Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

2016 ◽  
Vol 48 ◽  
pp. 131-145 ◽  
Author(s):  
P. Laiolo ◽  
S. Gabellani ◽  
L. Campo ◽  
F. Silvestro ◽  
F. Delogu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Distributed Hydrological Model

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.

scholarly journals Surface resistance calibration for a hydrological model using evapotranspiration retrieved from remote sensing data in Nahe catchment forest area

2015 ◽  
Vol 368 ◽  
pp. 81-86
Author(s):  
W. Bie ◽  
M. C. Casper ◽  
P. Reiter ◽  
M. Vohland
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Resistance ◽  
Hydrological Model ◽  
Deciduous Forest ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Distributed Hydrological Model ◽  
Forest Regions ◽  
Daily Evapotranspiration

Abstract. In this paper, a method combining graphical and statistical techniques is proposed for surface resistance calibration in a distributed hydrological model, WaSiM-ETH, by comparing daily evapotranspiration simulated by model WaSiM-ETH with corresponding daily evapotranspiration retrieved from remote sensing images. The study area locates in Nahe catchment (Rhineland-Palatinate, Germany, 4065 km2) forest regions. The remote sensing based observations are available for a very limited number of days but representative for most soil moisture conditions. By setting canopy resistance (rc) at 150 s/m, soil surface resistance (rse) at 250 s/m or at 300 s/m for deciduous forest and setting rc at 300 s/m, rse at 600 s/m or at 650 s/m for pine forest, the model exhibits its best overall performance in space and time. It is also found that with sufficient soil moisture, the model exhibits its best performance in space scale.

scholarly journals Impacts of Introducing Remote Sensing Soil Moisture in Calibrating a Distributed Hydrological Model for Streamflow Simulation

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 666 ◽  
Author(s):  
Lihua Xiong ◽  
Ling Zeng
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Objective Function ◽  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Soil Moisture Data ◽  
Streamflow Data ◽  
The Impact ◽  
Hydrological Variables ◽  
Streamflow Simulation

With the increased availability of remote sensing products, more hydrological variables (e.g., soil moisture and evapotranspiration) other than streamflow data are introduced into the calibration procedure of a hydrological model. However, how the incorporation of these hydrological variables influences the calibration results remains unclear. This study aims to analyze the impact of remote sensing soil moisture data in the joint calibration of a distributed hydrological model. The investigation was carried out in Qujiang and Ganjiang catchments in southern China, where the Dem-based Distributed Rainfall-runoff Model (DDRM) was calibrated under different calibration schemes where the streamflow data and the remote sensing soil moisture are assigned to different weights in the objective function. The remote sensing soil moisture data are from the SMAP L3 soil moisture product. The results show that different weights of soil moisture in the objective function can lead to very slight differences in simulation performance of soil moisture and streamflow. Besides, the joint calibration shows no apparent advantages in terms of streamflow simulation over the traditional calibration using streamflow data only. More studies including various remote sensing soil moisture products are necessary to access their effect on the joint calibration.

scholarly journals Assimilation of SMOS soil moisture into a distributed hydrological model and impacts on the water cycle variables over the Ouémé catchment in Benin

2016 ◽  
Vol 20 (7) ◽  
pp. 2827-2840 ◽  
Author(s):  
Delphine J. Leroux ◽  
Thierry Pellarin ◽  
Théo Vischel ◽  
Jean-Martial Cohard ◽  
Tania Gascon ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Water Table ◽  
Hydrological Model ◽  
Water Cycle ◽  
Tropical Rainfall Measuring Mission ◽  
Water Table Depth ◽  
Distributed Hydrological Model ◽  
Model Soil ◽  
Precipitation Estimation

Abstract. Precipitation forcing is usually the main source of uncertainty in hydrology. It is of crucial importance to use accurate forcing in order to obtain a good distribution of the water throughout the basin. For real-time applications, satellite observations allow quasi-real-time precipitation monitoring like the products PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, TRMM (Tropical Rainfall Measuring Mission) or CMORPH (CPC (Climate Prediction Center) MORPHing). However, especially in West Africa, these precipitation satellite products are highly inaccurate and the water amount can vary by a factor of 2. A post-adjusted version of these products exists but is available with a 2 to 3 month delay, which is not suitable for real-time hydrologic applications. The purpose of this work is to show the possible synergy between quasi-real-time satellite precipitation and soil moisture by assimilating the latter into a hydrological model. Soil Moisture Ocean Salinity (SMOS) soil moisture is assimilated into the Distributed Hydrology Soil Vegetation Model (DHSVM) model. By adjusting the soil water content, water table depth and streamflow simulations are much improved compared to real-time precipitation without assimilation: soil moisture bias is decreased even at deeper soil layers, correlation of the water table depth is improved from 0.09–0.70 to 0.82–0.87, and the Nash coefficients of the streamflow go from negative to positive. Overall, the statistics tend to get closer to those from the reanalyzed precipitation. Soil moisture assimilation represents a fair alternative to reanalyzed rainfall products, which can take several months before being available, which could lead to a better management of available water resources and extreme events.

scholarly journals Effect of spatial distribution of daily rainfall on interior catchment response of a distributed hydrological model

2006 ◽  
Vol 3 (4) ◽  
pp. 2175-2208 ◽  
Author(s):  
J. M. Schuurmans ◽  
M. F. P. Bierkens
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Groundwater Level ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Radar Data ◽  
Distributed Hydrological Model ◽  
Average Rainfall ◽  
Hydrological System ◽  
Insight Into

Abstract. We investigate the effect of spatial variability of daily rainfall on soil moisture, groundwater level and discharge using a physically-based, fully-distributed hydrological model. We focus on the effect of rainfall spatial variability on day-to-day variability of the interior catchment response, as well as on its effect on the general hydrological behavior of the catchment. The study is performed in a flat rural catchment (135 km2) in The Netherlands, where climate is semi-humid (average precipitation 800 mm/year, evapotranspiration 550 mm/year) and rainfall is predominantly stratiform. Both range-corrected radar data (resolution 2.5×2.5 km2) as well as data from a dense network of 30 raingauges are used, observed for the period March–October 2004. Eight different rainfall scenarios, either spatially distributed or spatially uniform, are used as input for the hydrological model. The main conclusions from this study are: (i) using a single raingauge as rainfall input carries a great risk for the prediction of discharge, groundwater level and soil moisture, especially if the raingauge is situated outside the catchment; (ii) taking into account the spatial variability of rainfall instead of using areal average rainfall as input for the model is needed to get insight into the day-to-day spatial variability of discharge, groundwater level and soil moisture content; (iii) to get insight into the general behavior of the hydrological system it is sufficient to use correct predictions of areal average rainfall over the catchment.

scholarly journals Incorporating Advanced Scatterometer Surface and Root Zone Soil Moisture Products into the Calibration of a Conceptual Semi-Distributed Hydrological Model

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3366
Author(s):  
Martin Kubáň ◽  
Juraj Parajka ◽  
Rui Tong ◽  
Isabella Pfeil ◽  
Mariette Vreugdenhil ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Forest Cover ◽  
Hydrological Model ◽  
Root Zone ◽  
Retrieval Algorithm ◽  
Multiple Objective ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Alpine Catchments

The role of soil moisture is widely accepted as a significant factor in the mass and energy balance of catchments as a controller in surface and subsurface runoff generation. The paper examines the potential of a new dataset based on advanced scatterometer satellite remote sensing of soil moisture (ASCAT) for multiple objective calibrations of a dual-layer, conceptual, semi-distributed hydrological model. The surface and root zone soil moisture indexes based on ASCAT data were implemented into calibration of the hydrological model. Improvements not only in the instrument specifications, i.e., better temporal and spatial sampling, but also in the higher radiometric accuracy and retrieval algorithm, were applied. The analysis was performed in 209 catchments situated in different physiographic and climate zones of Austria for the period 2007–2018. We validated the model for two validation periods. The results show that multiple objective calibrations have a substantial positive effect on constraining the model parameters. The combined use of soil moisture and discharges in the calibration improved the soil moisture simulation in more than 73% of the catchments, except for the catchments with higher forest cover percentages. Improvements also occurred in the runoff model efficiency, in more than 27% of the catchments, mostly in the watersheds with a lower mean elevation and a higher proportion of farming land use, as well as in the Alpine catchments where the runoff is not significantly influenced by snowmelt and glacier runoff.

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