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Since the early 1980s, several regions of Morocco have experienced alternating series of wet and dry periods related to climate change, with significant consequences for the country’s economy. This study aims to map flood hazards by using a hydraulic modeling approach, with a specific focus on the Oued (river) Zaouiat Sidi Hamza passing through Zaouiat Sidi Hamza township belonging to the High Ziz watershed (province of Midelt, region of Drâa-Tafilalet, Morocco). Hydraulic modeling and flood simulation were carried out followed by mapping of the flood hazard. The Oued Zaouiat Sidi Hamza River can cause torrential flooding issues, particularly during periods of heavy storms, impacting agricultural land and certain buildings on both river banks. All the cultivated areas developed alongside the river are at risk of flooding. Moreover, undermining and erosion of the river’s banks lead to rising high-water levels and flooding agricultural terraces. The use of geographic information systems and hydraulic modeling tools is essential to gain a deeper understanding of this situation. Also, the mapping of lineaments and fractures in the study area, carried out by satellite image processing, helped to quantify the directional influence of these lineaments on the flow of the hydrographic network, on the orientation of the circulation of surface water, and on the storage of groundwater. According to this study, the most vulnerable areas to flooding and erosion are those that receive the most water in the basin and have steep slopes. Decision-makers can use the results to produce development plans tailored to combat these risks and raise awareness among the population concerned, improving water resource evaluation and forecasting, as well as improving agricultural production.

This study aims to contribute to a better estimation of the density of fractures likely to favour the drainage of surface water in the High Ziz River (HZR) basin. The method adopted consists of the use of different airborne image processing techniques (filtering, enhancement and slope analysis) which allow a good discrimination of image discontinuities (lineaments) that can then be used for producing lineament maps. The influence of these lineaments on the underground flow is then studied. Indeed, it was possible to extract the lineament network, following the exploitation of remote sensing and an objectively completed analog analysis using the PCI Geomatica LINE module and its directional filters (Sobel directional filters by the ACP method), and to extract the hydrographic network of the HZR basin, using the ArcHydro tool. After superimposing these data, their thematic maps (of the lineament and hydrographic network) were developed. In addition, this comparison of the two hydrographic networks and lineament maps showed us very varied flow directions influenced by geological structures, particularly fracturing. The topography of the region also has a secondary impact on flows through the presence of slopes generally oriented towards the SE of the basin. The correlation of the results with the different directions of the orders of the hydrographic network allowed us to identify the potential effects of lineaments on the orientations of surface water circulation. In addition to these results, the realization of the Rose diagram indicated that the dominant trend in lineaments is N90–45N° (NE–SW).

One of the adverse impacts of climate change is drought, and the complex nature of droughts makes them one of the most important climate hazards. Drought indices are generally used as a tool for monitoring changes in meteorological, hydrological, agricultural and economic conditions. In this study, we focused on meteorological drought events in the High Ziz river Basin, central High Atlas, Morocco. The application of drought index analysis is useful for drought assessment and to consider methods of adaptation and mitigation to deal with climate change. In order to analyze drought in the study area, we used two different approaches for addressing the change in climate and particularly in precipitation, i) to assess the climate variability and change over the year, and ii) to assess the change within the year timescale (monthly, seasonally and annually) from 1971 to 2017. In first approach, precipitation data were used in a long time scale e.g. annual and more than one-year period. For this purpose, the Standardized Precipitation Index (SPI) was considered to quantify the rainfall deficit for multiple timescales. For the second approach, trend analysis (using the Mann-Kendall (M-K) test) was applied to precipitation in different time scales within the year. The results showed that the study area has no significant trend in annual rainfall, but in terms of seasonal rainfall, the magnitude of rainfall during summer revealed a positive significant trend in three stations. A significant negative and positive trend in monthly rainfall was observed only in April and August, respectively.

In order to facilitate the monitoring of groundwater quality in France, the groundwater bodies (GWB) in the Provence-Alpes-Côte d'Azur region have been grouped into 11 homogeneous clusters on the basis of their physico-chemical and bacteriological characteristics. This study aims to test the legitimacy of this grouping by predicting whether water samples belong to a given sampling point, GWB or group of GWBs. To this end, 8673 observations and 18 parameters were extracted from the Size-Eaux database, and this dataset was processed using discriminant analysis and various machine learning algorithms. The results indicate an accuracy of 67% using linear discriminant analysis and 69 to 83% using ML algorithms, while quadratic discriminant analysis underperforms in comparison, yielding a less accurate prediction of 59%. The importance of each parameter in the prediction was assessed using an approach combining recursive feature elimination (RFE) techniques and random forest feature importance (RFFI). Major ions show high spatial range and play the main role in discrimination, while trace elements and bacteriological parameters of high local and/or temporal variability only play a minor role. The disparity of the results according to the characteristics of the GWB groups (geography, altitude, lithology, etc.) is discussed. Validating the grouping of GWBs will enable monitoring and surveillance strategies to be redirected on the basis of fewer, homogeneous hydrogeological units, in order to optimize sustainable management of the resource by the health agencies. [ABSTRACT FROM AUTHOR]

Global increases in the occurrence and frequency of flood have highlighted the need for resilience approaches to deal with future floods. The principal component analysis (PCA) has been used widely to understand the resilience of the urban system to floods. Based on feature extraction and dimensionality reduction, the PCA reduces datasets to representations consisting of principal components. Kernel PCA (KPCA) is the nonlinear form of PCA, which efficiently presents a complicated data in a lower dimensional space. In this work the KPCA techniques was applied to measure and map flood resilience across a local level. Therefore, it aims to improve the performance achieved by non-linear PCA application, compared to standard PCA. Twenty-one resilience indicators were gathered, including social, economic, physical, and natural components into a composite index (Flood resilience Index). The experimental results demonstrate the KPCA performance to get a better Flood Resilience Index, guiding q decision making to strengthen the flood resilience in our case of study of M’diq-Fnideq and martil municipalities in Northern of Morocco.

The objective of this study is to investigate the evolution of rainfall and flow in the Bouregreg watershed, and to identify the most vulnerable regions to climate change over a period of 36 years from 1977 to 2013. Results show significant variations between these sub-regions in term of monthly flows and monthly regimes. January and February rainfall amounts are the most affected by the reduction of rainfall since the drought started end of the 1970's, inducing a reduction of flows at all hydrological stations mainly since 1979. The year 1996 shows very high precipitations over all sub-basins, and also separates two periods with different rainfall time series variations according to two regions over the basin: the region of the Tsalat sub-basin in the Southeast wet and mountainous area (Middle Atlas) shows a durable decrease of rainfall compared to the Ain Loudah sub-basin in the Center-West semi-arid plateau area. [ABSTRACT FROM AUTHOR]

Enhancing resilience is critical for coastal urban systems to cope with and minimize flood disaster risks. Global increases in the frequency of floods is a major concern for many areas in Africa. In this regard, urban planners need increasingly accurate approaches to set up a standard for measuring the resilience to floods. In Morocco, this issue is still not fully covered by the scientific community, despite the obvious need for a new approach adapted to local conditions. Using three northern coastal municipalities, this study applied a composite index and geographic information system approach to measure and map resilience to floods. The approach is also based on a linear ranking of resilience parameters, offering a more optimal classification of spatial resilience variation. The findings allowed to identify specific areas with different resilience levels and revealed the relationship between urban dimensions and the flood resilience degree. This approach provides an efficient decision support tool to facilitate flood risk management especially in terms of prioritization of protective actions. [ABSTRACT FROM AUTHOR]

A 110 ha dump, located in the Akrach shallow aquifer area in Morocco, was studied in order to characterize the quality of groundwater around the landfill, to delineate the contaminated area and to determine the factors favouring the contamination of groundwater. This dump is located in the city of Oum Azza (15 km south from Rabat), (Map 1). between the Akrach River in the west and the Sidi Mohamed Ben Abdellah Dam in the east. To assess groundwater pollution from this landfill, piezometric monitoring and Hydrochemical analyses were conducted on 22 wells. The results highlight a significant degradation in the groundwater quality, especially in the parts located in the direct vicinity downstream the dump. In the impacted areas, electrical conductivity was above 1100 μS cm-1, bicarbonates were higher than 508 mg L-1, chlorides, sulphate, and nitrates contents were higher than 850, 200 and 1 mg L-1, respectively. In addition we found high cadmium (50 - 100 μg L-1) and chromium (40 - 230 μg L-1) contents, i.e. much higher than the WHO guidelines for drinking or irrigation water. A principal component analysis conducted on this dataset highlights the absence of a prevalent principal component (PC), with the variance distributed across many PCs. The mechanisms responsible for the chemical variance of the hydro system are therefore numerous and fairly balanced in terms of influence. Finally, a hierarchical classification brings out three groups of observations, each group corresponding to a level of pollution. [ABSTRACT FROM AUTHOR]

Coastal and marine management require the evaluation of multiple environmental threats and issues. However, there are gaps in the necessary data and poor access or dissemination of existing data in many countries around the world. This research identifies how remote sensing can contribute to filling these gaps so that environmental agencies, such as the United Nations Environmental Programme, European Environmental Agency, and International Union for Conservation of Nature, can better implement environmental directives in a cost-effective manner. Remote sensing (RS) techniques generally allow for uniform data collection, with common acquisition and reporting methods, across large areas. Furthermore, these datasets are sometimes open-source, mainly when governments finance satellite missions. Some of these data can be used in holistic, coastal and marine environmental management frameworks, such as the DAPSI(W)R(M) framework (Drivers–Activities–Pressures–State changes–Impacts (on Welfare)–Responses (as Measures), an updated version of Drivers–Pressures–State–Impact–Responses. The framework is a useful and holistic problem-structuring framework that can be used to assess the causes, consequences, and responses to change in the marine environment. Six broad classifications of remote data collection technologies are reviewed for their potential contribution to integrated marine management, including Satellite-based Remote Sensing, Aerial Remote Sensing, Unmanned Aerial Vehicles, Unmanned Surface Vehicles, Unmanned Underwater Vehicles, and Static Sensors. A significant outcome of this study is practical inputs into each component of the DAPSI(W)R(M) framework. The RS applications are not expected to be all-inclusive; rather, they provide insight into the current use of the framework as a foundation for developing further holistic resource technologies for management strategies in the future. A significant outcome of this research will deliver practical insights for integrated coastal and marine management and demonstrate the usefulness of RS to support the implementation of environmental goals, descriptors, targets, and policies, such as the Water Framework Directive, Marine Strategy Framework Directive, Ocean Health Index, and United Nations Sustainable Development Goals. Additionally, the opportunities and challenges of these technologies are discussed. [ABSTRACT FROM AUTHOR]