Estimating daily evapotranspiration in the agricultural-pastoral ecotone in Northwest China: A comparative analysis of the Complementary Relationship, WRF-CLM4.0, and WRF-Noah methods

Xuefeng Xu; Xuliang Li; Xuejin Wang; Chansheng He; Wei Tian; Jie Tian; Lixiao Yang

doi:10.1016/j.scitotenv.2020.138635

Estimating daily evapotranspiration in the agricultural-pastoral ecotone in Northwest China: A comparative analysis of the Complementary Relationship, WRF-CLM4.0, and WRF-Noah methods

Sci Total Environ. 2020 Aug 10:729:138635. doi: 10.1016/j.scitotenv.2020.138635. Epub 2020 Apr 28.

Authors

Xuefeng Xu¹, Xuliang Li¹, Xuejin Wang¹, Chansheng He², Wei Tian¹, Jie Tian¹, Lixiao Yang¹

Affiliations

¹ Key Laboratory of West China's Environmental System (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China.
² Key Laboratory of West China's Environmental System (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China; Department of Geography, Western Michigan University, Kalamazoo, MI 49008, USA. Electronic address: he@wmich.edu.

PMID: 32498153
DOI: 10.1016/j.scitotenv.2020.138635

Abstract

Accurate estimation of evapotranspiration (ET) over regional scale is essential for ecohydrological research, agricultural production, and water resources management. However, few studies have been done to estimate regional ET in data lacking, highly heterogeneous arid areas such as the Agricultural-Pastoral Ecotone in Northwest China (APENC). In this study, we compared three actual ET-estimation methods driven by Weather Research and Forecasting (WRF) model in a semi-arid region. We selected the state of the art Weather Research and Forecasting-Community Land Model 4.0 (WRF-CLM4.0) model, the widely used WRF-Noah model and an empirical Complementary Relationship (CR) model to compare their model structures and mechanisms of estimating daily ET in the study region. The WRF model was chosen to address the problem of data scarcity in the study region and to derive model input for ET estimation with high spatial resolution. The seasonal and pooled performances of the three models were verified with in situ observations. Results indicate that the WRF-CLM4.0 model shows a better applicability in the study region, with a superior performance for the pooled datasets (Pearson correlation coefficient [r] = 0.89, root-mean-square error [RMSE] = 0.66 mm/d and Nash-Sutcliffe efficiency coefficient [NSE] = 0.90), while the CR model has a comparable performance (r = 0.91, RMSE = 0.86 mm/d and NSE = 0.85) and the WRF-Noah model shows the worst performance (r = 0.82, RMSE = 0.94 mm/d and NSE = 0.81). The differences are mainly caused by different representations of the land surface characteristics and hydrology of the study region by the three different models. Our analysis shows that the WRF-CLM4.0 model and the CR model are more applicable to the APENC than the WRF-Noah model. For regional applications, the CR model, with fewer parameters and simpler structure, is able to capture the local characteristic and well-suited for data lacking, highly heterogeneous landscapes such as the APENC.

Keywords: Agricultural-pastoral ecotone in Northwest China; Community land model; Complementary relationship; Daily regional ET; Noah model; Weather research and forecasting.