Deriving a high-quality daily dataset of large-pan evaporation over China using a hybrid model

Du, Jizeng; Xu, Xiaolin; Liu, Hongxi; Wang, Lanyuan; Cui, Baoshan

doi:10.1016/j.watres.2023.120005

Cited by 2 publications

(1 citation statement)

References 66 publications

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“…However, usually only one or two pans are available within a catchment, and these pans exclusively capture daily evaporation. So the PE pan may not resonate with real-world conditions [32,33]. Various methods can improve the spatiotemporal accuracy of PE distribution.…”

Section: Introductionmentioning

confidence: 99%

The WRF-Driven Grid-Xin’anjiang Model and Its Application in Small and Medium Catchments of China

Gong,

Hu,

Yao

et al. 2023

Water

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The distributed Grid-Xin’anjiang (Grid-XAJ) model is very sensitive to the spatial and temporal distribution of data when used in humid and semi-humid small and medium catchments. We used the successive correction method to merge the gauged rainfall with rainfall forecasted by the Weather Research and Forecasting (WRF) model to enhance the spatiotemporal accuracy of rainfall distribution. And we used the Penman–Monteith equation to calculate the potential evapotranspiration (PEPM). Then, we designed two forcing scenarios (WRF-driven rainfall (Wr) + PEPM, WRF-merged rainfall (Wm) + PEPM) to drive the Grid-XAJ model for flood forecasting. We found the WRF-driven Grid-XAJ model held significant potential in flood forecasting. The Grid-XAJ model provided only an approximation of flood hygrographs when driven by scenario Wr + PEPM. The results in scenario Wm + PEPM showed a high degree-of-fit with observed floods with mean Nash–Sutcliffe efficiency coefficient (NSE) values of 0.94 and 0.68 in two catchments. Additionally, scenario Wm + PEPM performed better flood hygrographs than scenario Wr + PEPM. The flood volumes and flow peaks in scenario Wm + PEPM had an obvious improvement compare to scenario Wr + PEPM. Finally, we observed that the model exhibited superior performance in forecasting flood hydrographs, flow peaks, and flood volumes in humid catchments compared with semi-humid catchments.

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Section: Introductionmentioning

confidence: 99%

The WRF-Driven Grid-Xin’anjiang Model and Its Application in Small and Medium Catchments of China

Gong,

Hu,

Yao

et al. 2023

Water

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Land Cover Mapping in East China for Enhancing High-Resolution Weather Simulation Models

Ma,

Shao,

Yang

et al. 2024

Remote Sensing

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This study was designed to develop a 30 m resolution land cover dataset to improve the performance of regional weather forecasting models in East China. A 10-class land cover mapping scheme was established, reflecting East China’s diverse landscape characteristics and incorporating a new category for plastic greenhouses (totaling 8687.9 km2 with 6340.5 km2 in Shanghai specifically). Plastic greenhouses are key to understanding surface heterogeneity in agricultural regions, as they can significantly impact local climate conditions, such as heat flux and evapotranspiration, yet they are often not represented in conventional land cover classifications. This is mainly due to the lack of high-resolution datasets capable of detecting these small yet impactful features. For the six-province study area, we selected and processed Landsat 8 imagery from 2015–2018, filtering for cloud cover. Complementary datasets, such as digital elevation models (DEM) and nighttime lighting data, were integrated to enrich the inputs for the Random Forest classification. A comprehensive training dataset was compiled to support Random Forest training and classification accuracy. We developed an automated workflow to manage the data processing, including satellite image selection, preprocessing, classification, and image mosaicking, thereby ensuring the system’s practicality and facilitating future updates. We included three Weather Research and Forecasting (WRF) model experiments in this study to highlight the impact of our land cover maps on daytime and nighttime temperature predictions. The resulting regional land cover dataset achieved an overall accuracy of 83.2% and a Kappa coefficient of 0.81. These accuracy statistics are higher than existing national and global datasets. The model results suggest that the newly developed land cover, combined with a mosaic option in the Unified Noah scheme in WRF, provided the best overall performance for both daytime and nighttime temperature predictions. In addition to supporting the WRF model, our land cover map products, with a planned 3–5-year update schedule, could serve as a valuable data source for ecological assessments in the East China region, informing environmental policy and promoting sustainability.

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Deriving a high-quality daily dataset of large-pan evaporation over China using a hybrid model

Cited by 2 publications

References 66 publications

The WRF-Driven Grid-Xin’anjiang Model and Its Application in Small and Medium Catchments of China

The WRF-Driven Grid-Xin’anjiang Model and Its Application in Small and Medium Catchments of China

Land Cover Mapping in East China for Enhancing High-Resolution Weather Simulation Models

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