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The sensitivity of research on shoreline monitoring of coastal erosion is justified due to high density population, climate changes impacts, and intensified development, which are squeezing the ecosystem of coastal zones around the world. The budding fields of optical remote sensing such source medium and high-resolution satellite imagery in conjunction with avenue programming of Digital Shoreline Analysis System (DSAS) are widely used extended tools for analyzing the rate of coastal erosion and deposition. Although, there is a geometric growth in the research published documents in the last decades after the start of DSAS in 1990, but its broad insight into global peer groups, its scientometrics, pattern and trends in research activities in monitoring coastal erosion or shoreline change is missing. To breach this gap, 99 bibliographic records published in the Web of Science core collection for the period of 1994-2019 were analyzed using the VOSviewer software. Further, the analysis about global insight of research activities using DSAS in shoreline change analysis focused on (i) general scientometric characteristics of published output, (ii) experts in research themes and their cooperation, (iii) publishable journal list, (iv) institutional distribution and international collaboration, and (v) potential hotspot areas. This systematic analysis of the theme, graphically using rigorous scientmetric tools, will help coastal researchers to visualize the current research trends and prospective guideline for future research. The output of the present study will provide a robust road map to early carrier researchers for their advance inquiry in these fields in coming days. [ABSTRACT FROM AUTHOR]

Soil salinity is one of the most damaging environmental issues worldwide, essentially in arid and semi-arid regions, caused by various factors. Spatial estimation and prediction of salinity is important to predict land evaluation in order to develop and determine leaching factor and the precise management for maximum production. The Lower Cheliff is characterized by the augmentation of rate of soil salinity in 80% of area. In this study, the relationship between both elevation and soil salinity was analysed, giving their role in understanding and estimating the spatial distribution of soil salinity in the Lower Cheliff plain. To conduct this work, 406 samples were taken and analysis of electric conductivity was performed as well as the measurement of the elevation using a GPS. The correlations of soil salinity with elevation were analysed as well. In this study, a great focus on the use of the multiple linear regressions, ordinary kriging and artificial neural network methods was given. The results showed that soil salinity had a good correlation with elevation, and according to the values of coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE), the superiority of MLP model was implied with the value of R² = 0.994, RMSE = 0.63 and MAE = 0.33. [ABSTRACT FROM AUTHOR]

The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997-2009) from a raingauge and also using daily rainfall data (1998-2013) from the Tropical Rainfall Measuring Mission (TRMM). The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8-16-month and 256- 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified. [ABSTRACT FROM AUTHOR]

The existence of long and reliable streamflow data records is essential to establishing strategies for the operation of water resources systems. In areas where streamflow data records are limited or present missing values, rainfall-runoff models are typically used for reconstruction and/or extension of river flow series. The main objective of this paper is to verify the application of Kohonen Neural Networks (KNN) for estimating streamflows in Piancó River. The Piancó River basin is located in the Brazilian semiarid region, an area devoid of hydrometeorological data and characterized by recurrent periods of water scarcity. The KNN are unsupervised neural networks that cluster data into groups according to their similarities. Such models are able to classify data vectors even when there are missing values in some of its components, a very common situation in rainfall-runoff modeling. Twenty two years of rainfall and streamflow monthly data were used in order to calibrate and test the proposed model. Statistical indexes were chose as criteria for evaluating the performance of the KNN model under four different scenarios of input data. The results show that the proposed model was able to provide reliable estimations even when there were missing values in the input data set. [ABSTRACT FROM AUTHOR]

This paper aims to calibrate a physically-based, event-oriented runoff-erosion model by means of a global optimization method known as cuckoo-host co-evolution (CHC) which has co-evolutionary changes incorporated into the traditional cuckoo search algorithm. The physically-based erosion model that was chosen to be optimized here is the watershed erosion simulation program (WESP), which was developed for small semiarid basins to simulate runoff and erosion processes. The optimization technique was tested with the field data collected in an experimental watershed located in a semiarid region of Brazil, and such technique showed to be effective in order to locate the optimal erosion parameter values. On the basis of these results, such values for a semiarid region are given, which could be recommended as an initial estimate for other similar areas. [ABSTRACT FROM AUTHOR]

In this application-based study, the influence of the catchment discretization on the optimization of runoff-erosion modeling using a particle swarm optimization to a physically-based erosion model named WESP (Watershed Erosion Simulation Program) is conducted. This study is carried in the semiarid region of Brazil, more precisely in a micro-catchment (MCN3) of Sumé Experimental Basin. A comparative assessment is done by statistical analysis and mean relative error (MRE) in order to evaluate the performance of the optimization technique when discretizing the catchment in different ways. Thus, the catchment is represented in three ways of discretization (i.e., n1 = 4 elements, n2 = 10 elements and n3 = 23 elements). The difficulties involved in calibration of physically-based erosion models have been partly attributable to the lack of robust optimization tools, hence several robust optimization techniques have been proposed in the past years; however, the way the catchment is represented could interfere on the results. Thus, this paper presents the essential concepts of the runoff-erosion WESP model, the global optimization method known as Repulsive Particle Swarm (RPS), and the optimization results using the three catchment discretization. The results show that there are small differences among the calculated sediment yield using the three ways of basin discretization, although the 23 elements division seems to give the best results. [ABSTRACT FROM AUTHOR]

The increase of house condominiums in the Brazilian cities is gradually increasing due to problems concerning traffic tie-up, air pollution level, amongst others. In these condominiums, large green areas for leisure, comfort and better life quality for the joint owners are reserved. The large house gardens need hard maintenance, which raises the water demand in the condominiums. The use of the rainwater is an alternative that could be used in Brazil and other countries to minimize the use of potable water in nonpotable water needs, such as car wash, garden irrigation, etc. This paper evaluates the precipitation in João Pessoa city (capital of Paraíba state, Brazil), according to the frequency analysis and significance test. Thus, it was applied a robust tool to analyze signal frequency, named wavelet transform, which is appropriated to analyze irregular events and non-stationary series. It was analyzed two precipitation series of João Pessoa city, 1937-1970 and 1980-1996, when it was observed a significant annual signal at level 10%, which revealed the existence of an annual rainy season, which is very convenient for the water storage for further using during the dry season. Finally, the reservoir is an important item in the rainwater system and it has to be correctly design in order to make the system economically practicable. The Rippl method was used for the reservoir sizing analysis. [ABSTRACT FROM AUTHOR]