Ousmane Seidou - Academia.edu (original) (raw)

Papers by Ousmane Seidou

Climatic Change

The original article has been corrected. During typesetting, a mistake was made in the Introducti... more The original article has been corrected. During typesetting, a mistake was made in the Introduction of the article by including incorrect information.

Flood Impact Mitigation and Resilience Enhancement, 2020

Flood early warning systems (FEWSs)—one of the most common flood-impact mitigation measures—are c... more Flood early warning systems (FEWSs)—one of the most common flood-impact mitigation measures—are currently in operation globally. The UN Office for Disaster Risk Reduction (UNDRR) strongly advocates for an increase in their availability to reach the targets of the Sendai Framework for Disaster Risk Reduction and Sustainable Development Goals (SDGs). Comprehensive FEWS consists of four components, which includes (1) risk knowledge, (2) monitoring and forecasting, (3) warning, dissemination, and communication, and (4) response capabilities. Operational FEWSs have varying levels of complexity, depending on available data, adopted technology, and know-how. There are apparent differences in sophistication between FEWSs in developed countries that have the financial capabilities, technological infrastructure, and human resources and developing countries where FEWSs tend to be less advanced. Fortunately, recent advances in remote sensing, artificial intelligence (AI), information technologi...

Healthy water resources are key to every nation’s wealth and well-being. Unfortunately, stressors... more Healthy water resources are key to every nation’s wealth and well-being. Unfortunately, stressors such as climate change, land-use shifts, and increased water consumption are threatening water availability and access worldwide. The pressure on water resources is projected to increase dramatically in the future and turn into a global crisis unless bold actions are taken. Researchers and practitioners are therefore under great pressure to develop methodologies and tools that can streamline projected changes into adaptation decisions. The vast majority of climate change adaptation studies use a top-down approach, which essentially consists of using of a limited set of climate change scenarios to discover future risks. However, recent research has identified critical limitations to that approach; for instance, even when multimodel multi-scenario projections are used, not all possible future conditions are covered and therefore plausible risks may be overlooked. There is also no establis...

Climatic Change, 2022

The Congo River Basin, located in central Africa, is the second-largest river basin in the world,... more The Congo River Basin, located in central Africa, is the second-largest river basin in the world, after the Amazon. It has a drainage area of approximately 3.7 M km2 and is home to 75 million people. A significant part of the population is exposed to recurrent floods and droughts, and climate change is likely to worsen these events. Climate change studies of the Congo River basin have so far focused on annual and seasonal precipitation, but little attention was paid to extreme climatic events. This study aims to assess future changes in rainfall-induced flash floods and drought regimes in the Congo basin from the present day to 2100, using four selected extreme climatic indices as proxies to these two natural disasters. The indices are the total annual precipitation (PCPTOT), the number of days where rainfall is above 20 mm (PCP20), the standardized precipitation index (SPI), and the standardized precipitation-evapotranspiration index (SPEI). The indices were calculated with the sta...

Floods are major water-related disasters that affect millions of people resulting in thousands of... more Floods are major water-related disasters that affect millions of people resulting in thousands of mortalities and billiondollar losses globally every year. Flood Early Warning Systems (FEWS) - one of the floods risk management measures - are currently operational in many countries. The UN Office for Disaster Risk Reduction recognises their importance and strongly advocates for an increase in their availability under the targets of the Sendai Framework for Disaster Risk Reduction, and Sustainable Development Goals (SDGs). However, despite widespread recognition of the importance of FEWS for disaster risk reduction (DRR), there’s a lack of information on their availability and status around the world, their benefits and costs, challenges and trends associated with their development. This report contributes to bridging these gaps by analyzing the responses to a comprehensive online survey with over 80 questions on various components of FEWS (risk knowledge, monitoring and forecasting, ...

Since the 90s, several studies were conducted to evaluate the predictability of the Sahelian rain... more Since the 90s, several studies were conducted to evaluate the predictability of the Sahelian rainy season and propose seasonal rainfall forecasts to help stakeholders to take the adequate decisions to adapt with the predicted situation. Unfortunately, two decades later, the forecasting skills remains low and forecasts have a limited value for decision making while the population is still suffering from rainfall interannual variability: this shows the limit of commonly used predictors and forecast approaches for this region. Thus, this paper developed and tested new predictors and new approaches to predict the upcoming seasonal rainfall amount over the Sirba watershed. Predictors selected through a linear correlation analysis were further processed using combined linear methods to identify those having high predictive power. Seasonal rainfall was forecasted using a set of linear and non-linear models. An average lag time up to eight months was obtained for all models. It is found that the combined linear methods performed better than non-linear, possibly because non-linear models require larger and better datasets for calibration. The R 2 , Nash and Hit rate score are

WIT Transactions on Ecology and the Environment, 2017

Weather generators reproduce artificial climate time series that are commonly used for hydrologic... more Weather generators reproduce artificial climate time series that are commonly used for hydrological modeling and climate adaptation studies. To examine the representativeness of a stochastically generated climate time series, a novel stochastic method is suggested where these time series are projected in two spaces (the Climate Statistics Space-CSS; and the Risk and Performance Indicators Space-RPIS). A visual inspection as well as the Mahalanobis distance are used to assess the two spaces relative position and their proximity to the points representing the observations. The dimensions of the CSS are a subset of climate statistics, while the dimensions of the RPIS are a set of risk and performance indicators calculated using streamflow time series. A rainfall-runoff model is used to convert all climate time series from the CSS into streamflow time series in the RPIS. Three stochastic weather generators were used in this study: The Weather Generator École de Technologie Supérieure (WeaGETS), the Multisite Stochastic Weather Generator (MulGETS) using two different generation algorithms, and a k-nearest neighbour weather generator. Each generator was used to construct precipitation, maximum and minimum temperatures time series representing the historical period. The suggested approach was tested on a 41-years-long climate and flow time series from South Nation watershed in Eastern Ontario, Canada. The MulGETS model was able to perform well where the point representing the observations was centered inside the cloud of points representing the synthetic time series in some CSS.

Journal of African Earth Sciences, 2021

Abstract The Inner Niger Delta (IND) is a complex hydraulic system where the flood dynamics and c... more Abstract The Inner Niger Delta (IND) is a complex hydraulic system where the flood dynamics and connectivity between water bodies is the main driver for ecosystem services and economic activities. Therefore, it is of pivotal importance that hydraulic models used to assess ecosystem services and socio-economic usages in the IND are capable of capturing both the inundation and connectivity dynamics. A particularity of the IND is that a strong hysteresis effect can be observed in the stage-discharge relationships at all hydrometric stations in the area. However, existing hydrodynamic models of the IND typically use a static stage-discharge relationship as the downstream boundary condition during both the rise and recession of the flood, which leads to potential inaccuracies when trying to predict the flood extent. This paper explores how the simulation results of the flood and connectivity dynamics in the IND can be improved by using a looped rating curve at the downstream model boundary. The looped rating curve is described using the dimensionless discharges and water levels (DLRC) method. The results show that simulation with DLRC improves the accuracy in predicting floodplain extent and connectivity dynamics between the Niger river system and an important lake in the IND. The improvement in water level predictions decreased steadily with the distance from the downstream boundary of the modelled area.

The African Sahel is known for its climate variability that often translates into recurrent droug... more The African Sahel is known for its climate variability that often translates into recurrent droughts. Rainfall has drastically decreased substantially across the Sahel from the 1950s until at least the late 1980s. It is unclear from the literature and from the fifth IPCC assessment report whether the trend in annual rainfall in the next decades would be decreasing as observed throughout the \(20^{th}\) century or increasing as suggested by a significant number of climate models. There is however a low to medium confidence that extreme rainfalls would increase. The objective of this paper is to demonstrate that both possibilities (an increase or a decrease in rainfall in the future) may results in more opportunities to mobilize water for populations in the Sahel. To demonstrate that, the ability of 20 regional climate models is evaluated based on their ability to reproduce key parameters of the rainy season in Niger, West Africa. The outputs of the 10 best models are then downscaled ...

Wave climatology has a significant impact on pollution transport and dispersion through the coast... more Wave climatology has a significant impact on pollution transport and dispersion through the coastal areas. Indeed, the height and the energy of the wave are influenced by wind characteristics such as wind speed, wind duration, fetch length and etc. Among these characteristics, wind speed has the most important role; that is, the greater wind speed results in greater waves. In this study, significant wave height is estimated over the Qatar coastal areas under the climate change scenarios. In line with this goal, downscaled wind speed outputs using the Quantile – Quantile transformation is used. Indeed, the monthly 100-year wind speed extracted from the downscaled wind speeds probability distribution. The projected wave climatology may be implemented as an input for various practical applications through the coastal areas.

Water Quality Research Journal, 2021

Agricultural extensification and forest cover loss can significantly impact aquatic ecosystems. T... more Agricultural extensification and forest cover loss can significantly impact aquatic ecosystems. This study considered the conversion of forests to agriculture (and vice versa) in an agriculturally dominated watershed in Eastern Ontario, Canada. A series of de- and reforestation scenarios were developed, and water quantity/quality simulations were executed using the Soil and Water Assessment Tool (SWAT) using 30 years of real-world weather observations. Results indicated that streamflow and sediment loads were not sensitive to forest loss, while continuing the recent rate of deforestation of 0.8% (0.2% of the watershed area) per year would, by 2032, increase annual loads of nitrate by 5.6%, total nitrogen by 1.5%, and total phosphorus by 6.8%. Additionally, the same land-use scenarios were simulated with the inclusion of vegetated filter strips (VFS) and grassed waterways. Some reforestation scenarios were sufficient to reduce total nitrogen concentrations below water quality guideli...

Water International, 2021

The countries sharing the Niger River suffer from poor access to clean water and energy as well a... more The countries sharing the Niger River suffer from poor access to clean water and energy as well as food insecurity. The Niger River Basin Authority is tasked with advancing progress in all these areas while also reducing environmental degradation. To help the basin authority and its investors prioritize portfolio activities that support multiple securities of interest, we developed a mixed-methods approach that engaged basin countries in qualitatively ranking projects to meet energy, environmental and food security goals, complemented by quantitative modelling for the more complex ranking of water and environmental sustainability goals, necessitated by complex upstream-downstream linkages.

International Journal of Disaster Risk Reduction, 2020

Flood Early Warning Systems (FEWS) are implemented in many parts of the world, but early warnings... more Flood Early Warning Systems (FEWS) are implemented in many parts of the world, but early warnings do not always translate into an emergency response from all individuals at risk. This article examines challenges such as warning communication and community response capabilities. Literature review, global online survey results, and experiential knowledge helped identify cross-cutting issues such as failure to use participatory approaches involving communities and addressing their concerns in warning, insufficient preparedness and response levels of FEWS, inadequate translation of disaster risk reduction (DRR) policies into action at the community level, lack of DRR knowledge and practices among key stakeholders, insufficient gender and social inclusion in all stages of FEWS, gaps in institutional communication and collaboration, and, finally, technical and financial constraints. The paper also discusses the contribution of Civil Society Organizations (CSOs) in addressing the identified challenges and eventually strengthening FEWS locally. CSOs were found to act positively at local level challenges and significantly contribute to addressing them through tailored solutions to community concerns. Such solutions include DRR awareness campaigns to educate the communities and key officials; enhanced communication between vulnerable communities and local authorities; transforming reactive community response that relied on government officials to a risk-informed and self-prepared community response; gender inclusion and diversity in various stages of FEWS; and advocacy campaigns to build resilience to disasters. Eventually, policy-based recommendations that can help to root out the challenges discussed in this study are presented.

Stochastic Environmental Research and Risk Assessment, 2020

While Stochastic Weather Generators (SWGs) are used intensively in climate and hydrological appli... more While Stochastic Weather Generators (SWGs) are used intensively in climate and hydrological applications to simulate hydroclimatic time series and estimate risks and performance measures linked to climate variability, there have been few investigations into how many realizations are required for a robust estimation of these measures. Given the computational cost and time necessary to force climate-sensitive systems with multiple realizations, the estimation of the optimal number of synthetic time series to generate with a particular SWG for a predefined accuracy when estimating a particular risk or performance measure is particularly important. In this paper, the required number of realizations of five SWGs coupled with a SWAT model (the Soil and Water Assessment Tool) needed in order to achieve a predefined Relative Root Mean Square Error is investigated. The statistical indices used are the mean, standard deviation, skewness, and kurtosis of four hydroclimatic variables: precipitation, maximum and minimum temperature, and annual streamflow obtained for each observed and model-generated time series. While the results vary somewhat across SWGs, variables and indicators, they overall show that the marginal improvement decreases dramatically after 25 realizations. The results also indicate that the benefit of generating more than 100 realizations of climate and streamflow data is very minimal. The methodology presented herein can be applied in further investigations of other set of risk indicators, SWGs, hydrological models, and watersheds to minimize the required workload. Keywords Stochastic weather generators Á Stochastic hydrological modeling Á Hydrometeorology Á Hydrological risk assessment Á Climate ensemble Á Climate sensitivity Á Climate realizations Á Hydrological realizations

Journal of Geography, Environment and Earth Science International, 2018

Flood is one of the most important natural disasters that cause huge loss of life and properties ... more Flood is one of the most important natural disasters that cause huge loss of life and properties every year around the world. Moreover, the International Federation of the Red Cross and Red Crescent Societies pointed out that floods were by far the greatest cause of homelessness. In West Africa, many countries are damaged from flooding almost every season. Thus, this study aimed to set a seasonal flood forecast model and carried out an evaluation of the level of risk associated with each seasonal forecast. HEC-RAS (Hydrologic Engineering Centers River Analysis System) was used to develop a hydro-dynamical model of Niger river on a 160km reach (80km upstream to 80kmdownstream of Niamey), then a simple risk measure was used to calculate the probability of overtopping the flood protection dykes in Niamey. Results show that the hydro-dynamical model reproduced well the rating curve over the period 2009-2014. A subsequent copula analysis demonstrated a dependency between flow on the Niger river and flow on the Sirba River, the main tributary contributing to the seasonal flood at Niamey. The Gumbel copula was found to be the best among the tested 5 copulas to represent the dependency between peak flow on the main channel of the Niger River and concomitant flow on the Sirba river. It is found that for the six dykes the probabilities of being overtopped by the flood range from very high (100%) to relatively low (16.67 %) over the 34 years of simulation.

This study evaluated the impact of climate change on water resources in a large semi-arid urban w... more This study evaluated the impact of climate change on water resources in a large semi-arid urban watershed located in Niamey Republic of Niger, West Africa. The watershed was modeled using the fully integrated surface-subsurface HydroGeoSpheremodel at a high spatial resolution. Historical (1980-2005) and projected (2020-2050) climate scenario derived from the outputs of three Regional Climate Models (RCM) under the RCP 4.5 scenario were statistically downscaled using the multiscale quantile mapping bias correction method. Results show that the bias correction method is optimum at daily and monthly scales, and increased RCM resolution does not improve the performance of the model. The three RCMs predict increases of up to 1.6% in annual rainfall and of 1.58°C for mean annual temperatures between the historical and projected periods. The durations of the Minimum Environmental Flow (MEF) conditions, required to supply drinking and agriculture water, were found to be sensitive to changes...

Computers & Fluids, 2018

An ideal two-dimensional (2D) shallow water model should be able to simulate correctly various ty... more An ideal two-dimensional (2D) shallow water model should be able to simulate correctly various types of waves including pure gravity and inertia-gravity waves. In this paper, two different triangular C-grid methods are considered, and their dispersion of pure gravity waves, frequencies of inertia-gravity waves and geostrophic balance solutions are investigated. The proposed C-grid methods employ different spatial discretization schemes for coupling shallow water equations together with the various reconstruction techniques for tangential velocity estimation. The proposed reconstruction technique for the second method, which is analogous to a hexagonal C-grid scheme, is shown to be energy conservative and satisfies the geostrophic balance exactly while it supports the unphysical geostrophic modes for hexagonal C-grid. Because of the importance of the application of 2D shallow water models on fully unstructured grids, particular attention is also given to various types of isosceles triangles that may appear in such grids. For the gravity waves, the results of the phase speed ratio of the computed phase speeds over the analytical one are shown and compared. The non-dimensional frequencies of various modes for inertiagravity waves are also investigated and compared in terms of being monotonic and isotropic respect to the continuous solution. The analyses demonstrate some advantages of the first method in phase speed behaviour for gravity waves and monotonicity of inertia-gravity dispersion. The results of the dispersion analysis are verified through a number of numerical tests. The first method, which is shown to have a better performance, examined through more numerical tests in presence of various source terms and results confirm its capability.

Hydrological Sciences Journal, 2018

Two methods for generating streamflow forecasts in a Sahelian watershed, the Sirba basin, were co... more Two methods for generating streamflow forecasts in a Sahelian watershed, the Sirba basin, were compared. The direct method used a linear relationship to relate sea-surface temperature to annual streamflow, and then disaggregated on a monthly time scale. The indirect method used a linear relationship to generate annual precipitation forecasts, a temporal disaggregation to generate daily precipitation and the SWAT (Soil and Water Assessment Tool) model to generate monthly streamflow. The accuracy of the forecasts was assessed using the coefficient of determination, the Nash-Sutcliffe coefficient and the Hit score, and their economic value was evaluated using the cost/loss ratio method. The results revealed that the indirect method was slightly more effective than the direct method. However, the direct method achieved higher economic value in the majority of cost/loss situations, allowed for predictions with longer lead times and required less information.

Advances in Meteorology, 2018

Climate change may accelerate the water cycle at a global scale, resulting in more frequent extre... more Climate change may accelerate the water cycle at a global scale, resulting in more frequent extreme climate events. This study analyzed changes in extreme precipitation events employing climate projections statistically downscaled at a station-space scale in South Korea. Among the CMIP5 climate projections, based on spatial resolution, this study selected 26 climate projections that provide daily precipitation under the representative concentration pathway (RCP) 4.5. The results show that a 20-year return period of precipitation event during a reference period (1980∼2005) corresponds to a 16.6 yr for 2011 to 2040, 14.1 yr for 2041 to 2070, and 12.8 yr for 2071 to 2100, indicating more frequent extreme maximum daily precipitation may occur in the future. In addition, we found that the probability density functions of the future periods are located out of the 10% confidence interval of the PDF for the reference period. The result indicates that the design standard under the reference ...