scholarly journals Estimating the Effect of Climate Internal Variability and Source of Uncertainty in Climate-Hydrological Projections in a Representative Watershed of Northeastern China

2021 ◽  
Author(s):  
Wenjun Cai ◽  
Xueping Zhu ◽  
Xuehua Zhao ◽  
Yongbo Zhang
Keyword(s):  
Rainy Season ◽  
Hydrological Model ◽  
Swat Model ◽  
Internal Variability ◽  
Climate Simulation ◽  
Model Parameters ◽  
Climate Projections ◽  
Hydrological Simulation ◽  
Simulation Process ◽  
Uncertainty Sources

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.

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

2021 ◽  
Author(s):  
Wenjun Cai ◽  
Jia Liu ◽  
Xueping Zhu ◽  
Xuehua Zhao
Keyword(s):  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Internal Variability ◽  
Climate Impact ◽  
Global Climate Models ◽  
Climate Simulation ◽  
Hydrological Simulation ◽  
Simulation Process

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.

scholarly journals Uncertainty analysis in model parameters regionalization: a case study involving the SWAT model in Mediterranean catchments (Southern France)

2014 ◽  
Vol 18 (6) ◽  
pp. 2393-2413 ◽  
Author(s):  
H. Sellami ◽  
I. La Jeunesse ◽  
S. Benabdallah ◽  
N. Baghdadi ◽  
M. Vanclooster
Keyword(s):  
Model Prediction ◽  
Hydrological Model ◽  
Swat Model ◽  
Behavioral Model ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Southern France ◽  
Model Parameter ◽  
Ungauged Catchment ◽  
Prediction Uncertainty

Abstract. In this study a method for propagating the hydrological model uncertainty in discharge predictions of ungauged Mediterranean catchments using a model parameter regionalization approach is presented. The method is developed and tested for the Thau catchment located in Southern France using the SWAT hydrological model. Regionalization of model parameters, based on physical similarity measured between gauged and ungauged catchment attributes, is a popular methodology for discharge prediction in ungauged basins, but it is often confronted with an arbitrary criterion for selecting the "behavioral" model parameter sets (Mps) at the gauged catchment. A more objective method is provided in this paper where the transferrable Mps are selected based on the similarity between the donor and the receptor catchments. In addition, the method allows propagating the modeling uncertainty while transferring the Mps to the ungauged catchments. Results indicate that physically similar catchments located within the same geographic and climatic region may exhibit similar hydrological behavior and can also be affected by similar model prediction uncertainty. Furthermore, the results suggest that model prediction uncertainty at the ungauged catchment increases as the dissimilarity between the donor and the receptor catchments increases. The methodology presented in this paper can be replicated and used in regionalization of any hydrological model parameters for estimating streamflow at ungauged catchment.

scholarly journals Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium

2004 ◽  
Vol 8 (5) ◽  
pp. 931-939 ◽  
Author(s):  
G. Heuvelmans ◽  
B. Muys ◽  
J. Feyen
Keyword(s):  
Stream Flow ◽  
Hydrological Model ◽  
Swat Model ◽  
Single Parameter ◽  
Model Parameters ◽  
Study Region ◽  
Entire Study ◽  
Time Periods ◽  
Parameter Values ◽  
Parameter Approach

Abstract. Operational applications of a hydrological model often require the prediction of stream flow in (future) time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders), with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the simulation of a large river basin. Keywords: hydrological model, regionalisation, parameterisation, spatial variability

Study on Hydrological Simulation of Jin River Based on SWAT-X Model

2011 ◽  
Vol 84-85 ◽  
pp. 238-243
Author(s):  
Yu Jie Fang ◽  
Wen Bin Zhou ◽  
Ding Gui Luo
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Parameters ◽  
Parameter Sensitivity Analysis ◽  
Hydrological Simulation ◽  
Resources Management ◽  
Using Data ◽  
Sensitive Parameters ◽  
Water Assessment

Hydrological simulation is the basis of water resources management and utilization. In this study, Soil and Water Assessment Tool (SWAT) model was applied to Jin River Basin for hydrological simulation on ArcView3.3 platform. The basic database of Jin river Basin was built using ArcGis9.2. Based on the LH-OAT parameter sensitivity analysis, the sensitive parameters of runoff were identified, including CN2, Gwqmn, rchrg_dp, ESCO, sol_z, SLOPE, SOL_AWC, sol_k, Gwrevap, and then model parameters related to runoff were calibrated and validated using data observed in weifang, yifeng, shanggao and gaoan hydrological stations during 2001-2008. The simulation showed that the simulated values were reasonably comparable to the observed data (Re<20%, R2 >0.7 and Nash-suttcliffe > 0.7), suggesting the validity of SWAT model in Jin River Basin.

scholarly journals Hydrological model optimization using multi-gauge calibration (MGC) in a mountainous region

2020 ◽  
Author(s):  
Sead Ahmed Swalih ◽  
Ercan Kahya
Keyword(s):  
Climate Change ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Spatial Dimension ◽  
Model Parameters ◽  
Climate Projections ◽  
Predictive Capacity ◽  
Black Sea Region ◽  
The Impact

Abstract It is a challenge for hydrological models to capture complex processes in a basin with limited data when estimating model parameters. This study aims to contribute in this field by assessing the impact of incorporating spatial dimension on the improvement of model calibration. Hence, the main objective of this study was to evaluate the impact of multi-gauge calibration in hydrological model calibration for Ikizdere basin, Black Sea Region in Turkey. In addition, we have incorporated the climate change impact assessment for the study area. Four scenarios were tested for performance assessment of calibration: (1) using downstream flow data (DC), (2) using upstream data (UC), (3) using upstream and downstream data (Multi-Gauge Calibration – MGC), and (4) using upstream and then downstream data (UCDC). The results have shown that using individual gauges for calibration (1 and 2) improve the local predictive capacity of the model. MGC calibration significantly improved the model performance for the whole basin unlike 1 and 2. However, the local gauge calibrations statistical performance, compared to MGC outputs, was better for local areas. The UCDC yields the best model performance and much improved predictive capacity. Regarding the climate change, we did not observe an agreement amongst the future climate projections for the basin towards the end of the century.

scholarly journals Partitioning Uncertainty Components of an Incomplete Ensemble of Climate Projections Using Data Augmentation

2019 ◽  
Vol 32 (8) ◽  
pp. 2423-2440 ◽  
Author(s):  
Guillaume Evin ◽  
Benoit Hingray ◽  
Juliette Blanchet ◽  
Nicolas Eckert ◽  
Samuel Morin ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Data Augmentation ◽  
Climate Model ◽  
Internal Variability ◽  
Climate Impact ◽  
Climate Projections ◽  
Model Combination ◽  
Uncertainty Sources ◽  
Climate Change Responses ◽  
Impact Models

Abstract The quantification of uncertainty sources in ensembles of climate projections obtained from combinations of different scenarios and climate and impact models is a key issue in climate impact studies. The small size of the ensembles of simulation chains and their incomplete sampling of scenario and climate model combinations makes the analysis difficult. In the popular single-time ANOVA approach for instance, a precise estimate of internal variability requires multiple members for each simulation chain (e.g., each emission scenario–climate model combination), but multiple members are typically available for a few chains only. In most ensembles also, a precise partition of model uncertainty components is not possible because the matrix of available scenario/models combinations is incomplete (i.e., projections are missing for many scenario–model combinations). The method we present here, based on data augmentation and Bayesian techniques, overcomes such limitations and makes the statistical analysis possible for single-member and incomplete ensembles. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. This approach is illustrated for projections of regional precipitation and temperature for four mountain massifs in France. It is applicable for any kind of ensemble of climate projections, including those produced from ad hoc impact models.

scholarly journals Uncertainty analysis of a spatially-distributed hydrological model with rainfall multipliers

2016 ◽  
Vol 43 (12) ◽  
pp. 1062-1074 ◽  
Author(s):  
Arpana Rani Datta ◽  
Tirupati Bolisetti
Keyword(s):  
Uncertainty Analysis ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Error Model ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Input Uncertainty ◽  
Spatially Distributed ◽  
Input Error

This paper has developed an input error model to account for input uncertainty, and applied the rainfall multiplier approaches to the calibration and uncertainty analysis of Soil and Water Assessment Tool (SWAT), a spatially-distributed hydrological model. The developed input error model has introduced the season-dependent rainfall multipliers to the Bayesian framework and reduced the dimension of the posterior probability density function. The method is applied to a watershed located in Southwestern Ontario, Canada. The results of the developed method are compared with two other methods. The SWAT model parameters and the input error model parameters are jointly inferred by a Markov chain Monte Carlo sampler. The results show the measured precipitation data overestimates the true precipitation values for the study area. The uncertainty in model prediction is underestimated for high flows and overestimated for low flows. There is no significant change in the estimation of parameter uncertainty and streamflow prediction uncertainty in the developed method from those in the other methods. The study emphasizes that the rainfall multiplier approaches are applicable to spatially-distributed hydrological modelling for accounting of input uncertainty.

scholarly journals Effect of watershed subdivision and estimation of climatic variables on hydrological simulation with the swat model in semi-arid mediterranean basins

2018 ◽  
pp. 114-133
Author(s):  
Francisco Gomariz Castillo ◽  
Francisco Alonso Sarría
Keyword(s):  
Input Data ◽  
Hydrological Model ◽  
Swat Model ◽  
Climatic Variables ◽  
Climate Information ◽  
Hydrological Simulation ◽  
Hargreaves Model ◽  
Discretization Schemes ◽  
The Usa ◽  
Semi Arid

Los resultados de cualquier intento de modelización hidrológica dependen de la calidad y discretización de los datos de entrada. En este trabajo se evalúa cómo la utilización de diferentes capas de variables climáticas de entrada (precipitación y ETP) y diferentes esquemas de discretización de la cuenca influyen en los resultados de un modelo hidrológico bien conocido (SWAT). En concreto se prueban 4 conjuntos de variables de entrada y discretización. Los estadísticos utilizados para evaluar la exactitud obtenida con estos conjuntos son RMSE, PBIAS, NSE y r2. Los resultados muestran que el uso de mejores modelos para obtener series de ETP (Penman Monteith FAO o Hargreaves calibrado) mejora considerablemente la exactitud del modelo respecto a las series obtenidas con el modelo de Hargreaves sin calibrar (opción por defecto en SWAT). Sin embargo, no se aprecian diferencias entre los resultados obtenidos con Penman Monteith FAO y Hargreaves calibrado. Por otro lado, el uso de información climática distribuida mejora notablemente los resultados obtenidos con información agregada. Se observa también la necesidad de calibrar los parámetros de SWAT ya que los valores por defecto están optimizados para ambientes templados de EEUU. The results of hydrological modelling depend on the quality and spatial resolution of the input data. This paper evaluates how the use of different estimations of climatic variables input layers (precipitation and ET P ) and different basin discretization schemes influence affect the results of a contrasted hydrological model (SWAT). Specifically, 4 se ts of input and discretization variables are tested. The statistics used to evaluate the accuracy obtained with these sets are RMSE, PBIAS, NSE and r 2 . The results show that the use of better models to obtain ET P series (Penman Monteith FAO or calibrated Hargreaves) considerably improves the accuracy of the model compared to the series obtained with the uncalibrated Hargreaves model (default option in SWAT). However, there is no difference between the results obtained with Penman Monteith FAO and calibrate d Hargreaves. On the other hand, the use of distributed climate information significantly improves the results obtained with aggregated information. There is also a need to calibrate SWAT parameters as the default values are optimized for temperate environ ments in the USA.

scholarly journals Improved Model Parameter Transferability Method for Hydrological Simulation with SWAT in Ungauged Mountainous Catchments

2020 ◽  
Vol 12 (9) ◽  
pp. 3551 ◽  
Author(s):  
Fanhao Meng ◽  
Chula Sa ◽  
Tie Liu ◽  
Min Luo ◽  
Jiao Liu ◽  
...  
Keyword(s):  
Water Resources ◽  
Swat Model ◽  
Model Parameters ◽  
Mountainous Areas ◽  
Hydrological Simulation ◽  
Appearance Time ◽  
Model Parameter ◽  
Mountainous Catchments ◽  
Improved Model ◽  
Catchment Model

The sustainability of water resources in mountainous areas has a significant contribution to the stabilization and persistence of the ecological and agriculture systems in arid and semi-arid areas. However, the insufficient understanding of hydrological processes in ungauged mountainous catchments (UMCs) is not able to scientifically support the sustainable management of water resources. The conventional parameter transferability method (transplanting the parameters of the donor catchment model with similar distances or attributes to the target catchment model) still has great potential for improving the accuracy of the hydrological simulation in UMC. In this study, 46 river catchments, with discharge survey stations and multi-type catchment characteristics in Xinjiang, are separated into the target catchments and donor catchments to promote an improved model parameter transferability method (IMPTM). This method synthetically processes the SWAT model parameters based on the distance approximation principle (DAP) and the attribute similarity principle (ASP). The performance of this method is tested in a random gauged catchment and compared with other traditional methods (DAP and ASP). The daily runoff simulation results in the target catchment have relatively low accuracy by both the DAP method ( N S = 0.27, R 2 = 0.55) and ASP method ( N S = 0.36, R 2 = 0.65), which implies the conventional approach is not capable of processing the parameters in the target regions. However, the simulation result by IMPTM is a significant improvement ( N S = 0.69, R 2 = 0.85). Moreover, the IMPTM can accurately catch the flow peak, appearance time, and recession curve. The current study provides a compatible method to overcome the difficulties of hydrological simulation in UMCs in the world and can benefit hydrological forecasting and water resource estimation in mountainous areas.

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