Conference Agenda

Overview and details of the sessions and sub-session of this conference. Please select a date or session to show only sub-sessions at that day or location. Please select a single sub-session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in CEST. The current conference time is: 13th Dec 2021, 09:45:05am CET

 
 
Session Overview
Session
Dr4 S.2.5: HYDROLOGY
Time:
Wednesday, 21/July/2021:
8:30am - 9:30am

Session Chair: Prof. Massimo Menenti
Session Chair: Prof. Xiaoling Chen
Workshop: Dragon 4

ID. 32442 EOWAQYWET
ID. 32397 CAL/VAL Mw data
ID. 32439 MUSYCADHARB


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Presentations
8:30am - 8:50am
Accepted
ID: 337 / Dr4 S.2.5: 1
Oral Presentation for Dragon 4
Cryosphere & Hydrology: 32442 - New Earth Observations Tools for Water Resource and Quality Monitoring in Yangtze Wetlands and Lakes (EOWAQYWET)
Solid Earth & Disaster Risk Reduction: 32244 - Earth Observations for Geohazard Monitoring and Risk Assessment

New Earth Observations tools for Water resource and quality monitoring in Yangtze wetlands and lakes

Herve Yesou1, Hongtao Duan2, Juliane Huth3, Yachang Chang4, Steven Loiselle6, Zhenguo Niu5, Julien Briant1, Martin Wikelski4, Yeaqiao Wang7, Shuhua Qi7, Lei Cao8, Claudia Kuenzer3, Jean-François Cretaux9, Xijun Lai2, Xiaoling Chen10

1ICUBE SERTIT, Unv. Strasbourg, France; 2NIGLAS, nanjing, Pr China; 3Earth Obs. Center, DLR, Wessling, Germany; 4Max Planck inst., Radolfzell, Germany; 5Radi, Beijing, PR China; 6CSGI, Unv Sienna, Italy; 7PLKL, Nor. Univ. Nanchang, PR China; 8RCEES, CSA, Biejing, PR China; 9LEGO,? Toulouse, France; 10LIESMARS, univ Wuhan, PR China

The United Nations Sustainable Development Goals (SDGs) identify the sustainable management of freshwater as crucial for providing the economic, social and environmental well-being of the present and future generations. Lakes in the intermediate basin of the Yangtze River (YIB), play a fundamental role in regional bio-geochemical cycles and provide major services to the YIB communities including water supply, water purification, flood regulation (SDG 6.1.1 &6.3.2), climate regulation (SDG 13), food (SDG 2), recreational opportunities (SDG 3) and biodiversity (SDG 15). However, the extreme temporal and spatial variability of these massive but extremely shallow ecosystems prevents a reliable quantification of their dynamics with respect to changes in climate and land use.

Over these complex landscapes, a priority task is improving the monitoring and assessment capacity of authorities of these important resources. By exploiting the Sentinel HR constellation, well as Chinese VHR satellites, Dragon researchers developed automated or semi-automated methods to explore spatial and temporal changes to the complex ecosystems of Dongting and Poyang Lakes, as well as more than 80 water bodies in the YIB. Sentinel systematic acquisitions were used to create a dense time series, making analysis more consistent, also to over a year of a prioritised S1 acquisition. Now it is a 20 years monitoring of Poyang lake water surfaces that have been achieved. Water height was also monitored over the intermediate Yangtze basin, and combined with Hydroweb data in 3 lakes, and a dozen of virtual stations on the major rivers. One task consisted in addition to verify that all most sensitive areas would be covered by the OLTC procedure. This Sentinel3 on-board command served as the base to validate the reception window on the a priori elevation of the study lakes.

The phenology of wetland vegetation was shown to link to the dynamics of water level of the lake across the year and have important impacts on the migratory birds. Understanding the relationship between hydrological regimes and the spatial-temporal pattern of wetland vegetation is vital to collaborate the economic development and the protection of the migratory birds in the Poyang Lake, even the low reaches of Yangzi River. It was demonstrated that the White-naped cranes Antigone vipio wintering at Poyang Lake wetlands, southeast of China, mainly used the habitats created by the hydrological variations, i.e. seasonal water level fluctuation. Based on the results of the Dragon project, it was identified that White-naped cranes follow the water level recession process, keeping close to the boundary of water patches at most of the time. Similar approach has been followed also for swan geese and diving ducks.

The second pilar of the project was focused on water quality assessment and monitoring. In the Yangtze area, lakes supply freshwater and ecosystem services to nearly a billion people. Lake transparency, usually denoted by Secchi disk depth (SSD), is responsive to catchment characteristics, regulates many ecosystem features, and serves as a sentinel of water quality. Understanding spatio-temporal variations in water quality allow for the identification of major drivers of change and possible management and mitigation alternatives. Water transparency was retrieved over lakes for 2000-2018 models were developed to explore changes in catchment conditions, climate and human activities. The results showed that hydrological and climate related drivers strong influence water quality in these sensitive but vital lakes. Lake depth plays a mjor role in seasonal variations of sediment resuspension, and therefore transparency in the YIB. Likewise, wind speed and direction also influence lake water quality. During the summer, weak wind speeds and increased precipitation increase lake depth, leading to maximum transparency. Using the monthly climatological data, lakes showed two possible trends, based on the hydrological conditions of the lake. For the three largest lakes, the Dongting, Poyang, and Chaohu, in-situ water levels were higher in summer, limiting resuspension of lake sediments, often with high concentrations of phosphorus and other contaminants.

Dragon 4 results highlights the benefits of interdisciplinary approaches to gain a better understanding of managing complex freshwater ecosystems and ecosystem services. The results of the Dragon studies are being used to improve water resource monitoring and show the potential for collaborative research in Earth Observation.



8:50am - 9:10am
Accepted
ID: 335 / Dr4 S.2.5: 2
Oral Presentation for Dragon 4
Cryosphere & Hydrology: 32397 - Calibration and Validation of Microwave Remote Sensing Data for Water Cycle Research

Calibration and Validation of Microwave Remote Sensing Data for Water Cycle Research

Jiancheng Shi1, Yann Kerr2, Dongkai Yang3, Alain Geiger4, Tianjie Zhao5, Jinmei Pan5, Mutian Han3, Ladina Steiner4, Dabin Ji5, Rui Li5, Michael Meindl4, Panpan Yao5, Yunlong Zhu3, Xuebao Hong3, Tao Chen5, Lu Hu5

1The National Space Science Center, Chinese Academy of Sciences,Beijing, China; 2CESBIO (CNRS/IRD/CNES/UPS), Toulouse, France; 3School of Electronic and Information Engineering, Beihang University,Beijing, China; 4Institute Geodesy and Photogrammetry, ETH, Zurich, Switzerland; 5The Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Soil moisture and snow water monitoring using microwave remote sensing data has gained wide interests in recent years. In order to improve the accuracy of soil moisture and snow water estimations, in the Shandian River and Xiaoluan River basin, multi-resolution, multi-angle and multi-spectral airborne data were obtained. The near surface soil moisture (0 cm ~ 5 cm) ,200 m by 200 m quadrats and two soil moisture and temperature profile and precipitation networks were established. The result shows that the L-band active and passive observations exhibit a large variation of ~30 dB and ~80 K, respectively, corresponding to soil moisture range from 0.1 cm3/cm3 to 0.5 cm3/cm3; In Altay National Reference Meteorological station, L, C, and X, Ku and Ka band radiometers were installed and snow process model was validated. The result shows that the SNTHERM+MEMLS simulated TB showed an RMSE of 2.56 K and 3.3 K, respectively at 18.7 and 36.5 GHz vertical polarization, compared to ground-based radiometer measurements; Based on Global Navigation Satellite System-Interferometry and Reflectometry (GNSS-IR) technique, two methods were proposed to reconstruct the power of the direct and reflected signal. Experiment data were used to validate the proposed method, which demonstrated the feasibility of the proposed methods. The results showed that the retrieval error is within ±0.1 cm3/cm3 in most of the cases. Another experiment was carried out to measure the penetration depth of GNSS signal directly. The results showed that the maximum penetration depth under 0.1577 ~ 0.3394 cm3/cm3 soil moisture is less than 21 cm. To determine the snow water content (SWE) a new set-up using refracted signals and path-delay estimation methods were devised, tested and validated. The comparison with state-of-art snow pillow, snow scale, and manual measurements showed an agreement below 5%. It reveals that radiometer, radar observation and GNSS-IR multiple microwave remote sensing technologies have great potentials for global water cycle key components retrievals.

Shi-Calibration and Validation of Microwave Remote Sensing Data-335Oral4.pdf


9:10am - 9:30am
Accepted
ID: 299 / Dr4 S.2.5: 3
Oral Presentation for Dragon 4
Cryosphere & Hydrology: 32439 - Multi-source Hydrological Data Products to Monitor High Asian River Basins and Regional Water Security (MUSYCADHARB)

Multi – source hydrological data products to monitor High Asian River Basins and regional water security

Massimo Menenti1, Xin Li2, Li Jia3, Kun Yang4, Francesca Pellicciotti5, Marco Mancini6, Maria Josè Escorihuela7, Jiancheng Shi8

1Delft University of Technology, 2600 GA Delft, The Netherlands; 2Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China; 3State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China; 4Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 10084, China; 5Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland; 6Politecnico di Milano, Milano 20133, Italy; 7IsardSAT, Barcelona 08001, Spain; 8National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China

The project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia and to clarify the roles of the interactions between the land surface and the atmosphere over the Tibetan Plateau in the Asian monsoon system. Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems.

Energy-budget-based glacier mass balance and hydrological models driven by satellite observations were developed. These models can be applied to describe glacier-melt contribution to river flow. Satellite hydrological data products were used for forcing, calibration, validation and data assimilation in a distributed river basin model. A pilot study was carried out on the Red River basin.

Multiple hydrological data products were generated using the data collected by Chinese satellites. Total Precipitable Water was retrieved with FY-3D/MWRI data, Snow Cover Area with FY-4A and Himawari-8 and Snow Water Equivalent with FY-3B/MWRI data. A data processing chain was developed to produce the Chinese 16 m GF-1 Analysis Ready Data (ARD). These data were used to retrieve land surface reflectance and to map land cover. A global LAI product at 1 km spatial and 5-day temporal resolution was generated with FY3/MERSI data. LAI was retrieved at higher spatial resolution with the GF1/WFV data at 16 m spatial and 10-day temporal resolution. A new ET dataset from 2000 to 2018 was generated, including rainfall interception loss, snow/ice sublimation and open water evaporation. Higher resolution data were used to characterize glaciers and their response to environmental forcing. These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped with GF, S2/MSI and L8/OLI data. The geodetic mass balance was estimated between 2000 and 2017 with ZY-3 Stereo Images and the SRTM DEM. Surface velocity was studied with L5/TM, L8/OLI and S2/MSI data over the period 2013 – 2019. An updated method was developed to improve the retrieval of glacier albedo by correcting glacier reflectance for anisotropy and a new data set on glacier albedo was generated for the period 2001–2020.

A detailed glacier energy and mass balance model was developed with the support of field experiments at the Parlung 4 and the No. 24 Glacier, both in the Tibetan Plateau. Besides meteorological measurements, the field experiments included glaciological and hydrological measurements. The energy balance model was formulated in terms of enthalpy for easier treatment of water phase transitions. The model was applied to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier the accumulated glacier melt during the whole period was between 1.5 m w.e. and 2.5 m w.e. in the accumulation zone and between 4.5 m w.e. and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e. at the terminus. The glacier mass balance over a period of time hides the seasonality in forcing by precipitation and temperature and the gradient in precipitation within the glaciers. These were observed by combining intensive field campaigns with continuous automatic observations.

The linkage of the glacier and snow-pack mass balance with water resources in a river basin was analysed in the Chiese (Italy) and Heihe (China) basins by developing and applying integrated hydrological models using satellite retrievals in multiple ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature (LST) to map soil hydrological properties, i.e. soil hydraulic conductivity, Brooks-Corey index, soil depth, minimum stomatal and soil resistances. A watershed model was developed by coupling ecohydrological and socioeconomic systems. Integrated modelling is supported by an updated and parallelized data assimilation system. The latter exploits retrievals of brightness temperature (AMSR), LST (MODIS), precipitation (TRMM and FY-2D) and in-situ measurements.

In the case-study on the Red River Basin a new algorithm has been applied to disaggregate the SMOS soil moisture retrievals by making use of the correlation between evaporative fraction and soil moisture.

Menenti-Multi – source hydrological data products to monitor High Asian River Basins and regional water s.pdf


 
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