Effects of Climate/Land Surface Changes on Streamflow With Consideration of Precipitation Intensity and Catchment Characteristics in the Yellow River Basin

2018 ◽  
Vol 123 (4) ◽  
pp. 1942-1958 ◽  
Author(s):  
Meixia Lv ◽  
Zhuguo Ma ◽  
Meizhao Lv
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
Precipitation Intensity ◽  
The Yellow River ◽  
Catchment Characteristics ◽  
The Yellow River Basin ◽  
Surface Changes

scholarly journals Evaluation of Evapotranspiration Estimates in the Yellow River Basin against the Water Balance Method

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1884 ◽  
Author(s):  
Guojie Wang ◽  
Jian Pan ◽  
Chengcheng Shen ◽  
Shijie Li ◽  
Jiao Lu ◽  
...  
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
Balance Method ◽  
The Yellow River ◽  
Water Balance Method ◽  
Global Land ◽  
The Yellow River Basin

Evapotranspiration (ET), a critical process in global climate change, is very difficult to estimate at regional and basin scales. In this study, we evaluated five ET products: the Global Land Surface Evaporation with the Amsterdam Methodology (GLEAM, the EartH2Observe ensemble (E2O)), the Global Land Data Assimilation System with Noah Land Surface Model-2 (GLDAS), a global ET product at 8 km resolution from Zhang (ZHANG) and a supplemental land surface product of the Modern-ERA Retrospective analysis for Research and Applications (MERRA_land), using the water balance method in the Yellow River Basin, China, including twelve catchments, during the period of 1982–2000. The results showed that these ET products have obvious different performances, in terms of either their magnitude or temporal variations. From the viewpoint of multiple-year averages, the MERRA_land product shows a fairly similar magnitude to the ETw derived from the water balance method, while the E2O product shows significant underestimations. The GLEAM product shows the highest correlation coefficient. From the viewpoint of interannual variations, the ZHANG product performs best in terms of magnitude, while the E2O still shows significant underestimations. However, the E2O product best describes the interannual variations among the five ET products. Further study has indicated that the discrepancies between the ET products in the Yellow River Basin are mainly due to the quality of precipitation forcing data. In addition, most ET products seem to not be sensitive to the downward shortwave radiation.

scholarly journals Drought Monitoring over Yellow River Basin from 2003–2019 Using Reconstructed MODIS Land Surface Temperature in Google Earth Engine

2021 ◽  
Vol 13 (18) ◽  
pp. 3748
Author(s):  
Xiaoyang Zhao ◽  
Haoming Xia ◽  
Li Pan ◽  
Hongquan Song ◽  
Wenhui Niu ◽  
...  
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Drought Index ◽  
Yellow River ◽  
Yellow River Basin ◽  
Condition Index ◽  
Drought Indices ◽  
The Yellow River ◽  
Drought Conditions ◽  
The Yellow River Basin

Drought is one of the most complex and least-understood environmental disasters that can trigger environmental, societal, and economic problems. To accurately assess the drought conditions in the Yellow River Basin, this study reconstructed the Land Surface Temperature (LST) using the Annual Temperature Cycle (ATC) model and the Normalized Difference Vegetation Index (NDVI). The Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature-Vegetation Drought Index (TVDI), which are four typical remote sensing drought indices, were calculated. Then, the air temperature, precipitation, and soil moisture data were used to evaluate the applicability of each drought index to different land types. Finally, this study characterized the spatial and temporal patterns of drought in the Yellow River Basin from 2003 to 2019. The results show that: (1) Using the LST reconstructed by the ATC model to calculate the drought index can effectively improve the accuracy of drought monitoring. In most areas, the reconstructed TCI, VHI, and TVDI are more reliable for monitoring drought conditions than the unreconstructed VCI. (2) The four drought indices (TCI, VCI, VH, TVDI) represent the same temporal and spatial patterns throughout the study area. However, in some small areas, the temporal and spatial patterns represented by different drought indices are different. (3) In the Yellow River Basin, the drought level is highest in the northwest and lowest in the southwest and southeast. The dry conditions in the Yellow River Basin were stable from 2003 to 2019. The results in this paper provide a basis for better understanding and evaluating the drought conditions in the Yellow River Basin and can guide water resources management, agricultural production, and ecological protection of this area.

scholarly journals Prediction of Sediment Yield in the Middle Reaches of the Yellow River Basin Under Extreme Precipitation

2020 ◽  
Vol 8 ◽  
Author(s):  
Suzhen Dang ◽  
Xiaoyan Liu ◽  
Huijuan Yin ◽  
Xinwei Guo
Keyword(s):  
River Basin ◽  
Loess Plateau ◽  
Sediment Yield ◽  
Extreme Precipitation ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
The Loess Plateau ◽  
The Yellow River Basin

The Yellow River is one of the rivers with the largest amount of sediment in the world. The amount of incoming sediment has an important impact on water resources management, sediment regulation schemes, and the construction of water conservancy projects. The Loess Plateau is the main source of sediment in the Yellow River Basin. Floods caused by extreme precipitation are the primary driving forces of soil erosion in the Loess Plateau. In this study, we constructed the extreme precipitation scenarios based on historical extreme precipitation records in the main sediment-yielding area in the middle reaches of the Yellow River. The amount of sediment yield under current land surface conditions was estimated according to the relationship between extreme precipitation and sediment yield observations in the historical period. The results showed that the extreme rainfall scenario of the study area reaches to 159.9 mm, corresponding to a recurrence period of 460 years. The corresponding annual sediment yield under the current land surface condition was range from 0.821 billion tons to 1.899 billion tons, and the median annual sediment yield is 1.355 billion tons, of which more than 91.9% of sediment yields come from the Hekouzhen to Longmen sectionand the Jinghe River basin. Therefore, even though the vegetation of the Loess Plateau has been greatly improved, and a large number of terraces and check dams have been built, the flood control and key project operation of the Yellow River still need to be prepared to deal with the large amount of sediment transport.

scholarly journals Simulation of Water Cycle Changes in the Yellow River Basin under Changing Conditions

10.29007/cxp9 ◽  
2018 ◽  
Author(s):  
Yongnan Zhu ◽  
Zhaohui Lin ◽  
Yong Zhao ◽  
Lizhen Wang
Keyword(s):  
Climate Change ◽  
Land Use ◽  
River Basin ◽  
Land Surface ◽  
Water Cycle ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Daily Precipitation Data ◽  
The Yellow River Basin

This study analyzed the combined effects of climate change and land use changes in the Yellow River Basin over the last 45 years. Based on the China Land-use Data for Hundred Years dataset (CLDH), East Asia daily precipitation data, and 6-h NCEP/NCAR reanalysis data, the Coupled Land Surface and Hydrology Model System (CLHMS) was applied to simulate the water cycle processes in the Yellow River under changing conditions from 1962 to 2006. During the study period, the evaporation, infiltration, and surface runoff in the Yellow River Basin all showed a decreasing trend. Comparative tests indicated that climate change was a major factor impacting water cycle variations.

scholarly journals Responses of streamflow to climate and land surface change in the headwaters of the Yellow River Basin

2009 ◽  
Vol 45 (7) ◽  
Author(s):  
Hongxing Zheng ◽  
Lu Zhang ◽  
Ruirui Zhu ◽  
Changming Liu ◽  
Yoshinobu Sato ◽  
...  
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Surface Change ◽  
The Yellow River Basin

scholarly journals CCAM: China Catchment Attributes and Meteorology dataset

2021 ◽  
Vol 13 (12) ◽  
pp. 5591-5616
Author(s):  
Zhen Hao ◽  
Jin Jin ◽  
Runliang Xia ◽  
Shimin Tian ◽  
Wushuang Yang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
River Basin ◽  
Large Scale ◽  
Yellow River ◽  
Potential Evapotranspiration ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Catchment Characteristics ◽  
The Yellow River Basin

Abstract. The absence of a compiled large-scale catchment characteristics dataset is a key obstacle limiting the development of large-sample hydrology research in China. We introduce the first large-scale catchment attribute dataset in China. We compiled diverse data sources, including soil, land cover, climate, topography, and geology, to develop the dataset. The dataset also includes catchment-scale 31-year meteorological time series from 1990 to 2020 for each basin. Potential evapotranspiration time series based on Penman's equation are derived for each basin. The 4911 catchments included in the dataset cover all of China. We introduced several new indicators that describe the catchment geography and the underlying surface differently from previously proposed datasets. The resulting dataset has a total of 125 catchment attributes and includes a separate HydroMLYR (hydrology dataset for machine learning in the Yellow River Basin) dataset containing standardized weekly averaged streamflow for 102 basins in the Yellow River Basin. The standardized streamflow data should be able to support machine learning hydrology research in the Yellow River Basin. The dataset is freely available at https://doi.org/10.5281/zenodo.5729444 (Zhen et al., 2021). In addition, the accompanying code used to generate the dataset is freely available at https://github.com/haozhen315/CCAM-China-Catchment-Attributes-and-Meteorology-dataset (last access: 26 November 2021) and supports the generation of catchment characteristics for any custom basin boundaries. Compiled data for the 4911 basins covering all of China and the open-source code should be able to support the study of any selected basins rather than being limited to only a few basins.

scholarly journals Estimation of Heating-Up Effecting in the Yellow River Basin Based on MODIS Data

2021 ◽  
Author(s):  
Ziwu Pan ◽  
Jun Zhu ◽  
Fen Qin
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
Temperature Data ◽  
Tibet Plateau ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Heating Up

Abstract Using MODIS land surface temperature data, air temperature data and elevation data from 2000 to 2015 in the Yellow River Basin. The GWR analysis method with high accuracy was chosen to establish the regression model of plateau air temperature, land surface temperature and altitude. In the 12-month GWR regression model, the determination coefficient (Adjusted R2) was above 0.95 or more (0.959-0.980) and the root-mean-square error (RMSE)was between 0.740 and 1.029°C. Depending on the model, the air temperature of the Yellow River Basin is estimated and the accuracy is verified. On this basis, the average monthly air temperature in the basin is converted to altitudes of 4500m and 5000m, and the heating-up effects of various shapes in the basin are compared and discussed. The results show that: (1) Using the GWR method, combined with the observation data of the ground station, the accuracy of the air temperature estimation in the Yellow River Basin can be increased to 0.740°C; (2) According to the estimated annual variation of the spatial distribution of the 12-month average temperature, in the upper of the Tibet Plateau, the Huangshui Valley and the Gannan Plateau have lower annual air temperatures and less spatial distribution. While the air temperature in the northeast of the upstream Inner Mongolia plateau was higher, which was related to the rapid drying temperature rise near the desert. The change of mean monthly temperature in the middle and lower reaches is relatively high and the change is small, which is closely linked to the fact that it is located in the low-elevation area of the basin plain and has perennial light and heat.(3) The heating-up effect in the Yellow River Basin is outstanding. It is preliminaries estimated that at the same altitude, the Tibet Plateau is about 1.5~8°C higher than the Loess Plateau, and about 6~13°C higher than the North China Plain.

Comparison and evaluation of multiple land surface products for the water budget in the Yellow River Basin

2020 ◽  
Vol 584 ◽  
pp. 124534 ◽  
Author(s):  
Yonghe Liu ◽  
Zongliang Yang ◽  
Peirong Lin ◽  
Ziyan Zheng ◽  
Shengjin Xie
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Water Budget ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
The Yellow River Basin
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