The application of artificial neural networks (ANNs) has been widely used recently in streamflow forecasting because of their flexible mathematical structure. However, several researchers have indicated that using ANNs in streamflow forecasting often produces a timing lag between observed and simulated time series. In addition, ANNs under-or overestimate a number of peak flows. In this paper, we proposed three data-processing techniques to improve ANN prediction and deal with its weaknesses. The Wilson-Hilferty transformation (WH) and two methods of baseflow separation (one parameter digital filter, OPDF, and recursive digital filter, RDF) were coupled with ANNs to build three hybrid models: ANN-WH, ANN-OPDF and ANN-RDF. The network behaviour was quantitatively evaluated by examining the differences between model output and observed variables. The results show that even following the guidelines of the Wilson-Hilferty transformation, which significantly reduces the effect of local variations, it was found that the ANN-WH model has shown no significant improvement of peak flow estimation or of timing error. However, combining baseflow with streamflow and rainfall provides important information to ANN models concerning the flow process operating in the aquifer and the watershed systems. The model produced excellent performance in terms of various statistical indices where timing error was totally eradicated and peak flow estimation significantly improved. ARTICLE HISTORY

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.

The water resources of the Taza region are diverse and consist of important surface water and groundwater resources. The area is part of the most important groundwater reserves of Morocco. Recently, the region was prone to many flood events where remarkable fluctuations of rainfall and extreme climatic events have been observed. However, there is a lack of studies that cover the different hydrologic aspects of the area and especially, the extreme hydrologic events of the Taza River watershed in which the Taza city is located. To cover this lack, the current study presents an overview of the watershed, including geology, climatology, hydrogeology, geomorphology and especially hydrology. The study focused on the determination of the extreme hydrologic events related to extreme rainfall and streamflow to present basic data sets for further studies. Despite the data scarcity, complexity and the intricate river drainage network of the region, we were able to represent the main hydrologic aspect of the watershed and understand and predicting the system behavior. It was found that the area can be prone to flood risk because of the high flow rates that were calculated using meteorological and hydrological models. In addition, it was found that the basin land use affects directly the hydrodynamic of the river and thus, influence the flood magnitude. The study provides valuable information for understanding the watershed hydrology with a detail never presented before for the study area, where researchers and decision makers can benefit from the outcomes of the study and carry out further assessing the resilience of the watershed to anthropogenic pressure and climate change.

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Abstract:Design flood estimation in ungauged catchments is of great importance in hydrologic practice especially where there is no available data about streamflow. Except the watershed of Anseghmir who is equipped with a gauge station, all the other watersheds are ungauged catchments. The use of frequency analysis of series of rainfall and streamflow is very important for the characterization of the hydrologic resources of the Upper Moulouya. The region has a semiarid climate that requires a good knowledge of the watershed's potential water to assist policy makers in forecasting extreme events, managing water resources and decision making. The frequency analysis was used to determine the design flood of different return periods. The results obtained are used in Gradex method to estimate the hydrologic variables of each subcatchment of the Upper Moulouya. Once the hydrologic study is completed, a principal components analysis was made to highlight the affinities between the different subcatchments and to deduce the hydrologic and hydrographic parameters that better characterize them.