WASSI-C生态水文模型响应单元空间尺度的确定——以杂古脑流域为例

doi:10.3724/SP.J.1258.2013.00014

植物生态学报 ›› 2013, Vol. 37 ›› Issue (2): 132-141.DOI: 10.3724/SP.J.1258.2013.00014

WASSI-C生态水文模型响应单元空间尺度的确定——以杂古脑流域为例

刘宁¹, 孙鹏森¹^,^*(), 刘世荣¹, 孙阁²

¹中国林业科学研究院森林生态环境与保护研究所, 国家林业局森林生态环境重点实验室, 北京 100091
²Eastern Forest Environmental Threat Assessment Center, USDA Forest Service, Raleigh, NC 27606, USA

收稿日期:2012-08-27 接受日期:2012-12-18 出版日期:2013-08-27 发布日期:2013-01-31
通讯作者: 孙鹏森
作者简介:* (E-mail: sunpsen@caf.ac.cn)
基金资助:
国家科技支撑项目(2012BAD22B01);中国林业科学研究院院所基金海外人才专项(CAFYBB2008007);林业公益性行业科研专项(200804001)

Determination of spatial scale of response unit for the WASSI-C eco-hydrological model—a case study on the upper Zagunao River watershed of China

LIU Ning¹, SUN Peng-Sen¹^,^*(), LIU Shi-Rong¹, SUN Ge²

¹Key Laboratory of Forest Ecology and Environment of the State Forestry Administration, Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China
²Eastern Forest Environmental Threat Assessment Center, USDA Forest Service, Raleigh, NC 27606, USA

Received:2012-08-27 Accepted:2012-12-18 Online:2013-08-27 Published:2013-01-31
Contact: SUN Peng-Sen

摘要/Abstract

摘要：

模型基本单元空间尺度的确定是大尺度生态水文模型应用的前提, 也是提高模型模拟精度的关键。该文以长江流域岷江上游的杂谷脑河上游流域为例, 通过设置最小流域面积阈值, 构建不同的水文响应单元划分方案, 探讨生态水文模型WASSI-C响应单元的最佳空间响应尺度。结果表明: 模型响应单元空间尺度的变化对模型精度有显著影响, 模拟效果存在随响应单元划分面积阈值增加先提高再稳定的趋势, 面积阈值小于85 km²时, 模型的模拟效果较好。此外, 面积阈值小于85 km²时, 模型模拟的水、碳循环变量验证的拟合相关性系数和效率系数均趋于稳定, 因此可以将模型水文响应单元流域划分的面积阈值确定为85 km²。基于这一尺度的模拟与验证研究, 分析了WASSI-C模型中关键变量设置对模拟结果的影响。

关键词: 生态水文模型, 水文响应单元, 空间尺度

Abstract:

Aims Optimal spatial scale of hydrological response unit (HRU) is a precondition for eco-hydrological modeling as it is essential to improve accuracy. Our objective was to evaluate the spatial scale of HRU for application of the WASSI-C model.
Methods We determined the best HRU scale for the eco-hydrological model (WASSI-C) through examining the modeling accuracies at different HRU thresholds. This study focused on a large watershed, the upper Zagunao River watershed, situated in the upper reach of the Minjiang River, Yangtze River Basin, China.
Important findings Variation of spatial scales in HRU significantly affected the modeling accuracy. With the increase of the spatial scale of HRU, the accuracy of simulated results first increased then remained relatively unchanged and then decreased, suggesting existence of a threshold around 85 km² in HRU for this model for this watershed. We validated the model using this optimum spatial scale and discussed the potential to improve model output by addressing input parameters such as temperature.

Key words: eco-hydrological model, hydrological response unit (HRU), spatial scale

刘宁, 孙鹏森, 刘世荣, 孙阁. WASSI-C生态水文模型响应单元空间尺度的确定——以杂古脑流域为例. 植物生态学报, 2013, 37(2): 132-141. DOI: 10.3724/SP.J.1258.2013.00014

LIU Ning, SUN Peng-Sen, LIU Shi-Rong, SUN Ge. Determination of spatial scale of response unit for the WASSI-C eco-hydrological model—a case study on the upper Zagunao River watershed of China. Chinese Journal of Plant Ecology, 2013, 37(2): 132-141. DOI: 10.3724/SP.J.1258.2013.00014

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链接本文: https://www.plant-ecology.com/CN/10.3724/SP.J.1258.2013.00014

https://www.plant-ecology.com/CN/Y2013/V37/I2/132

图/表 12

参考文献 22

[1]	Cao MK, Woodward FI (1998). Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change. Global Change Biology, 4, 185-198.
[2]	Foley JA, Prentice IC, Ramankutty N, Levis S, Pollard D, Sitch S, Haxeltine A (1996). An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global Biogeochemical Cycles, 10, 603-628.
[3]	Hao FH, Zhang XS, Cheng HG (2004). Discussion on reasonable subdivision level of watershed for distributed hydrologic model. Journal of Soil and Water Conversation, 17, 75-78. (in Chinese with English abstract)
	[ 郝芳华, 张雪松, 程红光 (2004). 分布式水文模型亚流域合理划分水平刍议. 水土保持学报, 17, 75-78.]
[4]	Hamon WR (1963). Computation of direct runoff amounts from storm rainfall. International Association of Hydrological Sciences Publication, 63, 52-62.
[5]	Jiang XY (1963). The primary study on habitat type of alpine forest in Miyaluo and Markang, West Sichuan. Scientia Silvae Sinicae, 8, 321-335.
[6]	Liu J, Chen JM, Cihlar J, Park WM (1997). A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sensing of Environment, 62, 158-175.
[7]	Liu N, Sun PS, Liu SR (2012). Research advances in simulating land water-carbon coupling. Chinese Journal of Applied Ecology, 23, 3187-3196. (in Chinese with English abstract)
	[ 刘宁, 孙鹏森, 刘世荣 (2012). 陆地水碳耦合模拟研究进展. 应用生态学报, 23, 3187-3196.]
[8]	McCuen RH, Knight Z, Cutter AG (2006). Evaluation of the Nash-Sutcliffe efficiency index. Journal of Hydrologic Engineering, 11, 597-602.
[9]	Penman HL (1948). Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 193, 120-145.
[10]	Shi XZ, Yu DS, Xu SX, Warner ED, Wang HJ, Sun WX, Zhao YC, Gong ZT (2010). Cross-reference for relating genetic soil classification of China with WRB at different scales. Geothermal, 155, 344-350.
[11]	Sun G, Alstad K, Chen JQ, Chen SP, Ford CR, Lin GH, Liu CF, Lu N, McNulty SG, Miao HX, Noormets A, Vose JM, Wilske B, Zeppel M, Zhang Y, Zhang ZQ (2011a). A general predictive model for estimating monthly ecosystem evapotranspiration. Ecohydrology, 4, 245-255.
[12]	Sun G, Caldwell P, Noormets A, McNulty SG, Cohen E, Myers JM, Domec JC, Treasure E, Mu QZ, Xiao JF, John R, Chen JQ (2011b). Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model. Journal of Geophysical Research, 116, G00J05.
[13]	Tague CL, Band LE (2004). RHESSys: regional hydroecologic simulation system―an object-oriented approach to spatially distributed modeling of carbon, water, and nutrient cycling. Earth Interactions, 8, 1-42.
[14]	Tian HQ, Liu ML, Zhang C, Ren W, Xu XF, Chen GS, Lü CQ, Tao B (2010). The dynamic land ecosystem model (DLEM) for simulating terrestrial processes and interactions in the context of multifactor global change. Acta Geographica Sinica, 65, 1027-1047. (in Chinese with English abstract)
	[ 田汉勤, 刘明亮, 张弛, 任巍, 徐小锋, 陈广生, 吕超群, 陶波 (2010). 全球变化与陆地系统综合集成模拟——新一代陆地生态系统动态模型(DLEM). 地理学报, 65, 1027-1047.]
[15]	Wang GX, Qian J, Cheng GD (2001). Current situation and prospect of the ecological hydrology. Advance in Earth Sciences, 16, 314-323. (in Chinese with English abstract)
	[ 王根绪, 钱鞠, 程国栋 (2001). 生态水文科学研究的现状与展望. 地球科学进展, 16, 314-323.]
[16]	Wang LH, Yan DH, Long AH, Yang SY (2009). Advances in basin ecohydrological process modelling. Advance in Earth Sciences, 24, 891-898. (in Chinese with English abstract)
	[ 王凌河, 严登华, 龙爱华, 杨舒媛 (2009). 流域生态水文过程模拟研究进展. 地球科学进展, 24, 891-898.]
[17]	Wang SP, Zhang ZQ, Sun G, McNulty S, Zhang ML, Li JL (2008). Effect of grid size and time step of MIKESHE on hydrological processes modeling at watershed scale. Hydrology, 28, 1-7. (in Chinese with English abstract)
	[ 王盛萍, 张志强, 孙阁, McNulty S, 张满良, 李建牢 (2008). 基于物理过程分布式流域水文模型尺度依赖性. 水文, 28, 1-7.]
[18]	Wolock DM (1995). Effects of subbasin size on topographic characteristics and simulated flow paths in Sleepers River watershed, Vermont. Water Resource Research, 31, 1989-1997.
[19]	Wood EF, Sivapalan M, Beven K, Band L (1998). Effects of spatial variability and scale with implications to hydrologic modeling. Journal of Hydrology, 102, 29-47.
[20]	Yu Z, Sun PS, Liu SR (2011). Phenological change of main vegetation types along a North-South Transect of Eastern China. Chinese Journal of Plant Ecology, 35, 316-329. (in Chinese with English abstract)
	[ 余振, 孙鹏森, 刘世荣 (2011). 中国东部南北样带主要植被类型物候期的变化. 植物生态学报, 35, 316-329.]
[21]	Zhang K, Kimball JS, Nemani RR, Running SW (2010). A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006. Water Resource Research, 46, W9522.
[22]	Zhang XS, Hao FH, Cheng HG, Yang ZF (2004). Influence of subdivision of watershed on distributed hydrological model. Shuili Xuebao, 35, 119-123. (in Chinese with English abstract)
	[ 张雪松, 郝芳华, 程红光, 杨志峰 (2004). 亚流域划分对分布式水文模型模拟结果的影响. 水利学报, 35, 119-123.]

数据集 Dataset		来源 Source	用途 Usage		分辨率 Resolution ratio		年份 Year
气象数据(温度和降水) Climate data (temperature and precipitation)		国家气象局 State Meteorological Administration, China	输入数据 Input data		1 km × 1 km		2000
植被覆盖数据 Vegetation cover data		中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	输入数据 Input data		1 km × 1 km		2000
叶面积指数 Leaf area index (LAI)		中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	输入数据 Input data		1 km × 1 km		2000
土壤属性数据 Soil property data		中国科学院南京土壤研究所 Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China	输入数据 Input data		1 km × 1 km
总初级生产力 Gross primary production (GPP)		中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	模型验证 Model validation		1 km × 1 km		2000
蒸散 Evapotran- spiration (ET)	MODIS蒸散 MODIS_ET	中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	模型验证 Model validation	1 km × 1 km			2000
蒸散 Evapotran- spiration (ET)	Zhang蒸散Zhang_ET	ET全球数据集 Global ET database (ftp://ftp.ntsg.umt.edu)	模型验证 Model validation	8 km × 8 km			2000
径流 Runoff (RUNOFF)		四川省水文资源勘测局 Hydrology and Water Resource Investigation Bureau of Sichuan Province, China	模型验证 Model validation			2000

数据集 Dataset		来源 Source	用途 Usage		分辨率 Resolution ratio		年份 Year
气象数据(温度和降水) Climate data (temperature and precipitation)		国家气象局 State Meteorological Administration, China	输入数据 Input data		1 km × 1 km		2000
植被覆盖数据 Vegetation cover data		中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	输入数据 Input data		1 km × 1 km		2000
叶面积指数 Leaf area index (LAI)		中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	输入数据 Input data		1 km × 1 km		2000
土壤属性数据 Soil property data		中国科学院南京土壤研究所 Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China	输入数据 Input data		1 km × 1 km
总初级生产力 Gross primary production (GPP)		中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	模型验证 Model validation		1 km × 1 km		2000
蒸散 Evapotran- spiration (ET)	MODIS蒸散 MODIS_ET	中分辨率成像光谱仪 Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis.gsfc.nasa.gov)	模型验证 Model validation	1 km × 1 km			2000
蒸散 Evapotran- spiration (ET)	Zhang蒸散Zhang_ET	ET全球数据集 Global ET database (ftp://ftp.ntsg.umt.edu)	模型验证 Model validation	8 km × 8 km			2000
径流 Runoff (RUNOFF)		四川省水文资源勘测局 Hydrology and Water Resource Investigation Bureau of Sichuan Province, China	模型验证 Model validation			2000

植被类型 Vegetation type	GEP = a × ET		REC = m + n × GEP
植被类型 Vegetation type	a ± SD	R²	m ± SD	n ± SD	R²
农田 Cropland	3.13 ± 1.69	0.78	40.6 ± 3.84	0.43 ± 0.02	0.77
郁闭灌丛 Closed shrubland	1.37 ± 0.62	0.77	11.4 ± 15.62	0.69 ± 0.15	0.74
落叶阔叶林 Deciduous broad-leaved forest	3.20 ± 1.26	0.93	30.8 ± 2.93	0.45 ± 0.03	0.83
常绿阔叶林 Evergreen broad-leaved forest	2.59 ± 0.54	0.92	19.6 ± 8.74	0.61 ± 0.06	0.63
常绿针叶林 Evergreen coniferous forest	2.46 ± 0.96	0.89	9.9 ± 2.24	0.68 ± 0.03	0.80
草地 Grassland	2.12 ± 1.66	0.84	18.9 ± 2.31	0.64 ± 0.02	0.82
混交林 Mixed forest	2.74 ± 1.05	0.89	24.4 ± 4.24	0.62 ± 0.05	0.88
稀疏灌丛 Open shrubland	1.33 ± 0.47	0.85	9.7 ± 3.03	0.56 ± 0.08	0.81
高山草甸 Alpine meadow	1.26 ± 0.77	0.80	25.2 ± 3.23	0.53 ± 0.07	0.65
湿地 Wetland	1.66 ± 1.33	0.78	7.8 ± 3.04	0.56 ± 0.03	0.80

植被类型 Vegetation type	GEP = a × ET		REC = m + n × GEP
植被类型 Vegetation type	a ± SD	R²	m ± SD	n ± SD	R²
农田 Cropland	3.13 ± 1.69	0.78	40.6 ± 3.84	0.43 ± 0.02	0.77
郁闭灌丛 Closed shrubland	1.37 ± 0.62	0.77	11.4 ± 15.62	0.69 ± 0.15	0.74
落叶阔叶林 Deciduous broad-leaved forest	3.20 ± 1.26	0.93	30.8 ± 2.93	0.45 ± 0.03	0.83
常绿阔叶林 Evergreen broad-leaved forest	2.59 ± 0.54	0.92	19.6 ± 8.74	0.61 ± 0.06	0.63
常绿针叶林 Evergreen coniferous forest	2.46 ± 0.96	0.89	9.9 ± 2.24	0.68 ± 0.03	0.80
草地 Grassland	2.12 ± 1.66	0.84	18.9 ± 2.31	0.64 ± 0.02	0.82
混交林 Mixed forest	2.74 ± 1.05	0.89	24.4 ± 4.24	0.62 ± 0.05	0.88
稀疏灌丛 Open shrubland	1.33 ± 0.47	0.85	9.7 ± 3.03	0.56 ± 0.08	0.81
高山草甸 Alpine meadow	1.26 ± 0.77	0.80	25.2 ± 3.23	0.53 ± 0.07	0.65
湿地 Wetland	1.66 ± 1.33	0.78	7.8 ± 3.04	0.56 ± 0.03	0.80

面积阈值 Area threshold (km²)	10	12.5	15	25	35	40	50	85	100	160	200	300	650
水文响应单元数 Number of hydrologic response units (HRUs)	105	78	64	45	35	27	24	21	15	11	7	3	1
水文响应单元的平均面积 Mean area of all HRUs (km²)	22.9	30.8	37.5	53.4	68.6	88.9	104.5	126.4	160.2	218.4	343.2	800.9	2 403

WASSI-C生态水文模型响应单元空间尺度的确定——以杂古脑流域为例

Determination of spatial scale of response unit for the WASSI-C eco-hydrological model—a case study on the upper Zagunao River watershed of China

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参考文献 22

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Metrics

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敏感性排序 Sensibility rank	参数 Parameter	理论区间 Theory interval	单位 Unit	最优值 Optimal value
1	REXP	1-5	-	2.4
2	UZFWM	5-150	mm	22
3	LZFSM	5-400	mm	36
4	LZSK	0.01-0.35	-	0.060
5	LZPK	0.001-0.05	-	0.016
6	LZTWM	10-500	mm	162
7	UZK	0.10-0.75	-	0.15
8	ZPERC	5-350	-	80
9	UZTWM	10-300	mm	30
10	LZFPM	10-1000	mm	65
11	PFREE	0.0-0.8	-	0.20

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