Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Marahatta, Suresh; Aryal, Deepak; Devkota, Laxmi Prasad; Bhattarai, Utsav; Shrestha, Dibesh

doi:10.3390/w13111548

Cited by 20 publications

(21 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Larger values of PBIAS (.30%) using PERSIANN-CDR and MERRA2 also result in unsatisfactory performance. The differences in the simulated and observed flows can be attributed to many factors: (i) errors in precipitation estimations, (ii) higher spatial variability in the precipitation due to orographic effects, (iii) errors in stream gauge observations and (iv) possible errors in model structure or combinations of the above (Manfreda et al 2020;Marahatta et al 2021). These results indicate that satellite precipitation products are suitable for hydrological simulations at a monthly scale in a complex topographic region.…”

Section: Comparison At a Monthly Scalementioning

confidence: 90%

“…The Soil and Water Assessment Tool (SWAT), Variable Infiltration Capacity (VIC) and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) are semi-distributed models, and Visualizing Ecosystem Land Management Assessments (VELMA) and Variant of Système Hydrologique Européen (MIKE SHE) are fully distributed models (Devkota & Gyawali 2015;Sitterrson et al 2017;Pandey et al 2020). These are either continuous or event-based flow generating models (Hossain Hewa & Wella-Hewage 2019;Marahatta et al 2021). The SWAT model was selected as the most popular model from a list of 73 hydrological models (Mannschatz et al 2016).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of satellite-based and reanalysis precipitation datasets by hydrologic simulation in the Chenab river basin

Ougahi

Mahmood

2022

Journal of Water and Climate Change

View full text Add to dashboard Cite

Several satellite-based and reanalysis products with a high spatial and temporal resolution have become available in recent decades, making it worthwhile to study the performance of multiple precipitation forcing data on hydrological modeling. This study aims to examine the veracity of five precipitation products employing a semi-distributed hydrological model, i.e., the Soil and Water Assessment Tool (SWAT) to simulate streamflow over the Chenab River Basin (CRB). The performance indices such as coefficient of determination (R2), Nash–Sutcliff efficiency (NSE) and percentage bias (PBIAS) were used to compare observed and simulated streamflow at daily and monthly scales during calibration (2015–2018) and validation (2019–2020). The hydrologic performance of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA) 5-Land (ERA5) was very good at daily (calibration R2=0.83, NSE=0.81, PBIAS=−6%; validation R2=0.75, NSE=0.74, PBIAS=−9.6%) and monthly ( calibration R2=0.94, NSE=0.94, PBIAS=−3.3%; validation R2=0.91, NSE=0.89, PBIAS=−3.2%) scales. This study suggests that the ERA5 precipitation product was the most reliable of the five precipitation products, while the CHIRPS performance was the worst. These findings contribute to highlighting the performance of five precipitation products and reference in the selection of precipitation data as input data to the SWAT model in similar regions.

show abstract

Section: Comparison At a Monthly Scalementioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Evaluation of satellite-based and reanalysis precipitation datasets by hydrologic simulation in the Chenab river basin

Ougahi

Mahmood

2022

Journal of Water and Climate Change

View full text Add to dashboard Cite

show abstract

“…Despite abundant recent studies on future hydro‐climatic projections due to CC (e.g., Bhattarai et al, 2022; Dhaubanjar et al, 2019; Marahatta et al, 2021), their impacts on flood inundation at the watershed scale are still limited in Nepal. Consequently, very few studies (Dewan, 2015) have quantified the flood impacts on the socio‐economic sectors.…”

Section: Introductionmentioning

confidence: 99%

“…Among the various methods available for bias correction, Quantile Mapping (QM) is considered as a relatively better technique for improving the performance of climate models (Tegegne et al, 2017). Studies like Dhaubanjar et al (2019) and Marahatta et al (2021) have applied this technique in CC studies in different basins of Nepal. However, climate projections are approximations which vary considerably with location and physiographic regions, thus, warranting careful interpretation of their results.…”

mentioning

confidence: 99%

An artificial neural network‐hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal

Bhattarai

Pandey

et al. 2022

J Flood Risk Management

Self Cite

View full text Add to dashboard Cite

Recurring floods have devastating consequences on the East Rapti Watershed (ERW), but effective mitigation/adaptation measures are lacking. This article aims at establishing a rainfall-runoff (RR) relationship; estimating depth and extent of inundation under climate change scenarios; assessing impacts on the socio-economy; and identifying and evaluating adaptation strategies in the ERW. Artificial Neural Network (ANN) was used to generate peak flows which were then entered into a hydraulic model to simulate inundation. Results were validated with field survey. The calibrated and validated RR and hydraulic models were fed with projected future climate (2021-2050) derived from multiple regional-climate-models to assess the changes in inundation. Results showed the peak discharge likely exceeds 10,500 m 3 /s at the ERW outlet in the extreme future flood scenario with corresponding inundation of 80 km 2 and up to a depth of 11 m sweeping away over 1000 houses and 19 km 2 of agricultural land in the critical areas. Constructing a 17 km long embankment in the critical areas along the right bank of the East Rapti River could reduce the flood spread by 35%, safeguarding 78% of the houses and saving 51% agricultural land compared with the scenarios without the embankment. K E Y W O R D S adaptation strategies, ANN, climate change, East Rapti Watershed, flood modelling, HEC-RAS | INTRODUCTIONFlood, a major natural disaster across the globe, accounted for 44% of all disaster events during 2000-2019 worldwide (UNDRR, 2020). About 41% of the total flood events during the period was observed in Asia alone impacting 1.5 billion people. Climate change (CC) is further exacerbating extreme events such as floods and exposing more population and property at risk (Fahad & Wang, 2019). Nepal ranks 30th in terms of vulnerability to flood risk, the problem being more prominent in the flat southern plains (UNDP, 2021).Flood modelling and hazard mapping are wellestablished methods for effectively assessing associated

show abstract

“…Many scholars belonging to different geophysical domains have studied the consequences of climate change. For example, here are some reviews of relevant research in recent times (17)(18)(19)(20)(21) . However, none of these research works represented a study on seasonal water availability.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Impacts of Climate Change on Varied River-Flow Regimes of Peninsular India

Veerabhadrannavar¹,

Venkatesh²

2022

IJST

View full text Add to dashboard Cite

Objectives: Precipitation is a major component of the hydrological cycle. Precipitation varies in intensity throughout time and space. The discharge at the outlet of the catchment is directly proportional to the precipitation received in the catchment. The current research looks at the precipitation as well as discharge patterns in the Sagar and Kokkarne catchments in the Western Ghats of Karnataka, India. Methods: In the present research, the soil water assessment tool (SWAT) has been applied to monitor and quantify the streamflow of the Sagar and Kokkarne catchments. Precipitation and discharge analysis for the period of 2021-2050 for both of the catchments is carried out. The seasonal and yearly discharge patterns of the catchments were studied using the Coordinated Regional Downscaling Experiment-South Asia data for the RCP 4.5 scenario for the period 2021-2050. Findings: During the Southwest monsoon and Northeast Monsoon, about 81.44 % and 14.22 % of the precipitation in Sagar catchment and about 87.34 % and 6.93 % of the precipitation in Kokkarne catchment were obtained respectively. The contribution of the Southwest Monsoon in both the catchment is greatest, followed by the Northeast monsoon. During the period 2021-2050, less than 80 % probability of discharge is expected for 23 years and more than 20 % probability of discharge is expected for 4 years. The maximum discharge expected in Sagar and Kokkarne catchments are 16.96 m 3 /sec and 213.87 m 3 /sec respectively. Novelty: The patterns of the precipitation and discharge of two different catchments on each side of the Western Ghats of Karnataka are compared in the current study to understand the impact of climate change on catchment hydrology in these regions.

show abstract

Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Cited by 20 publications

References 59 publications

Evaluation of satellite-based and reanalysis precipitation datasets by hydrologic simulation in the Chenab river basin

Evaluation of satellite-based and reanalysis precipitation datasets by hydrologic simulation in the Chenab river basin

An artificial neural network‐hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal

Assessment of Impacts of Climate Change on Varied River-Flow Regimes of Peninsular India

Contact Info

Product

Resources

About