Addressing the incorrect usage of wavelet-based hydrological and water resources forecasting models for real-world applications with best practices and a new forecasting framework - Quilty, John; Adamowski, Jan (Journal of Hydrology, 2018)

A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes - Quilty, John; Adamowski, Jan (Environmental Modelling & Software, 2020)

Modeling sustainability visions: A case study of multi-scale food systems in Southwestern Ontario - Halbe, Johannes; Adamowski, Jan (Journal of Environmental Management, 2019)

Use of digital elevation models for flood susceptibility assessment via a hydrogeomorphic approach: A case study of the Basento River in Italy - Albano, Raffaele; Adamowski, Jan (Natural Hazards, 2025)
Abstract Floods are the most common and threatening natural risk for many countries in the world. Flood risk mapping is therefore of great importance for managing socio-economic and environmental impacts. Several researchers have proposed low-complexity and cost-effective flood mapping solutions that are useful for data scarce environments or at large-scale. Among these approaches, a line of recent research focuses on hydrogeomorphic methods that, due to digital elevation models (DEMs), exploit the causality between past flood events and the hydraulic geometry of floodplains. This study aims to compare the use of freely-available DEMs to support an advanced hydrogeomorphic method, Geomorphic Flood Index (GFI), to map flood-prone areas of the Basento River basin (Italy). The five selected DEMs are obtained from different sources, are characterized by different resolutions, spatial coverage, acquisition process, processing and validation, etc., and include: (i) HydroSHEDS v.1.1 (resolution 3 arc-seconds), hydrologically conditioned, derived primarily from STRM (NASA) and characterized by global coverage; (ii) ASTER GDEM v.3 with a res. of around 30 m (source: METI and NASA) and global coverage; (iii) EU-DEM v. 1.1 (res. 1 arc-second), Pan-European and combining SRTM and ASTER GDEM, customized to obtain a consistency with the EU-Hydro and screened to remove artefacts (source: Copernicus Land Monitoring Service); (iv) TinItaly DEM v. 1.1, (res. 10 m-cell size grid) and produced and distributed by INGV with coverage of the entire Italian territory; (v) Laser Scanner DEM with high resolution (5 m cell size grid) produced on the basis of Ground e Model Keypoint and available as part of the RSDI geoportal of the Basilicata Region with coverage at the regional administrative level. The effects of DEMs on the performance of the GFI calibration on the main reach of the Basento River, and its validation on one of its mountain tributaries (Gallitello Creek), were evaluated with widely accepted statistical metrics, i.e., the Area Under the Receiver Operating Characteristics (ROC) curve (AUC), Accuracy, Sensitivity and Specificity. Results confirmed the merits of the GFI in flood mapping using simple watershed characteristics and showed high Accuracy (AUC reached a value over 0.9 in all simulations) and low dependency on changes in the adopted DEMs and standard flood maps (1D and 2D hydraulic models or three return periods). The EU-DEM was identified as the most suitable data source for supporting GFI mapping with an AUC > 0.97 in the calibration phase for the main river reach. This may be due in part to its appropriate resolution for hydrological application but was also due to its customized pre-processing that supported an optimal description of the river network morphology. Indeed, EU-DEM obtained the highest performances (e.g., Accuracy around 98%) even in the validation phase where better results were expected from the high-resolution DEM (due to the very small size of Gallitello Creek cross-sections). For other DEMs, GFI generally showed an increase in metrics performance when, in the calibration phase, it neglected the floodplains of the river delta, where the standard flood map is produced using a 2D hydraulic model. However, if the DEMs were hydrologically conditioned with a relatively simple algorithm that forced the stream flow in the main river network, the GFI could be applied to the whole Basento watershed, including the delta, with a similar performance.
Keywords: Infolettre; Infolettre_Fevrier_2025

Assessment of 30 gridded precipitation datasets over different climates on a country scale - Araghi, Alireza; Adamowski, Jan F. (Earth Science Informatics, 2024)

Assessing the benefits of serious games to support sustainable decision-making for transboundary watershed governance - Furber, Alison; Medema, Wietske; Adamowski, Jan (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2018)

Participatory mapping of ecosystem services to understand stakeholders’ perceptions of the future of the Mactaquac Dam, Canada - Reilly, Kate; Adamowski, Jan; John, Kimberly (Ecosystem Services, 2018)

Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach - Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan (Environmental Research, 2018)

Investigating monthly precipitation variability using a multiscale approach based on ensemble empirical mode decomposition - Alizadeh, Farhad; Roushangar, Kiyoumar; Adamowski, Jan (Paddy and Water Environment, 2019)

Integrated assessment of localized SSP–RCP narratives for climate change adaptation in coupled human-water systems - Alizadeh, Mohammad Reza; Adamowski, Jan; Inam, Azhar (Science of The Total Environment, 2022)

Hybrid artificial intelligence-time series models for monthly streamflow modeling - Mehdizadeh, Saeid; Fathian, Farshad; Adamowski, Jan F. (Applied Soft Computing, 2019)

A Stochastic Data‐Driven Ensemble Forecasting Framework for Water Resources: A Case Study Using Ensemble Members Derived From a Database of Deterministic Wavelet‐Based Models - Quilty, John; Adamowski, Jan; Boucher, Marie‐Amélie (Water Resources Research, 2019)
Abstract In water resources applications (e.g., streamflow, rainfall‐runoff, urban water demand [UWD], etc.), ensemble member selection and ensemble member weighting are two difficult yet important tasks in the development of ensemble forecasting systems. We propose and test a stochastic data‐driven ensemble forecasting framework that uses archived deterministic forecasts as input and results in probabilistic water resources forecasts. In addition to input data and (ensemble) model output uncertainty, the proposed approach integrates both ensemble member selection and weighting uncertainties, using input variable selection and data‐driven methods, respectively. Therefore, it does not require one to perform ensemble member selection and weighting separately. We applied the proposed forecasting framework to a previous real‐world case study in Montreal, Canada, to forecast daily UWD at multiple lead times. Using wavelet‐based forecasts as input data, we develop the Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, the first multiwavelet ensemble stochastic forecasting framework that produces probabilistic forecasts. For the considered case study, several variants of Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, produced using different input variable selection methods (partial correlation input selection and Edgeworth Approximations‐based conditional mutual information) and data‐driven models (multiple linear regression, extreme learning machines, and second‐order Volterra series models), are shown to outperform wavelet‐ and nonwavelet‐based benchmarks, especially during a heat wave (first time studied in the UWD forecasting literature). , Key Points A stochastic data‐driven ensemble framework is introduced for probabilistic water resources forecasting Ensemble member selection and weighting uncertainties are explicitly considered alongside input data and model output uncertainties Wavelet‐based model outputs are used as input to the framework for an urban water demand forecasting study outperforming benchmark methods

Applying the Theory of Reliability to the Assessment of Hazard, Risk and Safety in a Hydrologic System: A Case Study in the Upper Sola River Catchment, Poland - Ozga-Zielinski, Bogdan; Adamowski, Jan; Ciupak, Maurycy (Water, 2018)

Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates - Araghi, Alireza; Adamowski, Jan; Martinez, Christopher J. (Journal of Water and Climate Change, 2020)
Abstract Reference evapotranspiration (ETo) is one of the most important factors in the hydrologic cycle and water balance studies. In this study, the performance of three simple and three wavelet hybrid models were compared to estimate ETo in three different climates in Iran, based on different combinations of input variables. It was found that the wavelet-artificial neural network was the best model, and multiple linear regression (MLR) was the worst model in most cases, although the performance of the models was related to the climate and the input variables used for modeling. Overall, it was found that all models had good accuracy in terms of estimating daily ETo. Also, it was found in this study that large numbers of decomposition levels via the wavelet transform had noticeable negative effects on the performance of the wavelet-based models, especially for the wavelet-adaptive network-based fuzzy inference system and wavelet-MLR, but in contrast, the type of db wavelet function did not have a detectable effect on the performance of the wavelet-based models.

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model - Barzegar, Rahim; Aalami, Mohammad Taghi; Adamowski, Jan (Stochastic Environmental Research and Risk Assessment, 2020)

The role of place meanings in opposition to water-related infrastructure projects: the case of the Mactaquac Dam, New Brunswick, Canada - Reilly, Kate H.; Adamowski, Jan F.; John, Kimberly (Ecology and Society, 2019)

Smoothed Particle Hydrodynamics Modeling with Advanced Boundary Conditions for Two-Dimensional Dam-Break Floods - Mirauda, Domenica; Albano, Raffaele; Sole, Aurelia; Adamowski, Jan (Water, 2020)
To simulate the dynamics of two-dimensional dam-break flow on a dry horizontal bed, we use a smoothed particle hydrodynamics model implementing two advanced boundary treatment techniques: (i) a semi-analytical approach, based on the computation of volume integrals within the truncated portions of the kernel supports at boundaries and (ii) an extension of the ghost-particle boundary method for mobile boundaries, adapted to free-slip conditions. The trends of the free surface along the channel, and of the impact wave pressures on the downstream vertical wall, were first validated against an experimental case study and then compared with other numerical solutions. The two boundary treatment schemes accurately predicted the overall shape of the primary wave front advancing along the dry bed until its impact with the downstream vertical wall. Compared to data from numerical models in the literature, the present results showed a closer fit to an experimental secondary wave, reflected by the downstream wall and characterized by complex vortex structures. The results showed the reliability of both the proposed boundary condition schemes in resolving violent wave breaking and impact events of a practical dam-break application, producing smooth pressure fields and accurately predicting pressure and water level peaks.

More food with less water – Optimizing agricultural water use - Smilovic, Mikhail; Gleeson, Tom; Adamowski, Jan; Langhorn, Colin (Advances in Water Resources, 2019)

Determination of duration, threshold and spatiotemporal distribution of extreme continuous precipitation in nine major river basins in China - Jin, Haoyu; Chen, Xiaohong; Adamowski, Jan; Hatami, Shadi (Atmospheric Research, 2024)
Keywords: Infolettre; Infolettre_Mars_2024

A statistical approach for the estimation of water quality characteristics of ungauged streams/watersheds under stationary conditions - Khalil, Bahaa; Adamowski, Jan; Abdin, Alaa; Elsaadi, Aiman (Journal of Hydrology, 2019)

Insights from socio-hydrological modeling to design sustainable wastewater reuse strategies for agriculture at the watershed scale - Jeong, Hanseok; Bhattarai, Rabin; Adamowski, Jan; Yu, David J. (Agricultural Water Management, 2020)

Multi-objective decision-making for green infrastructure planning (LID-BMPs) in urban storm water management under uncertainty - Raei, Ehsan; Reza Alizadeh, Mohammad; Reza Nikoo, Mohammad; Adamowski, Jan (Journal of Hydrology, 2019)

Fuzzy-based conflict resolution management of groundwater in-situ bioremediation under hydrogeological uncertainty - Taravatrooy, Narges; Nikoo, Mohammad Reza; Adamowski, Jan Franklin; Khoramshokooh, Nafiseh (Journal of Hydrology, 2019)

Regionalization of flood magnitudes using the ecological attributes of watersheds - Jabbarian Amiri, Bahman; Baheri, Bahareh; Fohrer, Nicola; Adamowski, Jan Franklin (Geocarto International, 2020)

Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region - Mouatadid, Soukayna; Raj, Nawin; Deo, Ravinesh C.; Adamowski, Jan F. (Atmospheric Research, 2018)

Delimitation of groundwater zones under contamination risk using a bagged ensemble of optimized DRASTIC frameworks - Barzegar, Rahim; Asghari Moghaddam, Asghar; Adamowski, Jan; Nazemi, Amir Hossein (Environmental Science and Pollution Research, 2019)

Evidence for the occurrence of hydrogeochemical processes in the groundwater of Khoy plain, northwestern Iran, using ionic ratios and geochemical modeling - Barzegar, Rahim; Asghari Moghaddam, Asghar; Nazemi, Amir Hossein; Adamowski, Jan (Environmental Earth Sciences, 2018)

Multi-step water quality forecasting using a boosting ensemble multi-wavelet extreme learning machine model - Barzegar, Rahim; Asghari Moghaddam, Asghar; Adamowski, Jan; Ozga-Zielinski, Bogdan (Stochastic Environmental Research and Risk Assessment, 2018)

A New Approach to Predict Daily pH in Rivers Based on the “à trous” Redundant Wavelet Transform Algorithm - Rajaee, Taher; Ravansalar, Masoud; Adamowski, Jan F.; Deo, Ravinesh C. (Water, Air, & Soil Pollution, 2018)

An Entropy-Based Approach to Fuzzy Multi-objective Optimization of Reservoir Water Quality Monitoring Networks Considering Uncertainties - Pourshahabi, Shokoufeh; Nikoo, Mohammad Reza; Raei, Ehsan; Adamowski, Jan Franklin (Water Resources Management, 2018)

Temporal and depth variation of water quality due to thermal stratification in Karkheh Reservoir, Iran - Noori, Roohollah; Berndtsson, Ronny; Franklin Adamowski, Jan; Rabiee Abyaneh, Maryam (Journal of Hydrology: Regional Studies, 2018)

A GIS Tool for Mapping Dam-Break Flood Hazards in Italy - Albano, Raffaele; Mancusi, Leonardo; Adamowski, Jan; Cantisani, Andrea; Sole, Aurelia (ISPRS International Journal of Geo-Information, 2019)
Mapping the delineation of areas that are flooded due to water control infrastructure failure is a critical issue. Practical difficulties often present challenges to the accurate and effective analysis of dam-break hazard areas. Such studies are expensive, lengthy, and require large volumes of incoming data and refined technical skills. The creation of cost-efficient geospatial tools provides rapid and inexpensive estimates of instantaneous dam-break (due to structural failure) flooded areas that complement, but do not replace, the results of hydrodynamic simulations. The current study implements a Geographic Information System (GIS) based method that can provide useful information regarding the delineation of dam-break flood-prone areas in both data-scarce environments and transboundary regions, in the absence of detailed studies. Moreover, the proposed tool enables, without advanced technical skills, the analysis of a wide number of case studies that support the prioritization of interventions, or, in emergency situations, the simulation of numerous initial hypotheses (e.g., the modification of initial water level/volume in the case of limited dam functionality), without incurring high computational time. The proposed model is based on the commonly available data for masonry dams, i.e., dam geometry (e.g., reservoir capacity, dam height, and crest length), and a Digital Elevation Model. The model allows for rapid and cost-effective dam-break hazard mapping by evaluating three components: (i) the dam-failure discharge hydrograph, (ii) the propagation of the flood, and (iii) the delineation of flood-prone areas. The tool exhibited high accuracy and reliability in the identification of hypothetical dam-break flood-prone areas when compared to the results of traditional hydrodynamic approaches, as applied to a dam in Basilicata (Southern Italy). In particular, the over- and under-estimation rates of the proposed tool, for the San Giuliano dam, Basilicata, were evaluated by comparing its outputs with flood inundation maps that were obtained by two traditional methods whil using a one-dimensional and a two-dimensional propagation model, resulting in a specificity value of roughly 90%. These results confirm that most parts of the flood map were correctly classified as flooded by the proposed GIS model. A sensitivity value of over 75% confirms that several zones were also correctly identified as non-flooded. Moreover, the overall effectiveness and reliability of the proposed model were evaluated, for the Gleno Dam (located in the Central Italian Alps), by comparing the results of literature studies concerning the application of monodimensional numerical models and the extent of the flooded area reconstructed by the available historical information, obtaining an accuracy of around 94%. Finally, the computational efficiency of the proposed tool was tested on a demonstrative application of 250 Italian arch and gravity dams. The results, when carried out using a PC, Pentium Intel Core i5 Processor CPU 3.2 GHz, 8 GB RAM, required about 73 min, showing the potential of such a tool applied to dam-break flood mapping for a large number of dams.

Using bootstrap ELM and LSSVM models to estimate river ice thickness in the Mackenzie River Basin in the Northwest Territories, Canada - Barzegar, Rahim; Ghasri, Mahsa; Qi, Zhiming; Quilty, John; Adamowski, Jan (Journal of Hydrology, 2019)

A participatory system dynamics modeling approach to facilitate collaborative flood risk management: A case study in the Bradano River (Italy) - Perrone, Antonio; Inam, Azhar; Albano, Raffaele; Adamowski, Jan; Sole, Aurelia (Journal of Hydrology, 2020)

Using the Mann–Kendall test and double mass curve method to explore stream flow changes in response to climate and human activities - Pirnia, Abdollah; Golshan, Mohammad; Darabi, Hamid; Adamowski, Jan; Rozbeh, Sajad (Journal of Water and Climate Change, 2019)
Abstract Analyzing intra-annual stream flow can reveal the main causes for runoff changes and the contributions of climate variability and human activities. For this purpose, the Mann–Kendall and cumulative rank difference (CRD) tests, and the double mass curve method, were applied to a time series of hydro-meteorological variables from 1971 to 2010 in the Tajan River basin in Iran. Results indicated that runoff changes in the wet and dry seasons after 1999 had significant respective decreasing and increasing trends, at the 0.01 confidence level, due to dam construction. In the pre-dam period (1991–1998), the results of the double mass curve method showed that climate variability and human activities contributed 57.76% and 42.24%, respectively, to the runoff decrease during the wet season. For the post-dam period (1999–2010), climate variability and anthropogenic activities contributed 24.68% and 75.32%, respectively, to the wet season runoff decrease of 116.55 mm. On the other hand, in the same period during the dry season, climate variability contributed −30.68% and human activities contributed 130.68% to the runoff increase of 41.45 mm. It is evident that runoff changes in both wet and dry seasons were mainly due to human activities associated with dam construction to meet water supply demands for agriculture.

Comparative assessment of time series and artificial intelligence models to estimate monthly streamflow: A local and external data analysis approach - Mehdizadeh, Saeid; Fathian, Farshad; Safari, Mir Jafar Sadegh; Adamowski, Jan F. (Journal of Hydrology, 2019)

Probabilistic Event Based Rainfall-Runoff Modeling Using Copula Functions - Abdollahi, Sajjad; Akhoond-Ali, Ali Mohammad; Mirabbasi, Rasoul; Adamowski, Jan Franklin (Water Resources Management, 2019)

Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting - Mouatadid, Soukayna; Adamowski, Jan F.; Tiwari, Mukesh K.; Quilty, John M. (Agricultural Water Management, 2019)

The Potential of Serious Games to Solve Water Problems: Editorial to the Special Issue on Game-Based Approaches to Sustainable Water Governance - Medema, Wietske; Mayer, Igor; Adamowski, Jan; Wals, Arjen E.J.; Chew, Chengzi (Water, 2019)
In this editorial, the authors (and guest editors) introduce the Special Issue titled Understanding Game-based Approaches for Improving Sustainable Water Governance: The Potential of Serious Games to Solve Water Problems. The authors take another look at the twelve contributions, starting from the subtitle question: what is the potential? The authors summarize the insights and give directions for future research.

Regionalizing Flood Magnitudes using Landscape Structural Patterns of Catchments - Amiri, Bahman Jabbarian; Junfeng, Gao; Fohrer, Nicola; Mueller, Felix; Adamowski, Jan (Water Resources Management, 2018)

A real-time hourly water index for flood risk monitoring: Pilot studies in Brisbane, Australia, and Dobong Observatory, South Korea - Deo, Ravinesh C.; Byun, Hi-Ryong; Kim, Ga-Byn; Adamowski, Jan F. (Environmental Monitoring and Assessment, 2018)

Groundwater Pollution Sources Apportionment in the Ghaen Plain, Iran - Vesali Naseh, Mohammad; Noori, Roohollah; Berndtsson, Ronny; Adamowski, Jan; Sadatipour, Elaheh (International Journal of Environmental Research and Public Health, 2018)

Influences of afforestation policies on soil moisture content in China’s arid and semi-arid regions - Cao, Jianjun; Tian, Hong; Adamowski, Jan F.; Zhang, Xiaofang; Cao, Zijian (Land Use Policy, 2018)

Flood scenario spatio-temporal mapping via hydrological and hydrodynamic modelling and a remote sensing dataset: A case study of the Basento river (Southern Italy) - Albano, Raffaele; Limongi, Carmine; Dal Sasso, Silvano Fortunato; Mancusi, Leonardo; Adamowski, Jan (International Journal of Disaster Risk Reduction, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model - Ciupak, Maurycy; Ozga-Zielinski, Bogdan; Adamowski, Jan; Deo, Ravinesh C; Kochanek, Krzysztof (Water, 2019)
An implementation of bias correction and data assimilation using the ensemble Kalman filter (EnKF) as a procedure, dynamically coupled with the conceptual rainfall-runoff Hydrologiska Byråns Vattenbalansavdelning (HBV) model, was assessed for the hydrological modeling of seasonal hydrographs. The enhanced HBV model generated ensemble hydrographs and an average stream-flow simulation. The proposed approach was developed to examine the possibility of using data (e.g., precipitation and soil moisture) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF), and to explore its usefulness in improving model updating and forecasting. Data from the Sola mountain catchment in southern Poland between 1 January 2008 and 31 July 2014 were used to calibrate the HBV model, while data from 1 August 2014 to 30 April 2015 were used for validation. A bias correction algorithm for a distribution-derived transformation method was developed by exploring generalized exponential (GE) theoretical distributions, along with gamma (GA) and Weibull (WE) distributions for the different data used in this study. When using the ensemble Kalman filter, the stochastically-generated ensemble of the model states generally induced bias in the estimation of non-linear hydrologic processes, thus influencing the accuracy of the Kalman analysis. In order to reduce the bias produced by the assimilation procedure, a post-processing bias correction (BC) procedure was coupled with the ensemble Kalman filter (EnKF), resulting in an ensemble Kalman filter with bias correction (EnKF-BC). The EnKF-BC, dynamically coupled with the HBV model for the assimilation of the satellite soil moisture observations, improved the accuracy of the simulated hydrographs significantly in the summer season, whereas, a positive effect from bias corrected (BC) satellite precipitation, as forcing data, was observed in the winter. Ensemble forecasts generated from the assimilation procedure are shown to be less uncertain. In future studies, the EnKF-BC algorithm proposed in the current study could be applied to a diverse array of practical forecasting problems (e.g., an operational assimilation of snowpack and snow water equivalent in forecasting models).

A critical review on the application of the National Sanitation Foundation Water Quality Index - Noori, Roohollah; Berndtsson, Ronny; Hosseinzadeh, Majid; Adamowski, Jan Franklin; Abyaneh, Maryam Rabiee (Environmental Pollution, 2019)

Serious games as a catalyst for boundary crossing, collaboration and knowledge co-creation in a watershed governance context - Jean, Steven; Medema, Wietske; Adamowski, Jan; Chew, Chengzi; Delaney, Patrick; Wals, Arjen (Journal of Environmental Management, 2018)

Correction to: Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales - Amini, Mohammad Amin; Torkan, Ghazale; Eslamian, Saeid; Zareian, Mohammad Javad; Adamowski, Jan Franklin (Acta Geophysica, 2019)

Effect of Land Use Change on Soil Carbon Storage over the Last 40 Years in the Shi Yang River Basin, China - Yang, Shurong; Sheng, Danrui; Adamowski, Jan; Gong, Yifan; Zhang, Jian; Cao, Jianjun (Land, 2018)

Quantile-based downscaling of rainfall extremes: Notes on methodological functionality, associated uncertainty and application in practice - Hassanzadeh, Elmira; Nazemi, Ali; Adamowski, Jan; Nguyen, Truong-Huy; Van-Nguyen, Van-Thanh (Advances in Water Resources, 2019)

Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales - Amini, Mohammad Amin; Torkan, Ghazale; Eslamian, Saeid; Zareian, Mohammad Javad; Adamowski, Jan Franklin (Acta Geophysica, 2019)

An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines - Choubin, Bahram; Moradi, Ehsan; Golshan, Mohammad; Adamowski, Jan; Sajedi-Hosseini, Farzaneh; Mosavi, Amir (Science of The Total Environment, 2019)

Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models - Barzegar, Rahim; Razzagh, Siamak; Quilty, John; Adamowski, Jan; Kheyrollah Pour, Homa; Booij, Martijn J. (Journal of Hydrology, 2021)

A century of observations reveals increasing likelihood of continental-scale compound dry-hot extremes - Alizadeh, Mohammad Reza; Adamowski, Jan; Nikoo, Mohammad Reza; AghaKouchak, Amir; Dennison, Philip; Sadegh, Mojtaba (Science Advances, 2020)
Compound dry-hot events enlarge homogenously due to teleconnected land-atmosphere feedbacks. , Using over a century of ground-based observations over the contiguous United States, we show that the frequency of compound dry and hot extremes has increased substantially in the past decades, with an alarming increase in very rare dry-hot extremes. Our results indicate that the area affected by concurrent extremes has also increased significantly. Further, we explore homogeneity (i.e., connectedness) of dry-hot extremes across space. We show that dry-hot extremes have homogeneously enlarged over the past 122 years, pointing to spatial propagation of extreme dryness and heat and increased probability of continental-scale compound extremes. Last, we show an interesting shift between the main driver of dry-hot extremes over time. While meteorological drought was the main driver of dry-hot events in the 1930s, the observed warming trend has become the dominant driver in recent decades. Our results provide a deeper understanding of spatiotemporal variation of compound dry-hot extremes.

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin - Bostanmaneshrad, Farshid; Partani, Sadegh; Noori, Roohollah; Nachtnebel, Hans-Peter; Berndtsson, Ronny; Adamowski, Jan Franklin (Science of The Total Environment, 2018)

Serious Games as Planning Support Systems: Learning from Playing Maritime Spatial Planning Challenge 2050 - Jean, Steven; Gilbert, Laura; Medema, Wietske; Keijser, Xander; Mayer, Igor; Inam, Azhar; Adamowski, Jan (Water, 2018)
The inherent complexity of planning at sea, called maritime spatial planning (MSP), requires a planning approach where science (data and evidence) and stakeholders (their engagement and involvement) are integrated throughout the planning process. An increasing number of innovative planning support systems (PSS) in terrestrial planning incorporate scientific models and data into multi-player digital game platforms with an element of role-play. However, maritime PSS are still early in their innovation curve, and the use and usefulness of existing tools still needs to be demonstrated. Therefore, the authors investigate the serious game, MSP Challenge 2050, for its potential use as an innovative maritime PSS and present the results of three case studies on participant learning in sessions of game events held in Newfoundland, Venice, and Copenhagen. This paper focusses on the added values of MSP Challenge 2050, specifically at the individual, group, and outcome levels, through the promotion of the knowledge co-creation cycle. During the three game events, data was collected through participant surveys. Additionally, participants of the Newfoundland event were audiovisually recorded to perform an interaction analysis. Results from survey answers and the interaction analysis provide evidence that MSP Challenge 2050 succeeds at the promotion of group and individual learning by translating complex information to players and creating a forum wherein participants can share their thoughts and perspectives all the while (co-) creating new types of knowledge. Overall, MSP Challenge and serious games in general represent promising tools that can be used to facilitate the MSP process.

Interregional imbalance in the Yellow River Basin: Insights from flood-sediment transport, socioeconomic, and environmental subsystems - Hu, Hao; Tian, Guiliang; Adamowski, Jan F.; Albano, Raffaele; Liu, Yixue; Jing, Xiaodong; Zhao, Qiuya (Journal of Environmental Management, 2024)
Keywords: Infolettre; Infolettre_Decembre_2024

Contributions of climate, elevated atmospheric CO2 concentration and land surface changes to variation in water use efficiency in Northwest China - Yang, Linshan; Feng, Qi; Wen, Xiaohu; Barzegar, Rahim; Adamowski, Jan F; Zhu, Meng; Yin, Zhenliang (CATENA, 2022)

Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment - Azareh, Ali; Rafiei Sardooi, Elham; Choubin, Bahram; Barkhori, Saeed; Shahdadi, Ali; Adamowski, Jan; Shamshirband, Shahaboddin (Geocarto International, 2021)
Keywords: Site_internet_RIISQ

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones - Barzegar, Rahim; Asghari Moghaddam, Asghar; Norallahi, Shahrokh; Inam, Azhar; Adamowski, Jan; Alizadeh, Mohammad Reza; Bou Nassar, Jessica (Groundwater, 2020)
Abstract The DRASTIC technique is commonly used to assess groundwater vulnerability. The main disadvantage of the DRASTIC method is the difficulty associated with identifying appropriate ratings and weight assignments for each parameter. To mitigate this issue, ratings and weights can be approximated using different methods appropriate to the conditions of the study area. In this study, different linear (i.e., Wilcoxon test and statistical approaches) and nonlinear (Genetic algorithm [GA]) modifications for calibration of the DRASTIC framework using nitrate (NO 3 ) concentrations were compared through the preparation of groundwater vulnerability maps of the Meshqin‐Shahr plain, Iran. Twenty‐two groundwater samples were collected from wells in the study area, and their respective NO 3 concentrations were used to modify the ratings and weights of the DRASTIC parameters. The areas found to have the highest vulnerability were in the eastern, central, and western regions of the plain. Results showed that the modified DRASTIC frameworks performed well, compared to the unmodified DRASTIC. When measured NO 3 concentrations were correlated with the vulnerability indices produced by each method, the unmodified DRASTIC method performed most poorly, and the Wilcoxon–GA–DRASTIC method proved optimal. Compared to the unmodified DRASTIC method with an R 2 of 0.22, the Wilcoxon–GA–DRASTIC obtained a maximum R 2 value of 0.78. Modification of DRASTIC parameter ratings was found to be more efficient than the modification of the weights in establishing an accurately calibrated DRASTIC framework. However, modification of parameter ratings and weights together increased the R 2 value to the highest degree. , Article impact statement : The results showed that both linear and nonlinear methods are useful in modifying the ratings and weights of the DRASTIC method for assessing the groundwater vulnerability.

Large Scale Flood Risk Mapping in Data Scarce Environments: An Application for Romania - Albano, Raffaele; Samela, Caterina; Crăciun, Iulia; Manfreda, Salvatore; Adamowski, Jan; Sole, Aurelia; Sivertun, Åke; Ozunu, Alexandru (Water, 2020)
Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth–damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability.

Quantifying flood events in Bangladesh with a daily-step flood monitoring index based on the concept of daily effective precipitation - Deo, Ravinesh C.; Adamowski, Jan F.; Begum, Khaleda; Salcedo-Sanz, Sancho; Kim, Do-Woo; Dayal, Kavina S.; Byun, Hi-Ryong (Theoretical and Applied Climatology, 2019)

Exploring the hydrogeochemical evolution of cold and thermal waters in the Sarein-Nir area, Iran using stable isotopes (δ18O and δD), geothermometry and multivariate statistical approaches - Barzegar, Rahim; Asghari Moghaddam, Asghar; Tziritis, Evangelos; Adamowski, Jan; Bou Nassar, Jessica; Noori, Mohammad; Aalami, Mohammad Taghi; Kazemian, Naeimeh (Geothermics, 2020)

Multi-household grazing management pattern maintains better soil fertility - Cao, Jianjun; Xu, Xueyun; Deo, Ravinesh C.; Holden, Nicholas M.; Adamowski, Jan F.; Gong, Yifan; Feng, Qi; Yang, Shurong; Li, Mengtian; Zhou, Junju; Zhang, Jian; Liu, Minxia (Agronomy for Sustainable Development, 2018)

Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model - Tien Bui, Duie; Khosravi, Khabat; Shahabi, Himan; Daggupati, Prasad; Adamowski, Jan F.; M.Melesse, Assefa; Thai Pham, Binh; Pourghasemi, Hamid Reza; Mahmoudi, Mehrnoosh; Bahrami, Sepideh; Pradhan, Biswajeet; Shirzadi, Ataollah; et al. (Remote Sensing, 2019)
Floods are some of the most dangerous and most frequent natural disasters occurring in the northern region of Iran. Flooding in this area frequently leads to major urban, financial, anthropogenic, and environmental impacts. Therefore, the development of flood susceptibility maps used to identify flood zones in the catchment is necessary for improved flood management and decision making. The main objective of this study was to evaluate the performance of an Evidential Belief Function (EBF) model, both as an individual model and in combination with Logistic Regression (LR) methods, in preparing flood susceptibility maps for the Haraz Catchment in the Mazandaran Province, Iran. The spatial database created consisted of a flood inventory, altitude, slope angle, plan curvature, Topographic Wetness Index (TWI), Stream Power Index (SPI), distance from river, rainfall, geology, land use, and Normalized Difference Vegetation Index (NDVI) for the region. After obtaining the required information from various sources, 151 of 211 recorded flooding points were used for model training and preparation of the flood susceptibility maps. For validation, the results of the models were compared to the 60 remaining flooding points. The Receiver Operating Characteristic (ROC) curve was drawn, and the Area Under the Curve (AUC) was calculated to obtain the accuracy of the flood susceptibility maps prepared through success rates (using training data) and prediction rates (using validation data). The AUC results indicated that the EBF, EBF from LR, EBF-LR (enter), and EBF-LR (stepwise) success rates were 94.61%, 67.94%, 86.45%, and 56.31%, respectively, and the prediction rates were 94.55%, 66.41%, 83.19%, and 52.98%, respectively. The results showed that the EBF model had the highest accuracy in predicting flood susceptibility within the catchment, in which 15% of the total areas were located in high and very high susceptibility classes, and 62% were located in low and very low susceptibility classes. These results can be used for the planning and management of areas vulnerable to floods in order to prevent flood-induced damage; the results may also be useful for natural disaster assessment.
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