Analysis of Spatial Autocorrelation Patterns of Heavy and Super-Heavy Rainfall in Iran

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gistatistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran,have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.     

A BEM investigation on the influence of underground cavities on the seismic response of canyons

Two-dimensional site effects caused by cavities under topographical functions can considerably impact the seismic reaction of the ground surface. Due to the complexity of scattering issues by topographical features above subterranean cavity, few studies have been done in this field. In the present study, the seismic response of semi-sine-shaped canyons above a subterranean cavity (hole) of different dimensions, depths and locations is examined. The medium is assumed to have a linear elastic constitutive behavior exposed to vertically propagating incident SV and P waves. All calculations are performed using the direct boundary element technique in the time domain. It is observed that a cavity below a canyon can considerably change the ground response of the surface in different periodic bands. The seismic interaction between canyon and cavity with respect to various geometrical parameters will lead to different amplification patterns in the center and edge of the canyon. One of the most important results is the increase in amplification of long periods compared with the case of a canyon without cavity. Moreover, parametric research shows the fact that the cavity detail and canyon height, the ratio of cavity to the canyon size and cavity location impact on the seismic amplification of the canyon surface. Finally, spectral amplification coefficients of the canyon surface led by the cavity are reported for different cases of the canyon–cavity interaction.     

Sediment yield assessment and identification of check dam sites for Rawal Dam catchment

Sediment yield is the amount of erosional debris from drainage basin deposited in reservoirs. The economic life of storage reservoir depends upon the estimation of the time it takes for the reservoir to be filled with the deposition of sediments. This research is based on assessing the sediment yield in Rawal Dam catchment by using Soil and Water Assessment Tool (SWAT) model. Digital Elevation Model (DEM), land use maps, soil maps, and weather data of the study watershed were used as input to SWAT model. Monthly sedimentation data of year 2010 and discharge data from 1998 to 2005 is being used for model calibration and validation, respectively. Whereas simulations are being generated from 1998 to 2011 for both sedimentation and discharge. Modified Universal Soil Loss Equation (MUSLE) was used for the estimation of sediment yield. The Nash and Sutcliffe coefficient of the model was found to be 0.79 which depicts its effectiveness. After the estimation of the sediment yield and discharge by using SWAT model, double mass curve was used to evaluate the sedimentation rate. The rate of sediment transport can be reduced by the construction of check dams. Various sites have also been proposed for check dams construction to prevent the sediments transported into the Rawal Catchment.     

Capability of vis-NIR spectroscopy and Landsat 8 spectral data to predict soil heavy metals in polluted agricultural land (Iran)

Heavy metals are toxic elements that have hazardous effect on the environment. They cause soil pollution as a result of their toxicity, potential reactivity, and mobility in soils. There are so many methods for the measurement of heavy metal concentrations in soils and aquatic systems. The traditional methods used for detecting heavy metal distribution in soil involve laboratory analysis and raster sampling. Both of them are expensive and time-consuming for large areas. Remote sensing techniques are used for obtaining the earth’s surface information, and these techniques have been used in the investigations of heavy metal distributions in preliminary analysis of soils as a rapid method. Today, near-infrared reflectance spectroscopy (NIRS) of soil characteristics has been of interest as a significant object. The present investigation is focused on the detection of heavy metals in contaminated soils by the application of reflectance spectroscopy in the spectral range of 350 to 2500 nm. This study also discusses the circumstances of the applied current methods for the detection and estimation of arsenic (As), cadmium (Cd), nickel (Ni), and lead (Pb) in contaminated agricultural soils. In the first part of laboratory spectroscopy, estimations were done using heavy metal reflectance spectroscopy and partial least square regression (PLSR) approaches, while in the second part, the heavy metal estimations were done using soil organic carbon reflectance spectroscopy through the PLSR approaches. Similar to the tasks above, estimations of As, Cd, Ni, and Pb by using Landsat 8 images were done in the forms of direct and indirect methods and the distribution of heavy metals in the study area was determined. Finally, the results obtained using direct and indirect methods were compared with the wet chemical measurements of heavy metals and organic carbon. It was found that although the direct detection of heavy metals using the images of Landsat 8 produced more accurate results than the indirect detections, the results obtained from laboratory spectroscopy corresponded more with the results from atomic adsorption spectroscopy. On the other hand, based on the fact that the soil has a complex content, the use of nonlinear methods, such as artificial neural networks in predicting soil heavy metal contents, could be regarded as a trusted method.     

Long-term improvement of agricultural vegetation by floodwater spreading in the Gareh Bygone Plain,Iran. In the pursuit of human security,is artificial recharge of groundwater more lucrative than selling oil?

In southern Iran’s Gareh Bygone Plain, water-supply qanats in four mixed farming communities were desiccated by over-pumping of illegal dug wells throughout the area. Emergency situations developed, resulting in city-ward migration. Since 1983, 193 million m³ of water has been supplied to those communities by floodwater spreading (FWS) to facilitate spate irrigation of sandy rangeland (2,034 ha) and artificial recharge of groundwater (ARG), of which 76 % has recharged the aquifer. This resulted in a reverse migration of the population. The irrigated area in the 2010–2011 growing season increased 13.2 fold when compared to the pre-FWS period, and year-round forage for about 700 sheep has been provided since 1991. The ARG is a logical alternative to building large dams in Iran; 420,000 km² of coarse-grained alluvium provides capacity to store 5,000 km³ of water, representing more than ten times the annual precipitation of the whole country. As the equivalent cost for building dams to accommodate that volume is estimated at US$12.5?×?10¹², the potential value of the alluvium may be realized. ARG on the recharge areas of 33,000 of the desiccated qanats eventually could rejuvenate them. As agricultural commodities absorb 19 % of the monetary value of Iran’s imports, and ARG activities could supply the water to produce them, alluvium is even more valuable than oil, which provides foreign exchange. More importantly, ARG on 140,000 km² of the alluvium could strengthen the capacity to adapt to droughts and reduce the number and impact of water-related emergency situations.