scholarly journals Suitability of Satellite-Based Precipitation Products for Water Balance Simulations Using Multiple Observations in a Humid Catchment

2019 ◽  
Vol 11 (2) ◽  
pp. 151 ◽  
Author(s):  
Dan Zhang ◽  
Xiaomang Liu ◽  
Peng Bai ◽  
Xiang-Hu Li
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Balance ◽  
Spatial Patterns ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Multiple Observations ◽  
Humid Region ◽  
Regional Water

This study assesses the suitability of five popular satellite-based precipitation products in modeling water balance in a humid region of China during the period 1998–2012. The satellite-based precipitation products show similar spatial patterns with varying degrees of overestimation or underestimation, compared with the gauged precipitation. A distributed hydrological model is used to evaluate the suitability of satellite-based precipitation products in simulating streamflow, evapotranspiration and soil moisture. The simulations of streamflow and evapotranspiration forced by the MSWEP precipitation perform best among the five satellite-based precipitation products, where the Kling-Gupta efficiency (KGE) between the simulated and observed streamflow ranges from 0.75 to 0.91, and the KGE between the simulated and observed evapotranspiration ranges from 0.46 to 0.61. However, the KGE between the simulated and observed soil moisture is negative, indicating that the performance of soil moisture simulation forced by satellite-based precipitation is poor. In addition, this study finds the spatial pattern of simulated streamflow is dominated by the distribution of precipitation, whereas the distribution of evapotranspiration and soil moisture is controlled by the parameters of the hydrological model. This study is useful for the improvement of hydrological modeling based on remote sensing and the monitoring of regional water resources.

scholarly journals Spatial pattern evaluation of a calibrated national hydrological model – a remote sensing based diagnostic approach

2017 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Remote Sensing Data ◽  
Driving Mechanism ◽  
Distributed Hydrological Model ◽  
Eof Analysis ◽  
Sensing Data ◽  
Spatio Temporal

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two source energy balance model (TSEB) driven mainly by satellite remote sensing data. The main hypothesis of the study is that while both approaches are essentially estimates, the spatial patterns of the remote sensing based approach are explicitly driven by observed land surface temperature and therefore represent the most direct spatial pattern information of ET; enabling its use for distributed hydrological model evaluation. Ideally the hydrological model simulation and remote sensing based approach should present similar spatial patterns and driving mechanism of ET. However, the spatial comparison showed that the differences are significant and indicating insufficient spatial pattern performance of the hydrological model. The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in 6 domains that are calibrated independently from each other, as it is often the case for large scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of Leaf Area Index (LAI), root depth (RD) and Crop coefficient (Kc) for each land cover type. This zonal approach of model parametrization ignores the spatio-temporal complexity of the natural system. To overcome this limitation, the study features a modified version of the DK-Model in which LAI, RD, and KC are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatio-temporal variability and spatial consistency between the 6 domains. The effects of these changes are analyzed by using the empirical orthogonal functions (EOF) analysis to evaluate spatial patterns. The EOF-analysis shows that including remote sensing derived LAI, RD and KC in the distributed hydrological model adds spatial features found in the spatial pattern of remote sensing based ET.

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.

Calibration of a semi-distributed hydrological model adding constrains from remotely sensed snow cover and soil moisture products

2020 ◽  
Author(s):  
Rui Tong ◽  
Juraj Parajka ◽  
Jürgen Komma ◽  
Günter Blöschl
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Snow Melt ◽  
Distributed Hydrological Model ◽  
Calibration Methods ◽  
Discharge Simulation ◽  
Normalized Difference Snow Index ◽  
Discharge Modeling

<p>Remote sensing products have been widely applied in hydrological modeling for more realistic representations of hydrological processes. In this study, in addition to gauged discharge, the combined MODIS snow cover maps and ERS scatterometer based soil moisture products were added to constrain a semi-distributed conceptual hydrological model. The latest version of MODIS snow cover images provides a daily Normalized Difference Snow Index (NDSI) in a 500-meter resolution. We derived the snow cover maps by using a new NDSI thresholding method from the MODIS Aqua (MYD10A1) and Terra (MOD10A1) daily snow cover products. Furthermore, the newest ERS soil moisture product also provided a finer spatial resolution of 500-meter over Austria. The semi-distributed TUW-model was tested in 213 catchments using both single and multiple object calibration methods. We found that the semi-distributed TUW-model performed well in discharge modeling. Moreover, applying the MODIS snow cover maps improved the accuracy in the snow-melt season, while the soil moisture product helped the discharge simulation in the no-snow period.</p>

scholarly journals DRYP 1.0: a parsimonious hydrological model of DRYland Partitioning of the water balance

2021 ◽  
Vol 14 (11) ◽  
pp. 6893-6917
Author(s):  
E. Andrés Quichimbo ◽  
Michael Bliss Singer ◽  
Katerina Michaelides ◽  
Daniel E. J. Hobley ◽  
Rafael Rosolem ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Groundwater Recharge ◽  
Overland Flow ◽  
Hydrological Model ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Transmission Losses ◽  
Total Transmission ◽  
Groundwater Aquifer

Abstract. Dryland regions are characterised by water scarcity and are facing major challenges under climate change. One difficulty is anticipating how rainfall will be partitioned into evaporative losses, groundwater, soil moisture, and runoff (the water balance) in the future, which has important implications for water resources and dryland ecosystems. However, in order to effectively estimate the water balance, hydrological models in drylands need to capture the key processes at the appropriate spatio-temporal scales. These include spatially restricted and temporally brief rainfall, high evaporation rates, transmission losses, and focused groundwater recharge. Lack of available input and evaluation data and the high computational costs of explicit representation of ephemeral surface–groundwater interactions restrict the usefulness of most hydrological models in these environments. Therefore, here we have developed a parsimonious distributed hydrological model for DRYland Partitioning (DRYP). The DRYP model incorporates the key processes of water partitioning in dryland regions with limited data requirements, and we tested it in the data-rich Walnut Gulch Experimental Watershed against measurements of streamflow, soil moisture, and evapotranspiration. Overall, DRYP showed skill in quantifying the main components of the dryland water balance including monthly observations of streamflow (Nash–Sutcliffe efficiency, NSE, ∼ 0.7), evapotranspiration (NSE > 0.6), and soil moisture (NSE ∼ 0.7). The model showed that evapotranspiration consumes > 90 % of the total precipitation input to the catchment and that < 1 % leaves the catchment as streamflow. Greater than 90 % of the overland flow generated in the catchment is lost through ephemeral channels as transmission losses. However, only ∼ 35 % of the total transmission losses percolate to the groundwater aquifer as focused groundwater recharge, whereas the rest is lost to the atmosphere as riparian evapotranspiration. Overall, DRYP is a modular, versatile, and parsimonious Python-based model which can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland regions.

scholarly journals Integration of Remote Sensing Evapotranspiration into Multi-Objective Calibration of Distributed Hydrology–Soil–Vegetation Model (DHSVM) in a Humid Region of China

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1841 ◽  
Author(s):  
Suli Pan ◽  
Li Liu ◽  
Zhixu Bai ◽  
Yue-Ping Xu
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithm ◽  
Hydrological Model ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Vegetation Model ◽  
Multi Objective ◽  
Humid Region ◽  
Linux Cluster ◽  
Single Objective

This study presents an approach that integrates remote sensing evapotranspiration into multi-objective calibration (i.e., runoff and evapotranspiration) of a fully distributed hydrological model, namely a distributed hydrology–soil–vegetation model (DHSVM). Because of the lack of a calibration module in the DHSVM, a multi-objective calibration module using ε-dominance non-dominated sorted genetic algorithm II (ε-NSGAII) and based on parallel computing of a Linux cluster for the DHSVM (εP-DHSVM) is developed. The module with DHSVM is applied to a humid river basin located in the mid-west of Zhejiang Province, east China. The results show that runoff is simulated well in single objective calibration, whereas evapotranspiration is not. By considering more variables in multi-objective calibration, DHSVM provides more reasonable simulation for both runoff (NS: 0.74% and PBIAS: 10.5%) and evapotranspiration (NS: 0.76% and PBIAS: 8.6%) and great reduction of equifinality, which illustrates the effect of remote sensing evapotranspiration integration in the calibration of hydrological models.

scholarly journals Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

2021 ◽  
Vol 13 (5) ◽  
pp. 853
Author(s):  
Mohsen Soltani ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Principal Component ◽  
Small Scale ◽  
Dependence Structure ◽  
Test Case ◽  
Catchment Scale ◽  
Balance Approach

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

scholarly journals Diagnostic calibration of a hydrological model in an alpine area

2014 ◽  
Vol 11 (1) ◽  
pp. 1253-1300 ◽  
Author(s):  
Z. He ◽  
F. Tian ◽  
H. C. Hu ◽  
H. V. Gupta ◽  
H. P. Hu
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Generation Mechanism ◽  
Spatiotemporal Variability ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Alpine Area ◽  
Long Time ◽  
Tailan River Basin

Abstract. Hydrological modeling depends on single- or multiple-objective strategies for parameter calibration using long time sequences of observed streamflow. Here, we demonstrate a diagnostic approach to the calibration of a hydrological model of an alpine area in which we partition the hydrograph based on the dominant runoff generation mechanism (groundwater baseflow, glacier melt, snowmelt, and direct runoff). The partitioning reflects the spatiotemporal variability in snowpack, glaciers, and temperature. Model parameters are grouped by runoff generation mechanism, and each group is calibrated separately via a stepwise approach. This strategy helps to reduce the problem of equifinality and, hence, model uncertainty. We demonstrate the method for the Tailan River basin (1324 km2) in the Tianshan Mountains of China with the help of a semi-distributed hydrological model (THREW).

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