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High accuracy surface modeling method (HASM) has the capacity of constructing a surface with a higher accuracy than classical methods. However, surface construction with HASM requires a large amount of computing time due to the intensive computing arising from solving the large linear systems. An effective linear system solving method is essential to cutting down the computing time so that HASM could be applied in constructing large scale surface with high resolution. This paper aims to study the performances of seven linear system solution methods, including HASM-GS, HASM-MGS, HASM-DSPM, HASM-CG, HASM-PCG, HASM-GCG and HASM-GPCG, thus providing a guideline for choosing the right method for HASM under different situations of computing environment. These seven methods were tested against a real-world DEM surface in the Boyang lake basin, which owns a complex topography. Three performance metrics were used, including convergence rates, computing time and consumed memory size. We found that to attain the same accuracy HASM-DSPM method consumed the least memory, HASM-GCG and HASM-GPCG needed less computing time than other methods and HASM-PCG had the fastest convergent rate. This study could provide valuable suggestions for HASM users to make a wise choice of linear system solving method for different surface construction applications.