Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration

Faramarzi, Monireh; Srinivasan, Raghavan; Iravani, Majid; Bladon, Kevin D.; Abbaspour, Karim C.; Zehnder, Alexander J. B.; Goss, Greg G.

doi:10.1016/j.envsoft.2015.09.006

Cited by 81 publications

(51 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, neglecting the uncertainty stemming from different sources of input data during calibration might produce outputs that are not appropriate or representative of real situations [8]. In other words, inappropriate input data (e.g., climate data with errors or incomplete values) can result in unrealistic model parameters [9], which will in turn produce unrealistic model outputs. Therefore, no matter how the model is used, it is always good to know how it performs based on different datasets [10].…”

Section: Introductionmentioning

confidence: 99%

“…Several studies have attempted to explore the sensitivity of hydrological models to land use [11,12], climate [9,13,14], or digital elevation models (DEM) [12,15]. Some studies conducted initial tests on the available data prior to calibration, then chose the data that appeared to perform the best based on certain model efficiency criteria [16,17].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

Kamali

Abbaspour

Yang

2017

Water

View full text Add to dashboard Cite

A large number of local and global databases for soil, land use, crops, and climate are now available from different sources, which often differ, even when addressing the same spatial and temporal resolutions. As the correct database is unknown, their impact on estimating water resource components (WRC) has mostly been ignored. Here, we study the uncertainty stemming from the use of multiple databases and their impacts on WRC estimates such as blue water and soil water for the Karkheh River Basin (KRB) in Iran. Four climate databases and two land use maps were used to build multiple configurations of the KRB model using the soil and water assessment tool (SWAT), which were similarly calibrated against monthly river discharges. We classified the configurations based on their calibration performances and estimated WRC for each one. The results showed significant differences in WRC estimates, even in models of the same class i.e., with similar performance after calibration. We concluded that a non-negligible level of uncertainty stems from the availability of different sources of input data. As the use of any one database among several produces questionable outputs, it is prudent for modelers to pay more attention to the selection of input data.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

Kamali

Abbaspour

Yang

2017

Water

View full text Add to dashboard Cite

show abstract

“…One of the three Canadian Prairie Provinces, Alberta has an area of about 661,000 km 2 that encompasses 17 river basins principally originating from the east slopes of the Canadian Rockies, and that drain eastward to Hudson Bay through the provinces of Saskatchewan and Manitoba or northward to the Arctic Ocean [48]. Alberta has a relatively dry climate.…”

Section: Study Area Hydrologic Model and Data Overviewmentioning

confidence: 99%

“…The stream flow data used for the study are daily average discharges as simulated by the SWAT model [48]. Input variables for the SWAT hydrologic model of Alberta have been carefully selected to represent the actual physical processes related to natural and anthropogenic features (e.g., snow, potholes, glaciers, reservoirs, dams, and irrigated agriculture), and to minimize input data uncertainties [48].…”

Section: Study Area Hydrologic Model and Data Overviewmentioning

confidence: 99%

“…Input variables for the SWAT hydrologic model of Alberta have been carefully selected to represent the actual physical processes related to natural and anthropogenic features (e.g., snow, potholes, glaciers, reservoirs, dams, and irrigated agriculture), and to minimize input data uncertainties [48]. The model has been extensively calibrated and validated using the discharge data of about 130 hydrometric stations for the 1983-2007 period in the province [47] (See Table S1), and can simulate stream flow and other water resource components in 2255 sub-basins across the province.…”

Section: Study Area Hydrologic Model and Data Overviewmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of the Combined Effects of Threshold Selection and Parameter Estimation of Generalized Pareto Distribution with Applications to Flood Frequency Analysis

Gharib

Davies

Goss

et al. 2017

Water

Self Cite

View full text Add to dashboard Cite

Abstract:Floods are costly natural disasters that are projected to increase in severity and frequency into the future. Exceedances over a high threshold and analysis of their distributions, as determined through the Peak Over Threshold (POT) method and approximated by a Generalized Pareto Distribution (GPD), respectively, are widely used for flood frequency analysis. This study investigates the combined effects of threshold selection and GPD parameter estimation on the accuracy of flood quantile estimates, and develops a new, widely-applicable framework that significantly improves the accuracy of flood quantile estimations. First, the performance of several parameter estimators (i.e., Maximum Likelihood; Probability Weighted Moments; Maximum Goodness of Fit; Likelihood Moment; Modified Likelihood Moment; and Nonlinear Weighted Least Square Error) for the GPD was compared through Monte Carlo simulation. Then, a calibrated Soil and Water Assessment Tool (SWAT) model for the province of Alberta, Canada, was used to reproduce daily streamflow series for 47 watersheds distributed across the province, and the POT was applied to each. The Goodness of Fit for the resulting flood frequency models was measured by the upper tail Anderson-Darling (AD) test and the root-mean-square error (RMSE) and demonstrated improvements for more than one-third of stations by averages of 65% (AD) and 47% (RMSE), respectively.

show abstract

Effectiveness of Soil and Water Conservation Practices Under Climate Change in the Gorganroud Basin, Iran

Azari

Saghafian

Moradi

et al. 2017

CLEAN Soil Air Water

Self Cite

View full text Add to dashboard Cite

Assessing the effectiveness of conservation practices under changed climatic conditions has proven to be invaluable in selecting the adaptation practices. Conservationists are concerned that past effective practices may no longer be effective in the future climate change. This research is aimed at assessing the effectiveness of soil and water conservation practices under future climate change, with respect to sediment yield leaving a watershed. For this purpose, the Soil and Water Assessment Tool, SWAT, was applied to simulate various climate change scenarios with three soil and water conservation practices to assess possible changes in stream flow, and sediment yield of the Gorganroud watershed in the northern part of Iran. Study results demonstrated that the impact of climate change in the increase of watershed sediment yield is more than the stream flow and varies from 35.9 to 47.7% for the period 2040-2069. Implementing conservation practices under climate change can reduce the sediment yield of watershed up to 7.2% and for the sub-basin scale up to 46.4%. Range management practices were found to be the most effective practice in the decrease of sediment at the sub-basin scale and porous gully plugs and terrace construction, the most effective at the watershed scale. The results indicate that soil and water conservation practices will be more effective at reducing sediment yields under anticipated future climates. Though, implementation of each conservation practice solely was not sufficient to compensate for climate change-driven increases in sediment yield. This study provides valuable information for watershed managers and decision makers regarding selection of soil and water conservation practices for adaptation to climate change.

show abstract

Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration

Cited by 81 publications

References 63 publications

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

Assessment of the Combined Effects of Threshold Selection and Parameter Estimation of Generalized Pareto Distribution with Applications to Flood Frequency Analysis

Effectiveness of Soil and Water Conservation Practices Under Climate Change in the Gorganroud Basin, Iran

Contact Info

Product

Resources

About