摘要
研究水文过程模拟时DEM分辨率对流域特征参数和产流的影响,以汉江上游马道流域为研究区,采用60m×60m、120m×120m、250m×250m、500m×500m和1000m×1000m五种不同分辨率的DEM对1981-1985年的流域径流进行模拟,结果表明:不同分辨率DEM流域地形分析计算机自动提取得到的最长河道相差较小,但河道总长、坡度等相差较大,进而影响了分布式水文模型径流模拟的效率。流域中选取4个参考研究区,用归一化的径流-河道总长比指数(NRLI)描述径流模拟与地形参数相关性,分析不同DEM分辨率对各个研究区的NRLI影响可知:低分辨率DEM的NRLI较为平缓,高分辨率DEM的NRLI在较小的研究区波动偏大,但NRLI整体趋于1,由此可以粗略推测流域内局部地区产流量,这一发现可以有效地应用于对流域水资源空间分布快速评估实践中。
Taking Madao watershed in upstream of the Hanjiang River Basin as a target, by means of different spatial resolution DEMs of the study watershed in 60m× 60m, 120m× 120m, 250 × 250m, 500m× 500m andl000m× 1000m respectively, the rainfall-runoff processes from 1981 to 1985 were simulated with AVSWAT2000 to investigate the effects of DEMs in different spatial resolution on the performance of the simulations induced by the topographic characteristic parameters. The statistical resuits showed no evident difference derived in the longest channel length retrieval from different resolution DEMs, but greater differences were found in total channel length and channel dropping extractions. Due to such difference, the simulation efficiencies with AVSWAT2000 were affected evidently. Comparing the simulated runoff under different resolution of DEMs, it was found that the best performance of simulation was obtained by using the 60m× 60m DEM while the worst one was that using the 1000m× 1000m DEM. For examining the relationship of the simulated runoff with watershed topographic features under varied resolution DEM, Normalization of runoff-total length index (NRLI) were proposed and four reference sub-watersheds were selected for the purpose. It was found that NRLI was influenced by DEM resolution, the NRLI fluctuates evenly when the poorest resolution DEM was employed, but considerably with the highest resolution DEM being used, however, it trends to be constant in any circumstances with the values close to 1, which implies its potential usage in discharge predictions at any point along the main river channels.
出处
《遥感信息》
CSCD
2007年第3期8-13,19,共7页
Remote Sensing Information
基金
973项目(2006CB400502
2006CB309404)
中科院"百人计划"择优支持项目(8-047401)