Uncertainty in hydrological analysis using multi-GCM predictions and multi-parameters under RCP 2.6 and 8.5 scenarios in Manipur River basin, India (original) (raw)
Related papers
Future climate change impact on hydrological regime of river basin using SWAT model
Global Journal of Environmental Science and Management, 2019
Hydrological components in a river basin can get adversely affected by climate change in coming future. Manipur River basin lies in the extreme northeast region of India nestled in the lesser Himalayan ranges and it is under severe pressure from anthropogenic and natural factors. Basin is un-gauged as it lies in remote location and suffering from large data scarcity. This paper explores the impact of climate change towards understanding the interrelationships between various complex hydrological factors in the river basin. An integrated approach is applied by coupling Soil and Water Assessment Hydrological Model and Hadley Center Coupled Model based on temperature, rainfall and geospatial data. Future representative concentration pathways 2.6, 4.5 and 8.5 scenarios for 2050s and 2090s decades were used to evaluate the effects of climatic changes on hydrological parameters. Both annual mean temperature and annual precipitation is predicted to be increased by 2.07 o C and 62% under RCP 8.5 by the end of 21 st century. This study highlights that change in meteorological parameters will lead to significant change in the hydrological regime of the basin. Runoff, actual evapotranspiration and water yield are expected to be increased by 40.96 m 3 /s, 52.2% and 86.8% respectively under RCP 8.5. This study shows that water yield and evapotranspiration will be most affected by increase in precipitation and temperature in the upper and middle subbasins. Different region within the basin is likely to be affected by frequent landslides and flood in coming decades.
Journal of Earth Science & Climatic Change, 2015
Climate change is one of the most important global environmental challenges, which affects the entire earth system in terms of negative impacts on food production, water supply, health, livelihood, energy, etc. The intent of the present study was to assess the impact of climate change on the water balance components of a data-starved Upper Baitarani River basin of Eastern India using ArcSWAT model. The ArcSWAT model was calibrated using SUFI-2 technique. The daily observed streamflow data from 1998 to 2003 were employed for calibration and those for 2004-2005 for validation. The calibration results were found to be satisfactory with the Nash-Sutcliffe efficiency (NSE) and mean absolute error (MAE) of 0.88 and 9.70 m 3 /s for the daily time step, respectively. Also, the model was validated successfully for simulating daily streamflow (NSE=0.80 and MAE=10.33 m 3 /s). The calibrated and validated model was then used to evaluate basin response to the anticipated climate changes by the end of the 21st century. Twelve independent as well as twenty eight combined areaspecific climatic scenarios were considered in this study to evaluate the impact of climate change on the hydrology of the basin. The analysis of model results for the 12 Independent Climatic Scenarios indicated a reduction in the surface runoff ranging from 2.5 to 11 % by changing the temperature from 1 to 5°C, whereas the increase in rainfall by 2.5 to 15 % suggested an increase in surface runoff by 6.67 to 43.42 % from the baseline condition. In case of 28 Combined Scenarios compared to the baseline condition, the changes in surface runoff would vary from −4.55 to 37.53 %, the groundwater recharge would change from −8.7 to 23.15 % and the evapotranspiration would increase from 4.05 to 11.88 %. It is concluded that future changes in the climatic condition by the end of the 21st century are most likely to produce significant impacts on the streamflow in the study area. The findings of this study and those of follow-up studies in this direction will be useful for guiding suitable adaptation measures for sustainable water management in the basin in the face of impending climate change.
Journal of Water and Climate Change, 2022
The estimate of changes in hydrological fluxes from a climate change perspective is inevitable for assessing the sustainability of watersheds and conserving water resources. Here, we quantify and assess the changes in different hydrological flux components for the Manu-Deo River Basin (MDRB) of northeast India using Soil and Water Assessment Tool (SWAT) simulations and multi-temporal data at various resolutions. Sequential Uncertainty Fitting (SUFI-2) optimization is used to calibrate and validate the simulations for the periods 1984–2006 and 2007–2016 and for the four future representative concentration pathway (RCP) scenarios. The model performed reasonably well for the calibration and validation of daily data, in accordance with the Nash–Sutcliffe efficiency and coefficient of determination (0.54/0.55 and 0.52/0.72, respectively). The analysis for the period 1985–2013 reveals a decreasing trend in streamflow, which indicates increasing trends of drought there. Furthermore, it sho...
Water
Understanding the likely impacts of climate change (CC) and Land Use Land Cover (LULC) on water resources (WR) is critical for a water basin’s mitigation. The present study intends to quantify the impact of (CC) and (LULC) on the streamflow (SF) of the Parvara Mula Basin (PMB) using SWAT. The SWAT model was calibrated and validated using the SWAT Calibration Uncertainty Program (SWAT-CUP) for the two time periods (2003–2007 and 2013–2016) and (2008–2010 and 2017–2018), respectively. To evaluate the model’s performance, statistical matrices such as R2, NSE, PBIAS, and RSR were computed for both the calibrated and validated periods. For both these periods, the calibrated and validated results of the model were found to be very good. In this study, three bias-corrected CMIP6 GCMs (ACCESS-CM2, BCC-CSM2-MR, and CanESM5) under three scenarios (ssp245, ssp370, and ssp585) have been adopted by assuming no change in the existing LULC (2018). The results obtained from the SWAT simulation at t...
Modeling Earth Systems and Environment, 2018
This study evaluates surface runoff generation under climate change scenarios for Ilala watershed in Northern highlands of Ethiopia. The climate change scenarios were analyzed using delta based statistical downscaling approach of RCPs 4.5 and 8.5 in R software packages. Hydrological response to climate changes were evaluated using the Soil and Water Assessment Tool model. The Soil Water Analysis Calibration and Uncertainty Program of Sequential Uncertainty fitting version 2 algorithm was also used to compute the uncertainty analysis, calibration and validation process. The results show that the minimum and maximum temperature increases for the future of 1.7 and 4.7 °C respectively. However, the rainfall doesn't show any significant increase or decrease trend in the study area. The 95% prediction uncertainty brackets the average values of observation by 71 and 74% during the calibration and validation processes, respectively. Similarly, R-factor equals to 0.5 and 0.6 during calibration and validation periods. The simulated and observed hydrographs of the total river yield showed a good agreement during calibration (NSE = 0.51, R 2 = 0.54) and validation (NSE = 0.54, R 2 = 0.63). From the total rainfall received only 6.2% portion of the rainfall was changed into surface runoff. The rainfall-runoff relationship was strongly correlated with R 2 = 0.97. Moreover, there had been also high evapotranspiration (ET) loss in the watershed; almost 75% of the total rainfall was lost as ET and 7.8% as ground water recharge. Due to an increase trend in temperature and evaporation loss for the future, the surface runoff also declined from 1.74% in RCP4.5 near-term to 0.36% in RCP8.5 end-term periods. This implies, proper planning and implementation of appropriate water management strategies is needed for sustainable water resources management in the region.
Journal of Water and Climate Change, 2020
Climate change impact on the hydrology of the Betwa river basin, located in the semi-arid region of Central India, was assessed using the Soil and Water Assessment Tool (SWAT), driven by hypothetical scenarios and Model of Interdisciplinary Research on Climate version 5 (MIROC5) Global Circulation Model projections. SWAT-Calibration and Uncertainty Programs (SWAT-CUP) was used for calibration and validation of SWAT using multi-site streamflow data. The coefficient of determination, Nash–Sutcliffe efficiency, RMSE-observations standard deviation ratio and percent bias during calibration and validation period varied from 0.83–0.92, 0.6–0.91, 0.3–0.63 and −19.8–19.3, respectively. MIROC5 projections revealed an increase in annual mean temperature in the range of 0.7–0.9 °C, 1.2–2.0 °C and 1.1–3.1 °C during the 2020s, 2050s, and 2080s, respectively. Rainfall is likely to increase in the range of 0.4–9.1% and 5.7–15.3% during the 2050s and 2080s, respectively. Simulation results indicate...
The Soan river basin lies near the vicinity of the capital city of Pakistan. It has monsoon every year, which is the major contributor of precipitation in this region, because of which the region has huge variations in the dry and rainy periods requiring the assessment of changes in water resources budget and hydrological regime. In this paper, the model performance has been evaluated for past (1981-2000) and future (2046-2065) by simulating against a reference data set, by using the internet based DIAS CMIP5 tool. The process includes selection of models from fifteen global climate models on the basis of the evaluation for relative distribution which is spatial correlation coefficient (Scorr) and evaluation of absolute value (RMSE). For the selected models, the bias correction is applied on the threshold data to get the corrected data by using APHRODITE precipitation data in DIAS CMIP5 tool. The obtained analysis results for precipitation are interpolated in ArcGIS tool by using kriging interpolation technique. The graphs are plotted for rainfall probability, monthly average rainfall analysis, annual total rain fall, extreme rain days and no rain days. The results from five global climate models show gradual increase in precipitation intensity in future where as two models show a rapid increase in precipitation intensity in future for Soan river basin. The monthly average rainfall analysis shows some variation in the past and future values. These variations are different for all models. The kriging interpolation for past and future shows that the upper Soan river basin will have more rainfall as compare to lower basin. The rainfall intensity is increasing with time so it is more for 200-year period as compare to 50-year period. The kriging interpolation results for the rainfall frequency of MIROC-5 model show huge increase in precipitation in future which is even more than twice as compare to the past values, so proper precautions should be taken against such an increase which may cause floods in future.
2015
The sign of climate change and its impact is revealing on different water resource system. The present study was conducted to understand the climate change impacts on surface water availability of Robigumer and Beressa River catchments in Jemma sub basin in Abbay Basin. The Soil and Water Assessment Tool (SWAT) model was applied to study the current (1984- 2008) and future scenarios (2026-2100) runoff magnitude in the catchments and associated uncertainty with the simulated outputs. The model was calibrated for the period of 1984 to 2000 and validated for the period of 2001-2008. The flow parameters that significantly limit the runoff in the catchment and the model uncertainty were assessed using SUFI2 in SWAT– CUP, Cn2, Esco, Canmx and Cn2, Esco and Blai, were the most significant parameter in Beressa and Robigumer catchment respectively. In the end, the future climate change impact studies on water availability of the catchments were done based on the outputs of the Regional Clima...
Water, 2019
The study aims to evaluate the long-term changes in meteorological parameters and to quantify their impacts on water resources of the Haro River watershed located on the upstream side of Khanpur Dam in Pakistan. The climate data was obtained from the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) for MIROC-ESM model under two Representative Concentration Pathway (RCP) scenarios. The model data was bias corrected and the performance of the bias correction was assessed statistically. Soil and Water Assessment Tool was used for the hydrological simulation of watershed followed by model calibration using Sequential Uncertainty Fitting version-2. The study is useful for devising strategies for future management of Khanpur Dam. The study indicated that in the future, at Murree station (P-1), the maximum temperature, minimum temperature and precipitation were anticipated to increase from 3.1 °C (RCP 4.5) to 4.0 °C (RCP 8.5), 3.2 °C (RCP 4.5) to 4.3 °C (RCP 8.5) and 8.6% ...
In the present study, the downscaled future climate data from the General Circulation Model (GCM), CanESM2 has been used to calculate the monthly crop water requirements of the major crops cultivated in the Jayakwadi command area, Maharashtra, India. Statistical downscaling was carried out using the statistical downscaling model and the future irrigation demands were estimated using the CROPWAT model. Statistical downscaling of the CanESM2 GCM model and prediction of the future temperature and precipitation was done for two representative concentration pathways (RCP) scenarios namely the RCP 4.5 and RCP 8.5. Further, the future irrigation demands were estimated under the RCP 4.5 and 8.5 scenarios for the period 2011-2100 with three-time spells of 30 years centered on the 2020s (2011-2040), 2050s (2041-2070), and 2080s (2071-2100). The results indicated an increase in temperature and precipitation over time spells when compared to the base period (1961-2005). The annual average temperature has been projected to increase by 0.306 °C and 0.358 °C by the 2080s when compared to the base period under the RCP 4.5 and RCP 8.5 scenarios, respectively. The annual average precipitation has been projected to increase from 856.58 mm in the base period to 1410.11 mm and 1784.06 mm under RCP 4.5 and RCP 8.5, respectively. The average reference evapotranspiration (ET o) values showed an increase from 5.41 mm/day to 5.45 mm/ day, 5.53 mm/day, and 5.57 mm/day for the periods 2020s, 2050s and 2080s respectively in the RCP 8.5 scenario. The average annual irrigation demand showed a reduction of 14.07% and 14.72% for RCP 4.5 and RCP 8.5 scenarios respectively. The estimated variations in demand values can be used for optimal irrigation planning in the culturable command area of the Jayakwadi reservoir.