Hydrological models are widely used for runoff simulation throughout the world. The objective of this study is to check the performance of the HEC-HMS model for continuous runoff simulation of Gilgel Gibe watershed. It includes sensitivity analysis, calibration, and validation. The model calibration was conducted with data from the year 1991 to 2002 and validated for the year 2003 to 2013 period using daily observed stream flow near the outlet of the watershed. To check the consistency of the model, both the calibration and validation periods were divided into two phases. The sensitivity analysis of parameters showed that curve number (CN) and wave travel time (K) were the most sensitive, whereas channel storage coefficient (x) and lag time (tlag) were moderately sensitive. The model performance measured using Nash–Sutcliff Efficiency (NSE), Percentage of Bias (PBIAS), correlation coefficient (R2), root mean square error (RMSE), and Percentage Error in Peak (PEP). The respective values were 0.795, 8.225%, 0.916, 27.105 m3 s–1 and 7.789% during calibration, and 0.795, 23.015%, 0.916, 29.548 m3 s–1 and –19.698% during validation. The result indicates that the HEC-HMS model well estimated the daily runoff and peak discharge of Gilgel Gibe watershed. Hence, the model is recommended for continuous runoff simulation of Gilgel Gibe watershed. The study will be helpful for efficient water resources and watershed management for Gilgel Gibe watershed. It can also be used as a reference or an input for any future hydrological investigations in the nearby un-gauged or poorly gauged watershed.

Changes in land use as a result of human activities may generate the alteration of hydrometeorological disasters. Erosion, sedimentation, floods and landslides frequently occur in the Sanenrejo watershed (±292 km2), located in East Java, Indonesia. In this paper, the soil and water assessment tool (SWAT) model is used to evaluate the hydrological processes in this small watershed. The digital elevation model (DEM) is used as the primary input for deriving the topographic and physical properties of the watershed. Other input data used for the modelling processes include soil type, land use, observed discharge data and climate variables. These data are integrated into the SWAT to calculate discharge, erosion and sedimentation processes. The existing observed discharge data used to calibrate the SWAT output at the watershed outlet. The calibration results produce Nash–Sutcliffe efficiency ( NSE) of 0.62 and determination coefficient (R2) of 0.75, then the validation result of 0.5 (NSE) and 0.63 (R2). The middle area faced the highest erosion and sedimentation that potentially contribute to hydrometeorological disasters.

The problem of flood vulnerability has been reviewed in several studies, however, the reviews focused exclusively either on the social or on the physical component of the problem. The components of flood vulnerability are interdependent and each of them makes an equally important contribution to the flood vulnerability index. This study identifies and evaluates the integrated flood vulnerability index ( FVI) of an area by considering its multiple components (social, economic, and environmental). The Analytic Hierarchy Process (AHP) method was applied to evaluate the weight of each component. The evaluation was based on the judgements of experts working at local government policy- making agencies. The input data for the AHP were acquired through a questionnaire survey. Eleven indicators that delivered significant results were then selected. The FVI results show high flood vulnerability at the local scale. The FVI provides the basis for the identification of villages with high vulnerability indices. The results provide essential information about pluvial flood vulnerability at the local scale, about the area with the highest vulnerability index, and the most vulnerable villages. The results also show that the components that have a significant impact on the flood vulnerability index include environmental components (43.4%), social components (28.5%), and physical components (28.1%).

In the current study, it was tried to investigate the medicinal plants of the native flora of the Northern Tien Shan to bring them into domestication. The study was carried out on the territory of a botanical garden located at an altitude of 880 m a.s.l., in the foothill steppe zone of the Zailiysky Alatau ridge, People’s Republic of China on light chestnut loamy soils. In 2018–2019, more than 90 samples of 51 species of medicinal plants of the Northern Tien Shan flora was selected from 17 families for introduction tests. The families Compositae (10 genera, 12 species) and Lamiaceae (12 genera, 13 species) were represented by the largest numbers of genera and species. The family Leguminosae was represented by four species from four genera; the families Polygonaceae and Ranunculaceae, by three species each; the family Rosaceae, by two species; and the remaining 11 families, by one species each. The results suggested that the majority of medicinal plants of the Northern Tien Shan tested can be successfully cultivated in the foothill zone of the Zailiysky Alatau. The results indicated that when propagated by seed, the laboratory germination varied from 2 to 30%, and the mass of seeds was 0.21 g. When sown in spring, the field germination was 8%, and when sown in autumn, 42% from 50 to 70% of seedlings survived until the end of the growing season. The massive flowering was observed in the third year, and the plants vegetated until the end of the growing season.

This article examines the short- and long-run effects of water price, system input, income, temperature on domestic water demand for Amman area over the period of 1980–2012. An empirical, dynamic autoregressive distributed lag (ARDL) model for water demand is developed on a yearly basis. This approach is capable of testing and analysing the dynamic relationship with time series data using a single equation regressions. Results show the ability of the model to predicting future trends (short- and long-run association). The main results indicate that water demand in limited water environment is partially captured in the long-run by the amount of water reaching the customer. The short- and long-run elasticities of water price (–0.061, –0.028) and high temperature (0.023, 0.054) indicate inelastic behaviour on water demand both in short- and long-run, while the lagged water price has a significant effect on demand. Income represented by gross domestic product (GDP) slightly affects water consumption in the long-run and insignificantly in the short-run (0.24, 0.24). Water consumption is strongly linked to consumption habits measured by lagged billed amount 0.35, and is strongly linked to amount of supplied water both in short- and long-run (0.47, 0.53). These results suggest that water needs should be satisfied first to allow controlling water demand through a good pricing system.
Moreover, the association identified between demand and water system input, and the lesser elasticities of water price and other explanatory variables confirm the condition of water deficit in Amman area and Jordan. The results could be rolled out to similar cities suffering scarce water resources with arid and semi-arid weather conditions.

A multiple regression model approach was developed to estimate buffering indices, as well as biogas and methane productions in an upflow anaerobic sludge blanket (UASB) reactor treating coffee wet wastewater. Five input variables measured (pH, alkalinity, outlet VFA concentration, and total and soluble COD removal) were selected to develop the best models to identify their importance on methanation. Optimal regression models were selected based on four statistical performance criteria, viz. Mallow’s Cp statistic (Cp), Akaike information criterion ( AIC), Hannan– Quinn criterion ( HQC), and Schwarz–Bayesian information criterion ( SBIC). The performance of the models selected were assessed through several descriptive statistics such as measure of goodness-of-fit test (coefficient of multiple determination, R2; adjusted coefficient of multiple determination, Adj-R2; standard error of estimation, SEE; and Durbin–Watson statistic, DWS), and statistics on the prediction errors (mean squared error, MSE; mean absolute error, MAE; mean absolute percentage error, MAPE; mean error, ME and mean percentage error, MPE). The estimated model reveals that buffering indices are strongly influenced by three variables (volatile fatty acids (VFA) concentration, soluble COD removal, and alkalinity); while, pH, VFA concentration and total COD removal were the most significant independent variables in biogas and methane production. The developed equation models obtained in this study, could be a powerful tool to predict the functionability and stability for the UASB system.

A field survey has been conducted for the study area using the Global Positioning System (GPS) and geological and geomorphological maps of the area. The study area is one of the important areas in Iraq characterized by scarce water resources. The purpose of the study is to determine the hydro-chemical processes and their relationship to groundwater quality carried out in the southwestern desert region of Iraq, where the region lacks extensive studies of water resources. Twenty-eight groundwater samples were collected from wells distributed between the eastern borders of Saudi Arabia and the West Bank of the Euphrates River. For the purpose of hydrogeochemical analyses, the Fetter method was used to collect and examine samples. A large part of the recharge area is located in Saudi Arabia, where the groundwater bearing aquifer represented by the Dammam formation extends to Iraq and Saudi Arabian International borders. The analysis determined the order of cations (Na+ > Ca2+ > Mg2+ > K+) and anions (Cl– > SO42– > HCO3–). High values of the variation coefficient (CV) correspond to the concentration of potassium, sodium and chloride ions (CV: 68.7, 64.7 and 64 respectively). To identify the hydrochemical water facies, the Piper diagram was used. It was found that 53% of the water samples belong to the Na-Cl type and 40% are of the Ca-Mg-Cl type, while the rest of the samples are the Ca-Cl type. To identify geochemical processes, it was found that ion exchange processes via chloroalkaline indices 1 and 2 are prevalent between Ca2+, Mg2+ in the groundwater and Na+, K+ in water bearing rocks. To learn more about the processes that led to the concentration of certain ions, such as sodium, it was found that they tend to be of silicate minerals related to surface runoff of water in recharge areas and carbonic rocks. It was also found that rock / soil-groundwater interaction and evaporation processes were the formal processes in the saturated zone and evaporation in the unsaturated zone are prevalent processes of groundwater ion concentration.

Gauging stations of meteorological networks generally record rainfall on a daily basis. However, sub-daily rainfall observations are required for modelling flood control structures, or urban drainage systems. In this respect, determination of temporal distribution of daily rainfall, and estimation of standard duration of rainfall are significant in hydrological studies. Although sub-daily rainfall gauges are present at meteorological networks, especially in the developing countries, their number is very low compared to the gauges that record daily rainfall.
This study aims at developing a method for estimating temporal distribution of maximum daily rainfall, and hence for generating maximum rainfall envelope curves. For this purpose, the standard duration of rainfall was examined. Among various regression methods, it was determined that the temporal distribution of 24-hour rainfall successfully fits the logarithmic model. The logarithmic model’s regression coefficients (named a and b) were then linked to the geographic and meteorological characteristics of the gauging stations. The developed model was applied to 47 stations located at two distinct geographical regions: the Marmara Sea Region and Eastern Black Sea Region, Turkey. Various statistical criteria were used to test the method's accuracy, and the proposed model provided successful results. For instance, the RMSE values of the regression coefficients a and b in Marmara Regions are 0.004 and 0.027. On the other hand, RMSE values are 0.007 and 0.02 for Eastern Black Sea Region.

The present study aimed to assess groundwater quality according to the water quality index (WQI) in Ali Al- Gharbi district of the Maysan Governorate in eastern Iraq. For this purpose, 10 physical parameters such as pH, total hardness ( TH), magnesium (Mg2+), calcium (Ca2+), potassium (K+), sodium (Na+), sulphate (SO42–), chloride (Cl–), nitrate (NO3–), and total dissolved solids ( TDSs) were examined since 2019 from 16 different locations (viz. wells). The analysis results indicated that 18.75% of the water samples were of good quality, 56.25% of them had low quality, and 25% of such samples were very poor. The WQI also varied from 69.67 and 297.6. Therefore, prior to water use, there is a dire need for some treatments, as protecting this district from pollution is significant.

Using microorganisms in eliminating or reducing the impacts of harmful remnants is very ancient manner. The current study was conducted to explore the potential of utilizing some fungi species that isolated from the main sewage treatment plant in Al-Muamirah area, Babylon-Iraq, in reducing some pollutants. Six fungi taxa Aspergillus flavus, A. niger, A. terrues, Candida albicans, C. krusei, and Penicillium digitatum were identified before any treatment process, whereas only four fungi species A. flavus 20%, A. niger 20%, A. terrues 10%, and P. digitatum 18% were recognized after completing the physical and chemical treatment stages. Only three taxa A. niger, A. terrues, and P. digitatum were employed to reveal their capability in treating the sewage water, which represent the biological treatment stage as the final step of the treatment processes. The results showed a considerable capability of these fungi species in decreasing many variables values such as pH, total soluble solids (TSS), electrical conductivity (EC), salinity, total alkalinity, chlorides, nitrite, and phosphate. Where, slightly low reduction was detected in TSS value in all experiments (1.1–5.9%), similarly, both EC and salinity which were decreased with low ratios (6.6%, 3.9%, respectively). Taxon A. terrues exhibited high ability in reducing the total alkalinity and chloride ions in the treated water (30.9%, 43%, respectively) in comparison with the other two fungi species. Furthermore, all three fungi species were posed high capability in decreasing nutrients, where both nitrite and phosphate ions were highly reduced (87–97% and 22.8–32.1%, respectively). Based on these findings, we suggest using other microorganisms and exploring their capacity in removing the pollutants, and revealing the ability of the above fungi taxa in removing other pollutants.

From a management perspective, water quality is determined by the desired end use. Water intended for leisure, drinking water, and the habitat of aquatic organisms requires higher levels of purity. In contrast, the quality standards of water used for hydraulic energy production are much less important.
The main objective of this work is focused on the development of an evaluation system dealing with supervised classification of the physicochemical quality of the water surface in the Moulouya River through the use of artificial intelligence. A graphical interface under Matlab 2015 is presented. The latter makes it possible to create a classification model based on artificial neural networks of the multilayer perceptron type (ANN-MLP).
Several configurations were tested during this study. The configuration [9 8 3] retained gives a coefficient of determination close to the unit with a minimum error value during the test phase.
This study highlights the capacity of the classification model based on artificial neural networks of the multilayer perceptron type (ANN-MLP) proposed for the supervised classification of the different water quality classes, determined by the calculation of the system for assessing the quality of surface water (SEQ-water) at the level of the Moulouya River catchment area, with an overall classification rate equal to 98.5% and a classification rate during the test phase equal to 100%.

Baseflow is the primary source of water for irrigation and other water needs during prolonged dry periods; accurate and rapid estimation of baseflow is therefore crucial for water resource allocation. This research aims to estimate baseflow contribution during dry periods in three small watersheds in East Java: Surabaya-Perning (114 km2), Lamong-Simoanggrok (235 km2), and Bangsal-Kedunguneng (26 km2). Six recursive digital filters (RDFs) algorithms are explored using a procedure consisting of calibration, validation, evaluation and interpretation. In this study, the period of July to September is considered as the peak of the dry season. Moreover, data for the period 1996 to 2005 is used to calibrate the algorithms. By yearly averaging, values are obtained for the parameters and then used to test performance during the validation period from 2006 to 2015. Statistical analysis, flow duration curves and hydrographs are used to evaluate and compare the performance of each algorithm. The results show that all the filters explored can be applied to estimate baseflow in the region. However, the Lyne–Hollick (with RMSE = 0.022, 0.125, 0.010 and R2 = 0.951, 0.968, 0.712) and exponentially weighted moving average or EWMA (with RMSE = 0.022, 0.124, 0.009 and R2 = 0.957, 0.968, 0.891) for the three sub-watersheds versions give the best performance.

Water and wind erosion are the most powerful factors in the decrease of soil fertility and a threat to food security. The study was conducted on the steppe zone in Ukraine (total area of 167.4 thous. km2), including agricultural land (131.6 thous. km2). At the first stage, the modeling of spatial differentiation of water and wind erosion manifestations was carried out to calculate losses of soil (Mg·ha–1) and to determine their degradation. At the second stage, soil-climatic bonitet of zonal soils (points) is carried out to determine their natural fertility (Mg·ha–1). At the third stage, the spatial adjustment of the natural soil fertility to the negative effect of erosion was carried out. This made it possible to calculate crop losses and total financial losses due to water and wind erosion. The integrated spatial modeling showed that about 68.7% of arable land was constantly affected by the combined erosion, in particular the area of low eroded arable land (16.8%), and medium and highly eroded land (22.1%). Due to erodibility of soil, about 23.3% of agricultural land transferred from the category of high and medium quality to medium, low and very low quality, which is caused by the loss of soil fertility of up to 70%, crop losses of up to 1.93 Mg·ha–1 ha–1 and eduction of agricultural income up to 390 USD·ha–1. In the steppe region under the research, gross crop losses from erosion were up to 15.11 thous. Mg·ha–1 (3.05 mln USD). In order to protect soils, improve fertility and increase crop yields in the steppe zone in Ukraine, the following measures were suggested: adaptive and landscape erosion control design with elements of conservation farming in accordance with the spatial differentiation of soil quality and extent of water erosion deflation danger.

The purpose of this study is to develop mathematical models based on artificial intelligence: Models based on the support vectors regression (SVR) for drought forecast in the Ansegmir watershed (Upper Moulouya, Morocco). This study focuses on the prediction of the temporal aspect of the two drought indices (standardized precipitation index – SPI and standardized precipitation-evapotranspiration index – SPEI) using six hydro-climatic variables relating to the period 1979–2013. The model SVR3-SPI: RBF, ε = 0.004, C = 20 and γ = 1.7 for the index SPI, and the model SVR3-SPEI: RBF ε = 0.004, C = 40 and γ = 0.167 for the SPEI index are significantly better in comparison to other models SVR1, SVR2 and SVR4. The SVR model for the SPI index gave a correlation coefficient of R = 0.92, MSE = 0.17 and MAE = 0.329 for the learning phase and R = 0.90, MSE = 0.18 and MAE = 0.313 for the testing phase. As for the SPEI index, the overlay is slightly poorer only in the case of the SPI index between the observed values and the predicted ones by the SVR model. It shows a very small gap between the observed and predicted values. The correlation coefficients R = 0.88 for the learning, R = 0.86 for testing remain higher and corresponding to a quadratic error average MSE = 0.21 and MAE = 0.351 for the learning and MSE = 0.21 and MAE = 0.350 for the testing phase. The prediction of drought by SVR model remain useful and would be extremely important for drought risk management.

The article discusses the option for the application of the methodology for the solution of boundary value problems on the conformal mapping for the calculation of filtration process in the horizontal systematic drainage, provided that the drain is installed at a different depth. In particular, the case of methods combining fictitious areas and quasiconformal mappings for solving nonlinear boundary conditions problems for calculating filtration regimes in soils with free sections of boundaries (depression curves) and intervals of the “drainage” type. As an example, the authors designed a hydrodynamic flow grid, determined the values of the flows to the drain, established a section line and elicited other process characteristics. The algorithm for the numerical solution of model nonlinear boundary conditions problems of quasiconformal reflection in areas bounded by two equipotential lines and two flow lines, when for one of the sections, the boundary is an unknown (free) curve with fixed and free ends. The conducted numerical calculations prove that the problems and algorithms of their numerical solution, with a relatively small iterations number (k = 141) suggested in the paper, can be applied in the simulation of nonlinear filtration processes that arise in horizontal drainage systems. Total filtration flow obtained Q = 0.9 dm3·s–1; flow for drains Q1 = 0.55 dm3·s–1 and Q2 = 0.35 dm3·s–1 are quite consistent with practically determined values.

The accumulation of moisture from autumn and winter precipitation in poorly draining soil for plants in arid conditions during the initial stage of the vegetation period in the northern region of Kazakhstan was a severe production problem. Research methods included theoretical and experimental studies. In theoretical studies, the area of the treated surface by a chain harrow is determined. Then, the design of an improved harrow is proposed, including how the tooth chain tillage tools are positioned. Either as a “single action disc harrow” type with mounting four teeth on each chain link, or as a serial harrow with the tooth chain tillage tools located in a “diamond-shaped” double-action scheme with two teeth on each chain link. Experimental studies show that an improved harrow steadily performs the early spring harrowing process with a quality that meets normative requirements. In doing, so the working capacity is 4–5% higher than a serial harrow with a 4–5% lower fuel consumption. Furthermore, it is revealed that the early spring soil harrowing performed by tooth chain harrows allows the loss of productive moisture in the spring pre-sowing period by 1.8–1.9 times to be reduced compared to the untreated background.

This study attempts to find a fuzzy logic system for assessing the quality of water in water treatment plants (WTPs) providing water for irrigation purposes in the Basrah Governorate (South of Iraq). Each month, samples are taken in each of six major WTPs to measure electrical conductivity ( EC), and the content of sodium, magnesium and calcium. The calculated value which is the sodium adsorption ratio ( SAR) is plotted with EC on the Richard diagram. SAR and EC values are combined together in a fuzzy inference system (FIS) to find out a quality number called the fuzzy irrigation water quality index number ( FIWQI) which ranges from zero to one. The higher the value of the index, the better water quality. The Richard diagram, which helps to classify irrigation water, is used to adjust FIS components. Results show that the FIWQI for all WTPs changes depending on location and season. It ranges between 0.114–0.170, 0.120–0.190, 0.114–0.170, 0.114–0.202, 0.118–0.500 and 0.46–0.500 for Al-Bradhaia 1, Al-Jubaila 1, Shatt Al-Arab, Garmmah 1, Al-Rebat, and Old Shauaibah WTPs, respectively. The results indicate that WTPs effluent drawn from the Shatt Al-Arab River has poor water quality for irrigation purposes, except for an Old Shauaibah which receives water from another source called a sweet water canal. FIS results are compared with values obtained from the Richard diagram and 96% degree of compatibility between the two methods is attained. This indicates that FIS is an acceptable method for water quality classification.

The article discusses the spatial development of non-urban areas based on the use of local peat resources. Creating a methodology for the advanced spatial development of non-urban areas has peat resources based on multi- criteria optimisation of production and social infrastructures. The industrial and social infrastructure of the non-urban areas having reserves of peat, associated mineral, and industrial raw materials. Regularities, trends, and features of formation and functioning of the productive and social infrastructure of the natural and man-made complex in the development of peat reserves, associated mineral, and industrial raw materials. To achieve this goal, it is necessary to conduct interdisciplinary research and solve the following specific objectives: (1) the scientific justification of new technological processes and equipment for peat and mineral raw materials processing for obtaining new composite materials for multiple purposes; (2) the feature analysis of the use of local peat resources to provide the development of non-urban areas based on a set of scientific approaches; (3) the development of the methodology for project management of the natural and man-made complex to ensure multi-criteria optimisation of productive and social infrastructure. The example of the Khanty-Mansiysk Autonomous Okrug – Yugra development selected results of confronting the existing “big grand” and national challenges through the mechanisms of rational use of local peat resources non-urban areas are illustrated. The results indicated that by 2030 there would be a 3.8-fold increase in mineral extraction and a 5.9-fold increase in processing industries.

Over the past two decades, artificial neural networks (ANN) have exhibited a significant progress in predicting and modeling non-linear hydrological applications, such as the rainfall-runoff process which can provide useful contribution to water resources planning and management. This research aims to test the practicability of using ANNs with various input configurations to model the rainfall-runoff relationship in the Seybouse basin located in a semi-arid region in Algeria. Initially, the ANNs were developed for six sub-basins, and then for the complete watershed, considering four different input configurations. The 1st (ANN IP) considers only precipitation as an input variable for the daily flow simulation. The 2nd (ANN II) considers the 2nd variable in the model input with precipitation; it is one of the meteorological parameters (evapotranspiration, temperature, humidity, or wind speed). The third (ANN IIIP,T,HUM) considers a combination of temperature, humidity, and precipitation. The last (ANN VP,ET,T,HUM,Vw) consists in collating different meteorological parameters with precipitation as an input variable. ANN models are made for the whole basin with the same configurations as specified above. Better flow simulations were provided by (ANN IIP,T) and (ANN IIP,Vw) for the two stations of Medjez-Amar II and Bordj-Sabath, respectively. However, the (ANN VP,ET,T,HUM,Vw)’s application for the other stations and also for the entire basin reflects a strategy for the flow simulation and shows enhancement in the prediction accuracy over the other models studied. This has shown and confirmed that the more input variables, as more efficient the ANN model is.

The springs of the Taoura region flow from a syncline shaped structure. All resources in the region were mobilized as a result of increased demand. However, the development of anthropic activities and population growth in the area pose risk for groundwater. Analytical results obtained from a series of samplings in November 2017–April 2018, express the quality of water suitable for the irrigation of agricultural land. The highest values are recorded in April 2018 at 20.5 to 21.6°C and pH of 8.0 to 8.2. The study recorded high electrical conductivity from 1390 to 1495 μS·cm–1 and TDS from 1270 to 1500 mg·dm–3 in November 2017, which shows important mineralization that characterizes spring water. Physical parameters were measured in situ using a HORIBA multi-parameter probe. Chemical analyses were carried out using NFT 90-005 titration, and nitrogen parameters by DIN 38405-D92 spectrophotometry. Maximum levels of nitrates and phosphates were recorded at 228 and 18.4 mg·dm–3 respectively. The principal component analysis (PCA) showed a good correlation of the November 2017 period with mineralization parameters. Moreover, there is a strong correlation between the wet period and pollution factors. The two methods of analysis has allowed to distinguish three groups of geochemical water types: a bicarbonate calcium group typical for waters having transited in carbonate horizons. A second chloride calcium group shows basic exchange between water and clay levels, and the third chloride bicarbonate calcium group reveals an enrichment in calcium and chloride, which reflects water circulation with an exchange of the carbonated and evaporitic sedimentary rock matrix.

Biochar was prepared from corn ( Zea mays) stalks and impregnated with sulfuric acid. The biomass was impregnated for 24 h with a 50% solution of H2SO4 with impregnation ratios 1:2 (B 1:2) and 1:3 p/v (B 1:3); then, it was carbonized in a muffle furnace at 520°C for 30 min with a 10°C per min ramp. The adsorption capacity to remove anions (nitrate, sulfate, and phosphate) in an aqueous solution was evaluated by varying the temperature. The adsorption mechanism was studied by determining the thermodynamic parameters: Gibbs free energy (ΔGº), enthalpy (ΔHº) and entropy (ΔSº) standard. The biochars were characterized by Scanning Electron Microscopy-Energy Dispersive X-Ray Spectroscopy (SEM-EDS) analysis and were found to exhibit a heterogeneous surface and porous nature, with C, O, S, and Si. The experiments in the batch system showed the best performance of B 1: 2 in the removal of the three anions occurred at 303 K, while B 1: 3 had the best performance at 298 K. From the thermodynamic parameters, it was found that the removal processes are endothermic, their mechanism is by chemisorption. It is concluded that synthesized biochar is an excellent alternative to removing nutrient anions present in the solution.

This paper aims to analyse the flood discharge based on the Synthetic Unit Hydrograph (SUH), using the Soil Conservation Service method (SCS), the SUH of Nakayasu method, and the SUH of Gama I method. Modelling formed the basis of the research conducted on the Bengawan Solo River, Indonesia. The embankment construction on the Dengkeng–Pusur Section was designed as a method of flood control in 1988. The problem was that around its location are densely populated cities, industrial areas, and agricultural areas. In order to measure the risk of embankment failure and water structure planning in general, it is necessary to analyse the maximum flood discharge. There are several methods for analysing maximum flood discharge, so finding a suitable method is essential due to the lack of measuring tools to calculate flood discharge in some areas. The calculation is compared with the observation data at the Serenan AWLR station, which is in the Dengkeng–Pusur section. The observation rainfall data was covered a 20 year period (1999–2018). According to the method used, the analysis is based on series data on four rainfall stations, the watershed characteristics, and other parameters. Furthermore, the maximum flood discharge from the calculation is compared with the observational data at the Serenan station. The result shows that the best SUH is Gama I method compared to the observation maximum flood discharge in AWLR Serenan Station, with an 8.0% error. The other method, the SUH Nakayasu method with a 16.6% error, and the SUH SCS method with a 39.5% error.

Soil loss is a major problem for watersheds management in semi-arid environments. The objective of the present study is to analyze the annual and seasonal patterns of suspended loads and quantify the specific sediment yields in a semi-arid environment of the Mazafran Watershed in central Algeria. The obtained information of water discharge and suspended sediment load, recorded during 19 years, was confronted with precipitation data in order to establish the relationships between theforcing agents and erosive processes. The specific sediment yield was estimated by assessing rating curve data under two types of identified responses. The obtained results allowedconfirming the seasonality on suspended sediment transport in the studied basin, which accounts for 56% of the total suspended sediment load estimated in winter. The mean annual suspended sediment is estimated at 17.52 Mg·ha–1·y–1. The results highlighted that the type 2 event dominates the production of sediment in the study area in comparison with type 1 event. The analysis of the variability of rainfall erosivity index showed that there is a strong correlation between the annual precipitation and modified Fournier index ( MFI), and a weak correlation with the monthly precipitation concentration index ( PCI). Moreover, the spatial distribution of the modified Fournier index at the basin scale showed the highest precipitation aggressiveness in the Southern part of the study region for both type of events, whereas the precipitation aggressiveness low to moderate in the remaining part of the study region.

In this work, nickel adsorption onto low Jordanian zeolite dose is being investigated. Natural zeolite doses were stirred continuously with nickel solutions in batch reactors at 180 RPM for 24 hours, where the temperature was set to 20°C. The pH was initially 4.5 and reached 5.2 at equilibrium. The removal efficiency of nickel reaches maximum value when the initial nickel concentration is around 1 ppm and then tends to decrease when the initial nickel concentration increases above 1 ppm. The optimal nickel removal reaches 65% when the initial nickel concentration is 1 ppm and the zeolite dose is 26 mg·dm–3. This study investigates the behaviour of nickel removal and modelling isotherms below and above this critical peak point. At this level of zeolite dose, the adsorption does not follow either Freundlich or Langmuir isotherms, but rather, it follows Freundlich for the data plot just below the peak point with the highest coefficient of determination (R2) equals (0.98) when the zeolite dose is (26 mg·dm–3), whereas it follows Langmuir for the data plot just above the peak point with the highest coefficient of determination (R2) equals (0.99) when the zeolite dose is (10 mg·dm–3). These findings clarify the theory behind each isotherm and can be used to find new information for efficient treatment techniques.