STREAMFLOW SIMULATION: COMPARISON BETWEEN SOIL WATER ASSESSMENT TOOL AND ARTIFICIAL NEURAL NETWORK MODELS

2021 ◽  
Vol 5 (2) ◽  
pp. 173-182
Author(s):  
Shehu Usman Haruna ◽  
Aliyu Kasim Abba ◽  
Rabi'u Aminu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Soil Water ◽  
Assessment Tool ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Artificial Neural ◽  
Soil Water Assessment Tool ◽  
Water Assessment ◽  
Streamflow Simulation

The present study compared the performance of two different models for streamflow simulation namely: Soil Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN). During the calibration periods, the Nash-Sutcliff (NS) and Coefficient of Determination (R2) for SWAT was 0.74 and 0.81 respectively, whereas for ANN, it was 0.99 and 0.85 respectively. The ANN performs better during the validation period as the result revealed with NS and R2 having 0.98 and 0.89 respectively, while for the SWAT model it was 0.71 and 0.74 respectively. Based on the recommended comparison of graphical and statistical evaluation performances of both models, the ANN model performed better in estimating peak flow events than the SWAT model in the Upper Betwa Basin. Furthermore, the rigorous time required and expertise for calibration of the SWAT is much less as compared with the ANN. Moreover, the results obtained from both models demonstrate the performances of the

scholarly journals Sub-Daily Simulation of Mountain Flood Processes Based on the Modified Soil Water Assessment Tool (SWAT) Model

2019 ◽  
Vol 16 (17) ◽  
pp. 3118 ◽  
Author(s):  
Yongchao Duan ◽  
Fanhao Meng ◽  
Tie Liu ◽  
Yue Huang ◽  
Min Luo ◽  
...  
Keyword(s):  
High Altitude ◽  
Soil Water ◽  
Assessment Tool ◽  
Swat Model ◽  
High Temporal Resolution ◽  
Distributed Hydrological Model ◽  
Mountainous Areas ◽  
Accumulated Temperature ◽  
Soil Water Assessment Tool ◽  
Water Assessment

Floods not only provide a large amount of water resources, but they also cause serious disasters. Although there have been numerous hydrological studies on flood processes, most of these investigations were based on rainfall-type floods in plain areas. Few studies have examined high temporal resolution snowmelt floods in high-altitude mountainous areas. The Soil Water Assessment Tool (SWAT) model is a typical semi-distributed, hydrological model widely used in runoff and water quality simulations. The degree-day factor method used in SWAT utilizes only the average daily temperature as the criterion of snow melting and ignores the influence of accumulated temperature. Therefore, the influence of accumulated temperature on snowmelt was added by increasing the discriminating conditions of rain and snow, making that more suitable for the simulation of snowmelt processes in high-altitude mountainous areas. On the basis of the daily scale, the simulation of the flood process was modeled on an hourly scale. This research compared the results before and after the modification and revealed that the peak error decreased by 77% and the time error was reduced from ±11 h to ±1 h. This study provides an important reference for flood simulation and forecasting in mountainous areas.

scholarly journals Simulasi Skenario Penutupan Lahan untuk Melihat Kondisi Hidrologi di Das Lisu, Kabupaten Barru

2019 ◽  
Vol 11 (1) ◽  
pp. 49
Author(s):  
Samsul Labaco ◽  
Usman Arsyad ◽  
Anwar Umar
Keyword(s):  
Land Cover ◽  
Soil Water ◽  
Experimental Research ◽  
Rainy Season ◽  
Assessment Tool ◽  
Hydrological Cycle ◽  
Swat Model ◽  
Overlay Method ◽  
Soil Water Assessment Tool ◽  
Water Assessment

The disruption of hydrological cycle will reduce watershed's ability to store water, so that discharge in dry season decreases and discharge in rainy season increases. These problems are caused by changes in land cover from forested land to non-forested. This study aims to develop a scenario for land cover planning that should be applied in the Lisu Watershed, Barru Regency. This study is mapping based on non-experimental research. The data obtained were analyzed spatially by overlay method. The Soil Water Assessment Tool (SWAT) model is used in preparation of land cover planning scenarios to predict hydrological conditions. The results showed that scenario 2, namely land cover planning based on the district space map pattern is the best scenario. Addition of forest area to 61.60% resulting in the lowest yield of 3461.54 mm/year and 1519.53 mm/year. While the infiltration value produced is the highest infiltration value, which is 2299.20 mm/year.

scholarly journals Application of Soil Water Assessment Tool (SWAT) Model in Analyzing Nitrogen Transport Inside the Narmada River Basin

2021 ◽  
Vol 3 ◽  
Author(s):  
Prakrut Kansara ◽  
Venkataraman Lakshmi
Keyword(s):  
Soil Water ◽  
Agricultural Land ◽  
Assessment Tool ◽  
Swat Model ◽  
High Rate ◽  
Western India ◽  
Discharge Data ◽  
Narmada River ◽  
Soil Water Assessment Tool ◽  
Water Assessment

The Narmada River is one of the largest rivers in Western India encompassing a watershed area of 92,672 km2. It is one of the most important rivers for water needs of the state of Gujarat, Maharashtra, and Madhya Pradesh. The climate of the basin is humid and tropical but region surrounding this river watershed is predominantly dry and resembles semi-arid conditions. The population inside the states covering this watershed increased by an average of 23% from 1991 to 2011 causing multitude of water scarcity and water quality deterioration issues. These problems were caused by increase in sewage waste and untreated industrial discharge dumped into the river stream along with chemical fertilizers washing off from the farmlands flowing into the river. While there are several studies that model the watershed hydrology and water balance components, there has been no study that analyses the transport of nutrients inside the watershed. This study aims at using a semi-distributed hydrological model—Soil Water Assessment Tool (SWAT) to model the nitrogen (NO2 + NO3) transport and distribution inside the basin for 2001–2019. Nutrients and discharge data from Central Water Commission (CWC) of India were used to build this model along with other required input forcing obtained through remotely sensed datasets. We found that the subbasins near boundary of the Narmada watershed are experiencing significant increase in nitrogen concentrations at an estimated rate of 0.0001–0.002 mg/L/yr. The potential reason for such increase is high rate of conversion of forested land to agricultural land causing usage of fertilizers that are rich in nitrogen.

Applying the Soil Water Assessment Tool to 5th Canadian Division Support Base Gagetown

2014 ◽  
Vol 49 (4) ◽  
pp. 372-385
Author(s):  
Shawn Burdett ◽  
Michael Hulley ◽  
Andy Smith
Keyword(s):  
Water Quality ◽  
Soil Water ◽  
Land Management ◽  
Management Practices ◽  
Assessment Tool ◽  
Anthropogenic Activities ◽  
Quality Model ◽  
Sediment Yields ◽  
Soil Water Assessment Tool ◽  
Water Assessment

A hydrologic and water quality model is sought to establish an approach to land management decisions for a Canadian Army training base. Training areas are subjected to high levels of persistent activity creating unique land cover and land-use disturbances. Deforestation, complex road networks, off-road manoeuvres, and vehicle stream crossings are among major anthropogenic activities observed to affect these landscapes. Expanding, preserving and improving the quality of these areas to host training activities for future generations is critical to maintain operational effectiveness. Inclusive to this objective is minimizing resultant environmental degradation, principally in the form of hydrologic fluctuations, excess erosion, and sedimentation of aquatic environments. Application of the Soil Water Assessment Tool (SWAT) was assessed for its ability to simulate hydrologic and water quality conditions observed in military landscapes at 5th Canadian Division Support Base (5 CDSB) Gagetown, New Brunswick. Despite some limitations, this model adequately simulated three partial years of daily watershed outflow (NSE = 0.47–0.79, R2 = 0.50–0.88) and adequately predicted suspended sediment yields during the observation periods (%d = 6–47%) for one highly disturbed sub-watershed in Gagetown. Further development of this model may help guide decisions to develop or decommission training areas, guide land management practices and prioritize select landscape mitigation efforts.

scholarly journals Hydrological simulation in a tropical humid basin in the Cerrado biome using the SWAT model

2018 ◽  
Vol 49 (3) ◽  
pp. 908-923 ◽  
Author(s):  
Richarde Marques da Silva ◽  
José Carlos Dantas ◽  
Joyce de Araújo Beltrão ◽  
Celso A. G. Santos
Keyword(s):  
Assessment Tool ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Southeastern Brazil ◽  
Measured Variable ◽  
Hydrological Simulation ◽  
Cerrado Biome ◽  
Monthly Streamflow ◽  
P Factor ◽  
Water Assessment

Abstract A Soil and Water Assessment Tool (SWAT) model was used to model streamflow in a tropical humid basin in the Cerrado biome, southeastern Brazil. This study was undertaken in the Upper São Francisco River basin, because this basin requires effective management of water resources in drought and high-flow periods. The SWAT model was calibrated for the period of 1978–1998 and validated for 1999–2007. To assess the model calibration and uncertainty, four indices were used: (a) coefficient of determination (R2); (b) Nash–Sutcliffe efficiency (NS); (c) p-factor, the percentage of data bracketed by the 95% prediction uncertainty (95PPU); and (d) r-factor, the ratio of average thickness of the 95PPU band to the standard deviation of the corresponding measured variable. In this paper, average monthly streamflow from three gauges (Porto das Andorinhas, Pari and Ponte da Taquara) were used. The results indicated that the R2 values were 0.73, 0.80 and 0.76 and that the NS values were 0.68, 0.79 and 0.73, respectively, during the calibration. The validation also indicated an acceptable performance with R2 = 0.80, 0.76, 0.60 and NS = 0.61, 0.64 and 0.58, respectively. This study demonstrates that the SWAT model provides a satisfactory tool to assess basin streamflow and management in Brazil.

Predicting the ground vibration induced by mine blasting using imperialist competitive algorithm

2018 ◽  
Vol 35 (4) ◽  
pp. 1774-1787 ◽  
Author(s):  
Katayoun Behzadafshar ◽  
Fahimeh Mohebbi ◽  
Mehran Soltani Tehrani ◽  
Mahdi Hasanipanah ◽  
Omid Tabrizi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ground Vibration ◽  
Imperialist Competitive Algorithm ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Content Type ◽  
Competitive Algorithm ◽  
Spacing Ratio ◽  
Artificial Neural

PurposeThe purpose of this paper is to propose three imperialist competitive algorithm (ICA)-based models for predicting the blast-induced ground vibrations in Shur River dam region, Iran.Design/methodology/approachFor this aim, 76 data sets were used to establish the ICA-linear, ICA-power and ICA-quadratic models. For comparison aims, artificial neural network and empirical models were also developed. Burden to spacing ratio, distance between shot points and installed seismograph, stemming, powder factor and max charge per delay were used as the models’ input, and the peak particle velocity (PPV) parameter was used as the models’ output.FindingsAfter modeling, the various statistical evaluation criteria such as coefficient of determination (R2) were applied to choose the most precise model in predicting the PPV. The results indicate the ICA-based models proposed in the present study were more acceptable and reliable than the artificial neural network and empirical models. Moreover, ICA linear model with theR2 of 0.939 was the most precise model for predicting the PPV in the present study.Originality/valueIn the present paper, the authors have proposed three novel prediction methods based on ICA to predict the PPV. In the next step, we compared the performance of the proposed ICA-based models with the artificial neural network and empirical models. The results indicated that the ICA-based models proposed in the present paper were superior in terms of high accuracy and have the capacity to generalize.

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