A Flexible Framework HydroInformatic Modeling System—HIMS

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.

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

Journal of Water and Climate Change ◽

10.2166/wcc.2021.072 ◽

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.

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

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-368-305-2015 ◽

2015 ◽

Vol 368 ◽

pp. 305-311 ◽

Cited By ~ 5

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.

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A collaborated framework to improve hydrologic ecosystem services management with sparse data in a semi-arid basin

Hydrology Research ◽

10.2166/nh.2021.146 ◽

2021 ◽

Author(s):

Yifan Wu ◽

Yang Xu ◽

Guodong Yin ◽

Xuan Zhang ◽

Chong Li ◽

...

Keyword(s):

Ecosystem Services ◽

Assessment Tool ◽

Hydrological Cycle ◽

Swat Model ◽

Water Yield ◽

Infiltration Capacity ◽

Runoff Simulation ◽

Invest Model ◽

Integrated Valuation ◽

Semi Arid

Abstract Applying various models to assess hydrologic ecosystem services (HESs) management has the potential to encourage efficient water resources allocation. However, can a single model designed on these principles be practical to carry out hydrologic ecosystem services management for all purposes? We address this question by fully discussing the advantages of the variable infiltration capacity (VIC) model, the soil and water assessment tool (SWAT), and the integrated valuation of ecosystem services and tradeoffs (InVEST) model. The analysis is carried both qualitatively and quantitatively at the Yixunhe River basin, China, with a semi-arid climate. After integrating the advantages of each model, a collaborated framework and model selection method have been proposed and validated for optimizing the HESs management at the data sparse scenario. Our study also reveals that the VIC and SWAT model presents the better runoff reproducing ability of the hydrological cycle. Though the InVEST model has less accuracy in runoff simulation, the interannual change rate is similar to the other two models. Furthermore, the InVEST model (1.08 billion m3) has larger simulation result than the SWAT model (0.86 billion m3) for the water yield, while both models have close results for sediment losses assessment.

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

Water ◽

10.3390/w12030897 ◽

2020 ◽

Vol 12 (3) ◽

pp. 897 ◽

Cited By ~ 2

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.

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

Water ◽

10.3390/w12030657 ◽

2020 ◽

Vol 12 (3) ◽

pp. 657 ◽

Cited By ~ 4

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.

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

Water ◽

10.3390/w11030594 ◽

2019 ◽

Vol 11 (3) ◽

pp. 594 ◽

Cited By ~ 9

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.

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Model Uncertainty Analysis Methods for Semi-Arid Watersheds with Different Characteristics: A Comparative SWAT Case Study

Water ◽

10.3390/w11061177 ◽

2019 ◽

Vol 11 (6) ◽

pp. 1177 ◽

Cited By ~ 2

Author(s):

Lufang Zhang ◽

Baolin Xue ◽

Yuhui Yan ◽

Guoqiang Wang ◽

Wenchao Sun ◽

...

Keyword(s):

Uncertainty Analysis ◽

River Basin ◽

Model Uncertainty ◽

Assessment Tool ◽

Rapid Development ◽

Swat Model ◽

Observation Data ◽

Hydrological Models ◽

Distributed Hydrological Models ◽

Different Characteristics

Distributed hydrological models play a vital role in water resources management. With the rapid development of distributed hydrological models, research into model uncertainty has become a very important field. When studying traditional hydrological model uncertainty, it is very common to use multisite observation data to evaluate the performance of the model in the same watershed, but there are few studies on uncertainty in watersheds with different characteristics. This study is based on the Soil and Water Assessment Tool (SWAT) model, and uses two common methods: Sequential Uncertainty Fitting Version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis. We compared these methods in terms of parameter uncertainty, model prediction uncertainty, and simulation effects. The Xiaoqing River basin and the Xinxue River basin, which have different characteristics, including watershed geography and scale, were used for the study areas. The results show that the GLUE method had better applicability in the Xiaoqing River basin, and that the SUFI-2 method provided more reasonable and accurate analysis results in the Xinxue River basin; thus, the applicability was higher. The uncertainty analysis method is affected to some extent by the characteristics of the watershed.

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SWAT modeling of hydrology, sediment and nutrients from the Grand River, Ontario

Water Quality Research Journal ◽

10.2166/wqrj.2017.014 ◽

2017 ◽

Vol 52 (4) ◽

pp. 243-257 ◽

Cited By ~ 4

Author(s):

Aslam Hanief ◽

Andrew E. Laursen

Keyword(s):

Best Management Practices ◽

Stream Flow ◽

Lake Erie ◽

Management Practices ◽

Assessment Tool ◽

Swat Model ◽

Model Performance ◽

Nutrient Export ◽

Spatial And Temporal Patterns ◽

Grand River

Abstract The Grand River watershed (GRW) is an important agricultural area in Southern Ontario. Land use has been modified by various human endeavors, altering hydrology and increasing export of sediment and nutrients. The objective of this study was to predict spatial and temporal patterns of hydrology, and export of sediment and nutrients from the GRW to Lake Erie using the Soil and Water Assessment Tool (SWAT) model. The Sequential Uncertainty FItting (SUFI2) program was used to calibrate and validate stream flow for years 2001–2010. Calibration and validation of the SWAT model for monthly stream flow at York indicated good model performance (R2, NSE, and PBIAS = 0.64, 0.63 and 7.1 for calibration (2001–2005); = 0.82, 0.74 and 0.2, for validation (2006–2010)). The model was applied to predict sediment and nutrient export from the GRW into Lake Erie. Predicted loading at Dunnville (near the mouth) was 2.3 × 105 tonnes y−1 total suspended sediment, 7.9 × 103 tonnes y−1 TN, and 2.3 × 102 tonnes y−1 TP. This SWAT model can now be used to investigate the relative effects of best management practices, and to forecast effects of climate change, on sustainable water management, hydrology, and sediment and nutrient export to Lake Erie.

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Hydrological modeling using the SWAT Model in urban and peri-urban environments: The case of Kifissos experimental sub-basin (Athens, Greece)

10.5194/hess-2021-482 ◽

2021 ◽

Author(s):

Evgenia Koltsida ◽

Nikos Mamassis ◽

Andreas Kallioras

Keyword(s):

Surface Runoff ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Model Performance ◽

Curve Number ◽

Urban Environments ◽

Time Intervals ◽

Curve Number Method ◽

Hourly Rainfall

Abstract. SWAT (Soil and Water Assessment Tool) is a continuous time, semi-distributed river basin model that has been widely used to evaluate the effects of alternative management decisions on water resources. This study, demonstrates the application of SWAT model for streamflow simulation in an experimental basin with daily and hourly rainfall observations to investigate the influence of rainfall resolution on model performance. The model was calibrated for 2018 and validated for 2019 using the SUFI-2 algorithm in the SWAT-CUP program. Daily surface runoff was estimated using the Curve Number method and hourly surface runoff was estimated using the Green and Ampt Mein Larson method. A sensitivity analysis conducted in this study showed that the parameters related to groundwater flow were more sensitive for daily time intervals and channel routing parameters were more influential for hourly time intervals. Model performance statistics and graphical techniques indicated that the daily model performed better than the sub-daily model. The Curve Number method produced higher discharge peaks than the Green and Ampt Mein Larson method and estimated better the observed values. Overall, the general agreement between observations and simulations in both models suggests that the SWAT model appears to be a reliable tool to predict discharge over long periods of time.

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Response of the parameters of excess infiltration and excess storage model to land use cover change

Journal of Hydrology and Hydromechanics ◽

10.2478/johh-2020-0006 ◽

2020 ◽

Vol 68 (2) ◽

pp. 99-110 ◽

Cited By ~ 1

Author(s):

Yuexiu Wen ◽

Caihong Hu ◽

Guodong Zhang ◽

Shengqi Jian

Keyword(s):

Land Use ◽

Overland Flow ◽

Yellow River ◽

The Yellow River ◽

Model Parameters ◽

Runoff Generation ◽

The Loess Plateau ◽

Infiltration Capacity ◽

Infiltration Excess ◽

Generation Mechanisms

AbstractThe Loess Plateau is the main source of water in Yellow River, China. After 1980s, the Yellow river water presented a significant reduction, what caused the decrease of the Yellow river discharge had been debated in academic circles. We proceeded with runoff generation mechanisms to explain this phenomenon. We built saturation excess runoff and infiltration excess runoff generation mechanisms for rainfall–runoff simulation in Jingle sub-basin of Fen River basin on the Loess Plateau, to reveal the influence of land use change on flood processes and studied the changes of model parameters under different underlying conditions. The results showed that the runoff generation mechanism was mainly infiltration-excess overland flow, but the flood events of saturation-excess overland flow had an increasing trend because of land use cover change (the increase of forestland and grassland areas and the reduction of cultivated land). Some of the model parameters had physical significances，such as water storage capacity (WM), infiltration capacity (f), evapotranspiration (CKE), soil permeability coefficient (k) and index of storage capacity distribution curve (n) showed increasing trends, and index of infiltration capacity distribution curve (m) showed a decreasing trend. The above results proved the changes of runoff generation mechanism from the perspective of model parameters in Jingle sub-basin, which can provide a new perspective for understanding the discharge reduction in the Yellow River basin.

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