Jida Wang

Dr. Jida Wang

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Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 May 2023 in Science
Verified
Journal Article
Closed access
FYFangfang Yao
Fangfang Yao
BLBen Livneh
Ben Livneh
BRBalaji Rajagopalan
Balaji Rajagopalan
JWJida Wang
Jida Wang
JCJean-François Crétaux
Jean-François Crétaux
MBMuriel Berge-Nguyen
Muriel Berge-Nguyen
Climate change and human activities increasingly threaten lakes that store 87% of Earth’s liquid surface fresh water. Yet, recent trends and drivers of lake volume change remain largely unknown globally. Here, we analyze the 1972 largest global lakes using three decades of satellite observations, climate data, and hydrologic models, finding statistically significant storage declines for 53% of these water bodies over the period 1992–2020. The net volume loss in natural lakes is largely attributable to climate warming, increasing evaporative demand, and human water consumption, whereas sedimentation dominates storage losses in reservoirs. We estimate that roughly one-quarter of the world’s population resides in a basin of a drying lake, underscoring the necessity of incorporating climate change and sedimentation impacts into sustainable water resources management.

30 November 2018 in Nature Geoscience
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Journal Article
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JWJida Wang
Jida Wang
CSChunqiao Song
Chunqiao Song
JRJohn Reager
John Reager
FYFangfang Yao
Fangfang Yao
JFJames Famiglietti
James Famiglietti
YWYoshihide Wada
Yoshihide Wada

4 January 2024 in Geoscientific Model Development
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Journal Article
Open access
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KFKatja Frieler
Katja Frieler
JVJan Volkholz
Jan Volkholz
SLStefan Lange
Stefan Lange
JSJacob Schewe
Jacob Schewe
MMMatthias Mengel
Matthias Mengel
Michel BechtoldMichel Bechtold
Michel Bechtold
This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

21 April 2022 in Earth System Science Data
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Journal Article
Open access
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JWJida Wang
Jida Wang
BWBlake A. Walter
Blake A. Walter
FYFangfang Yao
Fangfang Yao
CSChunqiao Song
Chunqiao Song
MDMeng Ding
Meng Ding
YWYoshihide Wada
Yoshihide Wada
Dams and reservoirs are among the most widespread human-made infrastructures on Earth. Despite their societal and environmental significance, spatial inventories of dams and reservoirs, even for the large ones, are insufficient. A dilemma of the existing georeferenced dam datasets is the polarized focus on either dam quantity and spatial coverage (e.g., GlObal geOreferenced Database of Dams, GOODD) or detailed attributes for a limited dam quantity or region (e.g., GRanD (Global Reservoir and Dam database) and national inventories). One of the most comprehensive datasets, the World Register of Dams (WRD), maintained by the International Commission on Large Dams (ICOLD), documents nearly 60 000 dams with an extensive suite of attributes. Unfortunately, the WRD records provide no geographic coordinates, limiting the benefits of their attributes for spatially explicit applications. To bridge the gap between attribute accessibility and spatial explicitness, we introduce the Georeferenced global Dams And Reservoirs (GeoDAR) dataset, created by utilizing the Google Maps geocoding application programming interface (API) and multi-source inventories. We release GeoDAR in two successive versions (v1.0 and v1.1) at https://doi.org/10.5281/zenodo.6163413 (Wang et al., 2022). GeoDAR v1.0 holds 22 560 dam points georeferenced from the WRD, whereas v1.1 consists of (a) 24 783 dam points after a harmonization between GeoDAR v1.0 and GRanD v1.3 and (b) 21 515 reservoir polygons retrieved from high-resolution water masks based on a one-to-one relationship between dams and reservoirs. Due to geocoding challenges, GeoDAR spatially resolved ∼ 40 % of the records in the WRD, which, however, comprise over 90 % of the total reservoir area, catchment area, and reservoir storage capacity. GeoDAR does not release the proprietary WRD attributes, but upon individual user requests we may provide assistance in associating GeoDAR spatial features with the WRD attribute information that users have acquired from ICOLD. Despite this limit, GeoDAR, with a dam quantity triple that of GRanD, significantly enhances the spatial details of smaller but more widespread dams and reservoirs and complements other existing global dam inventories. Along with its extended attribute accessibility, GeoDAR is expected to benefit a broad range of applications in hydrologic modeling, water resource management, ecosystem health, and energy planning.

1 October 2019 in Remote Sensing of Environment
Verified
Journal Article
Closed access
FYFangfang Yao
Fangfang Yao
JWJida Wang
Jida Wang
CWChao Wang
Chao Wang
JCJean-François Crétaux
Jean-François Crétaux

27 May 2024 in Nature Geoscience
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Journal Article
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FXFenglin Xu
Fenglin Xu
Guoqing ZhangGuoqing Zhang
Guoqing Zhang
RWR. Iestyn Woolway
R. Iestyn Woolway
KYKun Yang
Kun Yang
YWYoshihide Wada
Yoshihide Wada
JCJean-Francois Cretaux
Jean-Francois Cretaux
Lakes on the Tibetan Plateau are expanding rapidly in response to climate change. The potential impact on the local environment if lake expansion continues remains uncertain. Here we integrate field surveys, remote sensing observations and numerical modelling to assess future changes in lake surface area, water level and water volume. We also assess the ensuing risks to critical infrastructure, human settlements and key ecosystem components. Our results suggest that by 2100, even under a low-emissions scenario, the surface area of endorheic lakes on the Tibetan Plateau will increase by over 50% (~20,000 km2) and water levels will rise by around 10 m relative to 2020. This expansion represents approximately a fourfold increase in water storage compared with the period from the 1970s to 2020. A shift from lake shrinkage to expansion was projected in the southern plateau around 2021. The expansion is primarily fuelled by amplified lake water inputs from increased precipitation and glacier meltwater, profoundly reshaping the hydrological connectivity of the lake basins. In the absence of hazard mitigation measures, lake expansion is projected to submerge critical human infrastructure, including more than 1,000 km of roads, approximately 500 settlements and around 10,000 km2 of ecological components such as grasslands, wetlands and croplands. Our study highlights the urgent need for water hazard mitigation and management across the Tibetan Plateau.