permafrost characteristics, permafrost vertical zonation, and mean annual ground temperature (MAGT),. We firstly use the altitude model to estimate the lower limit of permafrost along the Qinghai-Tibet Highway. And then, we use the following equation to calculate the MAGT on each grid. The equation was based on a relationship among MAGT, the altitude and the latitude. It is obtained using ground temperature measurements along the Qinghai-Tibet Highway (Cheng and Wang, 1982).

T=68.873-0.00827H-0.923L (3)
where T is MAGT; H is the altitude (m); L is the latitude. And for 40 data samples, the regression coefficient is 0.96.

The permafrost stability has been divided into five types according to the MAGT (Cheng and Wang, 1982). By using equation 3 and DTMs, the stability type of each grid along the Qinghai-Tibet Highway is computed. Then, the map of permafrost stability zones is obtained according to the MAGT of each grid and permafrost classification. The upper zone of permafrost generally exists in high mountain areas, middle zone exists in Chumaer river high plain areas, mountain base areas and river valley areas, and the lower zone do not exist alone the Qinghai-Tibet Highway. This result verified the effectiveness of the model.

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