High spatial resolution simulation of profile soil moisture by assimilating multi-source remote-sensed information into a distributed hydrological model

2021 ◽  
Vol 597 ◽  
pp. 126311
Author(s):  
Han Yang ◽  
Lihua Xiong ◽  
Dedi Liu ◽  
Lei Cheng ◽  
Jie Chen
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Hydrological Model ◽  
High Spatial Resolution ◽  
Distributed Hydrological Model ◽  
Resolution Simulation

scholarly journals An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation

2017 ◽  
Vol 44 ◽  
pp. 89-100 ◽  
Author(s):  
Luca Cenci ◽  
Luca Pulvirenti ◽  
Giorgio Boni ◽  
Marco Chini ◽  
Patrick Matgen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Hydrological Model ◽  
High Spatial Resolution ◽  
Flash Flood ◽  
Soil Moisture Data ◽  
Time Period ◽  
The Impact

Abstract. The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM–DA in recent years (e.g. the Advanced SCATterometer – ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM–DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014–February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM–DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM–DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM–DA framework for flash flood risk mitigation.

scholarly journals A new approach to accurate validation of remote sensing retrieval of evapotranspiration based on data fusion

2010 ◽  
Vol 7 (2) ◽  
pp. 1745-1784 ◽  
Author(s):  
C. Sun ◽  
D. Jiang ◽  
J. Wang ◽  
Y. Zhu
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Spatial Resolution ◽  
Hydrological Model ◽  
Assessment Tool ◽  
High Spatial Resolution ◽  
Meteorological Data ◽  
New Method ◽  
Distributed Hydrological Model ◽  
New Approach

Abstract. The study presented a new method of validating the remote-sensing (RS) retrieval of evapotranspiration (ET) under the support of a distributed hydrological model: Soil and Water Assessment Tool (SWAT). In this method, the output runoff data based on a fusion of ET data, meteorological data and rainfall data, etc. were compared with the observed runoff data, so as to carry out validation analysis. A new pattern of validating the ET data obtained from RS retrieval, which was more appropriate than the conventional means of observing the ET at several limited stations based on eddy covariance, was proposed. It has integrated the advantage of high requirement of ET with high spatial resolution in the distributed hydrological model and that of the capacity of providing ET with high spatial resolution in RS methods. First, the ET data in five years (2000–2004) were retrieved with RS according to the principle of energy balance. The temporal/spatial ditribution of monthly ET data and related causes were analyzed in the year of 2000, and the monthly ET in the five years was calculated according to the PM model. Subsequently, the results of the RS retrieval of ET and the PM-based ET calculation were compared and validated. Finnaly, the ET data obtained from RS retrieval was evaluated with the new method, under the support of SWAT, meteorologic data, Digital Elevation Model (DEM), landuse data and soil data, etc. as the input, being compared with the PM-based ET. According to the ET data analysis, it can be inferred that the ET obtained from RS retrieval was more continuous and stable with less saltation, while the PM-based ET presented saltation, especially in the year of 2000 and 2001. The correlation coefficient between the monthly ET in two methods reaches 0.8914, which could be explained by the influence from clouds and the inadequate representativeness of the meteorologic stations. Moreover, the PM-based ET was smaller than the ET obtained from RS retrieval, which was in accordance with previous studies (Jamieson, 1982; Dugas and Ainsworth, 1985; Benson et al., 1992; Pereira and Nova, 1992). After the data fusion, the correlation (R2=0.8516) between the monthly runoff obtained from the simulation based on ET retrieval and the observed data was higher than that (R2=0.8411) between the data obtained from the PM-based ET simulation and the observed data. As for the RMSE, the result (RMSE=26.0860) between the simulated runoff based on ET retrieval and the observed data was also superior to the result (RMSE=35.71904) between the simulated runoff obtained with PM-based ET and the observed data. As for the MBE parameter, the result (MBE=−8.6578) for the RS retrieval method was obviously better than that (MBE=−22.7313) for the PM-based method. The comparison of them showed that the RS retrieval had better adaptivity and higher accuracy than the PM-based method, and the new approach based on data fusion and the distributed hydrological model was feasible, reliable and worth being studied further.

Generation of spatially complete and daily continuous surface soil moisture of high spatial resolution

2019 ◽  
Vol 233 ◽  
pp. 111364 ◽  
Author(s):  
Di Long ◽  
Liangliang Bai ◽  
La Yan ◽  
Caijin Zhang ◽  
Wenting Yang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Surface Soil ◽  
High Spatial Resolution ◽  
Surface Soil Moisture ◽  
Continuous Surface

A new numerical model for simulating top surface soil moisture and runoff

2018 ◽  
Vol 35 (3) ◽  
pp. 1344-1363 ◽  
Author(s):  
Jiongfeng Chen ◽  
Wan-chang Zhang
Keyword(s):  
Soil Moisture ◽  
Stream Flow ◽  
Hydrological Model ◽  
Surface Soil ◽  
Flow Simulation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Surface Soil Moisture ◽  
Content Type ◽  
Simulation Results

PurposeThis paper aims to construct a simplified distributed hydrological model based on the surveyed watershed soil properties database.Design/methodology/approachThe new established model requires fewer parameters to be adjusted than needed by former hydrological models. However, the achieved stream-flow simulation results are similar and comparable to the classic hydrological models, such as the Xinanjiang model and the TOPMODEL.FindingsGood results show that the discharge and the top surface soil moisture can be simultaneously simulated, and that is the exclusive character of this new model. The stream-flow simulation results from two moderate hydrological watershed models show that the daily stream-flow simulation achieved the classic hydrological results shown in the TOPMODEL and Xinanjiang model. The soil moisture validation results show that the modeled watershed scale surface soil moisture has general agreement with the obtained measurements, with a root-mean-square error (RMSE) value of 0.04 (m3/m3) for one of the one-measurement sites and an averaged RMSE of 0.08 (m3/m3) over all measurements.Originality/valueIn this paper, a new simplified distributed hydrological model was constructed.

Sign in / Sign up

Export Citation Format

Share Document