1. 国家林业和草业局经济发展研究中心,北京,100714
2. 北京林业大学水土保持学院,北京,100083
3. 国家林业局水土保持重点实验室,北京,100083
4. 新疆维吾尔自治区林业规划院,乌鲁木齐,830000
5. 派力工程有限公司,北京,100093
[ "李想(1987-),男,辽宁抚顺人,博士,助理研究员,主要从事森林水文学、生态系统服务价值研究。E-mail:scy0418@163.com" ]
纸质出版:2018
移动端阅览
李想, 曾以禹, 朱思雨, 等. 北京山区径流侵蚀过程及WEPP模型适用性评价[J]. 水土保持学报, 2018,32(3):98-106.
LI Xiang, ZENG Yiyu, ZHU Siyu, et al. The Runoff-erosion Process and the Estimation of WEPP Model in Beijing Mountainous Area[J]. 2018, 32(3): 98-106.
李想, 曾以禹, 朱思雨, 等. 北京山区径流侵蚀过程及WEPP模型适用性评价[J]. 水土保持学报, 2018,32(3):98-106. DOI: 10.13870/j.cnki.stbcxb.2018.03.016.
LI Xiang, ZENG Yiyu, ZHU Siyu, et al. The Runoff-erosion Process and the Estimation of WEPP Model in Beijing Mountainous Area[J]. 2018, 32(3): 98-106. DOI: 10.13870/j.cnki.stbcxb.2018.03.016.
北京土石山区多发严重的土壤侵蚀甚至是泥石流,因此如何通过植被控制侵蚀,进而通过侵蚀模型预测预报侵蚀就显得十分重要。在北京山区简易径流小区内,人工模拟降雨5种雨强(5.7~75.6 mm/h)、不同树种(油松、栓皮栎)及不同株行距(1.0 m×1.0 m,1.5 m×1.5 m),探究树冠特征和降雨特征对径流侵蚀过程的影响,以及WEPP模型对径流过程、总径流量和总产沙量的模拟效果。结果表明:(1)小雨下(总降雨量≤25.2 mm)裸地与有林小区的累计径流量存在显著差异(p=4.9E-11),大雨下(总降雨量49.8,75.6 mm)差异不明显(p=0.35),裸地与有林小区在总径流量和径流系数上并没有差异显著(p=0.81,0.44),LAI与雨强均显著影响总径流量;(2)裸地小区总产沙量为有林小区的1.70倍,但ANOVA分析显示二者之间差异不显著(p=0.13),覆盖度与产沙率SLR之间存在良好的指数关系SLR=e-0.02C;(3) WEPP模型在大雨下对径流过程的模拟更为准确,小雨下对产流时间的模拟较实际产流时间延后10~20 min,累计径流量模拟值与实测值的差距随降雨历时增加而不断增加;(4) WEPP模型对总径流量和总产沙量的模拟效果较好(效率系数CE=0.61,0.91),各雨强下总径流量和总产沙量的模拟值分别是实测值的1.01,1.25倍。
Soil erosion and landslides occur occasionally in Beijing mountainous area
and vegetation is of great importance to control and predict soil erosion. Previous studies mainly focused on the estimation of total runoff volume (TRV) and total sediment yield (TSY)
and the test and simulation of runoff process has been largely disregarded even neglected. The study was conducted in runoff plots in mountainous area in Beijing to examine the simulation accuracy of WEPP model on runoff process
TRV and TSY under different simulated rainfall intensities (5.7~75.6 mm/h)
tree species (Pinus tabulaeformis
Quercus variabilis) and spacing (1.0 m×1.0 m
1.5 m×1.5 m). Results indicated that:(1) Significant differences were observed in accumulative runoff between bare soil plot and forested plots under light rainfalls (gross precipitation ≤ 25.2 mm)
while such differences were not captured in TRV and runoff coefficient. Both LAI and rainfall intensity significantly influenced TRV. (2) Though TSY in bare soil plot was 1.70 times larger than that in forested plots
no significant differences were found in ANOVA analysis
the soil loss rate (SLR) showed fine power relations with forest coverage in the equation SLR=e -0.02C; (3) Generally
the runoff process could be simulated accurately by WEPP model
yet the accuracy increased under heavy rainfalls (total precipitation was 49.8 and 75.6 mm). In contrast
the simulated time to runoff was 10~20 minutes later compared with the measured under light rainfall
and the simulated accumulative runoff was always higher than the measured value
and the gap between the simulated and measured increased with the increasing rainfall duration; (4) TRV and TSY were simulated well in WEPP model with CE of 0.61 and 0.91
respectively. Whereas the simulated TSY and TRV were 1.25 and 1.01 times larger than the measured values.
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