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

doi:10.3724/SP.J.1258.2013.00014

Abstract

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

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[J]. Chin J Plant Ecol, 2013, 37(2): 132-141.

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URL: https://www.plant-ecology.com/EN/10.3724/SP.J.1258.2013.00014

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

Figures/Tables 12

References 22

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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