Conference Agenda

Session
WS#3 ID.32439: MUSYCADHARB Part 1
Time:
Wednesday, 20/Jun/2018:
2:00pm - 3:30pm

Session Chair: Prof. Massimo Menenti
Session Chair: Prof. Xin Li
Workshop: Hydrology & Cryosphere
College of Geomatics - Room 509

Presentations
Oral

Progress in Hydrological Observation, Modeling and Data Assimilation at Watershed Scale

Xin Li, Chunfeng Ma, Xiaoduo Pan, Chunlin Huang

CAREERI,CAS, China, People's Republic of

A watershed, regarded as the best unit for practicing hydrological cycle and water resource research, possesses all of the complexities of the land surface system. Thus, integrating multi-source observations, hydrological modeling into a model-data assimilation framework at watershed scale is the most comprehensive way to understand the complexities of process of hydrological cycle, and is of utmost significance to provide insight into water resource management. This study presents a comprehensive overview on the progress of observation, modeling and data assimilation of watershed scale hydrological cycle. Specifically, several key progresses have been observed at: 1) development of an integrated watershed system model and closure of hydrological cycle at watershed scale, 2) improvement data assimilation algorithm and development data assimilation system, and 3) development of key water cycle elements estimating algorithms and products.

To understand complex watershed systems and to support integrated river basin management, we proposed a new modeling framework to incorporate emerging knowledge into integrated models through data exchange interfaces [1]. The model is expected to represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support and to provide an overarching framework for linking natural and social sciences. Based on the framework of the watershed system model, we analyzed the hydrological cycle in the Heihe River Basin [2]. The water budget was closed for different landscapes, river channel sections, and irrigation districts of the basin from 2001 to 2012.

We proposed soil moisture assimilation scheme that jointly assimilated the brightness temperature of Advanced Microwave Scanning Radiometer-Earth Observing System and Land Surface Temperature products of Moderate Resolution Imaging Spectroradiometer [3]. The data assimilation scheme could correct model bias by simultaneously updating model states and parameters with a dual ensemble Kalman filter. In addition, we developed a physically based hydrological data assimilation system using the gridded and parallelized Soil and Water Assessment Tool distributed hydrological model [4]. The system integrated remotely sensed and ground-based observational data with the Parallel Data Assimilation Framework. The system could accurately characterize watershed hydrological states and fluxes. As to the application of data assimilation to hydrological flux, significant progress has been obtained as well. For instance. Pan et al. [5] assimilated the two satellite precipitation products (The Tropical Rainfall Measuring Mission: TRMM and Fengyun-2D: FY-2D) into the weather research and forecasting model under framework of the 4D-Var data assimilation method in Heihe River Basin. The improved precipitation forecasting has been observed.

Remote sensing retrieval algorithms for key hydrological elements, such as soil moisture, evapotranspiration, have been witnessed progress. For instance, Li et al. [6] estimated continuous daily evapotranspiration at a 90-m spatial resolution using the Surface Energy Balance System (SEBS) by fusing high-temporal resolution Moderate Resolution Imaging Spectroradiometer and high spatial-resolution Advanced Space-borne Thermal Emission Reflectance Radiometer images. Ma et al. [7] proposed a probabilistic inversion algorithm for soil moisture estimation based on Bayes’ theorem and the Markov Chain Monte Carlo technique. They not only obtained highly accurate soil moisture estimation, but also quantified the uncertainties in the inversion algorithm.

Overall, significant progress has been made in the hydrological observation, modeling and data assimilation at watershed scale in recent year. We believe that more fruitful results would be expected in near future under these bases.

References

[1] X. Li, G. Cheng, H. Lin et al., “Watershed system model: the essentials to model complex human‐nature system at the river basin scale,” Journal of Geophysical Research Atmospheres, vol. 123, no. 6, pp. 3019-3034, 2018.

[2] X. Li, G. Cheng, Y. Ge et al., “Hydrological Cycle in the Heihe River Basin and Its Implication for Water Resource Management in Endorheic Basins,” Journal of Geophysical Research Atmospheres, vol. 123, no. 2, pp. 890-914, 2018.

[3] W. Chen, H. Shen, C. Huang et al., “Improving soil moisture estimation with a dual ensemble Kalman smoother by jointly assimilating AMSR-E brightness temperature and MODIS LST,” Remote Sensing, vol. 9, no. 3, pp. 273, 2017.

[4] Y. Zhang, J. Hou, J. Gu et al., “SWAT‐Based Hydrological Data Assimilation System (SWAT‐HDAS): Description and Case Application to River Basin‐Scale Hydrological Predictions,” Journal of Advances in Modeling Earth Systems, vol. 9, no. 8, 2017.

[5] X. D. Pan, X. Li, G. D. Cheng et al., “Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin,” Remote Sensing, vol. 9, no. 9, pp. 963, 2017.

[6] Y. Li, C. Huang, J. Hou et al., “Mapping daily evapotranspiration based on spatiotemporal fusion of ASTER and MODIS images over irrigated agricultural areas in the Heihe River Basin, Northwest China,” Agricultural & Forest Meteorology, vol. 244, pp. 82-97, 2017.

[7] C. Ma, X. Li, C. Notarnicola et al., “Uncertainty Quantification of Soil Moisture Estimations Based on a Bayesian Probabilistic Inversion,” IEEE Transactions on Geoscience & Remote Sensing, vol. 55, no. 6, pp. 3194-3207, 2017.


Oral

Surface Energy Balance of Glaciers and Snow-pack: Albedo, Temperature, Melting and Sublimation

Massimo Menenti1,2,4, Li Jia2,4, Ning Wang2, Yerong Wu1, Lian Liu3, Xinyu Mo2, Shaoting Ren2, Jing Zhang2, Yaoming Ma3, Weiqiang Ma3

1TU Delft, Netherlands, The; 2Remote Sensing and Digital Earth Institute (RADI), China; 3Institute of Tibetan Plateau Research (ITP), China; 4Capital Normal University (CNU), China

The surface energy balance of glaciers and snowpack is the main driver of the mass balance. A detailed analysis of Landsat images of the entire Qinghai – Tibet Plateau over the period 1995 – 2015 has documented a large variability of glacier spectral reflectance and albedo in relation with surface materials. The area of debris-covered glaciers accounted for approximately 20% of the total glacial area, and slightly decreased between 1995 and 2015. The area of glaciers at elevation under 5800 m decreased significantly over 20 years. The number of small glaciers, i.e. < 1 km2, decreased most, while the largest contribution to the reduction in glacial area was due to the larger glaciers, i.e. > 10 km2. To understand how closely glacier melting is related to surface properties, we need to map changes in glacier volume at high spatial resolution. A few satellites acquire stereo – images at high spatial resolution, i.e. ALOS / PRISM and Zi Yuan-3/ TLC, but spatial and temporal coverage is far from satisfactory. We focused on two case – studies on the Zhadang and Parlong nr.4 glaciers, where concurrent ground measurements are available. Preliminary results show that melting rate of glaciers correlates with the albedo and surface temperature. Decrease in glacier thickness over multiple years was clearly related with the mean surface temperature over the same period of time. The quality and spatial resolution of ground measurements of mass balance in the Parlong glaciers gave the opportunity to evaluate the relationship between the mean surface temperature and changes in glacier thickness over the entire glacier. This analysis gave an estimate of the mean surface temperature at which glacier melting starts.

At the same time, glacier surface velocity has been estimated and mapped using high resolution images, i.e. Gao Fen – 1. High spatial resolution maps of surface velocity can be related to maps of albedo and surface temperature and of glacier melt (change in thickness) at comparable spatial resolution.

Atmospheric forcing of the surface energy balance in glacial and snow – covered areas is being characterized using WRF fields generated at multiple spatial resolutions by applying a nested implementation with the inner domain having a 500 m x 500 m grid size. The accuracy of air temperature and wind speed is being evaluated with ground measurements at the Parlong 4 glacier. Radiative interactions of the land surface, particularly the glacial and snow – covered areas, with clouds and aerosols are being evaluated under a new project.


Oral

Recent Advances In The Water Losses Estimation, Water Gain Data Evaluation, And Water Resources Assessment

Li Jia1, Chaolei Zheng1, Guangcheng Hu1, Jing Lu1, Jie Zhou1, Qiting Chen1, Kun Wang1, Massimo Menenti1,2,3

1Institute of Remote Sensing an Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China; 2Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CN Delft, The Netherlands; 3Captical Normal University, Beijing, 100048, China

Quantitative information on water losses is important to understanding the global terrestrial water cycle and land – atmosphere interactions. Following the former study of last year, the ETMonitor estimated global evapotrasnspiration in 2008-2013 with a spatial resolution of 1 km was carefully validated mainly based on ground observation from FLUXNET, spatial variaiton was also cross-compared with other available global evapotranspiration products. The estimated ET agreed well with the in situ observations at site scale, with overall high correlation, low bias, and low root mean square error. Meanwhile, the estimated ET variation could capture the expected overall global ET patterns, and its spatial and temporal patterns were consistent with the current available global ET products such as the upscaled ET dataset from FLUXNET observations and GLEAM ET product, but is superior by high spatial and temporal resolutions. The separation between plant transpiraiton and soil evaporation made by the ETMonitor was also validated based on ground observation based on isotope technique and showed overall good agreement between ETMonitor estimation and isotope observation in partitioning transpiration and evaporation. In details, the ratio of transpiration and evaporation to the total ET generally agreed well with the isotope observation in the growing season in 2012 in one of the ground site of HiWATE experiment, while relative large bias was found in the beginning of the growing season when the soild surface was covered by mulching film.

Precipitation was the major regional water source and precipitaion based indocators were widely adopted in drought monitoring. However, large differene could be found among different earth observation based precipiation products. We evaluated the accuracy of multiple satellite-based precipitation products including the tropical rainfall measuring mission multisatellite precipitation analysis (TMPA) (TMPA 3B42RT and TMPA 3B42 version 7) and the Climate Prediction Center MORPHing technique (CMORPH) (CMORPH RAW and CMORPH BLD version 1.0) datasets and evaluated the impact of the accuracy and temporal coverage of these data products on the reliability of the standardized precipitation index (SPI) estimates for drought monitoring. The satellite-based SPI was compared with the SPI estimate using in situ precipitation observations from 2221 meteorological observation sites across China from 1998 to 2014. The SPI values calculated from the products calibrated with rain gauge measurementswere generally more consistent with the SPI obtained with in situ measurements than those obtained using noncalibrated products. The short data record of satellite precipitation data products was not the primary source of large errors in the SPI estimates, suggesting that the SPI estimate using satellite precipitation data products can be applied to drought assessment and monitoring. The satellite-based SPI can capture typical drought events throughout China, with the limitation that it is based on precipitation only and that different durations of antecedent precipitation are only suitable for specific drought conditions.

The water reource of different basins in China was also obstaind based on ETMonitor estimated ET combing with CMORPH precipitation data. ETMonitor was applied to obtaind regional ET dataset in China and southeast Asia in 2001 -2015 focusing on the key study region, the estimation adopted the ESA-CCI (European Space Agency - Climate Change Initiative) soil moisture data product as one of the inputs. The estimated ET agreed well with flux tower based observations from AsiaFLUX and the estimated ET from water balance method in basin scale. The obtained precipitaiton - ET showed strong correlation with the statistical data of differnet basins from Chinese Water Resource Department, while relative large disagreement mainly occurred at the region with large ground water consumption. Both precipitation and ET presented increasing trends in China, and it generally resulted in a non-significant increasing of available water resource in China. It may benefit the overall water resource supply nowadays, however increasing wate shortage were aslo found in the major grain producing regions and dense population regions. The results were partly contributed to the National Remote Sensing Monitoring for Sustainable Devepoment Report in China (2017).


Oral

Evapotranspiration Estimation based on Open Access Satellite Datasets

Chaolei Zheng1, Li Jia1, Guangcheng Hu1, Jing Lu1, Jie Zhou1, Qiting Chen1, Kun Wang1, Massimo Menenti1,2,3

1Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China; 2Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CN Delft, The Netherlands; 3Captical Normal University, Beijing, 100048, China

Evapotranspiration (ET) is a key terrestrial water cycle at the land-atmosphere interface, and the earth observation are expected to provide spatially and temporally continuous information on large scale ET variation. In currenty study, ETMonitor was applied to obtaind regional daily ET dataset in China and southeast Asia in 2001 -2015, and the estimation adopted the ESA-CCI (European Space Agency - Climate Change Initiative) soil moisture data product as one of the key inputs. To validate the estimated ET, in situ flux tower oberservations from AsiaFLUX datasets were first colleted. The quility of colleted latent heat flux at 30min inteval was carefully checked to obtain observed daily ET. Generally, high correlation coefficient was found escept in tropical humidity forest, where relative low correlation coefficient could be found mostly due to the unclear seasonal ET variation, while the low root mean squre error suggest the good agreement between our estimation and the flux tower observation. Meanwhile, the estimated ET was also compared with the water balance method estimated annual ET (ETwb) at basin scale. ETwb of the major basins in mainland of China was estimated as the the precipitation minus the sum of observed runoff and total water storage by GRACE. Their good agreement hilight the good potential of earth observation in basin water source evaluation. Furthermore, the spatial pattern of estimated ET was compared with other ET products, e.g. the MODIS official ET product, Global Land Evaporation Amsterdam Model (GLEAM v3a) ET products, the FLUXNET observations upscaled ET products, Surface Energy Balance System (SEBS) ET products. The estimated ET dataset can represent overall reasonable geographical patterns and seasonality, and it agrees well with other ET products in terms of spatial variation, however with the advantage of either high spatial-temporal resolution or high accuracy.


Oral

Hydrology products and river basins monitoring: Forcing, calibration, validation and data assimilation in basin scale hydrological models using satellite data products

Marco Mancini1, Chiara Corbari1, Nicola Paciolla1, Li Jia2, Chaolei Zheng2, Massimo Menenti2

1politenico di milano, Italy; 2RADI - Chinese accademy of Science, China

The main objective of this project is to improve the estimate of water balance under natural and human pressure on the Heihe basin in China by using MOST, ESA and NASA satellite data coupled with three distributed hydrological models (FEST-EWB & SHAW-DBHM, HeiFLOW). This will be achieved simulating evapotranspiration, soil moisture, discharge, SWE and groundwater dynamic at different spatial and temporal scales.

Multi-source remote sensing data, from visible to thermal infrared and microwave, will be used for forcing, calibration, validation and data assimilation of/into basin scale hydrological models. Vegetation parameters, snow coverage, LST and soil water content, lakes extent and water level height, and meteorological forcings will be retrieved.

In this year presentation, FEST-EWB model is run for the whole Heihe River basin at spatial resolution of 0.05° and temporal resolution of 1 hour. Results are provided in terms of hourly evapotranspiration, soil moisture and land surface temperature maps for the 2012.

FEST-EWB model algorithm solves the system of energy and mass balances in terms of a representative equilibrium temperature (RET) that is the land surface temperature that closes the energy balance equation and so governs the fluxes of energy and mass over the basin domain. This equilibrium surface temperature, which is a critical model state variable, is comparable to LST as retrieved from operational remote sensing data (MODIS, LANDSAT) which is used for the calibration of soil and vegetation parameters at pixel scale.

Evapotranspiration estimates are then compared at local scale with two eddy covariance data and at basin scale with the estimates from the ETMonitor model.