scholarly journals Simulation of runoff in Baitarani basin using composite and distributed curve number approaches in HEC-HMS model

MAUSAM ◽  
2021 ◽  
Vol 71 (4) ◽  
pp. 675-686
Author(s):  
SAHOO NIHARIKA ◽  
PANIGRAHI B. ◽  
DAS DWARIKA MOHAN ◽  
DAS D. P.
Keyword(s):  
Curve Number ◽  
Base Flow ◽  
Coefficient Of Determination ◽  
Validation Period ◽  
Runoff Simulation ◽  
Statistical Parameters ◽  
Calibration Period ◽  
Digital Elevation ◽  
Spatial Analyst ◽  
Elevation Model

The present study was conducted in Baitarani basin up to Anandapur gauging station of Odisha covering an area of 8603.7 km2. Pre-processing of basin from digital elevation model (DEM) was done using HEC-Geo-HMS extension and spatial analyst tool in ArcGIS. These pre-processed files were then imported to HEC-HMS for simulating runoff. In this study, runoff simulation was done using two methods, viz., composite and distributed curve number (CN) approaches. SCS curve number method was used for computation of runoff volume, SCS UH method for direct runoff, constant- monthly varying base flow method for base flow and Muskingum method for flow routing.  The model was calibrated and validated using both composite and distributed CN approaches. Data from 1st January, 2007 to 31st December, 2013 were used for calibration and 1st January, 2014 to 31st December, 2016 were used for validation. During the calibration period of composite CN approach, the statistical parameters like Nash-Sutcliffe efficiency (NSE), Coefficient of determination (R2), Percent bias (PBIAS) and RMSE-observations standard deviation ratio (RSR) were found to be 0.51, 0.63, 12.82 and 0.7, respectively and during the validation period they were found to be 0.53, 0.54,    -19.73 and 0.7, respectively. In case of distributed CN approach, the statistical parameters like NSE, R2, PBIAS and RSR were found to be 0.62, 0.63, -8.64 and 0.6, respectively during the calibration period and 0.67, 0.66, -2.25 and 0.6,  respectively during the validation period. The study indicated that distributed CN approach is more accurate than composite CN approach in simulation of runoff using HEC-HMS model.

scholarly journals Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2160
Author(s):  
Daniel Kibirige ◽  
Endre Dobos
Keyword(s):  
Soil Moisture ◽  
Expert Knowledge ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Regression Kriging ◽  
Environmental Covariates ◽  
Observatory Data ◽  
Digital Elevation ◽  
Elevation Model

Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.

scholarly journals Effects of digital elevation model resolution on topography-based runoff simulation under uncertainty

2014 ◽  
Vol 16 (6) ◽  
pp. 1343-1358 ◽  
Author(s):  
L. Cui ◽  
Y. P. Li ◽  
G. H. Huang ◽  
Y. Huang
Keyword(s):  
Water Resources ◽  
Digital Elevation Model ◽  
Water Resources Management ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Resources Management ◽  
Dem Resolution ◽  
Analysis Technique ◽  
Digital Elevation ◽  
Elevation Model

Topography plays a critical role in controlling water dispersion and soil movement in hydrologic modeling for water resources management with raster-based digital elevation model (DEM). This study aims to model effects of DEM resolution on runoff simulation through coupling fuzzy analysis technique with a topography based rainfall–runoff model (TOPMODEL). Different levels of DEM grid sizes between 30 m and 200 m are examined, and the results indicate that 30 m DEM resolution is the best for all catchments. Results demonstrate that the DEM resolution could have significant influence on the TOPMODEL rainfall–runoff simulation. Fuzzy analysis technique is used to further examine the uncertain DEM resolution based on considering Nash, sum of squared error, and sum of absolute error values of TOPMODEL. The developed model is calibrated and validated against observed flow during the period 2010–2012, and generally performed acceptably for model Nash–Sutcliffe value. The proposed method is useful for studying hydrological processes of watershed associated with topography uncertainty and providing support for identifying proper water resources management strategy.

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 Simulation Of Surface runoff For Upper Tapi Subcatchment Area (Burhanpur Watershed) Using SWAT

2014 ◽  
Vol XL-8 ◽  
pp. 391-397 ◽  
Author(s):  
V. Shivhare ◽  
M. K. Goel ◽  
C. K. Singh
Keyword(s):  
Surface Runoff ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Temperature And Precipitation ◽  
Digital Elevation ◽  
Arc Gis ◽  
Monthly Runoff ◽  
Hydrologic Unit ◽  
Water Surplus ◽  
Elevation Model

Water related activity that takes place in one part of a river basin may have consequence in the other part. Any plan related to inter basin transfer of water from a water surplus basin to a deficit basin has to take into account the water availability and demands under the present and future scenarios of water use. Watershed is a hydrologic unit where all stream exit from the common outlet. In the present study, Tapi subcatchment area (Burhanpur watershed) located in inter-state basin of Madhya Pradesh and Maharashtra, India, is selected for the estimation of surface runoff using SWAT model. The SWAT works in conjunction with Arc GIS 9.3. Various parameters Digital Elevation Model (DEM), slope derived from DEM, Landuse/Landcover (LULC) and NBSSLUP soil data and temporal data for temperature and precipitation was used as input for the model to predict runoff at the catchment outlet. The model was run from the year 1992 to 1997. The performance of the model in terms of simulated runoff was evaluated using statistical method and compared simulated monthly flow with the observed monthly flow values from 1992 to 1996 to a significant extent. The coefficient of determination (R<sup>2</sup>) for the monthly runoff values for 1992 to 1996 was observed to be 0.82, 0.68, 0.92, 0.69.

scholarly journals Estimation of synthetic flood design hydrographs using a distributed rainfall–runoff model coupled with a copula-based single storm rainfall generator

2014 ◽  
Vol 14 (7) ◽  
pp. 1819-1833 ◽  
Author(s):  
A. Candela ◽  
G. Brigandì ◽  
G. T. Aronica
Keyword(s):  
Curve Number ◽  
Geographical Information ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Digital Elevation ◽  
Design Hydrographs ◽  
Rainfall Runoff Model ◽  
Storm Rainfall ◽  
Elevation Model ◽  
Runoff Model

Abstract. In this paper a procedure to derive synthetic flood design hydrographs (SFDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) via copulas, which describes and models the correlation between two variables independently of the marginal laws involved, coupled with a distributed rainfall–runoff model, is presented. Rainfall–runoff modelling (R–R modelling) for estimating the hydrological response at the outlet of a catchment was performed by using a conceptual fully distributed procedure based on the Soil Conservation Service – Curve Number method as an excess rainfall model and on a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the distributed unit hydrograph definition, was performed by implementing a procedure based on flow paths, determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the primary return period of the SFDH, which provides the probability of occurrence of a hydrograph flood, peaks and flow volumes obtained through R–R modelling were treated statistically using copulas. Finally, the shapes of hydrographs have been generated on the basis of historically significant flood events, via cluster analysis. An application of the procedure described above has been carried out and results presented for the case study of the Imera catchment in Sicily, Italy.

scholarly journals Validation of High-resolution and Simple River Monitoring Technique using UAV-SFM Method

2020 ◽  
Vol 8 (5) ◽  
pp. 5409-5414
Keyword(s):  
Correction Method ◽  
Coefficient Of Determination ◽  
Error Analyses ◽  
Accuracy And Precision ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Submerged Area ◽  
First Time

This study tested the accuracy and precision of the UAV-SfM method, an automated photogrammetry technique called SfM (Structure from Motion) using multiple pictures taken by UAV (Unmanned Aerial Vehicle), in a section of Saba river, Yamaguchi, Japan. The method was applied in the submerged area as well as in the exposed area, taking into account the refraction at the water surface, for the first time in domestic rivers. When the resultant DEM (Digital Elevation Model) is considered as the map of riverbed elevation, the RMS (Root Mean Square) error and R2 (coefficient of determination) of UAV-SfM were 0.165 m and 0.93, respectively. In pixels with thick algae cover, large apparent overestimations reaching 0.351 m at maximum were observed because UAV-SfM actually measures the algae surface elevation, not the riverbed elevation. Error analyses also showed that the refraction correction method adopted in this study is working well in spite of its simplicity.

HYDROGEOMORPHOLOGICAL MODELING OF KHOR OMAR OMDURMAN - SUDAN BY USING GIS

2020 ◽  
pp. 20-36
Author(s):  
Omar Abd Almajd Sayd AHMMAD ◽  
Alimam omar ALİMAM AİL ◽  
Hussein Salem Hussein SALEM ◽  
Muzamil Elrais Ahmed ALI
Keyword(s):  
Meteorological Data ◽  
Satellite Image ◽  
Curve Number ◽  
Digital Data ◽  
Geographical Information ◽  
Hydrologic Modelling ◽  
Model Soil ◽  
Digital Elevation ◽  
Elevation Model

e study addressed the hydro geomorphological modeling of koher Omar Oum Dorman Area by analyzing many digital data, including satellite Image, and Digital Elevation Model, soil and meteorological data, by using ARC.GIS -WMS - Hydrologic Engineering Center – Hydrologic Modelling System, (HEC-HMS). in order to analyzing geomorphological characteristics and hydro geomorphological, estimation of the amount of runoff and determination of affected areas through Hydro morphometric measurements, determination of soil varieties and land cover to extract Curve number (CN) the study found that the annual surface runoff volume is 21830.5M3 – 33938.1M3 areas affected by runoff are located to the east and south-east of the basin of koher Omar, and the study Reflced Meany recommendetoin, the most important of which is the utilization of water in development processes and the application of Geographical information system in hydro geomorphological studies. Key words: : GIS – RS - Rain off - WMS.

scholarly journals GIS-based Approach to Estimate Surface Runoff in Small Catchments: A Case Study

2016 ◽  
Vol 35 (3) ◽  
pp. 97-116 ◽  
Author(s):  
Matej Vojtek ◽  
Jana Vojteková
Keyword(s):  
Surface Runoff ◽  
Daily Rainfall ◽  
Curve Number ◽  
Point Of View ◽  
Small Catchment ◽  
Gis And Remote Sensing ◽  
Runoff Modeling ◽  
Digital Elevation ◽  
Surface Runoff Modeling ◽  
Elevation Model

Abstract The issue of surface runoff assessment is one of the important and relevant topics of hydrological as well as geographical research. The aim of the paper is therefore to estimate and assess surface runoff on the example of Vyčoma catchment which is located in the Western Slovakia. For this purpose, SCS runoff curve number method, modeling in GIS and remote sensing were used. An important task was the creation of a digital elevation model (DEM), which enters the surface runoff modeling and affects its accuracy. Great attention was paid to the spatial interpretation of land use categories applying aerial imagery from 2013 and hydrological soil groups as well as calculation of maximum daily rainfall with N-year return periods as partial tasks in estimating surface runoff. From the methodological point of view, the importance of the paper can be seen in the use of a simple GIS-based approach to assess the surface runoff conditions in a small catchment.

scholarly journals Comparative Study of Two State-of-the-Art Semi-Distributed Hydrological Models

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 871 ◽  
Author(s):  
Pranesh Kumar Paul ◽  
Yongqiang Zhang ◽  
Ashok Mishra ◽  
Niranjan Panigrahy ◽  
Rajendra Singh
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Relative Length ◽  
Coefficient Of Determination ◽  
Validation Period ◽  
Calibration Period ◽  
Calibration And Validation ◽  
Annual Peak ◽  
Monthly Streamflow ◽  
Grid Based

Performance of a newly developed semi-distributed (grid-based) hydrological model (satellite-based hydrological model (SHM)) has been compared with another semi-distributed soil and water assessment tool (SWAT)—a widely used hydrological response unit (HRU)-based hydrological model at a large scale (12,900 km2) river basin for monthly streamflow simulation. The grid-based model has a grid cell size of 25 km2, and the HRU-based model was set with an average HRU area of 25.2 km2 to keep a balance between the discretization of the two models. Both the model setups are calibrated against the observed streamflow over the period 1977 to 1990 (with 1976 as the warm-up period) and validated over the period 1991 to 2004 by comparing simulated and observed hydrographs as well as using coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) as statistical indices. Result of SHM simulation (NSE: 0.92 for calibration period; NSE: 0.92 for validation period) appears to be superior in comparison to SWAT simulation (NSE: 0.72 for calibration period; NSE: 0.50 for validation period) for both calibration and validation periods. The models’ performances are also analyzed for annual peak flow, monthly flow variability, and for different flow percentiles. SHM has performed better in simulating annual peak flows and has reproduced the annual variability of observed streamflow for every month of the year. In addition, SHM estimates normal, moderately high, and high flows better than SWAT. Furthermore, total uncertainties of models’ simulation have been analyzed using quantile regression technique and eventually quantified with scatter plots between P (measured data bracketed by the 95 percent predictive uncertainty (PPU) band) and R (the relative length of the 95PPU band with respect to the model simulated values)-values, for calibration and validation periods, for both the model simulations. The analysis confirms the superiority of SHM over its counterpart. Differences in data interpolation techniques and physical processes of the models are identified as the probable reasons behind the differences among the models’ outputs.

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