scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

scholarly journals Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 594 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Monthly Runoff

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.

scholarly journals Development of load duration curve system in data-scarce watersheds based on a distributed hydrological model

2019 ◽  
Vol 50 (3) ◽  
pp. 886-900
Author(s):  
Jia Wang ◽  
Xin-hua Zhang ◽  
Chong-Yu Xu ◽  
Hao Wang ◽  
Xiao-hui Lei ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
River Basins ◽  
Point Sources ◽  
Guizhou Province ◽  
Polluted Water ◽  
Distributed Hydrological Model ◽  
Load Duration ◽  
Load Duration Curve

AbstractMany developing countries and regions are currently facing serious water environmental problems, especially the lack of monitoring systems for medium- to small-sized watersheds. The load duration curve (LDC) is an effective method to identify polluted waterbodies and clarify the point sources or non-point sources of pollutants. However, it is a large challenge to establish the LDC in small river basins due to the lack of available observed runoff data. In addition, the LDC cannot yet spatially trace the specific sources of the pollutants. To overcome the limitations of LDC, this study develops a LDC based on a distributed hydrological model of the Soil and Water Assessment Tool (SWAT). First, the SWAT model is used to generate the runoff data. Then, for the control and management of over-loaded polluted water, the spatial distribution and transportation of original sources of point and non-point pollutants are ascertained with the aid of the SWAT model. The development procedures of LDC proposed in this study are applied to the Jian-jiang River basin, a tributary of the Yangtze River, in Duyun city of Guizhou province. The results indicate the effectiveness of the method, which is applicable for water environmental management in data-scarce river basins.

scholarly journals Performance of HEC-HMS and SWAT to simulate streamflow in the sub-humid tropical Hemavathi catchment

2021 ◽  
Author(s):  
N. C. Sanjay Shekar ◽  
D. C. Vinay
Keyword(s):  
Model Calibration ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Curve Number ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Daily Streamflow ◽  
Compensation Factor ◽  
Elevation Model

Abstract The present study was conducted to examine the accuracy and applicability of the hydrological models Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center (HEC)- Hydrologic Modeling System (HMS) to simulate streamflows. Models combined with the ArcGIS interface have been used for hydrological study in the humid tropical Hemavathi catchment (5,427 square kilometer). The critical focus of the streamflow analysis was to determine the efficiency of the models when the models were calibrated and optimized using observed flows in the simulation of streamflows. Daily weather gauge stations data were used as inputs for the models from 2014–2020 period. Other data inputs required to run the models included land use/land cover (LU/LC) classes resulting from remote sensing satellite imagery, soil map and digital elevation model (DEM). For evaluating the model performance and calibration, daily stream discharge from the catchment outlet data were used. For the SWAT model calibration, available water holding capacity by soil (SOL_AWC), curve number (CN) and soil evaporation compensation factor (ESCO) are identified as the sensitive parameters. Initial abstraction (Ia) and lag time (Tlag) are the significant parameters identified for the HEC-HMS model calibration. The models were subsequently adjusted by autocalibration for 2014–2017 to minimize the variations in simulated and observed streamflow values at the catchment outlet (Akkihebbal). The hydrological models were validated for the 2018–2020 period by using the calibrated models. For evaluating the simulating daily streamflows during calibration and validation phases, performances of the models were conducted by using the Nash-Sutcliffe model efficiency (NSE) and coefficient of determination (R2). The SWAT model yielded high R2 and NSE values of 0.85 and 0.82 for daily streamflow comparisons for the catchment outlet at the validation time, suggesting that the SWAT model showed relatively good results than the HEC-HMS model. Also, under modified LU/LC and ungauged streamflow conditions, the calibrated models can be later used to simulate streamflows for future predictions. Overall, the SWAT model seems to have done well in streamflow analysis capably for hydrological studies.

scholarly journals A Flexible Framework HydroInformatic Modeling System—HIMS

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 962 ◽  
Author(s):  
Lili Wang ◽  
Zhonggen Wang ◽  
Changming Liu ◽  
Peng Bai ◽  
Xiaocong Liu
Keyword(s):  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Arid Areas ◽  
Hydrological Models ◽  
Runoff Generation ◽  
Infiltration Capacity ◽  
Water Cycling ◽  
Generation Mechanisms ◽  
Semi Arid

It is important to simulate streamflow with hydrological models suitable for the particular study areas, as the hydrological characteristics of water cycling processes are distinctively different due to spatial heterogeneity at the watershed scale. However, most existing hydrological models cannot be customized to simulate water cycling processes of different areas due to their fixed structures and modes. This study developed a HydroInformatic Modeling System (HIMS) model with a flexible structure which had multiple equations available to describe each of the key hydrological processes. The performance of the HIMS model was evaluated with the recommended structure for semi-arid areas by comparisons with two datasets of observed streamflow: the first one of 53 Australian watersheds, the second one of the Lhasa River basin in China. Based on the first dataset, the most appropriate watersheds were identified for the HIMS model utilization with areas of 400–600 km2 and annual precipitation of 800–1200 mm. Based on the second dataset, the model performance was statistically satisfied with Nash-Sutcliffe Efficient (NSE) greater than 0.87 and Water Error (WE) within ±20% on the streamflow simulation at hourly, daily, and monthly time steps. In addition, the water balance was mostly closed with respect to precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change at the annual time steps in both the periods of calibration and validation. Therefore, the HIMS model was reliable in estimating streamflow and simulating the water cycling processes for the structure of semi-arid areas. The simulated streamflow of HIMS was compared with those of the Variable Infiltration Capacity model (VIC) and Soil and Water Assessment Tool (SWAT) models and we found that the HIMS model performed better than the SWAT model, and had similar results to the VIC model with combined runoff generation mechanisms.

scholarly journals Exploring the application of flood scaling property in hydrological model calibration

2021 ◽  
Author(s):  
Yanchen Zheng ◽  
Jianzhu Li ◽  
Ting Zhang ◽  
Youtong Rong ◽  
Ping Feng
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Flood Frequency ◽  
Efficiency Coefficient ◽  
Distributed Hydrological Model ◽  
Flood Peak ◽  
Scaling Property ◽  
Streamflow Data

Abstract Model calibration has always been one major challenge in hydrological community. Flood scaling property (FS) is often used to estimate the flood quantiles for data-scarce catchments based on the statistical relationship between flood peak and contributing areas. This paper investigates the potential of applying FS and multivariate flood scaling property (MLR) as constraints in model calibration. Based on the assumption that the scaling property of flood exists in four study catchments in Northern China, eight calibration scenarios are designed with adopting different combination of traditional indicators and FS or MLR as objective functions. The performance of the proposed method is verified by employing a distributed hydrological model, namely Soil and Water Assessment Tool (SWAT) model. The results indicate that reasonable performance could be obtained in FS with less requirements of observed streamflow data, exhibiting better simulation on flood peak than Nash-Sutcliffe efficiency coefficient calibration scenario. The observed streamflow data or regional flood information are required in MLR calibration scenario to identify the dominant catchment descriptors, and MLR achieve better performance on catchment interior points, especially for the events with uneven distribution of rainfall. On account of the improved performance on hydrographs and flood frequency curve at watershed outlet, adopting the statistical indicators and flood scaling property simultaneously as model constraints is suggested. The proposed methodology enhances the physical connection of flood peak among sub-basins and considers watershed actual conditions and climatic characteristics for each flood event, facilitating a new calibration approach for both gauged catchments and data-scarce catchments.

scholarly journals Calibration of a Distributed Hydrological Model in a Data-Scarce Basin Based on GLEAM Datasets

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 897 ◽  
Author(s):  
Xin Jin ◽  
Yanxiang Jin
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Great Effort ◽  
Observation Data ◽  
Hydrological Models

The calibration of hydrological models is often complex in regions with scarce data, and generally only uses site-based streamflow data. However, this approach will yield highly generalised values for all model parameters and hydrological processes. It is therefore necessary to obtain more spatially heterogeneous observation data (e.g., satellite-based evapotranspiration (ET)) to calibrate such hydrological models. Here, soil and water assessment tool (SWAT) models were built to evaluate the advantages of using ET data derived from the Global Land surface Evaporation Amsterdam Methodology (GLEAM) to calibrate the models for the Bayinhe River basin in northwest China, which is a typical data-scarce basin. The result revealed the following: (1) A great effort was required to calibrate the SWAT models for the study area to obtain an improved model performance. (2) The SWAT model performance for simulating the streamflow and water balance was reliable when calibrated with streamflow only, but this method of calibration grouped the hydrological processes together and caused an equifinality issue. (3) The combination of the streamflow and GLEAM-based ET data for calibrating the SWAT model improved the model performance for simulating the streamflow and water balance. However, the equifinality issue remained at the hydrologic response unit (HRU) level.

scholarly journals Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran

2018 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Monthly Runoff

Hydrological models have been widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are nowadays available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, firstly soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall, SM2R-AMSRE, at different sites in the Karkheh river basin (KRB), southwest Iran. Secondly, the SWAT (Soil and Water Assessment Tool) hydrological model is applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall, due to soil moisture saturation, not accounted for in the SM2RAIN equation. The subsequent SM2R-AMSRE- SWAT- simulated monthly runoff reproduces well the observations at the 6 gauging stations (with coefficient of determination, R&sup2; &gt; 0.72), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation than the SWAT model with ground-based rainfall input. Furthermore, rainfall estimations of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model. The monthly runoff obtained with 3B42- rainfall have 0.39&lt; R2 &lt; 0.70 and are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SM2R-AMSRE- SWAT- simulated runoff above. Therefore, in spite of the afore-mentioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT, appears to be a viable approach in basins with limited ground-based rainfall data.

scholarly journals Uncertainty analysis of a spatially-distributed hydrological model with rainfall multipliers

2016 ◽  
Vol 43 (12) ◽  
pp. 1062-1074 ◽  
Author(s):  
Arpana Rani Datta ◽  
Tirupati Bolisetti
Keyword(s):  
Uncertainty Analysis ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Error Model ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Input Uncertainty ◽  
Spatially Distributed ◽  
Input Error

This paper has developed an input error model to account for input uncertainty, and applied the rainfall multiplier approaches to the calibration and uncertainty analysis of Soil and Water Assessment Tool (SWAT), a spatially-distributed hydrological model. The developed input error model has introduced the season-dependent rainfall multipliers to the Bayesian framework and reduced the dimension of the posterior probability density function. The method is applied to a watershed located in Southwestern Ontario, Canada. The results of the developed method are compared with two other methods. The SWAT model parameters and the input error model parameters are jointly inferred by a Markov chain Monte Carlo sampler. The results show the measured precipitation data overestimates the true precipitation values for the study area. The uncertainty in model prediction is underestimated for high flows and overestimated for low flows. There is no significant change in the estimation of parameter uncertainty and streamflow prediction uncertainty in the developed method from those in the other methods. The study emphasizes that the rainfall multiplier approaches are applicable to spatially-distributed hydrological modelling for accounting of input uncertainty.

scholarly journals Precipitation Forecast Contribution Assessment in the Coupled Meteo-Hydrological Models

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 34 ◽  
Author(s):  
Aida Jabbari ◽  
Jae-Min So ◽  
Deg-Hyo Bae
Keyword(s):  
Lead Time ◽  
Hydrological Model ◽  
Weather Prediction ◽  
Model Performance ◽  
Precipitation Forecast ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Point Scale ◽  
Meteorological Model ◽  
Temporal And Spatial

A numerical weather prediction and a rainfall-runoff model employed to evaluate precipitation and flood forecast for the Imjin River (South and North Korea). The real-time precipitation at point and catchment scales evaluated to select proper hydrological model to couple with atmospheric model. As a major limitation of previous studies, temporal and spatial resolutions of hydrological model are smaller than those of meteorological model. Here, through high resolution of temporal (10 min) and spatial (1 km × 1 km), the optimal resolution determined. The results showed Weather Research and Forecasting (WRF) model underestimated precipitation in point and catchment assessment and its skill was relatively higher for catchment than point scale, as illustrated by the lower Root Mean Square Error (RMSE) of 59.67, 160.48, 68.49 for the catchment and 84.49, 212.80 and 91.53 for the point scale in the events 2002, 2007 and 2011, respectively. The findings led to choose the semi-distributed hydrological model. The variations in temporal and spatial resolutions illustrated accuracy decrease; additionally, the optimal spatial resolution obtained at 8 km and temporal resolution did not affect the inherent inaccuracy of the results. Lead-time variation demonstrated that lead-time dependency was almost negligible below 36 h. With reference to this study, comparisons of model performance provided quantitative knowledge for understanding credibility and restrictions of meteo-hydrological models.

scholarly journals Coupling SWAT Model and CMB Method for Modeling of High-Permeability Bedrock Basins Receiving Interbasin Groundwater Flow

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 657 ◽  
Author(s):  
Javier Senent-Aparicio ◽  
Francisco J. Alcalá ◽  
Sitian Liu ◽  
Patricia Jimeno-Sáez
Keyword(s):  
Groundwater Flow ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
High Permeability ◽  
Groundwater Exploitation ◽  
Calibration And Validation ◽  
Naturally Occurring ◽  
New Formulation

This paper couples the Soil and Water Assessment Tool (SWAT) model and the chloride mass balance (CMB) method to improve the modeling of streamflow in high-permeability bedrock basins receiving interbasin groundwater flow (IGF). IGF refers to the naturally occurring groundwater flow beneath a topographic divide, which indicates that baseflow simulated by standard hydrological models may be substantially less than its actual magnitude. Identification and quantification of IGF is so difficult that most hydrological models use convenient simplifications to ignore it, leaving us with minimal knowledge of strategies to quantify it. The Castril River basin (CRB) was chosen to show this problematic and to propose the CMB method to assess the magnitude of the IGF contribution to baseflow. In this headwater area, which has null groundwater exploitation, the CMB method shows that yearly IGF hardly varies and represents about 51% of mean yearly baseflow. Based on this external IGF appraisal, simulated streamflow was corrected to obtain a reduction in the percent bias of the SWAT model, from 52.29 to 22.40. Corrected simulated streamflow was used during the SWAT model calibration and validation phases. The Nash–Sutcliffe Efficiency (NSE) coefficient and the logarithmic values of NSE (lnNSE) were used for overall SWAT model performance. For calibration and validation, monthly NSE was 0.77 and 0.80, respectively, whereas daily lnNSE was 0.81 and 0.64, respectively. This methodological framework, which includes initial system conceptualization and a new formulation, provides a reproducible way to deal with similar basins, the baseflow component of which is strongly determined by IGF.

Sign in / Sign up

Export Citation Format

Share Document