The effects of floodplain vegetation on river planform have been investigated for a medium-sized river using a 2D morphodynamic model with submodels for flow resistance and plant colonization. The flow resistance was divided into a resistance exerted by the soil and a resistance exerted by the plants. In this way it was possible to reproduce both the decrease in bed shear stress, reducing the sediment transport capacity of the flow within the plants, and the increase in hydraulic resistance, reducing the flow velocities. Colonization by plants was obtained by instantaneously assigning vegetation to the areas that became dry at low water stages. This colonization presents a step forward in the modelling of bank accretion. Bank erosion was related to bed degradation at adjacent wet cells. Bank advance and retreat were reproduced as drying and wetting of the computational cells at the channel margins. The model was applied to a hypothetical case with the same characteristics as the Allier River (France). The river was allowed to develop its own geometry starting from a straight, uniform, channel. Different vegetation densities produced different planforms. With bare floodplains, the river always developed a braided planform, even if the discharge was constant and below bankfull. With the highest vegetation density (grass) the flow concentrated in a single channel and formed incipient meanders. Lower vegetation density (pioneer vegetation) led to a transitional planform, with a low degree of braiding and distinguishable incipient meanders. The results comply with flume experiments and field observations reported in the literature.

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Most areas around the world lack fine rainfall records which are needed to derive Intensity-Duration-Frequency (IDF) curves, and those that are available are in the form of daily data. Thus, the disaggregation of rainfall data from coarse to fine temporal resolution may offer a solution to that problem. Most of the previous studies have adopted only historical rainfall data as the predictor to disaggregate daily rainfall data to hourly resolution, while only a few studies have adopted other historical climate variables besides rainfall for such a purpose. Therefore, this study adopts and assesses the performance of two methods of rainfall disaggregation one uses for historical temperature and rainfall variables while the other uses only historical rainfall data for disaggregation. The two methods are applied to disaggregate the current observed and projected modeled daily rainfall data to an hourly scale for a small urban area in the United Kingdom. Then, the IDF curves for the current and future climates are derived for each case of disaggregation and compared. After which, the uncertainties associated with the difference between the two cases are assessed. The constructed IDF curves (for the two cases of disaggregation) agree in the sense that they both show that there is a big difference between the current and future climates for all durations and frequencies. However, the uncertainty related to the difference between the results of the constructed IDF curves (for the two cases of disaggregation) for each climate is considerable, especially for short durations and long return periods. In addition, the projected and current rainfall values based on disaggregation case which adopts historical temperature and rainfall variables were higher than the corresponding projections and current values based on only rainfall data for the disaggregation.

A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the  downstream side of the structure to overcome an excessive exit gradient. The Geo-studio software was used to analyze 1200 different cases. For each case thelength of protection (L) and volume of structure (V) required to satisfy the safety factors mentioned previously were estimated for the input values, namely, the upstream cutoff depth (S1), the downstream cutoff depth (S2), the foundation width (B), the angle of inclination of the upstream cutoff (Ɵ1)  and the angle of inclination of the downstream cutoff (Ɵ2), H (differencehead), kr (degree of anisotropy) and D (depth of impervious layer). An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the crossover probability, the mutation probability and level,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factors that affects. the optimum solution is the $ number of population required. The minimum value that gives stable global optimum solution of this parameter is (30000) while other variables have little effect on the optimum solution.

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This study evaluated the suitability of an adsorption technique in drainage water treatment for irrigation purposes. The water samples for this study were sourced from different spots of Al-MASAB AL A’AM river. Three different locations (Latifia, Yusufiyah, and Swerah area) were considered in this study. Several studies have reported the use of activated carbon and ion exchangers for water treatment. In this work, a cheap alternative bio-filtration media (activated carbon derived from Apricot stones (ASAC)) was used. Several parameters are required in this technique for various estimations; such parameters include the chemical and physical properties of the water samples (like the pH, ionic concentration, electrical conductivity (EC), and total dissolved solids (TDS). The Freundlich equations was also applied to study the chemical adsorption process using ASAC. Also calculated were the adsorption constant (k) and the number of adsorbents (n). From the results of this study, the applied process was suitable for the removal of Ca+2, Mg+2 and CO3-2 ions from the sampled water.

The rain gauge, which is the preferred device for rain rate quantification, is susceptible to various types of errors. The problems of inconsistency and incompletion of rainfall time-series, in addition to data quality issues obstruct hydrometeorological analysis. Daily rainfall data from 30 gauges in Northern England were quality controlled by a double quality check procedure for the period 2006–2014 to solve any specific data quality issues. It emerged that fault readings happened only over a few days compared with the high percentage of missing data which could reach years. Thus, factors that impact gauges’ missing data were inspected. It was found that snowfalls, land cover-land use and bird distribution are the dominant factors that malfunctioning the rain gauge for long time periods, often producing successive missing days that could be extended months in total. However, when the missing data happened on separate days, then it seemed that high winds related with light rainfall resulted in drifting away the rainfall from the rain gauge and thus caused missing data. Moreover, the rainfall itself was not one of the major factors to malfunction the gauge, because the values of missed rainfall were not quite extreme to do this.