JWSS - Journal of Water and Soil Science

Since the development of surface water control needs accurate access to flow behavior of sediment rates, the lack of sediment measurement stations, the novelty of most stations and the lack of statistics on the deposit make it difficult to properly evaluate and simulate the flow behavior and their sediments. In a watershed, the morphological characteristics and sediment load of flow affect each other. It is, thus, important to know about the extent of this relationship to manage and control the flow in downstream areas. In the present study, using artificial neural networks and sediment rating regression methods based on the data from 136 events and also morphological parameters, we have attempted to predict the sediment load of Bagh Abbas basin. In the first step, we used flow data to predict the sediment load of both methods, and then basin morphological characteristics such as the compactness factor and form factor were added to the models. The results of this study showed that by using neural networks of Multilayer Perceptron (MLP) type with Levenberg – Marquardt algorithm and the stimulation function of tangent Sigmoid with two hidden layers and four neurons in each layer, we can predict suspended sediment discharge rate with a sufficient accuracy. Accuracy of the results obtained from the ANN method was higher than the accuracy of rating curve method. In the evaluation of NGANN & GANN network methods and SRC & MARS regression methods, correlation coefficients were respectively calculated as 0.94, 0.93, 0.767, 0.766, and root mean square errors (RMSE), 0.45, 0.49, 2.3 and 2.3. Nash coefficient (NS) was calculated respectively as 0.71, 0.58, 0.27 and 0.23. Therefore, the most efficient method among the four models is artificial neural network combined with morphological data (GANN). Furthermore, the findings of the study show that adding geomorphological parameters to sediment rating has little effect on the model performance.

Underground dams are structures built in underground and are capable of saving and making the underground water available. In this research, by using the SWOT analysis model, suitable locations were investigated for the development of an underground dam in the Keriyan area of Hormozgan province.  At first, the necessary data and information were provided by visiting the region and presenting a questionnaire to the residents of the area and experts to investigate the strengths, weaknesses, opportunities and threats in the region for the underground dams. In the final step, by using the SWOT model and QSPM matrix, a comprehensive and appropriate strategy for underground dams was determined. The results showed that among the internal factors, not decreasing the volume of the reservoir due to deposits and reducing the evaporation from the reservoir with a final value of 0.85 and 0.66, and among the external factors, the willingness and cooperation of the relevant organizations and the disruption of downstream water rights with a final value of 0.68 and 0.66 had the greatest impact on selecting the strategy. Based on the results related to the internal and external factors, the strategy was placed in the maximum-maximum quadrant; in line with the strategy, by using the strengths and opportunities, the weaknesses should be overcome and the threats should be tackled. Some strategies were presented. In order to prioritize these strategies, the quantitative matrix QSPM was used. Finally, the hydrological, economic, social and environmental evaluating strategies of underground dams, before and after the construction, with a final score of 19.3 were prioritized.