Quantitative and qualitative simulation of groundwater by mathematical models in Rafsanjan aquifer using MODFLOW and MT3DMS

Agriculture sector by using 80% of freshwater is the greatest water consumer in Iran. Excessive use of agricultural fertilizers in last decade, caused accumulation of enormous amounts of salts and subsequence declined the physical properties of soil. In desert and dry regions such as Rafsanjan plain, use of the groundwater resources is more than the surface water resources. Therefore, information about the quality of these resources remains a necessary task for optimum management, protection of water resources, and stopping the future damages. In this study, the groundwater quantity and quality of Rafsanjan plain was investigated by MODFLOW and MT3DMS. The presented quantitative model for this aquifer was compared by observed data and calibrated. This model was used to predict a 10-year period. Results show that water elevation decreases approximately 15 m for 10 years to come in this plain. Qualitative model results show that most quality parameters will increase. Electrical conductivity will increase more than other parameters. As values of this parameter will reach 16,000 µs/l for next 5 years. Therefore, we suggest that exploitation of water from these resources should be reduced and discharge from some of agricultural wells stop; also we suggested that recharge to groundwater resources should be increased and agricultural activities should be limited or improved using of modern irrigation systems in this plain.     

Comparison of IWG and SDSM weather generators for climate change impact assessment

Theoretical and Applied Climatology - Weather generators (WGs) typically have unique advantages to the climate change impacts assessment. However, each of them has the weaknesses, strengths, and...     

Forecasting of meteorological drought using Wavelet-ANFIS hybrid model for different time steps (case study: southeastern part of east Azerbaijan province, Iran)

Drought is accounted as one of the most natural hazards. Studying on drought is important for designing and managing of water resources systems. This research is carried out to evaluate the ability of Wavelet-ANN and adaptive neuro-fuzzy inference system (ANFIS) techniques for meteorological drought forecasting in southeastern part of East Azerbaijan province, Iran. The Wavelet-ANN and ANFIS models were first trained using the observed data recorded from 1952 to 1992 and then used to predict meteorological drought over the test period extending from 1992 to 2011. The performances of the different models were evaluated by comparing the corresponding values of root mean squared error coefficient of determination (R ²) and Nash–Sutcliffe model efficiency coefficient. In this study, more than 1,000 model structures including artificial neural network (ANN), adaptive neural-fuzzy inference system (ANFIS) and Wavelet-ANN models were tested in order to assess their ability to forecast the meteorological drought for one, two, and three time steps (6 months) ahead. It was demonstrated that wavelet transform can improve meteorological drought modeling. It was also shown that ANFIS models provided more accurate predictions than ANN models. This study confirmed that the optimum number of neurons in the hidden layer could not be always determined using specific formulas; hence, it should be determined using a trial-and-error method. Also, decomposition level in wavelet transform should be delineated according to the periodicity and seasonality of data series. The order of models with regard to their accuracy is as following: Wavelet-ANFIS, Wavelet-ANN, ANFIS, and ANN, respectively. To the best of our knowledge, no research has been published that explores coupling wavelet analysis with ANFIS for meteorological drought and no research has tested the efficiency of these models to forecast the meteorological drought in different time scales as of yet.     

Combining echo sounding,sediment and biological data to map benthic habitats in a coastal area of the Persian Gulf

Mapping surveys of coastal benthic habitat in Qeshm Island Geopark, Persian Gulf, were conducted using a combination of biological, sedimentological and echo‐sounding data. The survey area covered approximately 233 km² in a depth range of 5–25 m, and the data were acquired from a single beam echo sounder, grab, video and still photography. Sediment and macrofauna samples were collected by grab at 76 stations and subjected to classification and ordination analyses. Two acoustic classes were identified differentiating along the near/offshore axis. Sediment texture was dominated by fine grain sizes, with five distinct sub‐sediment types. In total, 214 macrobenthic taxa were identified, of which polychaetes accounted for 60%. Other dominant groups included young sponges, nematodes, malacostracan crustacean, bivalves, ostracods and ophiuroids. Underwater videos and still photos integrated the macrofaunal and sedimentary data and revealed a range of biogenic sedimentary features such as burrows and tubes. The biological data identified six main biological assemblages showing an inshore/offshore pattern. The macrobenthic abundance did not demonstrate a significant difference with depth, although polychaetes were positively correlated with depth. The highest abundance and species richness were observed at median depths. Species distribution and diversity did not show any correlation with sediment type. A preliminary habitat mapping of the south coast of the Qeshm Island Geopark has been carried out, integrating acoustic, sediment and biological data.     

Developing food,water and energy nexus workflows

ABSTRACT

There is a growing recognition of the interdependencies among the supply systems that rely upon food, water and energy. Billions of people lack safe and sufficient access to these systems, coupled with a rapidly growing global demand and increasing resource constraints. Modeling frameworks are considered one of the few means available to understand the complex interrelationships among the sectors, however development of nexus related frameworks has been limited. We describe three open-source models well known in their respective domains (i.e. TerrSysMP, WOFOST and SWAT) where components of each if combined could help decision-makers address the nexus issue. We propose as a first step the development of simple workflows utilizing essential variables and addressing components of the above-mentioned models which can act as building-blocks to be used ultimately in a comprehensive nexus model framework. The outputs of the workflows and the model framework are designed to address the SDGs.     

Identification of a geological region for earthquakes using syntactic pattern recognition of seismograms

A relational database has been developed which permits the storage and retrieval of waveforms, together with essential parameters of events. The capability of the method is tested by applying it to broad-band records from the Geoscope Noumea station (New Caledonia).     

Low-frequency transfer of seismic energy by superficial soil deposits and soft rocks

Recordings of recent strong earthquakes obtained on alluvial sites show that the maximum horizontal accelerations tend towards a limit of about 0.45 to 0.50g, associated with large displacements. by contrast, vertical accelerations do not appear to be subject to such a limit (1.7g for the 1979 Imperial Valley earthquake). Theoretical linear elasticity models, when applied to superficial layers of low strength, seem to be inadequate for the prediction of near-field ground motions in alluvial deposits. A good approximation for the horizontal component of certain Imperial Valley records was, however, obtained through a non-linear approach, using local soil properties together with a reasonable hypothesis for motion at the base of the superficial layers in question that included large values of acceleration for high-frequency shear waves.     

Dye Removal from Colored Textile Wastewater by Poly(propylene imine) Dendrimer: Operational Parameters and Isotherm Studies

This paper deals with the removal of textile dyes from aqueous solutions by poly(propylene imine) dendrimer (PPI). Direct red 80 (DR80), Acid Green 25 (AG25), Acid Blue 7 (AB7), and Direct Red 23 (DR23) were used as model dyes. The effects of operational parameters on dye removal such as dendrimer concentration, dye concentration, salt (inorganic anions), and pH have been studied at 25°C. The Langmuir and Freundlich isotherm models were investigated. In addition, dye desorption of dendrimer was studied. The results indicated that acidic pH supported the adsorption of dyes by dendrimer. Furthermore studies of dye concentration and salt effects exhibited that dye removal percentage by dendrimer was decreased. It was found that the isotherm data of DR80, AG25, and DR23 followed Langmuir isotherm and isotherm data of AB7 followed Freundlich isotherm models. Desorption tests showed that maximum dye releasing of 76.5% for DR80, 84.5% for AG25, 87% for AB7, and 93% for DR23 were achieved in aqueous solution at pH 12. Based on the data of present study, one could conclude that the dendrimer being an environmentally friendly adsorbent with relatively large adsorption capacity might be a suitable alternative for elimination of dyes from colored textile wastewater.