A MODEL TO EVALUATE THE ENGINEERING GEOLOGY ON FROZEN GROUND FROM XIDATAN TO WUDAOLIANG ALONG THE QINGHAI-XIZANG HIGHWAY USING GIS

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1 A MODEL TO EVALUATE THE ENGINEERING GEOLOGY ON FROZEN GROUND FROM XIDATAN TO WUDAOLIANG ALONG THE QINGHAI-XIZANG HIGHWAY USING GIS Wu Qingbai, Mi Haizhen, Li Xin, Li Wenjun State Key Laboratory of Frozen Soil Engineering, Lanzhou Institute of Glaciology and Geocryology, CAS. 260 Donggang West Road, Lanzhou, , China. Abstract Based on a Geographic Information System (GIS) for frozen ground along Qinghai-Xizang Highway (QXH), a computer model for frozen ground was developed from regional ground temperature, latitude and altitude data. Using the computer model, an engineering suitability coefficient (K) of engineering geology for frozen ground was proposed. The K value was determined by the differences in engineering geological conditions (EGC), which were divided into five types: excellent (10 to 8), good (8 to 6), generally suitable (6 to 4), requiring protection (4 to 2), and requiring complete protection (2 to 0). Considering the type of frozen ground, water content, ice content, ground temperature, and the engineering properties of frozen ground, a regression model between K and all the parameters was proposed. Finally, using the data in the GIS and from the regression model, a computer model for the engineering geological evaluation of frozen ground was developed. Introduction A Geographic Information System (GIS) for frozen ground along the Qinghai-Xizang Highway (QXH) is one of the cryospheric research programs in China. Its main purpose is to collect basic data on permafrost and to study the permafrost distribution, permafrost ground temperatures, interactions between the permafrost and natural environment, engineering geological conditions, and permafrost changing processes under climatic warming along the QXH. One goal is to provide service for QXH and for the proposed construction of the Qinghai-Xizang Railway. The study area is about 700 km long, from Xidatan to Naqu, and 20 km to 30 km wide along the QXH. The scale of the spatial graphic data is 1:250,000 and the grid dimensions are 100 x 100 meters. The spatial data base includes digital elevations, drill core data, ground temperatures, the Quaternary geology, and other permafrost data. There are three basic applied models discussed here: a digital terrain model, a permafrost distribution model, and an evaluation model of engineering geology on frozen ground. Modeling permafrost distribution Recent models for predicting permafrost distribution have emphasized the relationships between permafrost and vegetation, soils, topography, air temperatures and snow-cover. Nelson and Outcalt (1987) developed a computational method for the regional mapping of permafrost distribution on the basis of minimal climatic data and subsurface information. The energy budget model (Ng and Miller, 1977) utilizes a large number of radiation, thermal and aerodynamic parameters, and considers pathways to establish the heat balance at the surface. Jorgenson and Kreig (1990) more realistically consider landscape component maps, delineating vegetation, terrain units, equivalent latitude values, and regional climatic data for the site-specific, large scale mapping of permafrost. However, these models cannot be applied to regional mapping models in the permafrost regions along the QXH because of regional differences in surface characteristic parameters. MODEL OF THE LOWER LIMIT OF PERMAFROST There is an obvious three-dimensional zonation in the distribution of high-altitude permafrost based on altitudinal, latitudinal and aridity (longitudinal) trends (Cheng and Wang, 1982; Cheng, 1984). Thus, the permafrost distribution along the QXH must consider high-altitude permafrost characteristics, vertical zonation, mean annual ground temperatures, and permafrost stability. The model for the lower limits of permafrost distribution is established by the relationship between distribution altitude and latitude. This paper Wu Qingbai, et al. 1155

2 uses the research results obtained by Cheng (1984) for the Northern Hemisphere and a Gaussian distribution to describe: 2 H = 3650exp [ ( L ) ] where H is the lower altitudinal limit of permafrost, and L is the latitude. The lower limit of the permafrost distribution can be mapped by overlaying the computations from this model and the digital terrain model. [1] PERMAFROST DISTRIBUTION MODEL OF GROUND TEMPERATURE ZONATION Because there are not more complete data on mean annual ground temperature (MAGT) in the spatial database of GIS, this model cannot be built by spatial analysis. The model is built from trends in permafrost distribution along Qinghai-Xizang highway. Based on the vertical zonation of high-altitude permafrost and relationships among mean annual ground temperature, altitude and latitude, a computation model is proposed using the measured ground temperatures along the QXH. The parameters for the samples are provided in papers by Cheng and Wang (1982). The model, based on multiple line regression, is as follows: T = H L where T is MAGT, H is the altitude (m), L is the latitude, and the multiple regression coefficient is The [2] permafrost is divided into five types based on the MAGT (Table 1), which reflects the vertical zonation of high-altitude permafrost and the permafrost stability (Cheng and Wang, 1982). This model can be used with the digital terrain model for the QXH to compute the MAGT of every unit grid using IDRISI Version 4.1, A Grid-Based Geographic Analysis System (Clark University, J.R. Eastman, 1987). After conversion of the geographic codes, a database of ground temperatures compatible with the geographic spatial database of GIS is formed and stored. A map of permafrost zones, developed using quantitative mapping units according to the ground temperature of every unit and Table 1 can be derived (Figure 1). The X and Y coordinates are from a kilometer grid. Figure 1 shows the distribution of permafrost zones from Xidatan to Wudaolaing and the extensive vertical zonation. The upper zone of permafrost generally exists in high mountain areas, the middle zone exists in the Chumaer River high plain areas and river valley areas, and the lower zone does not exist along the QXH. Factors affecting the engineering geology of frozen ground With the development of computers and GIS, there appear to be many possible models to map engineering geology; for example, the statistical model (Wang, 1987), the expert system model (Li and Du, 1995), and the intricate evaluation model among others. The key to Figure 1. Permafrost zone map based on the permafrost distribution model The 7th International Permafrost Conference

3 Table 1. Permafrost zones on the Qinghai-Xizang Plateau (Cheng and Wang, 1982) * MAAT-Mean annual air temperature. MAGT-mean annual ground temperature mapping is to develop a precise geological concept model. In permafrost regions, engineering geology is affected by natural environmental factors, such as the climatic conditions, vegetation cover, soils, and frozen ground conditions, such as permafrost distribution and its thickness and the ground temperatures. Information concerning the engineering properties of frozen ground, for example, thaw settlement, frost heave and strength are also required. Frozen soil comprises a complex, multiphase system, usually consisting of four components: soil particles, ice, water and air, each having different physical-mechanical properties. The interaction of these components and their distribution within the system are basic to an understanding of the properties and engineering behaviour of frozen soils. A model for the engineering geology of frozen ground must realistically consider the water content (W), ice content (I), MAGT (T), permafrost table (H), thaw settlement coefficient (A) and the amount of settlement (S). Strength properties of the frozen soil are ignored for the QXH. An engineering suitability coefficient (K) is used to quantitatively analyze the suitability of building on frozen soil. This coefficient is defined as the engineering stability of the frozen soil, and is divided into five suitability classes (Table 2). Evaluating the model of engineering geology on frozen ground In the evaluation model, the following factors are considered: water content (W); ice content (I); MAGT (T); permafrost table (H); thaw settlement coefficient (A 0 ); the amount of settlement (S). The relationship among engineering suitability coefficient (K) and other factors is established by using multiple regression. The range to be evaluated is first divided into grid units, each with a dimension of 1 km by 1 km. The second step is finding and computing the water contents (W), ice contents (I), MAGT (T) and permafrost table depths (H) in each grid unit. The ice contents and permafrost table depths can be found in the spatial data of the GIS. The water content can be computed from the spatial data in the GIS, generally using the weighted means with depth. The MAGT (T) can be computed from the overlaying computation of the permafrost distribution model and digital terrain model. The thaw settlement coefficient (A 0 ) is determined from an experimental relationship between water content and A 0 (Tong, 1987; Zhu et al., 1983). Because of the initial water content during thaw settlement, some thaw settlement coefficients (A 0 ) can be negative. In order to getting the same critical standard, the limiting error standard method is used (Wang, 1982). All variable values become the value of the same grade (0--1). The method used was as follows: Wu Qingbai, et al. 1157

4 Table 2. Engineering suitability of frozen soil 1 EGC--Engineering geological conditions A = A A A A 0 min max min [3] where A 0 is thaw settlement with initial water content, Amin, Amax are the minimum and maximum thaw settlement coefficients. After the thaw settlement coefficients (A 0 ) are converted, the coefficient A is used in multiple linear regression. In the statistic analysis, forty-five typical samples from Xidatan to Wudaoliang were chosen. After multiple linear regression of the mentioned factors, the correlation coefficients obtained are shown in Table 3. The multiple regression model was established as follows: K = 270. W 074. I 016. T H 152. A 055. S The multiple regression coefficient is The engineering geology then can be evaluated by determining K in the model. After computation of the evaluation model, the map of K isolines is given and divided into evaluation units of engineering geological conditions. Because no definitive data exist along the QXH, especially for water contents, a quantitative evaluation map of the engineering geology of the frozen ground cannot be produced. The model provided in this paper is relatively simple and the required inputs are parameters that can be easily obtained by drilling and from the spatial database of the GIS. Meanwhile, the model can be applied to evaluate conditions when research data became available along the QXH. Future research will [4] include special emphasis on the distribution of water contents along QXH. The suitability of the model for hydraulic construction and civil engineering projects also will be examined. Conclusion Several conclusions can be drawn from this preliminary effort. The approach used for the model of permafrost distribution appears to work quite well along the QXH, and basically confirms the results of previous research. The model to evaluate the engineering geology of frozen soil can be applied to describe the regional engineering geological conditions, because the required parameters can be obtained by drilling and from the special database of the GIS. The strength of the frozen soil was ignored because it was not required for the QXH, which is a shortcoming in the evaluation model. However, other factors should be incorporated into the evaluation model, for example, vegetation, soil types, and strength of frozen soil. The model should also be applied more extensively to determine its suitability for the evaluation of other structures. Acknowledgments This research was supported by Cryosphere Research Programs and National Funds of Natural Science ( ). Table 3. Correlation coefficient of all samples 1158 The 7th International Permafrost Conference

5 References Cheng, Guodong (1984). Problems on zonation of highaltitude permafrost. Acta Geographica Sinica, 39, (In Chinese). Cheng, Guodong and Wang, Shaolin (1982). On the zonation of high-altitude permafrost in China. Journal of Glaciology and Geocryology, 4, 1-17 (In Chinese). Jorgenson, M.T. and Kreig, R.A (1990). A model for mapping permafrost distribution based on landscape component maps and climatic variables. In Proceedings 5th International Conference on Permafrost, pp Li, Tonglu and Du, Dongju (1995). Expert system for engineering geological evaluation of regional stability. In Proceedings 3rd National Symposium on Environmental Engineering Geology. Gansu Nationality Publisher, pp (In Chinese). Nelson, F.E. and Outcalt, S.I. (1987). A computational method for prediction and regionalization of permafrost. Arctic and Alpine Research, 19, Ng, E. and Miller, P. (1977). Validation of a model of the effect of tundra vegetation on soil temperatures. Arctic and Alpine Research, 9, Tong, Changjiang and Chen, Enyuan (1987). Thaw-consolidation behavior of seasonally frozen soils, Journal of Glaciology and Geocryology, 9, (In Chinese). Wang, Jingsheng (1987). On mapping of environmental engineering geology map. Hydrology and Engineering Geology, 78, Wang, Xueren (1982). Multiple variable statistic analysis of geological data. Science Publishing, Beijing (In Chinese). Zhu, Yuanlin, Zhang, Jiayi and Wu, Ziwang (1983). The computation of thaw settlement on frozen soil foundation. In Proceedings of Frozen Soil Research in Qinghai-Xizang Plateau. Science Press, Beijing, pp (In Chinese). Wu Qingbai, et al. 1159