Impacts of water resources management on land water storage in the North China Plain: Insights from multi-mission earth observations

Liu, Jun; Jiang, Liguang; Zhang, Xingxing; Druce, Daniel; Kittel, Cécile Marie Margaretha; Tøttrup, Christian; Bauer‐Gottwein, Peter

doi:10.1016/j.jhydrol.2021.126933

Cited by 23 publications

(4 citation statements)

References 68 publications

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“…As key replenishment areas for the central route, these regions benefit from regular water transfers and ecological replenishments during the flood season each year. These measures not only aid in the recovery of groundwater levels [65,66] but also positively influence surface water and ecological restoration [67]. The figure also illustrates the transformation among different water body types within these regions.…”

Section: Reasons For Spatially Varied Changesmentioning

confidence: 99%

The Divergent Changes in Surface Water Area after the South-to-North Water Diversion Project in China

Guo,

Li,

Xiao

et al. 2024

Remote Sensing

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Water scarcity is a significant challenge in China, and the South-to-North Water Diversion Project (SNWDP) aims to address the water deficit in the northern region. This study analyses Landsat 5/7/8 remote sensing imagery from 2001 to 2020 on the Google Earth Engine (GEE) cloud platform to assess the impact of the SNWDP on surface water bodies in water-receiving areas. Moreover, by integrating MODIS evapotranspiration data and ERA5 meteorological reanalysis data, this study comprehensively assesses the SNWDP’s contribution to varied surface water body changes. Using an improved multi-temporal water frequency method, this study extracts max, seasonal, and year-long water surface areas. The results reveal that Beijing and Henan provinces have experienced significant increases in water surface areas post-SNWDP, with their max water surface area growing at a rate of 10.42 km2/yr and 33.49 km2/year, respectively. However, water surface areas in several provinces, especially those along the east route, were not observed to increase. The spatially detailed Mann–Kendall test indicates that the expansion of year-long water bodies is mostly concentrated near the central route project, revealing spatial heterogeneity in the water replenishment effect. Cropland and impervious surfaces are the main contributors to transfers in and out of water bodies. Meteorological and water use factors for spatial variations in water changes are also identified. These findings provide insights into the varied hydrological consequences of the SNWDP and contribute to the evaluation and management of similar large-scale water diversion projects around the world.

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Section: Reasons For Spatially Varied Changesmentioning

confidence: 99%

The Divergent Changes in Surface Water Area after the South-to-North Water Diversion Project in China

Guo,

Li,

Xiao

et al. 2024

Remote Sensing

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“…The major cause may be that BJ and TJ are the primary cities that receive replenishment from the SNWTP [50]. Critical drought occurred in HN, SD and other areas after 2014, resulting in the massive exploitation of groundwater, which led to a serious decline in groundwater storage [50,51]. From January 2018 to December 2020, the overall rate of decline of the GWSA within the NCP exhibited a marked deceleration, with a decrease of nearly half.…”

Section: Gws Changes In the Ncp And Five Administrative Regionsmentioning

confidence: 99%

Reconstructing Groundwater Storage Changes in the North China Plain Using a Numerical Model and GRACE Data

Zhang

Sun

et al. 2023

Remote Sensing

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Groundwater has been extensively exploited in the North China Plain (NCP) since the 1970s, leading to various environmental issues. Numerous studies have utilized Gravity Recovery and Climate Experiment (GRACE) satellite data to analyze changes in groundwater storage in the NCP and provide valuable insights. However, the low spatial resolution of GRACE data has posed challenges for its widespread application, and there have been limited studies focusing on refining groundwater storage changes in the NCP. In addition, the lack of data on the gap period between GRACE and GRACE-FO hinders in-depth research on regional groundwater storage anomalies (GWSA). This paper applied a groundwater storage model called NGFLOW-GRACE to construct a groundwater storage change model in the NCP at spatial resolutions of both 1° and 0.05°. The groundwater storage change model was calibrated and driven using gratis data, with hydrogeological parameter values estimated using the shuffled complex evolution algorithm (SCE-UA). The model exhibited favorable performance, with correlation coefficients greater than 0.85 during the calibration period and 55% of coefficients greater than 0.50 during the validation period. Interestingly, the results indicate that different combinations of remote sensing data do not significantly impact the outcomes, while the hydraulic gradient coefficient demonstrates the highest sensitivity. Appropriate reconstructed data were selected within the empty window period, and by downscaling the model to a resolution of 0.05°, a complete cycle (January 2003 to December 2020) of GWSA was derived. Through comprehensive comparisons with previous research findings on both temporal and spatial scales, it can be concluded that the downscaled groundwater storage changes obtained from the established model demonstrated high reliability.

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“…Hydroweb (Crétaux et al, 2011), G-REALM (Global reservoirs and lakes monitor, Birkett et al, 2011), DAHITI (Database for hydrological time series of inland waters, Schwatke et al, 2015), AltEx (Markert et al, 2019), HydroSat (Tourian et al, 2022), Water level On VITO, and several studies (e.g., Gao et al, 2012;Tortini et al, 2020;Shen et al, 2022b) offer time series of altimetry-derived water level for inland waters by incorporating multiple laser or radar altimeters such as Jason-1/2/3, CryoSat-2, Sentinel-3A/B, and ICESat-1/2. Imagery-based water area estimates can be extracted from GSW (Global surface water, Pekel et al, 2016), DAHITI, Hydroweb, HydroSat, Bluedot Observatory, GRSAD (Global reservoir surface area dataset, Zhao & Gao, 2018), RealSAT (Khandelwal et al, 2022), and relevant studies (e.g., Busker et al, 2019;Liu et al, 2021;Donchyts et al, 2022). Storage anomalies are available in DAHITI, HydroSat, and several studies (e.g., Gao et al, 2012;Hou et al, 2022) using water level and area from satellite altimeters and images, and/or from imagery-based water area and the area-storage model constructed by digital elevation model (DEM, Vu et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Res-CN: hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs

Shen

Nielsen

Revel

et al. 2023

Preprint

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Abstract. Dams and reservoirs are human-made infrastructures that have attracted increasing attentions because of their societal and environmental significance. Towards better management and conservation of reservoirs, a dataset of reservoir-catchment characteristics is needed, considering that the amount water and material flowing into and out of reservoirs depends on their locations on the river network and the properties of upstream catchment. To date, no dataset exists for reservoir-catchment characteristics. The aim of this study is to develop the first database featuring reservoir-catchment characteristics for 3254 reservoirs with storage capacity totaling 682,595 km3 (73.2 % reservoir water storage capacity in China), to support the management and conservation of reservoirs in the context of catchment level. To ensure a more representative and accurate mapping of local variables of large reservoirs, reservoir catchments are delineated into full catchments (their full upstream contributing areas) and intermediate catchments (subtracting the area contributed by upstream reservoirs from full upstream of the current reservoir). Using both full catchments and intermediate catchments, characteristics of reservoir catchments were extracted, with a total of 512 attributes in six categories (i.e., reservoir catchment, topography, climate, soil and geology, land cover and use, and anthropogenic activity). Besides these static attributes, time series of 15 meteorological variables of catchments were extracted to support hydrological simulations for a better understanding of drivers of reservoir environment change. Moreover, we provide a comprehensive and extensive reservoir data set on water level (data available for 20 % of 3,254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %) from multisource satellites such as radar and laser altimeters and images from Landsat and Sentinel satellites. These products significantly enhance spatial and temporal coverage in comparison to existing similar products (e.g., 67 % increase in spatial resolution of water level and 225 % increase in storage anomaly) and contribute to our understanding of reservoir properties and functions within the Earth system by incorporated national or global hydrological modeling. In situ data of 138 reservoirs are employed in this study as a valuable reference for evaluation, thus enhancing our confidence in the data quality and enhancing our understanding of accuracy of current satellite datasets. Along with its extensive attributes, the Reservoir dataset in China (Res-CN) can support a broad range of applications such as water resources, hydrologic/hydrodynamic modeling, and energy planning. Res-CN is on Zenodo through https://doi.org/10.5281/zenodo.7390715 (Shen et al., 2022a).

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Impacts of water resources management on land water storage in the North China Plain: Insights from multi-mission earth observations

Cited by 23 publications

References 68 publications

The Divergent Changes in Surface Water Area after the South-to-North Water Diversion Project in China

The Divergent Changes in Surface Water Area after the South-to-North Water Diversion Project in China

Reconstructing Groundwater Storage Changes in the North China Plain Using a Numerical Model and GRACE Data

Res-CN: hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs

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