Conference Agenda

The response of glaciers to climate in the high elevation Tibetan Plateau (TP) is highly variable in space and time and strongly influenced by the monsoon, which affects both mass and energy fluxes. The contribution of mixed-phase precipitation events are rarely quantified in melt and mass balance models. Here we use a distributed energy balance model with new schemes for precipitation discrimination and albedo evolution, to understand the effect of dynamic modelling of monsoon precipitation on the summer mass balance of a glacier in the southeast TP. The main effect of modelling mixed-phase precipitation events in a dynamic way is to accumulate more high elevation snow and maintain higher albedo for most of the season. We show that it is challenging to reproduce this effect with traditional approaches based on simple discrimination of solid/liquid precipitation. The glacier-wide mass balance is found to be 1.01 m w.e. (~72%) more negative over one ablation season. This is due to the fact that a static threshold for rain-snow events reduces total snow accumulation and promotes earlier retreat of the snowline altitude during the pre-monsoon season which heightens the dominance of net shortwave energy fluxes for most of the summer.

This paper presents a new water and energy budget-based glacier mass balance model. Enthalpy, rather than temperature, is used in the energy balance equations to simplify the computation of the energy transfers through the water phase change and the movement of liquid water in the snow. A new parameterization for albedo estimation and state-of-the-art parameterization schemes for rainfall/snowfall type identification and surface turbulent heat flux calculations are implemented in the model. This model was driven with meteorological data and evaluated using mass balance and turbulent flux data collected during a field experiment implemented in the ablation zone of the Parlung No. 4 Glacier on the Southeast Tibetan Plateau during 2009 and 2015–2016. The evaluation shows that the model can reproduce the observed glacier ablation depth, surface albedo, surface temperature, sensible heat flux, and latent heat flux with high accuracy. Comparing with a traditional energy budget-based glacier mass balance model, this enthalpy-based model shows a superior capacity in simulation accuracy. Therefore, this model can reasonably simulate the energy budget and mass balance of glacier melting in this region and be used as a component of land surface models and hydrological models.

The effect of monsoon on the mass balance of glaciers in High Mountain Asia, especially of those that are partly or fully covered by debris, has not yet been fully understood. Due to its insulating effect, debris strongly alters energy fluxes reaching the ice, and thus affects the rates and timing of melt. Monsoon conditions, dominated by persistent clouds, lower temperature ranges, high atmospheric water content, lower incoming shortwave radiation and higher receipts of incoming longwave radiation, can result in very distinct surface fluxes and mass balance of glaciers. The energy balance further changes under the presence of water within the debris, which controls conductive and latent heat fluxes, while another flux is added to the balance by rainfall. These effects have rarely been quantified, and to date only for single glaciers. In this study, we investigate how monsoon events influence the summer surface energy balance of debris-covered glaciers along the climatic gradient of High Mountain Asia, where monsoon dominates in the Eastern regions and progressively looses influence when moving westwards towards the Karakoram, where westerlies influence is predominant.

We use for this energy balance models (EB) developed to simulate melt of ice under debris, or debris energy balance (DEB) models, and Automatic Weather Stations (AWS) data. Most DEB models have been developed and tested for glaciers in temperate and arid climates, where the influence of water within the debris plays a less important role and many neglect or treat only simplistically the water content of the debris. We thus also evaluate the transferability of DEB models to monsoonal environments, and test distinct schemes to account for water content in the debris. We validate results against in-situ measurements, and describe how these events influence the summer surface energy balance of debris-covered glaciers. This work is fundamental to the development and optimization of more simplified approaches, such as the Debris-Enhanced Temperature Index (DETI) model, to distributed glacier melt modelling and as a result, to catchment-scale glacio-hydrological modelling.

Heihe River Basin (HRB), regarded as the second largest endorheic river basin in China, originates from the alpine region, flows through the Hexi Corridor, and ends at desert hinterland. The unique and various climatic and landscape types make the basin an ideal testbed for multi-disciplinary research, including hydrology, climatology, geography, ecology and so on. Over the past decades, extensive research was conducted over the basin, and fruitful new findings were obtained consequently. Based on these scientific bases, we have carried out two large-scale remote sensing experiments [1, 2] and Integrated research on the eco-hydrological process of the Heihe River Basin [3]. The main scientific contribution of the Heihe remote sensing experiments and integrated research can be summarized into: 1) a comprehensive watershed observing system was established [4] and a multi-scale dataset for understanding watershed ecohydrological processes was obtained [5], 2) a comprehensive modeling platform was designed and implemented for integrated hydrological simulation [6], and 3) a multivariate land data assimilation system was established [7]. These key progresses have been well documented and reported. Nevertheless, several new points have been observed in recent years, including: 1) developing an integrated watershed system model and closing hydrological cycle at watershed scale, 2) improving data assimilation algorithm and data assimilation system, and 3) developing key water cycle elements estimating algorithms and products. Here we focus on summarizing these recent progresses.

New modeling strategy and model platform for hydrological simulation were proposed. We proposed a new modeling framework to incorporate emerging knowledge into integrated models through data exchange interfaces to comprehensively understand complex watershed systems and to support integrated river basin management [6, 8]. 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 [9]. The water budget was closed for different landscapes, river channel sections, and irrigation districts of the basin from 2001 to 2012.

An updated data assimilation scheme was proposed and parallelized assimilation system was implemented. A 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 [10] was proposed recently, which 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 [11]. 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. [12] 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.

Key retrieval algorithms for hydrological elements have been witnessed progress. For instance, Li et al. [13] 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. [14] 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, ecohydrological research over HRB in terms of the hydrological observation, modeling and data assimilation has been witnessed huge progress. The Chinese Academy of Sciences is performing the Second Tibetan Plateau Scientific Expedition (STEP) Program. The Qilian mountain and other endorheic river basins are the key expedition regions. The scientific findings and practical experiences of HRB should and could provide very useful prior knowledge for the program. Simultaneously, the observing system design scheme, modeling idea and data assimilation systems can be extensively examined, extended and widely applied in a more generic scope.

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 and in some Italian river basin by using MOST, ESA and NASA multi-source satellite data coupled with distributed hydrological models.

In this year presentation, following the scheduled activities, results will be presented for the Chinese Heihe basin and for the Italian Capitanata irrigation district.

For both case studies, the FEST-EWB hydrological model will be used in a synergic way with satellite data. In particular, its 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 the land surface temperature (LST) as retrieved from operational remote sensing data (SENTINEL3, MODIS, LANDSAT) which is used for the calibration of soil and vegetation parameters at pixel scale. Vegetation information (LAI, NDVI, fractional cover) and albedo are obtained from satellite data (SENTINEL2, MODIS, LANDSAT) and used as input parameters to the hydrological model.

For the Heihe river basin, FEST-EWB model is run 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.

Evapotranspiration estimates are then compared at local scale with two eddy covariance data, showing good agreement, and at basin scale with the estimates from the Chinese ETMonitor, and also global reanalysis products MOD16 ET, MERRA2, ERA-INTERIM, GLDAS-2 and GLEAM, reporting a general agreement but with irregularities, due to the different models hypotheses and algorithms.

For the Capitanatairrigation district, the model is run at 30 m of spatial resolution using the SENTINEL2 and LANDSAT images for vegetation input data and LANDSAT data for land surface temperature hydrological model calibration and data assimilation. Good estimates are obtained at basin scale in terms of RET, but also at local scale in terms of evapotranspiration and soil moisture against eddy covariance stations.

The district is an intensive cultivation area, mainly devoted to wheat, tomatoes and fresh vegetables cultivation. Hence, distributed irrigation quantity maps are also estimated from the combined use of satellite data and hydrological modelling.

Hydrological model is a simplification of a real-world system that aids in understanding, predicting, and managing regional water resources. However, it required different kinds of data for model localization and simulation. Microwave remote sensing products could provide space-time continuous data for improvement of hydrological modelling. In this study, two typical monsoon basins, Red River Basin (RRB) with tropical monsoon climate and Luan River Basin(LRB) with temperate monsoon climate, were selected for comparison. By using two long-term driving forcing dataset: The Chinese Meterological Assimulation Driving Dataset for the SWAT model(CMADS) and Global Land Data Assimilation Systems (GLDAS) , as well as GPM IMERG V5B and TRMM precipitation products, we simulated the soil moisture,runoff and crop yields in both basins by using Soil Water Assessment Tool (SWAT) model. The simulated runoff by SWAT model is expected to be fit well with observations; The simulated soil moisture can be validated by local measurements and improved SMOS& SMAP soil moisture products (Stefan et al., 2019). We compared the soil evaporative efficiency by remote sensing and those by SWAT. Then, we simulated crop yields under different irrigation Scenario in the downstream Red River Delta and Luanhe Delta. Our study reveals the usefulness of remote sensing products for water resource simulation in monsoon climate basins.