scholarly journals Gajahwong River Continuous Flow Simulation by Using Soil Moisture Accounting (SMA) of HEC HMS

2021 ◽  
Vol 930 (1) ◽  
pp. 012032
Author(s):  
P N Wardhana ◽  
LP Kusumawijaya
Keyword(s):  
Soil Moisture ◽  
Water Supply ◽  
Continuous Flow ◽  
Flow Simulation ◽  
Data Availability ◽  
Population Number ◽  
Discharge Data ◽  
Soil Moisture Accounting ◽  
Time Series Simulation ◽  
Parameter Values

Abstract Gajahwong River is located in the southern part of Java Island, Indonesia, specifically on Daerah Istimewa Yogyakarta. Gajahwong River has an important role along the area where its discharge is used especially for irrigation water supply. Other factors stressing Gajahwong basin’s water supply purpose are population number rise and land cover change that influence river streamflow in the whole year. Hence, a continuous flow simulation was conducted to analyze Gajahwong River water availability to supply its requirement. The Soil Moisture Accounting (SMA) module of HEC-HMS was employed to simulate the continuous flow of Gajahwong River, particularly in Wonokromo Outlet. The continuous flow was simulated from the year 2012 until 2015 based on observed discharge data availability. Comparison between simulated and observed discharge was quantified by using R2, Nash-Sutcliffe efficiency and PBIAS statistic value. The statistic above parameter values yielded a value of 0.90, 0.58, and 2.02%, respectively for daily time series simulation.

scholarly journals How crucial is it to account for the Antecedent Moisture Conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments

2009 ◽  
Vol 6 (2) ◽  
pp. 1707-1736 ◽  
Author(s):  
L. Berthet ◽  
V. Andréassian ◽  
C. Perrin ◽  
P. Javelle
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Flood Forecasting ◽  
Hydrologic Model ◽  
Data Availability ◽  
Data Set ◽  
Soil Moisture Accounting ◽  
Antecedent Moisture ◽  
Rainfall Runoff Model ◽  
Event Based

Abstract. This paper compares event-based and continuous hydrological modelling approaches for real-time forecasting of river flows. Both approaches are compared using a lumped hydrologic model (whose structure includes a soil moisture accounting (SMA) store and a routing store) on a data set of 178 French catchments. The main focus of this study was to investigate the actual impact of soil moisture initial conditions on the performance of flood forecasting models and the possible compensations with updating techniques. The rainfall runoff model assimilation technique we used does not impact the SMA component of the model but only its routing part. Tests were made by running the SMA store continuously or on event basis, everything else being equal. The results show that the continuous approach remains the reference to ensure good forecasting performances. We show, however, that the possibility to assimilate the last observed flow considerably reduces the differences in performance. Last, we present a robust alternative to initialize the SMA store where continuous approaches are impossible because of data availability problems.

scholarly journals Kalibrasi Model Soil Moisture Accounting dengan Software HEC-HMS di Stasiun Debit Pasir Pangaraian

2021 ◽  
Vol 1 (1) ◽  
pp. 13-21
Author(s):  
Yohanna Lilis Handayani ◽  
Gopal Adya Ariska ◽  
David Imannuel Ketaren
Keyword(s):  
Soil Moisture ◽  
Model Calibration ◽  
Daily Rainfall ◽  
Automatic Calibration ◽  
Calibration Data ◽  
Discharge Data ◽  
Climatological Data ◽  
Soil Moisture Accounting ◽  
Model Soil ◽  
Daily Discharge

This research aims to compare the results of the calibration of the Soil Moisture Accounting (SMA) model using Percent Error in Volume (PEV) and Peak Weighted Root Mean Square Error (RMSE). The SMA model calibration uses the HEC-HMS (Hydrologic Engineering Center – Hydrologic Modeling System). There are 12 calibrated parameters by automatic calibration. The input data are the area of ​​the watershed, daily rainfall, daily discharge data and climatological data. The data used is data from 2008 to 2017. The results show that PEV performance shows good results. While the RMSE showed poor results. PEV results are best at 7 years of calibration and 3 years of verification. The length of the calibration data has not affected the verification results.

scholarly journals How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments

2009 ◽  
Vol 13 (6) ◽  
pp. 819-831 ◽  
Author(s):  
L. Berthet ◽  
V. Andréassian ◽  
C. Perrin ◽  
P. Javelle
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Flood Forecasting ◽  
Hydrologic Model ◽  
Data Availability ◽  
Data Set ◽  
Soil Moisture Accounting ◽  
Antecedent Moisture ◽  
Rainfall Runoff Model ◽  
Event Based

Abstract. This paper compares event-based and continuous hydrological modelling approaches for real-time forecasting of river flows. Both approaches are compared using a lumped hydrologic model (whose structure includes a soil moisture accounting (SMA) store and a routing store) on a data set of 178 French catchments. The main focus of this study was to investigate the actual impact of soil moisture initial conditions on the performance of flood forecasting models and the possible compensations with updating techniques. The rainfall-runoff model assimilation technique we used does not impact the SMA component of the model but only its routing part. Tests were made by running the SMA store continuously or on event basis, everything else being equal. The results show that the continuous approach remains the reference to ensure good forecasting performances. We show, however, that the possibility to assimilate the last observed flow considerably reduces the differences in performance. Last, we present a robust alternative to initialize the SMA store where continuous approaches are impossible because of data availability problems.

scholarly journals Analisis Hidrologi Model Soil Moisture Accounting Menggunakan Program HEC-HMS (Studi Kasus : DAS Rokan AWLR Pasir Pangaraian)

2020 ◽  
Vol 20 (01) ◽  
pp. 11-18
Author(s):  
Gopal Adya Ariska ◽  
Yohanna Lilis Handayani ◽  
Bambang Sujatmoko
Keyword(s):  
Soil Moisture ◽  
Water Resources ◽  
Objective Function ◽  
Hydrological Modeling ◽  
Percentage Error ◽  
Discharge Data ◽  
Soil Moisture Accounting ◽  
Planning And Management ◽  
Discharge Volume ◽  
Calibration And Verification

(ID) Hidrologi suatu Daerah Aliran Sungai (DAS) rumit untuk diprediksi karena kekurangan data dan membutuhkan biaya yang mahal. Pada penelitian ini mengambil lokasi di sub DAS Rokan Hulu stasiun Pasir Pengaraian yang hampir setiap tahun terjadi banjir. Perencanaan dan pengolahan sumber daya air di suatu wilayah daerah aliran sungai sangat penting, maka dari itu perlunya mengetahui karakteristik suatu DAS. Perencanaan dan pengolaan sumber daya air memerlukan data debit aliran yang lengkap. Pada sub DAS ini data hujan, data debit dan data klimatologi menggunakan periode data sepuluh tahun yaitu dari tahun 2008-2017. Pemodelan hidrologi dilakukan pendekatan dengan beberapa metode, salah satunya metode soil moisture accounting di program HEC-HMS yang mana metode tersebut mensimulasikan suatu pergerakan air pada vegetasi, permukaan tanah dan di bawah permukaan tanah. Penyusunan periode kalibrasi dan verifikasi disusun dalam sembilan skema yang diharapkan mampu menghasilkan hasil yang paling optimal. Sembilan skema untuk Kalibrasi dan Verifikasi ini menggunakan metode objective function yaitu percent error in discharge volume. Skema yang paling optimal adalah skema VII (7 tahun kalibrasi 3 tahun Verifikasi), dengan nilai verifikasi 10,1%”Baik” dan Kalibrasi 0,0% “Sangat Baik”. (EN) The hydrology of a watershed is difficult to predict because of the lack of data and requires high costs. In this study taking location in the Rokan Hulu sub-watershed, Pasir Pengaraian station Almost every year flooding occurs. Planning and management of water resources in a watershed is very important and therefore it is necessary to know the characteristics of the watershed. Planning and management of water resources require complete data. in this sub-watershed rainfall data, discharge data and climatology data use a ten-year data period from 2008-2017. Hydrological modeling is approached with several methods, one of them is soil moisture accounting method in the HEC-HMS program where the method simulates a movement of water on vegetation, soil surface and below ground level. The preparation of the calibration and verification periods arranged in nine schemes is expected to produce the most optimal results. The nine schemes for Calibration and Verification use the objective function method, which is the percentage error in discharge volume. The most optimal scheme is the scheme VII (7 years calibration 3 years Verification), with a verification value of 10.1% "Good" and Calibration 0.0% "Very Good".  

scholarly journals A soil moisture accounting-procedure with a Richards' equation-based soil texture-dependent parameterization

2015 ◽  
Vol 51 (1) ◽  
pp. 506-523 ◽  
Author(s):  
Simon A. Mathias ◽  
Todd H. Skaggs ◽  
Simon A. Quinn ◽  
Sorcha N. C. Egan ◽  
Lucy E. Finch ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Texture ◽  
Richards Equation ◽  
Soil Moisture Accounting ◽  
Accounting Procedure

Water demand and water use efficiency of winter barley in Hungary

2011 ◽  
Vol 59 (1) ◽  
pp. 13-22
Author(s):  
Z. Varga-Haszonits ◽  
E. Enzsölné Gerencsér ◽  
Z. Lantos ◽  
Z. Varga
Keyword(s):  
Soil Moisture ◽  
Water Supply ◽  
Water Use Efficiency ◽  
Water Use ◽  
Potential Evapotranspiration ◽  
Growth Period ◽  
Winter Barley ◽  
Potential Yield ◽  
Yield Data ◽  
Use Efficiency

The temporal and spatial variability of soil moisture, evapotranspiration and water use were investigated for winter barley. Evaluations were carried out on a database containing meteorological and yield data from 15 stations. The spatial distribution of soil moisture, evapotranspiration and water use efficiency (WUE) was evaluated from 1951 to 2000 and the moisture conditions during the growth period of winter barley were investigated. The water supply was found to be favourable, since the average values of soil moisture remained above the lower limit of favourable water content throughout the growth period, except for September–December and May–June. The actual evapotranspiration tended to be close to the potential evapotranspiration, so the water supplies were favourable throughout the vegetation period. The calculated values of WUE showed an increasing trend from 1960 to 1990, but the lower level of agricultural inputs caused a decline after 1990. The average values of WUE varied between 0.87 and 1.09 g/kg in different counties, with higher values in the northern part of the Great Hungarian Plain. The potential yield of winter barley can be calculated from the maximum value of WUE. Except in the cooler northern and western parts of the country, the potential yield of winter barley, based on the water supply, could exceed 10 t/ha.

An advanced soil moisture accounting procedure for SCS curve number method

2007 ◽  
Vol 21 (21) ◽  
pp. 2872-2881 ◽  
Author(s):  
R. K. Sahu ◽  
S. K. Mishra ◽  
T. I. Eldho ◽  
M. K. Jain
Keyword(s):  
Soil Moisture ◽  
Curve Number ◽  
Soil Moisture Accounting ◽  
Scs Curve Number ◽  
Curve Number Method ◽  
Accounting Procedure

scholarly journals The suitability of remotely sensed soil moisture for improving operational flood forecasting

2014 ◽  
Vol 18 (6) ◽  
pp. 2343-2357 ◽  
Author(s):  
N. Wanders ◽  
D. Karssenberg ◽  
A. de Roo ◽  
S. M. de Jong ◽  
M. F. P. Bierkens
Keyword(s):  
Soil Moisture ◽  
Satellite Data ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Remotely Sensed ◽  
Added Value ◽  
Lead Times ◽  
Validation Data ◽  
Data Set ◽  
Discharge Data

Abstract. We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model (LISFLOOD) for flood predictions with lead times of up to 10 days. For this study, satellite-derived soil moisture from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) and SMOS (Soil Moisture and Ocean Salinity) is assimilated into the LISFLOOD model for the Upper Danube Basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into the hydrological model, an ensemble Kalman filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure increased performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation data set. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the mean absolute error (MAE) of the ensemble mean is reduced by 35%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of baseflows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the continuous ranked probability score (CRPS) shows a performance increase of 5–10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more observational data is assimilated into the system. The added values of the satellite data is largest when these observations are assimilated in combination with distributed discharge observations. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

scholarly journals Flow Prediction Using Remotely Sensed Soil Moisture in Irish Catchments

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2202
Author(s):  
Chanyu Yang ◽  
Fiachra E. O’Loughlin
Keyword(s):  
Soil Moisture ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Coefficient Of Determination ◽  
Energy Budgets ◽  
Care Needs ◽  
Soil Moisture Accounting ◽  
Model Soil ◽  
Ungauged Basin ◽  
Behavioural Parameter

Owing to a scarcity of in situ streamflow data in ungauged or poorly gauged basins, remote sensing data is an ideal alternative. It offers a valuable perspective into the dynamic patterns that can be difficult to examine in detail with point measurements. For hydrology, soil moisture is one of the pivotal variables which dominates the partitioning of the water and energy budgets. In this study, nine Irish catchments were used to demonstrate the feasibility of using remotely sensed soil moisture for discharge prediction in ungagged basins. Using the conceptual hydrological model “Soil Moisture Accounting and Routing for Transport” (SMART), behavioural parameter sets (BPS) were selected using two different objective functions: the Nash Sutcliffe Efficiency (NSE) and Coefficient of Determination (R2) for the calibration period. Good NSE scores were obtained from hydrographs produced using the satellite soil moisture BPS. While the mean performance shows the feasibility of using remotely sensed soil moisture, some outliers result in negative NSE scores. This highlights that care needs to be taken with parameterization of hydrological models using remotely sensed soil moisture for ungauged basin.

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