scholarly journals Estimating the role of climate internal variability and source of uncertainties in hydrological climate-impact projections

Author(s):  
Wenjun Cai ◽  
Jia Liu ◽  
Xueping Zhu ◽  
Xuehua Zhao

Abstract Hydrological climate-impact projections in future are limited by large uncertainties from various sources. Therefore, this study aimed to explore and estimate the sources of uncertainties involved in climate changing impacted assessment in a representative watershed of Northeastern China. Moreover, recent researches indicated that the climate internal variability (CIV) plays an important role in various of hydrological climate-impact projections. Six downscaled Global climate models (GCMs) under two emission scenarios and a calibrate Soil and Water Assessment Tool (SWAT) model were used to obtain hydrological projections in future periods. The CIV and signal-to-noise ratio (SNR) are investigated to analyze the the role of internal variability in hydrological projections. The results shows that the internal variability shows a considerable influence on hydrological projections, which need be partitioned and quantified particularly. Moreover, it worth noting the CIV can propagate from precipitation and ET to runoff projections through the hydrological simulation process. In order to partition the CIV and sources of uncertainties, the uncertainty decomposed frameworks based on analysis of variance (ANOVA) are established. The results demonstrate that the CIV and GCMs are the dominate contributors of runoff in rainy season. In contrast, the CIV and SWAT model parameter sets provided obvious uncertainty to runoff in January to May and October to December. The findings of this study advised that the uncertainty is complex in hydrological simulation process hence, it is meaning and necessary to estimate the uncertainty in climate simulation process, the uncertainty analysis results can provide effectively efforts to reduce uncertainty and then give some positive suggestions to stakeholders for adaption countermeasure under climate change.

2021 ◽  
Author(s):  
Wenjun Cai ◽  
Xueping Zhu ◽  
Xuehua Zhao ◽  
Yongbo Zhang

Abstract The decomposition and quantification of uncertainty sources in ensembles of climate-hydrological simulation chains is a key issue in climate impact researches. The mainly objectives of this study partitioning climate internal variability (CIV) and uncertainty sources in the climate-hydrological projections simulation process, the climate simulation process formed by six downscaled GCMs under two emission scenarios called GCMs-ES simulation chain, the hydrological simulation process add one calibrate Soil and Water Assessment Tool (SWAT) model called GCMs-ES-HM simulation chain. The CIV and external forcing of climate projections are investigated in each GCMs-ES simulation chain. The CIV of precipitation and ET are large in rainy season, and the single-to-noise ratio (SNR) are also relatively high in rainy season. Furthermore, the uncertainty decomposed frameworks based on analysis of variance (ANOVA) are established. The CIV and GCMs are the dominate contributors of runoff in rainy season. It worth noting the CIV can propagate from precipitation and ET to runoff projections. In additional, the hydrological model parameters are the third uncertainty contributor of runoff, which embody the hydrological model simulate process play important role in hydrological projections in future. The findings of this study advised that the uncertainty is complex in hydrological, hence, it is meaning and necessary to estimate the uncertainty in climate simulation process, the uncertainty analysis results can provide effectively efforts to reduce uncertainty and then give some positive suggestions to stakeholders for adaption countermeasure under climate change.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.


Author(s):  
Amina Mami ◽  
Djilali Yebdri ◽  
Sabine Sauvage ◽  
Mélanie Raimonet ◽  
José Miguel

Abstract Climate change is expected to increase in the future in the Mediterranean region, including Algeria. The Tafna basin, vulnerable to drought, is one of the most important catchments ensuring water self-sufficiency in northwestern Algeria. The objective of this study is to estimate the evolution of hydrological components of the Tafna basin, throughout 2020–2099, comparing to the period 1981–2000. The SWAT model (Soil and Water Assessment Tool), calibrated and validated on the Tafna basin with good Nash at the outlet 0.82, is applied to analyze the spatial and temporal evolution of hydrological components, over the basin throughout 2020–2099. The application is produced using a precipitation and temperature minimum/maximum of an ensemble of climate model outputs obtained from a combination of eight global climate models and two regional climate models of Coordinated Regional Climate Downscaling Experiment project. The results of this study show that the decrease of precipitation in January, on average −25%, ranged between −5% and −44% in the future. This diminution affects all of the water components and fluxes of a watershed, namely, in descending order of impact: the river discharge causing a decrease −36%, the soil water available −31%, the evapotranspiration −30%, and the lateral flow −29%.


2017 ◽  
Vol 50 (1) ◽  
pp. 117-137 ◽  
Author(s):  
Vishal Singh ◽  
Ashutosh Sharma ◽  
Manish Kumar Goyal

Abstract Here, a regional climate model (RCM) RegCM4 and Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models (GCMs) such as Coupled Physical Model (CM3), Coupled Climate Model phase 1 (CM2P1) and Earth System Model (ESM-2M) with their representative concentration pathway (RCP) datasets were utilized in projecting hydro-climatological variables such as precipitation, temperature, and streamflow in Teesta River basin in north Sikkim, eastern Himalaya, India. For downscaling, a ‘predictor selection analysis’ was performed utilizing a statistical downscaling model. The precision and applicability of RCM and GCM datasets were assessed using several statistical evaluation functions. The downscaled temperature and precipitation datasets were used in the Soil and Water Assessment Tool (SWAT) model for projecting the water yield and streamflow. A Sequential Uncertainty Parameter Fitting 2 optimization algorithm was used for optimizing the coefficient parameter values. The Mann–Kendall test results showed increasing trend in projected temperature and precipitation for future time. A significant increase in minimum temperature was found for the projected scenarios. The SWAT model-based projected outcomes showed a substantial increase in the streamflow and water yield. The results provide an understanding about the hydro-climatological data uncertainties and future changes associated with hydrological components that could be expected because of climate change.


Author(s):  
Srishti Gaur ◽  
Arnab Bandyopadhyay ◽  
Rajendra Singh

Abstract This study presents climate change impacts on streamflow for the Subarnarekha basin at two gauging locations, Jamshedpur and Ghatshila, using the Soil and Water Assessment Tool (SWAT) model driven by an ensemble of four regional climate models (RCMs). The basin's hydrological responses to climate forcing in the projected period are analysed under two representative concentration pathways (RCPs). Trends in the projected period relative to the reference period are determined for medium, high and low flows. Flood characteristics are estimated using the threshold level approach. The analysis of variance technique (ANOVA) is used to segregate the contribution from RCMs, RCPs, and internal variability (IV) to the total uncertainty in streamflow projections. Results show a robust positive trend for streamflows. Flood volumes may increase by 11.7% in RCP4.5 (2006–2030), 76.4% in RCP4.5 (2025–2049), 20.3% in RCP8.5 (2006–2030), and 342.4% in RCP8.5 (2025–2049), respectively, for Jamshedpur. For Ghatshila, increment in flow volume is estimated as 15.7% in RCP4.5 (2006–2025), 24.2% in RCP4.5 (2025–2049), 35.9% in RCP8.5 (2006–2030), and 224.6% in RCP8.5 (2025–2049), respectively. Segregation results suggests that the uncertainty in climate prediction is dominated by RCMs followed by IV. These findings will serve as an early warning for the alarming extreme weather events India is currently facing.


2020 ◽  
Vol 13 ◽  
pp. 1-8
Author(s):  
Kingsley Nnaemeka Ogbu ◽  
Emeka L Ndulue ◽  
Isiguzo Edwin Ahaneku ◽  
Ikenna Joseph Ubah

The Soil and Water Assessment Tool (SWAT) model was applied in this study to simulate stream-flow in the Oyun River Basin. The model was calibrated and validated using monthly stream-flow data for the basin. Model performance was satisfactory for calibration and validation with a coefficient of determination (R2) of 0.69 and 0.88, respectively. Climate change impact on Oyun River was assessed by driving the SWAT model with climate parameters obtained from two global climate models (HadGEM2-ES and BCC-CCSM1-1M) based on RCP 2.6 for 2050 – 2059 and 2080 – 2089 periods. With respect to a baseline period of 2000 – 2009, HadGEM2-ES predicted a 4.62% decrease in total stream-flow while the BCC-CSM1-1M predicted stream-flow increase by 6.18% for the 2050 – 2059 period. However, both HadGEM2-ES and BCC-CCSM1-1M predicted stream-flow to increase by 18.92% and 11.25% respectively for the 2080 period. The HadGEM2-ES model showed consistency in relating future rainfall predictions with future discharge trends for the periods under study. Model results show the need for adaptive measures to mitigate climate change impacts on the water resource system.


2018 ◽  
Vol 49 (3) ◽  
pp. 908-923 ◽  
Author(s):  
Richarde Marques da Silva ◽  
José Carlos Dantas ◽  
Joyce de Araújo Beltrão ◽  
Celso A. G. Santos

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.


Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 253 ◽  
Author(s):  
Dandan Guo ◽  
Hantao Wang ◽  
Xiaoxiao Zhang ◽  
Guodong Liu

Highly accurate and high-quality precipitation products that can act as substitutes for ground precipitation observations have important significance for research development in the meteorology and hydrology of river basins. In this paper, statistical analysis methods were employed to quantitatively assess the usage accuracy of three precipitation products, China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), next-generation Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), for the Jinsha River Basin, a region characterized by a large spatial scale and complex terrain. The results of statistical analysis show that the three kinds of data have relatively high accuracy on the average grid scale and the correlation coefficients are all greater than 0.8 (CMADS:0.86, IMERG:0.88 and TMPA:0.81). The performance in the average grid scale is superior than that in grid scale. (CMADS: 0.86(basin), 0.6 (grid); IMERG:0.88 (basin),0.71(grid); TMPA:0.81(basin),0.42(grid)). According to the results of hydrological applicability analysis based on SWAT model, the three kinds of data fail to obtain higher accuracy on hydrological simulation. CMADS performs best (NSE:0.55), followed by TMPA (NSE:0.50) and IMERG (NSE:0.45) in the last. On the whole, the three types of satellite precipitation data have high accuracy on statistical analysis and average accuracy on hydrological simulation in the Jinsha River Basin, which have certain hydrological application potential.


2015 ◽  
Vol 16 (2) ◽  
pp. 762-780 ◽  
Author(s):  
Pablo A. Mendoza ◽  
Martyn P. Clark ◽  
Naoki Mizukami ◽  
Andrew J. Newman ◽  
Michael Barlage ◽  
...  

Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located in the Colorado headwaters region, using four different hydrologic model structures [PRMS, VIC, Noah LSM, and Noah LSM with multiparameterization options (Noah-MP)]. To better understand the role of parameter estimation, model performance and projected hydrologic changes (i.e., changes in the hydrology obtained from hydrologic models due to climate change) are compared before and after calibration with the University of Arizona shuffled complex evolution (SCE-UA) algorithm. Hydrologic changes are examined via a climate change scenario where the Community Climate System Model (CCSM) change signal is used to perturb the boundary conditions of the Weather Research and Forecasting (WRF) Model configured at 4-km resolution. Substantial intermodel differences (i.e., discrepancies between hydrologic models) in the portrayal of climate change impacts on water resources are demonstrated. Specifically, intermodel differences are larger than the mean signal from the CCSM–WRF climate scenario examined, even after the calibration process. Importantly, traditional single-objective calibration techniques aimed to reduce errors in runoff simulations do not necessarily improve intermodel agreement (i.e., same outputs from different hydrologic models) in projected changes of some hydrological processes such as evapotranspiration or snowpack.


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