Saman Razavi

Saman Razavi
University of Saskatchewan | U of S · School of Environment and Sustainability

PhD

About

121
Publications
28,940
Reads
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2,821
Citations
Additional affiliations
November 2014 - present
University of Saskatchewan
Position
  • Professor (Assistant)
May 2013 - October 2014
University of Saskatchewan
Position
  • PostDoc Position
September 2008 - April 2013
University of Waterloo
Position
  • PhD Student

Publications

Publications (121)
Article
Full-text available
The Global Environmental Multiscale Model (GEM) is currently in operational use for data assimilation and forecasting at 25–15 km scales; regional 10 km scales over North America; and 2.5 km scales over Canada. To evaluate the GEM model for forecasting applications in Iran, global daily temperature and precipitation outputs of GEM at a 25 km scale...
Preprint
While conflict-and-cooperation phenomena in transboundary basins have been widely studied, much less work has been devoted to representing the process interactions in a quantitative way. This paper identifies the main factors in the riparian countries’ willingness to cooperate in the Eastern Nile River Basin, involving Ethiopia, Sudan, and Egypt, f...
Poster
Full-text available
Abstract submission is now open for the 10th International Conference on Sensitivity Analysis of Model Output (SAMO). The conference will be held at Florida State University, Tallahassee, Florida. The dates of the conference are March 14 -16, 2022, at the Florida State Conference Center. See: https://samo2022.math.fsu.edu/
Article
Full-text available
Cold regions provide water resources for half the global population yet face rapid change. Their hydrology is dominated by snow, ice and frozen soils, and climate warming is having profound effects. Hydrological models have a key role in predicting changing water resources but are challenged in cold regions. Ground‐based data to quantify meteorolog...
Article
Permafrost thaw has been observed in recent decades in the Northern Hemisphere and is expected to accelerate with continued global warming. Predicting the future of permafrost requires proper representation of the interrelated surface/subsurface thermal and hydrologic regimes. Land surface models (LSMs) are well suited for such predictions, as they...
Article
Full-text available
Highlights • Advances of science and policy has deep but informal roots in sensitivity analysis. • Modern sensitivity analysis is now evolving into a formal and independent discipline. • New areas such data science and machine learning benefit from sensitivity analysis. • Challenges, methodological progress, and outlook are outlined in this specia...
Article
Sensitivity analysis (SA) as a ‘formal’ and ‘standard’ component of scientific development and policy support is relatively young. Many researchers and practitioners from a wide range of disciplines have contributed to SA over the last three decades, and the SAMO (sensitivity analysis of model output) conferences, since 1995, have been the primary...
Article
Recent breakthroughs in artificial intelligence (AI), and particularly in deep learning (DL), have created tremendous excitement and opportunities in the earth and environmental sciences communities. To leverage these new ‘data-driven’ technologies, however, one needs to understand the fundamental concepts that give rise to DL and how they differ f...
Article
In this study, we develop a seamless hydro-economic modelling framework for river-basin scales by integrating a water resources system model and an economic model. This framework allows for the representation of both local-scale features, such as reservoirs, diversions, and water licenses and priorities, and regional- and provincial-scale features,...
Preprint
Full-text available
Cold regions provide water resources for half the global population yet face rapid change. Their hydrology is dominated by snow, ice and frozen soils, and climate warming is having profound effects. Hydrological models have a key role in predicting changing water resources, but are challenged in cold regions. Ground-based data to quantify meteorolo...
Article
Full-text available
Hydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequence of the Great Lakes Runoff Intercomparison Projects. The densely populated Lake Erie watershed studied here is an important international lake that has experie...
Article
Modernizing traditional irrigation systems has long been recognized as a means to reduce water losses. However, empirical evidence shows that this practice may not necessarily reduce water use in the long run; in fact, in many cases, the converse is true—a concept known as the rebound phenomenon. This phenomenon is at the heart of a fundamental res...
Preprint
Full-text available
Permafrost thaw has been observed in recent decades in the Northern Hemisphere and is expected to accelerate with continued global warming. Predicting the future of permafrost requires proper representation of the interrelated surface/subsurface thermal and hydrologic regimes. Land surface models (LSMs) are well suited for such predictions, as they...
Article
Full-text available
The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding...
Conference Paper
Full-text available
This presentation first provides an overview of a recent opinion piece by the author published in University Affairs, titled “Celebrate diversity, embrace equity and cultivate inclusion”, and then reviews anonymously some of the feedbacks the author received from the community. A main message is that diversity is easy to define and measure, and thu...
Preprint
Full-text available
The Global Environmental Multiscale Model (GEM) is an integrated forecasting and data assimilation system developed by Environment and Climate Change Canada. The model is currently in operational use for data assimilation and forecasting at global 25 km to 15 km scales; regional 10 km scales over North America; and 2.5 km scales over Canada. To dem...
Article
Full-text available
The uprisings in the wake of George Floyd’s tragic death in the U.S. last May have revealed once again the deep-seated challenges society faces in aspiring to equity, diversity and inclusion (EDI) principles. These challenges, sadly but not surprisingly, afflict academia and professional environments as well, which typically champion change for a b...
Article
Full-text available
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of...
Article
Snowmelt is a major driver of the hydrological cycle in cold regions, as such, its accurate representation in hydrological models is key to both regional snow depth and streamflow prediction. The choice of a proper method for snowmelt representation is often improvised; however, a thorough characterization of uncertainty in such process representat...
Article
Accurate estimation of snow mass or snow water equivalent (SWE) over space and time is required for global and regional predictions of the effects of climate change. This work investigates whether integration of remotely sensed terrestrial water storage (TWS) information, which is derived from the Gravity Recovery and Climate Experiment (GRACE), ca...
Article
Full-text available
Sensitivity analysis in Earth and environmental systems modeling typically demands an onerous computational cost. This issue coexists with the reliance of these algorithms on ad hoc designs of experiments, which hampers making the most out of the existing data sets. We tackle this problem by introducing a method for sensitivity analysis, based on t...
Preprint
Full-text available
The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society, yet limited by lack of understanding...
Article
Full-text available
Global sensitivity analysis (GSA) provides essential insights into the behavior of Earth and environmental systems models and identifies dominant controls of output uncertainty. Previous work on GSA, however, has typically been under the assumption that the controlling factors such as model inputs and parameters are independent, whereas, in many ca...
Article
Full-text available
Permafrost is an important feature of cold-region hydrology, particularly in river basins such as the Macken-zie River basin (MRB), and it needs to be properly represented in hydrological and land surface models (H-LSMs) built into existing Earth system models (ESMs), especially under the unprecedented climate warming trends that have been observed...
Conference Paper
The Great Lakes Runoff Inter-comparison Project (GRIP) includes a wide range of lumped and distributed models that are used operationally and/or for research purposes across Canada and the United States. Participating models are GEM-Hydro, WRF-Hydro, MESH, VIC, WATFLOOD, Noah-MP, HYPE, LBRM, GR4J, and a purely statistical model. As part of the Inte...
Article
Full-text available
Complex, software-intensive, technically advanced, and computationally demanding models, presumably with ever-growing realism and fidelity, have been widely used to simulate and predict the dynamics of the Earth and environmental systems. The parameter-induced simulation crash (failure) problem is typical across most of these models despite conside...
Article
Full-text available
Reservoirs significantly affect flow regimes in watershed systems by changing the magnitude and timing of streamflows. Failure to represent these effects limits the performance of hydrological and land-surface models (H-LSMs) in the many highly regulated basins across the globe and limits the applicability of such models to investigate the futures...
Presentation
Global and regional predictions of future climate depend on the reliable estimation of snow mass or snow water equivalent (SWE). Acquiring the accurate estimation of SWE over space and time is challenging. Because of the limitations of ground-based methods to characterize the snowpack, especially in areas with high snow spatial variability, both sa...
Article
Identifiability is a fundamental concept in parameter estimation, and therefore key to the large majority of environmental modeling applications. Parameter identifiability analysis assesses whether it is theoretically possible to estimate unique parameter values from data, given the quantities measured, conditions present in the forcing data, model...
Article
Full-text available
Hydrologic-Land Surface Models (H-LSMs) have been progressively developed to a stage where they represent the dominant hydrological processes for a variety of hydrological regimes and include a range of water management practices, and are increasingly used to simulate water storages and fluxes of large basins under changing environmental conditions...
Conference Paper
In many parts of the Northern Hemisphere, land surface hydrology is strongly affected by ablation of snow mass, and freshwater supply depends on its melt. Obtaining the accurate estimation of snow water equivalent (SWE) over space and time is a difficult task. In order to better represent the snowpack, especially in areas with high snow spatial var...
Preprint
Full-text available
Permafrost is an important feature of cold regions hydrology, particularly in basins such as the Mackenzie 9 River Basin (MRB), and needs to be properly represented in hydrological and land surface models (H-LSMs) 10 built into existing Earth System models (ESM), especially under the unprecedented climate warming 11 trends that have been observed....
Data
The dataset contains 0.125 resolution gridded soil texture data for Mackenzie and Nelson-Churchill River Basins. The data has been aggregated from two source datasets, namely Soil Landscapes of Canada 2.2 dataset and STATSGO2 dataset for USA. The final texture data has the minimum, maximum and average percent for sand, clay and organic components o...
Data
The bedrock dataset created by Shangguan et al. (2017) is aggregated to a lower resolution (larger pixels) of 0.125 degree for Mackenzie and Nelson-Churchill River Basins for its applicability with Hydrology and Land Surface Models. This dataset is in particular generated for using with MESH (Modélisation Environnementale communautaire - Surface Hy...
Article
Full-text available
Complex, software-intensive, technically advanced, and computationally demanding models, presumably with ever-growing realism and fidelity, have been widely used to simulate and predict the dynamics of the Earth and environmental systems. The parameter-induced simulation crash (failure) problem is typical across most of these models, despite consid...
Preprint
Full-text available
Reservoirs significantly affect flow regimes in watershed systems by changing the magnitude and timing of streamflows. Failure to represent these effects limits the performance of hydrological and land surface models (H-LSMs) in the many highly regulated basins across the globe and limits the applicability of such models to investigate the futures...
Poster
We propose efficient strategies to generate surrogate model responses when a model fails during simulation under particular parameter values, such that the sensitivity analysis can be completed, while minimizing the impact of those failures on the results.
Poster
Full-text available
VARS-TOOL , by incorporating a diversity of tools and features within a single platform, conveniently provides the user with the ingredients necessary for conducting exploratory research with a view to discovering new directions for advancing the field of sensitivity and uncertainty analysis.
Article
Full-text available
Environmental models are used extensively to evaluate the effectiveness of a range of design, planning, operational, management and policy options. However, the number of options that can be evaluated manually is generally limited, making it difficult to identify the most suitable options to consider in decision-making processes. By linking environ...
Article
Many applications of global sensitivity analysis (GSA) do not adequately account for the dynamical nature of earth and environmental systems models. Gupta and Razavi (2018) highlight this fact and develop a sensitivity analysis framework from first principles, based on the sensitivity information contained in trajectories of partial derivatives of...
Article
This paper investigates the problem of global sensitivity analysis (GSA) of Dynamical Earth System Models and proposes a basis for how such analyses should be performed. We argue that (a) performance metric-based approaches to parameter GSA are actually identifiability analyses, (b) the use of a performance metric to assess sensitivity unavoidably...
Article
Full-text available
VARS-TOOL is a software toolbox for sensitivity and uncertainty analysis. Developed primarily around the “Variogram Analysis of Response Surfaces” framework, VARS-TOOL adopts a multi-method approach that enables simultaneous generation of a range of sensitivity indices, including ones based on derivative, variance, and variogram concepts, from a si...
Article
Full-text available
Dynamical earth and environmental systems models are typically computationally intensive and highly parameterized with many uncertain parameters. Together, these characteristics severely limit the applicability of Global Sensitivity Analysis (GSA) to high-dimensional models because very large numbers of model runs are typically required to achieve...
Article
Full-text available
This document was developed by American Geophysical Union’s (AGU’s) Technical Committee on Hydrologic Uncertainty (www.hydrouncertainty.org) at the request of the AGU-Hydrology Section President in May-June 2018, to outline the three biggest research questions around hydrologic uncertainty.
Article
Full-text available
Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land su...
Conference Paper
Full-text available
Snow is a very dynamic feature, which displays important spatial and temporal variabilities, depending on landscape, topography, forest cover and geographical location. Its measurement is challenging. Among satellite measurement techniques, gravimetric retrievals from the Gravity Recovery and Climate Experiment (GRACE) satellites provide useful inf...
Poster
Full-text available
Baseflow is an important part of the hydrograph of many rivers. It might contribute a small volume overall, but it maintains flow in streams when other sources are absent. An accurate simulation of the recession part of the hydrograph, which is formed by baseflow, is difficult due to the complexity of several interacting processes, especially in th...
Article
Full-text available
Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems and health. However, nation-wide drought assessments are currently...