Discussion of “Interfacing the geographic information system,remote sensing,and the soil conservation service-curve number method to estimate curve number and runoff volume in the ASIR region of Saudi Arabia” by Fawzi S. Mohammad,Jan Adamowski

The soil conservation service curve number (SCS-CN) method is one of the most commonly used methods to compute the direct runoff from a rainfall event. Since the method was established, numerous researches were undertaken to improve the method through accurate estimation of its parameter and especially the curve number (CN). However, the essence of the SCS method, as an event-based Hortonian mechanism method, remained unchanged. The main assumption of the method related to the rainfall input is that the rainfall is continuous in time and uniform over the watershed. Mohammad and Adamowski (2015) paper apparently used the SCS method to estimate the annual runoff using the annual rainfall as one cumulative rainfall input value, which is a violation of the event-based principle of the method and of the assumption of the continuity of the rainfall event.To re-estimate the average annual runoff more realistically for the Asir region, Saudi Arabia, daily rainfall data from 14 rainfall stations are used for calculating the resulting runoff depths, on a daily event-by-event rainfall basis, throughout the whole simulation period. The resulting runoff depths are added for each year, and the total cumulative annual runoff values for each year are averaged to get the average annual runoff. The runoff values based on the previously mentioned procedure are an upper limit of the actual average annual runoff as the underlying SCS equations discard evaporation and similar long-term losses. Nevertheless, the average runoff values obtained in the discussion paper are an order of magnitude (at least five to tenfold) lower than the ones of the original paper. An equation is proposed to obtain a more realistic estimate of the average annual runoff, to be used with the average annual rainfall as an input, if the annual value is the only available rainfall information.     

Regional modeling of dust storm of February 8, 2015 in the southwest of Iran

According to World Meteorological Organization report in 2015, the southwest of Iran has become one of the dust sources in the region. And the objective of this research is to study the dust storms originating in this region. For this purpose, based on the weather data of 14 stations, the dust storms of the region were investigated, and the dust storm of February 7, 2015, was selected due to its very high concentration of dust particles (66 times the normal values). For the analysis of source areas and storm paths, the FNL data was used. The regional models of Navy Aerosol Analysis and Prediction System (NAAPS), Barcelona Supercomputing Centre-Dust Regional Atmospheric Model 8b (DREAM 8b), Non-hydrostatic Multiscale Model Barcelona Supercomputing Center (NMMB/BSC), and hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) were used to study and analyze the selected storm. The results showed that the dust event in February 8, 2016, has been the result of the polar front jet stream (PJF) caused by western immigrant system that had been over the Sahara in Africa, the deserts of Iraq, Syria, Saudi Arabia, and finally southwest of Iran in making the extreme dust event. According to the Moderate Resolution Imaging Spectroradiometer data and point models of NAAPS, optical depth was very high. The DREAM 8b and NMMB/BSC models confirmed the impact of the local factors and closeness to the dust source regions. The backward tracking of the model with the HYSPLIT model showed three tracks transporting the dust particles to the region. This software also showed that the dust particles occupied an atmospheric tunnel of 1.5 km in diameter.     

Assessment of proposed approaches for bathymetry calculations using multispectral satellite images in shallow coastal/lake areas: a comparison of five models

Bathymetric information for shallow coastal/lake areas is essential for hydrological engineering applications such as sedimentary processes and coastal studies. Remotely sensed imagery is considered a time-effective, low-cost, and wide-coverage solution for bathymetric measurements. This study assesses the performance of three proposed empirical models for bathymetry calculations in three different areas: Alexandria port, Egypt, as an example of a low-turbidity deep water area with silt-sand bottom cover and a depth range of 10.5 m; the Lake Nubia entrance zone, Sudan, which is a highly turbid, unstable, clay bottom area with water depths to 6 m; and Shiraho, Ishigaki Island, Japan, a coral reef area with varied depths ranging up to 14 m. The proposed models are the ensemble regression tree-fitting algorithm using bagging (BAG), ensemble regression tree-fitting algorithm of least squares boosting (LSB), and support vector regression algorithm (SVR). Data from Landsat 8 and Spot 6 satellite images were used to assess the performance of the proposed models. The three models were used to obtain bathymetric maps using the reflectance of green, red, blue/red, and green/red band ratios. The results were compared with corresponding results yielded by two conventional empirical methods, the neural network (NN) and the Lyzenga generalised linear model (GLM). Compared with echosounder data, BAG, LSB, and SVR results demonstrate higher accuracy ranges from 0.04 to 0.35 m more than Lyzenga GLM. The BAG algorithm, producing the most accurate results, proved to be the preferable algorithm for bathymetry calculation.     

Improved geological mapping using landsat-5 TM data in Weixi area, Yunnan province China

Different image processing algorithms have been evaluated in the context of geological mapping using Landsat TM data. False color composites, the principal component imagery, and IHS decorrelation stretching method for Landsat-5 TM data have been found useful for delineating the regional geological features, mainly to provide the maximum geological information of the studied area . The study testifies that using which image processing yields best results for geological mapping in arid and semiarid regions by preserving morphological and spectral information. Generally, the studied area can be divided into three main geological units: Basaltic intrusive rocks, Metamorphic with varying intensities and Sedimentary rocks.     

Simultaneous Determination of 11 Sulfonamides by HPLC–UV and Application for Fast Screening of Their Aerobic Elimination and Biodegradation in a Simple Test

Sulfonamides (SAs) are one of the most frequently used antibiotics. SAs have been found in various environmental compartments. If SAs are not degraded in the environment, they can affect bacteria by their antibiotic properties and contribute to bacterial antibiotic resistance. Therefore, the biodegradability of 11 SAs (sulfanilamide, sulfaguanidine monohydrate, sulfadiazine, sulfathiazole, sulfapyridine, sulfamerazine, sulfamethoxypyridazine, sulfachloropyridazine, sulfamethazine, sulfamethoxazole, and sulfadimethoxine) was studied. For this purpose, the Closed Bottle Test (CBT, OECD 301D) was performed, which includes a toxicity control. In order to monitor the environmental fate of the parent compound and to check for transformation products, a simple, efficient, and reliable HPLC–UV method for the simultaneous determination of these SAs has been developed. Acetonitrile and water (with 0.1% formic acid) were used as mobile phase solvents for gradient elution. The method was validated in terms of precision, detection and quantitation limits, selectivity, and analytical solution stability. In the CBT, none of these SAs was readily biodegradable. The HPLC–UV analysis confirmed that no degradation of any SA took place. In the toxicity control, these SAs showed no toxic effect in the used concentration of environmental bacteria applied in the test.