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.     

Regional analysis of streamflow drought: a case study in southwestern Iran

Droughts are complex natural hazards that, to a varying degree, affect some parts of the world every year. The range of drought impacts is related to drought occurring in different stages of the hydrological cycle and usually different types of droughts such as meteorological, agricultural, hydrological, and socio-economical are the most distinguished types. Hydrological drought includes streamflow and groundwater droughts. In this paper, streamflow drought was analyzed using the method of truncation level (at 70 % level) by daily discharges at 54 stations in southwestern Iran. Frequency analysis was carried out for annual maximum series of drought deficit volume and duration. 35 factors such as physiographic, climatic, geologic and vegetation were studied to carry out the regional analysis. According to conclusions of factor analysis, the six most effective factors include watershed area, the sum rain from December to February, the percentage of area with NDVI <0.1, the percentage of convex area, drainage density and the minimum of watershed elevation, explained 89.2 % of variance. The homogenous regions were determined by cluster analysis and discriminate function analysis. The suitable multivariate regression models were ascertained and evaluated for hydrological drought deficit volume with 2 years return period. The significance level of models was 0.01. The conclusion showed that the watershed area is the most effective factor that has a high correlation with drought deficit volume. Moreover, drought duration was not a suitable index for regional analysis.     

Analyzing drought history using Fuzzy Integrated Drought Index (FIDI): a case study in the Neyshabour basin,Iran

In arid to semi-arid climates, monitoring drought is very complicated because of different hydrometeorology variables effect on it. It is proposed in this paper to develop Fuzzy Integrated Drought Index (FIDI) which combines most important effective factors in developing drought. At first, Variable Infiltration Capacity (VIC) model calibrated simulated runoff to outlet basin runoff data for years 1993–1995. Results represent high performance of model in simulating runoff of outlet basin. Then, Precipitation Anomaly Percentage Index (PAPI), actual Evapotranspiration Anomaly Percentage Index (EAPI), Runoff Anomaly Percentage Index (RAPI), and Soil Moisture Anomaly Percentage Index (SMAPI) were constructed. FIDI was compared with the PAPI, RAPI and SMAPI for the period of 1985 to 2014. The results indicate that (1) the FIDI has more ability in determining start and persistence of drought event compared with PAPI, RAPI, and SMAPI; (2) in the low time scales, PAPI and SMAPI have high correlation with FIDI, and in the higher time scales, RAPI has the high correlation with FIDI; (3) spatially, the middle, west, and portion of north have higher drought risk in the Neyshabour basin.     

Eco-environmental change detection by using remote sensing and GIS techniques: a case study Basrah province, south part of Iraq

This study examines the temporal and spatial dynamics of eco-environment degradation processes and change detection as evident from land use survey datasets (1990–2003) for the Basrah province, Iraq was taken as a case. Using a combination of techniques of RS, GIS, and GPS, the study identifies five prominent eco-environment degradation processes, namely: desertification, secondary salinization, urbanization, vegetation degradation, and loss of wetlands. Rates of conversion were calculated and distribution patterns were mapped with the aid of GIS. The results suggest that wind erosion was the dominant cause of eco-environment degradation in more than half of the study area. Coupled with this were increases in salinization processes, affecting 17.6% of the land area in 2003. Overall, severe eco-environment degradation was noticed to be the dominant eco-environment degradation grade (61.9% of total area), followed by moderate eco-environment degradation (18.9% of total area) in 2003. Incorporation of both natural and anthropogenic factors in the analysis provided realistic assessment of the risk of land degradation. The study area, in general, is exposed to a high-risk of eco-environment degradation.     

Identification of hazardous waste landfill site: a case study from Zanjan province, Iran

The study of landfill sites is one of the most important studies in landfill engineering, and the landfill site selection involves combination of engineering, science, and politics. This paper describes a comprehensive hazardous waste landfill site selection methodology with the combined utilization of geographic information system and multiple criteria analysis methods, as applied to the Zanjan province in Iran. The six main data categories that were used are geological/engineering geological, geomorphological, hydrological/hydrogeological, climatological, pedological, and social/economical criteria, which included 31 input layers in total. A suitability map for hazardous waste landfilling was prepared for study area with five classes from most suitable to completely unsuitable. Finally, out of the three sites, one site was selected which was chosen by the local authorities. Our work offers a comprehensive methodology and provides essential support for decision-makers in the assessment of hazardous waste management problems in Zanjan province in I.R. Iran and other developing cities in other countries.     

Forecasting areas vulnerable to forest conversion using artificial neural network and GIS (case study: northern Ilam forests,Ilam province,Iran)

Forest conversion due to illegal logging and agricultural expansion is a major problem that is hampering biodiversity conservation efforts in the Zagros region. Yet, areas vulnerable to forest conversion are unknown. This study aims to predict the spatial distribution of deforestation in western Iran. Landsat images dated 1988, 2001, and 2007 are classified in order to generate digital deforestation maps which locate deforestation and forest persistence areas. Meanwhile, in order to examine deforestation factors’ investigation, deforestation maps with physiographic and human spatial variables are entered into the model. Areas vulnerable to forest changes in the Zagros forest region are predicted by a multilayer perceptron neural network (MLPNN) with a Markov chain model. The results show that about 19,294 ha forest areas are deforested in the last 19 years. The predictive performance of the model appears successful, which is validated using the actual land cover map of the same year from Landsat data. The validated map is found to be 94 % accurate. The validation is also tested using the relative operating characteristic approach which yielded a value of 0.96. The model is then further extended to predict forest cover losses for 2020. The MLPNN approach was found to have a great potential to predict land use/land cover changes because it permits developing complex, nonlinear models.     

Fire danger assessment with remote sensing: a case study in Northern China

Every year several million hectares of forest and grassland in China are affected by wildfires. The majority of wildfires occur in the northern part of China, where grasslands and forests are ubiquitous. A critical step toward the protection of life, property, and natural resources from wildfires is the development of a fire danger rating system. This paper presents a new method to assess fire danger that capitalizes on the abundance of environmental data available via remote sensing and applies this new method to the northern part of China. Using an analytical hierarchy process, a fire danger index was developed based on five environmental factors that are known to affect fire frequency and severity, including land surface temperature, vegetation curing, equivalent water thickness, vegetation continuity degree, and fuel weight. Data for these five factors were derived from satellite imagery, instead of point data, allowing for predictions to be made over a large geographic area. Fire danger ratings were then mapped for the region based on the fire danger index. In addition, the accuracy of the fire danger index was evaluated by statistical analyses. The fire danger index was significantly correlated with air temperature and precipitation, suggesting that changes in these two environmental variables will affect the predictions of the index.     

Reservoir operation using system dynamics under climate change impacts: a case study of Yamchi reservoir,Iran

This paper proposes a decision support system for Yamchi reservoir operation in semi-arid region of Iran. The paper consists of the following steps: Firstly, the potential impacts of climate change on the streamflow are predicted. The study then presents the projections of future changes in temperature and precipitation under A2 scenario using the LARS-WG downscaling model and under RCP2.6, RCP4.5, and RCP8.5 using the statistical downscaling model (SDSM) in the northwestern of Iran. To do so, a general circulation model of HadCM3 is downscaled by using the LARS-WG model. As a result, the average temperature, for the horizon 2030 (2011–2030), will increase by 0.77 °C and precipitation will decrease by 11 mm. Secondly, the downscaled variables are used as input to the artificial neural network to investigate the possible impact of climate change on the runoffs. Thirdly, the system dynamics model is employed to model different scenarios for reservoir operation using the Vensim software. System dynamics is an effective approach for understanding the behavior of complex systems. Simulation results demonstrate that the water shortage in different sectors (including agriculture, domestic, industry, and environmental users) will be enormously increased in the case of business-as-usual strategy. In this research, by providing innovative management strategies, including deficit irrigation, the vulnerability of reservoir operation is reduced. The methodology is evaluated by using different modeling tests which then motivates using the methodology for other arid/semi-arid regions.     

遥感技术在断裂研究中的应用——以张家口—蓬莱断裂带为例

张家口一蓬莱断裂带是一条北西西向活动断裂带。本文选取ETM+光学影像和SRTM高程影像作为主要数据源,结合研究区已有地质资料研究发现该带断裂构造的北西西向线性特征明显。从水系分布和错断地形等地貌标志判断,该断裂具有左阶组合样式和左行走滑活动特征。据遥感影像综合特征,可将该带分为张家口段、延庆-怀来段和北京一天津段,影像特征分段性显著,并与断裂带的分段性一致。研究结果表明,张家口-蓬莱断裂具有左行走滑的运动学特征,限制或错断北北东或北东向断裂,并且控制该区域的左阶雁列式第四纪盆地群和第四纪冲洪积物的分布。该断裂带各段对不同规模的水系分布和形态影响比较大,且北京-天津地区的华北平原段断裂对第四纪冲洪积扇和沿海地区的贝壳堤的形态和分布有一定的控制作用。地球物理深部数据和野外地质考察资料也证实了遥感解泽的结果,证明遥感技术在探查断裂构造空间展布和活动性鉴定中有着广泛的应用前景。     

Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India

Drought is a serious climatic condition that affects nearly all climatic zones worldwide, with semi-arid regions being especially susceptible to drought conditions because of their low annual precipitation and sensitivity to climate changes. Drought indices such as the standardized precipitation index (SPI) using meteorological data and vegetation indices from satellite data were developed for quantifying drought conditions. Remote sensing of semi-arid vegetation can provide vegetation indices which can be used to link drought conditions when correlated with various meteorological data based drought indices. The present study was carried out for drought monitoring for three districts namely Bhilwara, Kota and Udaipur of Rajasthan state in India using SPI, normalized difference vegetation index (NDVI), water supply vegetation index (WSVI) and vegetation condition index (VCI) derived from the Advanced Very High resolution Radiometer (AVHRR). The SPI was computed at different time scales of 1, 2, 3, 6, 9 and 12 months using monthly rainfall data. The NDVI and WSVI were correlated to the SPI and it was observed that for the three stations, the correlation coefficient was high for different time scales. Bhilwara district having the best correlation for the 9-month time scale shows late response while Kota district having the best correlation for 1-month shows fast response. On the basis of the SPI analysis, it was found that the area was worst affected by drought in the year 2002. This was validated on the basis of NDVI, WSVI and VCI. The study clearly shows that integrated analysis of ground measured data and satellite data has a great potential in drought monitoring.     

A proposed geotechnical-based method for evaluation of liquefaction potential analysis subjected to earthquake provocations (case study: Korzan earth dam, Hamedan province, Iran)

During the earthquakes, a number of earth dams have had severe damages or suffered major displacements as a result of liquefaction, thus modeling by computer codes can provide a reliable tool to predict the response of the dam foundation against earthquakes. These modeling can be used in the design of new dams or safety assessments of existing ones. In this paper, on the basis of the field and laboratory tests and by combination of several software packages a seismic geotechnical-based analysis procedure is proposed and verified by comparison with computer model tests and field and laboratory experiences. Verification or validation of the analyses relies to the ability of the applied computer codes. By using the Silakhor earthquake (2006, M _s 6.1) as a basis in order to check the efficiency of the proposed framework, the procedure is applied to the Korzan earth dam of Iran which is located in Hamedan Province to analyze and estimate the liquefaction and safety factor. Design and development of a computer code by the authors which was named as the ??Abbas Converter?? with graphical user interface which operates as logic connecter function that can compute and model the soil profiles is the critical point of this study. The results confirmed and proved the ability of the generated computer code on the evaluation of soil behavior during earthquake excitations. Also, this code was able to facilitate this study better than previous ones have, taking over the encountered problem.     

遥感影像地表温度反演与地热资源预测——以石家庄地区为例

热红外遥感技术可以反演地表温度信息,可在地热资源预测方面发挥重要作用.研究基于京津冀地区地热成藏模式,利用单窗算法反演出石家庄地区2015年3月6日地表温度,结合夜间热红外影像、遥感构造解译结果和剩余重力异常数据,综合分析,相互论证,圈定1处山地对流型地热远景区和2处沉积盆地型地热远景区.其中,平山县寺沟村昼夜地温值均...     

Groundwater exploration using remote sensing and geographic information systems in a semi-arid area (Southwest of Urmieh, Northwest of Iran)

Shortage of water required for drinking and agricultural uses is a subject with a vital importance in most arid and semi-arid regions. The area of this study is one of the semi-arid regions located in southwest of Urmieh lake, northwest of Iran, between N 37°00′, 37°15′ latitude and E 45°05′, 45°30′ longitude which is composed of Permian dolomitic limestone, limestone, and post-Jurassic granite with a very low primary porosity/permeability character. In order to delineate groundwater potential zones in this area, the study focused on identifying secondary porosity/permeability indicators such as lineaments, vegetation cover, lithology, drainage pattern, drainage density, etc. In this regard, a remote sensing and geographic information system-based methodology was selected. Landsat ETM, IRS (pan), SPOT data, digital elevation model, and digital image processing techniques such as filtering, false color composite, principal component analysis, band rationing and classification have been applied to reach the purposes. Information layers extracted for analysis and interpretation stage were then integrated with other data and modeled through the use of existing geographic information system (GIS) software and their related analytical functions. Finally, based on determined ground water favorability index for different sub zones, layers, weighting, and overlapping, a ground water potential index (GWPI) was defined which respectively was utilized to groundwater potential zoning and preparation of GWPI map of the region. Within the six different sub zones defined, two sub zones labeled with high and very good potential areas were highly recommended for further development and exploration purposes. Geophysical investigations in target areas confirm the labeled subzones. Based on the obtained results of the study, it can be concluded that remote sensing data are very useful tool to extract information of groundwater exploration. Also, application of geographic information systems to find target areas for groundwater exploration are effective to save time and cost.     

Groundwater quality degradation of urban areas (case study: Tehran city,Iran)

Groundwater quality of Tehran city is considered in this study. Nine sampling stations were selected, and composite sampling campaign was performed in summer 2012. Groundwater sampled from northern stations appeared to have acceptable characteristics for agricultural and drinking uses. The southern station samples did not meet the required guidelines. Concentration of SO₄ ^2?, Na⁺ and Cl^? obey a sharp ascending trend southwards. Accordingly, the electrical conductivity of the last station at the very southern areas is more than fifteen times greater than that of the first northern station. Tehran city is located in a semi-arid climate and experiences long hot summers. High rates of evapo-transpiration within urban green spaces and agricultural lands facilitate the salinization phenomenon in root zones. As a result, excess irrigation water eases the consequent percolation into aquifers. Furthermore, saline water intrusion from salt marshes located down south of the city is an expected consequence of wells overpumping. Such case is especially remarkable in hot seasons when an increased urban water demand is observed. Remarkable sulfate concentrations in saline water are mainly justified by percolation of sulfate containing fertilizers which are broadly used by local farmers in an uncontrolled manner. Surface run-offs and municipal wastewater leakage may also trigger the salinization process.     

Comparison of rockfall susceptibility assessment at local and regional scale: a case study in the north of Beijing (China)

This study shows a rockfall susceptibility assessment at local scale in north Beijing of China, including the identification of rockfall sources onsite by terrain and rock discontinuities analysis and run-out distance prediction by Rocfall^? simulation. Two types of rockfall were defined including one type on the cliffs with long inclined slopes and another type on the road slopes with low height. Two historical rockfall events were used to back-calibrating the parameters used for run-out distance simulation. Based on the work, rockfall susceptibility map at local scale was created in GIS, which was compared with the map obtained at regional scale (entire Huairou district scale). Due to the difference of approaches applied, procedure of assessment and types of source data acquired, the two resulting rockfall susceptibility maps are proved to be different. Still, both of them are useful and could be used at different level’s decision for rockfall prevention and mitigation. Different types of uncertainties exist in the study of rockfall susceptibility assessment. To reduce the uncertainties, studies on both approaches and techniques are suggested.     

The effects of removing bed materials on flow velocity (case study: Zaremrood River, Iran)

Nowadays, in parts of Iran, rivers and flood plains are being used as sand and silt mines, and the removal of river bed materials is performed without studying its effects on hydraulic behavior. On the other hand, the flood plain lands are in danger of floods and bank erosion. Zaremrood River in Tajan watershed due to removal of river bed material, two planes of before and after removal with scale of 1:1,000, has been used as basic data. The field investigation was emphasized on the end part of Zaremrood with a length of 5 km and starts from Ghandikola village to Ahoodasht Bridge. Using total station and field observations, the characteristics of reaches and cross sections of right bank, left bank, and main bed of river are written separately. Using software of HEC-RAS, ArcView 3.2, and extension HEC-GeoRAS, the flood zoning with different return periods to investigate water velocity and its changes, geometrical simulation of the bed, sides and flood way of rivers, and then by entering the results of HEC-GeoRAS into hydraulic software HEC-RAS for two before and after planes have been performed, and flow velocity was analyzed for three return periods of 10, 50, and 100 years. The results of this research showed that the velocities due to removal for floods with different return periods have increased, whereas water height and level during removal period have decreased.     

The role of blocking system in heavy precipitation of Iran (a case study: southeast of Iran January 2008)

This article concerns the analysis of the heavy precipitation, which allows investigating the effect of the blocking system on the unusual precipitation and temperature occurrence in Iran. The days of January 2008 have been the coldest days during the history of recorded data in Iran. Variation of precipitation during January 2008 compared with long-term data (30 years) shows the maximum positive anomaly in the stations located in southeast of Iran. However, the precipitation in consecutive days, 14–15 and 15–16 of January, produce a more important proportion of the heavy precipitation in this region. In order to study the role of the blocking system related to heavy precipitation in January 2008, the position and movement of the atmospheric systems including cyclones, anticyclones, fronts, and wind fields have been analyzed by the use of synoptic maps by the environment to circulation approach. Consequently, the weather maps indicated that the blocking system over the north of the Caspian Sea has caused the relatively deep low trough on January 5, 7, 14, 15, and 16, 2008, while the thermal and moisture gradients in the warm section of air masses have produced heavy precipitation. As a result, wind field of low levels (850 hPa) provided remarkable moisture fed by the Arabian Sea, Oman Sea, and Persian Gulf in the study area. Furthermore, the speed of wavelength and the position of the blocking system associated with the heavy precipitation can be clearly identified.     

Nonlinear site response evaluation of earthquakes: A case study from Sirdjan Balvavard Bridge,Kerman province,Iran

The aim of this study is to illustrate the soil conditions encountered at the proposed bridge sites to analyze and evaluate the test conducted, submit recommendations regarding foundation design. At first by field investigation, the required data was collected and after primary processing the acceptable data was selected. For nonlinear analysis of elastic and rigid half space bed rock, standard hyperbolic model was selected and performed, and the results were compared. The study clearly showed that the effect of bed rock on soil behavior during earthquake is one of the main factors controlling prediction of ground response. A critical aspect of this work was to develop and use a computer code “Abbas Converter” developed by the authors that has several advantages, such as quick installation, acting as a connecter function between the used softwares which can generate the input data corresponding to a defined format and finally, the results of this computer code can be easily exported to the other softwares used in this study. Moreover this code can make it easy to solve the problems encountered.     

A multitemporal analysis of tsunami impact on coastal vegetation using remote sensing: a case study on Koh Phra Thong Island, Thailand

The Indian Ocean tsunami event of December 26, 2004 not only left massive casualties and economic damages, but also raised concerns about the destruction and recovery of coastal ecosystems. This work aimed to analyze the spatial patterns and temporal trajectories of vegetation damage and recovery using a multisensor multitemporal remote sensing, dataset. Using the study area of Koh Phra Thong, Thailand as a case study, we demonstrate the capabilities of remote sensing analysis in assessing the consequences of an extreme flooding event on the dynamics of coastal vegetation. Field surveys and satellite mid-resolution multispectral satellite data covering the period from February 2003 to December 2009 were used to map flooded areas and coastal vegetation loss and recovery following the tsunami. Normalized Difference Reflectance change detection was performed to map the extent of flooded areas. Vegetation Fraction Cover derived using spectral unmixing techniques was used to study the multitemporal changes in coastal vegetation after the event. Vegetation change detection techniques were applied to characterize the vegetation cover changes in two different time frames: short-term changes (from 4?days to 1?year after the event), and long-term dynamics (up to 5?years after). Estimates of vegetation change (decline, recovery, and gain) were quantified and mapped, with extreme vegetation losses found directly after the tsunami (up to 79?% in flooded areas). After 1?year, different trends had developed, indicating that recovering vegetation had reached up to 55?% of pre-tsunami land cover, but with different trajectories for each vegetation type.