scholarly journals Irrigation, damming, and streamflow fluctuations of the Yellow River

2021 ◽  
Vol 25 (3) ◽  
pp. 1133-1150
Author(s):  
Zun Yin ◽  
Catherine Ottlé ◽  
Philippe Ciais ◽  
Feng Zhou ◽  
Xuhui Wang ◽  
...  
Keyword(s):  
Human Activities ◽  
Land Surface ◽  
Census Data ◽  
Yellow River ◽  
Land Surface Model ◽  
Anthropogenic Factors ◽  
The Yellow River ◽  
Surface Model ◽  
Monthly Streamflow ◽  
Dam Operation

Abstract. The streamflow of the Yellow River (YR) is strongly affected by human activities like irrigation and dam operation. Many attribution studies have focused on the long-term trends of streamflows, yet the contributions of these anthropogenic factors to streamflow fluctuations have not been well quantified with fully mechanistic models. This study aims to (1) demonstrate whether the mechanistic global land surface model ORCHIDEE (ORganizing Carbon and Hydrology in Dynamic EcosystEms) is able to simulate the streamflows of this complex rivers with human activities using a generic parameterization for human activities and (2) preliminarily quantify the roles of irrigation and dam operation in monthly streamflow fluctuations of the YR from 1982 to 2014 with a newly developed irrigation module and an offline dam operation model. Validations with observed streamflows near the outlet of the YR demonstrated that model performances improved notably with incrementally considering irrigation (mean square error (MSE) decreased by 56.9 %) and dam operation (MSE decreased by another 30.5 %). Irrigation withdrawals were found to substantially reduce the river streamflows by approximately 242.8±27.8×108 m3 yr−1 in line with independent census data (231.4±31.6×108 m3 yr−1). Dam operation does not change the mean streamflows in our model, but it impacts streamflow seasonality, more than the seasonal change of precipitation. By only considering generic operation schemes, our dam model is able to reproduce the water storage changes of the two large reservoirs, LongYangXia and LiuJiaXia (correlation coefficient of ∼ 0.9). Moreover, other commonly neglected factors, such as the large operation contribution from multiple medium/small reservoirs, the dominance of large irrigation districts for streamflows (e.g., the Hetao Plateau), and special management policies during extreme years, are highlighted in this study. Related processes should be integrated into models to better project future YR water resources under climate change and optimize adaption strategies.

scholarly journals Irrigation, damming, and streamflow fluctuations of the Yellow River

2020 ◽  
Author(s):  
Zun Yin ◽  
Catherine Ottlé ◽  
Philippe Ciais ◽  
Feng Zhou ◽  
Xuhui Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Flood Control ◽  
Yellow River ◽  
Dominant Factor ◽  
Anthropogenic Factors ◽  
The Yellow River ◽  
Surface Model ◽  
Operation Rules ◽  
Monthly Streamflow ◽  
Artificial Reservoirs

Abstract. The streamflow of the Yellow River is strongly affected by human activities of irrigation and dam regulation. Many attribution studies focused on the long-term trend of discharge, yet the contributions of these anthropogenic factors to streamflow fluctuations have not been well quantified. This study aims to quantify the roles of irrigation and artificial reservoirs in monthly streamflow fluctuations of the Yellow River from 1982 to 2014 by using the global land surface model ORCHIDEE with a new developed irrigation module, and a separate offline dam operation model. Validation with obsevations demonstrates the ability of our model in simulating the main hydrological processes under human disturbances in the Yellow River basin. Irrigation is found to be the dominant factor leading to 63.7 % reduction of the annual discharges. It might lead to discharge increase in the summer if irrigation is widely applied during a dry spring. After illustrating dam regulation as the primary driver affecting streamflow seasonality, we simulated the changes of water storages in several large artificial reservoirs by a new developed dam model, which does not require any prior knowledge from observations but only implements two simple operation rules based on their inherent regulation capacities: reducing peak flows for flood control and securing base flows during the dry season. Inclusion of dams with this simplified model substantially improved the simulated discharge by at least 42 %. Moreover, simulated water storage changes of the LongYangXia and LiuJiaXia dams coincide well with observations with a high correlation value of about 0.9. We also found that the artificial reservoirs can affect the inter-annual fluctuations of the streamflows, which however was not reproduced faithfully by our dam model due to lack of annual operation rules. From the mismatches between simulations and observations, we inferred the potential impacts of multiple medium reservoirs and five large irrigation districts (e.g., the Hetao Plateau), which were ignored in most previous hydrological studies.

Evaluation of multiple soil moisture products using in-situ observations over China

2021 ◽  
Author(s):  
Huiqing Li ◽  
Aizhong Ye ◽  
Yuhang Zhang ◽  
Wenwu Zhao
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Yellow River ◽  
Eastern China ◽  
Land Surface Model ◽  
Spatial And Temporal Variation ◽  
Surface Model ◽  
Drought Assessment ◽  
In Situ Observations

<p>Soil moisture (SM), a vital variable in the climate system, is applied in many fields. But the existing SM data sets from different sources have great uncertainty, hence need comprehensive verification. In this study, we collected and evaluated ten latest commonly used SM products over China, including four reanalysis data (ERA-Interim, ERA5, NCEP R2 and CFSR/CFSV2), three land surface model products (GLDAS 2.1 Noah, CLSM and VIC) and three remote sensing products (ESA CCI ACTIVE, COMBINED and PASSIVE). These products in their overlap period (2000-2018) were inter-compared in spatial and temporal variation. In addition, their accuracy was verified by a large quantity of in-situ observations. The results show that the ten SM products have roughly similar spatial patterns and small inter-annual differences, but there are still some deviations varying in regions and products. ERA5 displays the most encouraging overall performance in China. The estimates of SM in the northwest of China among all products generally perform poorly on capturing in-situ SM variability due to less coverage of observations. CLSM and ERA5 have a satisfactory correlation coefficient with the observed SM (R>0.7) in the northeast and south of China, respectively. ESA CCI ACTIVE performs with the optimal mean Equitable Threat Score (ETS) value, which indicates the promising ability to drought assessment, followed by CFSR/CFSV2 and ERA5. Specifically, ESA CCI ACTIVE expresses higher ETS in the Yellow River Basin, while CFSR/CFSV2 and ERA5 are more applicable in most areas of the eastern China. This study provides a reasonable reference for the application of SM products in China.</p>

L'apport de la télédétection spatiale à la modélisation des surfaces continentales

2020 ◽  
pp. 052
Author(s):  
Jean-Christophe Calvet ◽  
Jean-Louis Champeaux
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Land Surface Model ◽  
Static Model ◽  
Geographic Information ◽  
Surface Model ◽  
Model Parameters

Cet article présente les différentes étapes des développements réalisés au CNRM des années 1990 à nos jours pour spatialiser à diverses échelles les simulations du modèle Isba des surfaces terrestres. Une attention particulière est portée sur l'intégration, dans le modèle, de données satellitaires permettant de caractériser la végétation. Deux façons complémentaires d'introduire de l'information géographique dans Isba sont présentées : cartographie de paramètres statiques et intégration au fil de l'eau dans le modèle de variables observables depuis l'espace. This paper presents successive steps in developments made at CNRM from the 1990s to the present-day in order to spatialize the simulations of the Isba land surface model at various scales. The focus is on the integration in the model of satellite data informative about vegetation. Two complementary ways to integrate geographic information in Isba are presented: mapping of static model parameters and sequential assimilation of variables observable from space.

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