Comparison of evapotranspiration estimates based on the surface water balance, modified Penman‐Monteith model, and reanalysis data sets for continental China

Abstract

Evapotranspiration (ET) combines the land‐atmosphere water, energy, and carbon cycles and plays a critical role in climate studies. However, ET is difficult to quantify accurately. This study compares three 1982–2013 ET data sets for China based on surface water balance values, a modified Penman‐Monteith (MPM) model and reanalysis data. Water balance ET data, which have been widely used as benchmark data for regional ET, were calculated with and without considering reservoir water storage. MPM ET values were calculated from combinations of input data from different sources, including solar radiation and meteorological data. The MPM model is primarily energy determined, although the impacts of vegetation, soil moisture, air temperature, and wind speed on ET are also considered. The reanalysis ET data used in this study are derived from atmospheric and off‐line land reanalyses. We examined their spatial patterns, interannual variabilities, trends, and key drivers. We found that MPM ET is consistent with water balance ET in detecting ET trends for 1997 to 2013, whereas reanalysis ET is not. The trends and interannual variabilities of ET found via reanalyses are primarily determined by precipitation patterns. However, the precipitation data derived from the atmospheric reanalyses present significant uncertainties. Off‐line land reanalyses correct these biases but do not consider terrestrial water storage changes resulting from reservoir construction and interannual variability in vegetation. Both omissions may produce unreliable trends of ET in reanalyses for China. This study will help improve current ET simulations and contribute to further extending climate studies.

Complementary‐Relationship‐Based Modeling of Terrestrial Evapotranspiration Across China During 1982–2012: Validations and Spatiotemporal Analyses

“…In terms of the variations of country‐averaged annual ET a over last three decades, we found contrasting trends between pre‐late and post‐late 1990s. This is consistent with the conclusion of Mao and Wang (), which employed a modified Penman‐Monteith model driven by forcing of 2,479 weather stations across China.…”

“…While a wide range of studies have investigated the spatiotemporal pattern of ET a across China (Chen et al, ; Gao et al, ; Li, Liang, et al, ; Mao & Wang, ; Su et al, ; Sun et al, ; Yang et al, ), there exist considerable inconsistencies for both magnitudes and trends of ET a due primarily to the uncertainties in parameters and/or forcing of different models. In the present study, by fully taking advantage of the recent improvements in the nonlinear CR model formulation, we aim to (1) develop a 31‐year (1982–2012), 0.1° ET a product across China, along with independent validations using plot‐scale EC measurements and basin‐scale water‐balance‐derived evapotranspiration rates; (2) determine whether this new CR‐based ET a product improves upon previously available ET a products; and (3) quantify the spatial and temporal variability of ET a in China during the past three decades.…”

Quantitative Analysis of Terrestrial Water Storage Changes Under the Grain for Green Program in the Yellow River Basin

“…The other two ET data sets were from the Global Land Data Assimilation System (GLDAS), versions 2.0 and 2.1 (Rodell et al, ), which employed the Noah land surface model at a 0.25° spatial resolution. To date, ET is still particularly difficult to measure and simulate, especially at large spatial scales (Mao & Wang, ). Long et al () reported that the North American Land Data Assimilation System (NLDAS) ET , which is basically estimated by land surface models, has the lowest uncertainty compared with the ET results derived from remote sensing and GRACE satellites.…”

Temporal Characteristics of Actual Evapotranspiration Over China Under Global Warming

“…Su, Feng, and Feng (), Su, Feng, Zhou, et al () used reanalyses to examine AE variability over China with respect to climate change and found that the relationship between AE and pan evaporation was complementary with water control and proportional to energy control. Mao and Wang () compared three evapotranspiration data sets for China based on surface water balance values, a modified Penman‐Monteith (MPM) model, and reanalysis data and concluded that reanalysis evapotranspiration variables are consistent with MPM estimates in terms of spatial patterns, interannual variability, and temporal trends at the station scale.…”