- Volume:5 Issue:2, 2017
- تاریخ انتشار: 1396/04/04
- تعداد عناوین: 7
Assessment of Climate Change Impacts on Groundwater Recharge for Different Soil Types-Guelph Region in Grand River Basin, CanadaPages 1731-1744BackgroundGlobal warming and climate change are widely indicated as important phenomena in the 21st century that cause serious impacts on the global water resources. Changes in temperature, precipitation and evaporation are occurring in regions throughout the world, resulting in changes including, runoff, streamflow and groundwater regimes, reduced water quantity and quality.Materials And MethodsRelying upon thirty years of base data (19651994), three global circulation models (GCM), namely GISS, GFDM and CCC, are utilized to assess impact of climate change to groundwater recharge rates between years 2010 to 2050 for the Guelph region of the Grand River Basin in Canada. The resulting groundwater recharge rates for alternative soil layers are used to assess water balance conditions, and ultimately, the percolation rate to the groundwater using the Visual-HELP model.ResultsWhile the climate change impact assessment indicates that evaporation will increase and percolation will decrease during summer, increased percolation is indicated in winter due to additional freeze/thaw dimensions of climate change. The net effect is that the impact of climate change, based upon use of GCM models, is expected to increase groundwater recharge rate by 10% on average (7% for CCC, 10.6% for GISS and 12% for GFDM) in future.
Discussion andConclusionsAccording to the results of this research in the Guelph region, the monthly average percolation rate is higher with climate change; (i) the percolation rate is increased during winter due to freeze/thaw effects, while (ii) it is decreased during summer due to higher evaporation rate.Keywords: Climate change, GCM models, Grand River Basin, Groundwater, Guelph, Visual-HELP
Land Use Planning Using a Quantitative Model and Geographic Information System (GIS) In Sistan Region, IranPages 1745-1759BackgroundLand use planning is a science that determines the type of land use through studying the ecological and socio-economic characteristics of the land.Materials And MethodsA systematic method known as the Makhdoom Model was used for the analysis of maps to evaluate the land use and natural resources for future sustainable land planning of an area in Sistan region, using GIS as a tool. For this purpose, the ecological capability maps of different land uses, including forest and range, agriculture, ecotourism, rural and urban development were initially prepared by overlaying geographical maps in GIS for the study area. Then, the prioritization of land uses was assessed using a quantitative model by considering the ecological and socio-economic characteristics of the study area.ResultsThe results indicated that the maximum area of the proposed uses (28.7%) was related to conservation, showing this land use had high potential in the study area. Also, the minimum area of proposed uses was related to dry farming.
Discussion andConclusionsThis research proved that quantitative methods can be more useful than classic methods (qualitative).Keywords: Land use planning, Modified, GIS, Sistan region
Pages 1761-1770BackgroundSediments are integral part of wetlands providing a valuable key to recognize heavy metal fluctuations in the past.Materials And MethodsThe surface sediment samples were taken from thirteen sites, then prepared and digested with percholoric acid and nitric acid at 1:4 ratio, followed by flame atomic absorption spectrophotometry analysis.ResultsThe average of total metal concentration in 13 sites were found to be 9.182, 9.514, 45.351 and 43.456 µg g-1 for Pb, Zn, Cu and Ni, respectively. Also, comparison of sediment quality indices, including contamination factor (Cf), contamination degree (Cd), and modified contamination degree (mCd)) showed that Cu contamination was significantly different from the other heavy metals, while Ni contamination was average, and Pb and Zn contaminations were low.
Discussion andConclusionsThis research confirms that the Mighan wetland is polluted with heavy metals and their excessive accumulation in sediments.Keywords: Hakanson index, Mighan wetland, Sediment index
Pages 1771-1786BackgroundSoil salinization is a world-wide land degradation process in arid and semi-arid regions that leads to sever economic and social consequences.Materials And MethodsWe analyzed soil salinity by two statistical linear (multiple linear regression) and non-linear (artificial neural network) models using Landsat OLI data in Agh-Ghala plain located in north east of Iran. In situ soil electrical conductivity (EC) of 156 topsoil samples (depth of 0-15cm) was also determined. A Pearson correlation between 26 spectral indices derived from Landsat OLI data and in situ measured ECs was used to apply efficient indices in assessing soil salinity. The best correlated indices such as blue, green and red bands, intensity indices (Int1, Int2), soil salinity indices (Si1, Si2, Si3, Si11, Aster-Si), vegetation Indices (NDVI, DVI, RVI, SAVI), greenness and wetness indices were used to develop two models.ResultsComparison between two estimation models showed that the performance of ANN model (R2=0.964 and RMSE=2.237) was more reliable than that of MLR model (R2=0.506 and RMSE=9.674) in monitoring and predicting soil salinity. Out of the total area, 66% and 55.8% was identified as non-saline, slightly and very slightly saline for ANN and MLR models, respectively.ConclusionsThis shows that remote sensing data can be effectively used to model and map spatial variations of soil salinity.Keywords: Artificial Neural Network, Electrical conductivity, Landsat OLI data, Multiple linear regression, Iran
Pages 1787-1797BackgroundThis paper is devoted to preliminary assessment of the economic cost of land degradation in Albania resulting from unsustainable land use, based on comparing the costs of action for dealing with land degradation versus the costs of inaction.Materials And MethodsThe causes of land degradation are divided into proximate and underlying ones, which interact with each other to result in different levels of land degradation. The economic impacts of land degradation on soil uses are valued according to their typology and their different impacts have been classified spatially into on-site and off-site effects, distinguished according to the economic values that are affected.ResultsThe results showed that the on-site costs of soil degradation are significant, but are not be a major concern in the short run. However, on the local scale, impacts will be more substantial for the affected areas. The off-site costs of soil degradation are substantial, however. In some cases, they may exceed the on-site costs, despite the fact that a large part of the off-site costs could not be quantified.
Discussion andConclusionsSome of these issues, especially the conservation of water resources and their sustainable management to reduce sedimentation in rivers and dams, and flood risk reduction, call for immediate conservation measures.Keywords: Cost, Economic assessment, Environmental impact, Land use, Sustainability
Effects of Rainfall Intensity-Duration-Frequency Curves Reformation on Urban Flood Characteristics in Semiarid EnvironmentPages 1799-1813BackgroundA design storm is a theoretical storm event based on rainfall intensities associated with frequency of occurrence and having a set duration. Estimating design storm via rainfall intensitydurationfrequency (IDF) curves is important for hydrological planning of urban areas.
Material andMethodsThe impact of changes in rainfall intensitydurationfrequency (IDF) curves on flood properties in an urban area of Zanjan city was investigated, using Storm Water Management Model (SWMM). For the IDF curve generation, Sherman and Ghahreman-Abkhezr methods were compared.ResultsAccording to results, the estimated rainfall depth and, consequently the peak runoff rate for different return periods had decreased in the recent years, except for 2-year return period. Decrease in peak runoff rate was 30, 39, 41 and 42 percent for 5-10-20 and 50-year return periods, respectively. Based on the results, for peak runoff evaluated in 50-year return period using Sherman and Ghahreman-Abkhezr hyetograph, percent of flood that occurred before the peak runoff were 27 and 22 percent, respectively.
Discussion andConclusionDesign rainfall hyetograph showed that Sherman method gave larger rainfall intensity compared to Ghahreman-Abkhezr method. Estimated peak and total runoff volume follow trend of rainfall intensity. As Ghahreman-Abkhezr method use longer and newer rainfall data for creating IDF curves, we can conclude that climate change cause change in rainfall characteristics. The runoff modeling show that main urban drainage system had enough transfer capacity against the flood condition, but survey information indicated several inundations in some flat areas, curbs and gutters. Inappropriate design and obstruction of the runoff paths via urban garbage and sediments are some parameters that could lead to such local inundation.Keywords: Design storm, Flood, Rainfall IDF curve, Storm water, SWMM
Selenium Bio-accumulation and Bio-concentration Factors in some Plant Species in an Arid Area in Central Part of IranPages 1815-1827BackgroundConcentrations of Se in seven plant species (white mulberry, apricot, spindle tree, pistachio, wheat, barley, chives), and the associated soil samples were investigated in Shahrood and Damghan, Iran.Materials And MethodsSoil samples were taken from the surface zone (0-5 cm) and plough zone (5-20 cm) in 13 sampling locations. The collected soil and plant samples were taken to the laboratory, then digested usin USEPA's method and analyzed by Inductively Coupled Plasma Optical Emission Spectroscopy technique.ResultsSince there was a significant correlation (r=0.688, pConclusionsThe highest values of bio-concentration factors were recorded in chives followed by spindle tree and wheat, whereas the lowest level was detected in pistachio.Keywords: Agricultural activity, Bio-concentration factor, Soil pollution