Aquifer vulnerability assessment using GIS and fuzzy system: a case study in Tehran–Karaj aquifer,Iran

Aquifer vulnerability assessment techniques have been developed to predict which areas are more likely than others to become contaminated as a result of activities at or near the land surface. This research focuses on the evaluation of groundwater vulnerability to pollution in an urban area. Among several assessment methods, DRASTIC has been selected for this study. ArcGIS has been used to overlay and calculate different layers and obtain the vulnerability map. In order to show the importance of fuzzy algorithms in classification, both Boolean and fuzzy algorithms were used and compared. The fuzzy algorithm could recognize the areas with low and negligible vulnerability potentials whereas the Boolean model classified them as moderate. Two sensitivity tests, the map removal sensitivity analyses and single-parameter sensitivity analysis, were performed to show the importance of each parameter in the index calculation.     

Ellipsoidal Stokes Boundary-Value Problem with Ellipsoidal Corrections in the Boundary Condition

We would like to solve the Stokes boundary-value problem taking into consideration the ellipsoidal corrections in the boundary condition in ellipsoidal coordinates The original problem, i.e., the ellipsoidal Stokes boundary-value problem has been solved by Martinec and Grafarend (1997) We use the same philosophy expressed by Martinec (1998) to solve the spherical Stokes boundary-value problem with ellipsoidal corrections in the boundary condition We wish to show the magnitude of the integration kernel describing the effect of the ellipsoidal corrections in the boundary condition in a cap around the computational point.     

Geoid Determination Through Ellipsoidal Stokes Boundary-Value Problem by Splitting Its Solution to the Low-Degree and the High-Degree Parts

The ellipsoidal Stokes boundary-value problem is used to compute the geoidal heights. The low degree part of the geoidal heights can be represented more accurately by Global Geopotential Models (GGM). So the disturbing potential is splitted into a low-degree reference potential and a higher-degree potential. To compute the low-degree part, the global geopotential model is used, and for the high-degree part, the solution of the ellipsoidal Stokes boundary-value problem in the form of the surface integral is used. We present an effective method to remove the singularity of the high-degree of the spherical and ellipsoidal Stokes functions around the computational point. Finally, the numerical results of solving the ellipsoidal Stokes boundary-value problem and the difference between the high-degree part of the solution of the ellipsoidal Stokes boundary-value problem and that of the spherical Stokes boundary-value problem is presented.     

Soil moisture from operational meteorological satellites

In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS monitoring network located in the semi-arid part of the Duero basin in Spain. The remotely sensed soil-moisture products are retrieved from (1) the Advanced Microwave Scanning Radiometer (AMSR-E), which is a passive microwave sensor on-board NASA’s Aqua satellite, (2) European Remote Sensing satellite (ERS) scatterometer, which is an active microwave sensor on-board the two ERS satellites and (3) visible and thermal images from the METEOSAT satellite. Statistical analysis indicates that three satellite datasets contribute effectively to the monitoring of trends in surface soil-moisture conditions, but not to the estimation of absolute soil-moisture values. These sensors, or rather their successors, will be flown on operational meteorological satellites in the near future. With further improvements in processing techniques, operational meteorological satellites will increasingly deliver high-quality soil-moisture data. This may be of particular interest for hydrogeological studies that investigate long-term processes such as groundwater recharge.     

Landslide susceptibility assessment in the Anfu County,China: comparing different statistical and probabilistic models considering the new topo-hydrological factor (HAND)

The present study is aimed at producing landslide susceptibility map of a landslide-prone area (Anfu County, China) by using evidential belief function (EBF), frequency ratio (FR) and Mahalanobis distance (MD) models. To this aim, 302 landslides were mapped based on earlier reports and aerial photographs, as well as, carrying out several field surveys. The landslide inventory was randomly split into a training dataset (70%; 212landslides) for training the models and the remaining (30%; 90 landslides) was cast off for validation purpose. A total of sixteen geo-environmental conditioning factors were considered as inputs to the models: slope degree, slope aspect, plan curvature, profile curvature, the new topo-hydrological factor termed height above the nearest drainage (HAND), average annual rainfall, altitude, distance from rivers, distance from roads, distance from faults, lithology, normalized difference vegetation index (NDVI), sediment transport index (STI), stream power index (SPI), soil texture, and land use/cover. The validation of susceptibility maps was evaluated using the area under the receiver operating characteristic curve (AUROC). As a results, the FR outperformed other models with an AUROC of 84.98%, followed by EBF (78.63%) and MD (78.50%) models. The percentage of susceptibility classes for each model revealed that MD model managed to build a compendious map focused at highly susceptible areas (high and very high classes) with an overall area of approximately 17%, followed by FR (22.76%) and EBF (31%). The premier model (FR) attested that the five factors mostly influenced the landslide occurrence in the area: NDVI, soil texture, slope degree, altitude, and HAND. Interestingly, HAND could manifest clearer pattern with regard to landslide occurrence compared to other topo-hydrological factors such as SPI, STI, and distance to rivers. Lastly, it can be conceived that the susceptibility of the area to landsliding is more subjected to a complex environmental set of factors rather than anthropological ones (residential areas and distance to roads). This upshot can make a platform for further pragmatic measures regarding hazard-planning actions.     

Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann–Kendall and Şen tests

This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level fluctuation during the 1971–2013 period. Two new methods including nonparametric hybrid wavelet Mann–Kendall test and ?en’s methodology have been used to determine potential trends in the variables and their dominant periods. The results showed significant decreasing trends in the water level and streamflow series, moderate decreasing trend in the rainfall and relative humidity series, and increasing trends in the observed temperature data. The 8- , 12-month, and 2-year periods were detected as the dominant periods of the variables in monthly, seasonal, and annual timescales, respectively. The results from the interaction analysis revealed that the main factor influencing the water level at UL is decreasing trend in the streamflow series. Both the monthly series of UL’s water level and the streamflow series of the stations indicated two start points of significant decreasing trend in 1973 and 1998. Furthermore, a comparative analysis among the applied methods indicated a good agreement between the results of hybrid wavelet Mann–Kendall test and ?en’s trend analyzing method.     

Geospatial modeling to identify the effects of anthropogenic processes on landscape pattern change and biodiversity

This research used geospatial data to quantify biodiversity changes and landscape pattern change to track anthropogenic impacts of such changes at the Mouteh Wildlife Refuge (MWR), Isfahan, Iran. Satellite image duration of four decades, LandSat_1-5, and IRS-P6 data were used to develop land cover classification maps for 1971, 1987, 1998, and 2011. The number and size of land cover patches, the degree of naturalness, and the diversity indices were calculated and compared for a 40-year period. The results showed an increasing concern with regard to unplanned human activities. Some improvements of the natural landscape also occurred in the core protected zone of the study area. The number and size of land cover patches, the degree of naturalness, and the diversity indices were calculated. Overall changes in natural land use between 1971 and 1998 at MWR showed that the number of patches for natural land use has increased, but it also showed a decrease in 2011. Similar changes were observed for seminatural land use. Within the artificial classes, the number and area of patches were higher and the largest patch occurred in 2011. The maximum variation of diversity is related to the year 2011. The results showed an increasing concern with regard to unplanned human activities. Some improvements of the natural landscape also occurred in the core protected zone of the study area. Remote sensing and geographic information system offers an important means of detecting and analyzing temporal changes occurring in our landscape.     

Investigation of the Relationship between Sediment Graph and Hydrograph of Flood Events (Case Study: Gharachay River Tributaries,Arak, Iran)

Water Resources - In the comprehensive management of watersheds, the knowledge of the sedimentation process in flood conditions is considered as an important and challenging issue. The aim of this...     

Multi-level Optimization of Reservoir Scheduling Using Multi-resolution Wavelet-Based Up-scaled Models

This paper presents a multi-level procedure for production and injection scheduling through a numerical model-based optimization of well control variables. To calculate the net present value (NPV), the objective function of optimization, this procedure uses a number of discretized systems for a reservoir model with different degrees of up-scaling prepared according to a multi-resolution wavelet technique. These up-scaled models were incorporated into optimization based on a probability function. In early optimization iterations, due to the necessity to explore the search space quickly, the coarsest grid model has a higher chance for selection than the others; however, by a selection (with a low probability) of the finest up-scaled grid model in these iterations, solutions and objective function were tuned. In the later iterations of optimization, the finest up-scaled grid model probability was the highest in order to ensure the reliability of the final solution. The optimization algorithm is an adaptive simulated annealing algorithm coupled with a polytope. This procedure was evaluated in two case studies. The first case study was a horizontal 2D oil model with water flooding. The second case study was a vertical 2D oil model with gas injection. The results show that the proposed optimization procedure provides approximately the same accuracy compared to the situation in which the fine grid model is used for all the optimization iterations. Also, the run-time for the proposed optimization procedure is comparable to the run-time of the optimization in which only the coarsest grid model is used to calculate objective function. Moreover, the superiority of the wavelet-based up-scaling over an analogous multiple grid system optimization using uniformly up-scaled models is presented.