SWH双源蒸散模型模拟效果验证及不确定性分析

doi:10.11821/dlxb201611002

Abstract

Abstract:

Evapotranspiration (ET) is one of the core processes of water cycle in ecosystem and ET modeling is a hotspot and frontier in the field of the global climate changes. It is therefore important to provide spatiotemporal information of ET across diverse ecosystems in order to predict the response of ecosystem carbon and water cycles to changes in global climate and land use. The SWH model incorporates the Ball-Berry stomatal conductance model and a light use efficiency-based gross primary productivity (GPP) model into the Shuttleworth-Wallace model, which can simulate both ET and GPP. The newly developed SWH model presents a satisfactory prediction ability of simulating ET in a forest and a grassland ecosystem, respectively. However, the SWH model still lacks comprehensive evaluation and uncertainty analysis at regional scale. In this study, we (1) tested the model's performances on estimating ET and GPP at seasonal and annual time scales; (2) quantified the uncertainties of the model parameters and driving variables, including Normalized Difference Vegetation Index, NDVI and meteorological data; (3) quantified the sensitivity of model outputs to the parameters and driving variables; (4) quantified and separated the uncertainties of ET simulation from the parameters and driving variables. Results showed that the SWH model performed well for ET simulation at regional scale as indicated by high coefficient of determination (R² = 0.75) of linear regression of modeled against measured ET. Among the key parameters in the SWH model, two parameters related to estimating canopy stomatal conductance (g₀and a₁) make great contribution to the model uncertainty. Among the forcing variables, NDVI is most critical in estimating GPP, which contributes much to uncertainty in ET simulation. In comparison, the climatic forcing variables contributes less to uncertainty in ET simulation owing to the high accuracy of the climate data (such as radiation and air temperature) or model’s low sensitivities to some variables (such as precipitation).

Key words: SWH model, Shuttleworth-Wallace model, evapotranspiration, uncertainty analysis

Genan WU, Zhongmin HU, Shenggong LI, Han ZHENG, Xianjin ZHU, Xiaomin SUN, Guirui YU, Jingbao LI. Evaluation and uncertainty analysis of a two-source evapotranspiration model[J].Acta Geographica Sinica, 2016, 71(11): 1886-1897.

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References 19

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	b₂	b₃	a₁	g₀	d	ε_max	平均值
农田	0.9	1.5	4	1.6	0.2	1.2	2.0
草地	2.6	0.8	3.4	1.9	0.3	1.6	2.1
森林	0.4	1.5	3.7	1.2	0.1	1	1.7
平均值	1.3	1.3	3.7	1.6	0.2	1.3

	b₂	b₃	a₁	g₀	ε_max	D
农田	18.4	36.4	50.7	89.3	13.6	31.4
草地	26.5	54.9	40.8	123.5	41.7	50.5
森林	22.9	29.7	60.0	80.0	27.3	45.1
平均值	22.6	40.3	50.5	97.6	27.5	42.3

	b₂	b₃	a₁	g₀	ε_max	D
农田	0.16	0.55	2.04	1.46	0.16	0.06
草地	0.69	0.42	1.39	2.32	0.67	0.13
森林	0.10	0.44	2.20	0.94	0.27	0.05
平均值	0.31	0.47	1.87	1.57	0.37	0.08

	大气相对湿度	降水	光合有效辐射	气温	NDVI	平均值
长白山	4.5	0.0	4.5	2.9	4.9	2.7
鼎湖山	4.5	0.0	4.5	3.1	5.8	3.1
当雄	2.9	0.9	2.9	1.4	7.2	2.7
海北灌丛	4.1	2.4	4.1	2.0	5.7	3.0
内蒙	5.6	0.4	5.6	4.4	7.6	3.9
千烟洲	4.1	1.4	4.1	0.8	6.1	2.6
海北湿地	4.3	0.3	4.3	3.5	5.8	2.8
禹城	2.2	0.1	2.2	2.9	4.3	2.1
平均值	4.0	0.7	4.0	2.6	5.9

	降水	光合有效辐射	大气相对湿度	气温
长白山	110.8	10.9	11.0	26.9
鼎湖山	99.4	37.1	7.3	9.8
当雄	62.7	6.7	25.6	61.5
海北灌丛	45.8	6.2	10.1	72.3
内蒙	49.1	13.8	12.6	12.6
千烟洲	20.0	23.9	5.6	6.5
海北湿地	51.6	16.5	13.2	64.4
禹城	62.6	19.0	9.0	13.4
平均值	62.8	16.8	11.8	33.4

Evaluation and uncertainty analysis of a two-source evapotranspiration model

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	降水	光合有效辐射	大气相对湿度	气温	NDVI
长白山	0.00	0.49	0.50	0.78	0.71
鼎湖山	0.00	1.67	0.33	0.30	0.84
当雄	0.56	0.19	0.74	0.86	1.04
海北灌丛	1.10	0.25	0.41	1.45	0.83
内蒙	0.20	0.77	0.71	0.55	1.10
千烟洲	0.28	0.98	0.23	0.05	0.88
海北湿地	0.15	0.71	0.57	2.25	0.84
禹城	0.06	0.42	0.20	0.39	0.62
平均值	0.29	0.69	0.46	0.83	0.86

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