Integrating stable isotopes and factor analysis to delineate the groundwater provenance and pollution sources in the northwestern part of the Amman-Al Zarqa Basin, Jordan

Globally,groundwater contamination by nitrate is one of the most widespread environmental problems,particularly in arid and semiarid areas,which are characterized by low amounts of rainfall and groundwater recharge.The stable isotope composition of groundwater(δ2H-H2O andδ18O-H2O)and dissolved nitrate(δ15N-NO3–andδ18O-NO3–)and factor analysis(FA)were applied to explore groundwater provenance,pollution,and chemistry evolution in the northwestern part of the Amman-Al Zarqa Basin,Jordan.In this study,we collected 23 samples from the Lower Ajloun aquifer in 2021,including 1 sample from a groundwater well and 22 samples from springs.These samples were tested for electrical conductivity,total dissolved solids,pH,temperature,dissolved oxygen,the concentration of major ions(Ca2+,Mg2+,Na+,K+,HCO3–,Cl–,SO42–,and NO3–),and the stable isotope composition of groundwater and dissolved nitrate.The results revealed that groundwater in the study area is mainly Ca–Mg–HCO3 type and can be classified as fresh water,hard water,and very hard water.The range and average concentration of NO3–were 3.5–230.8 and 50.9 mg/L,respectively.Approximately 33%of the sampling points showed NO3–levels above the maximum allowable concentration of 50.0 mg/L set by the World Health Organization(WHO)guidelines for drinking water quality.The values ofδ18O-H2O andδ2H-H2O showed that groundwater in the study area is part of the current water cycle,originating in the Mediterranean Sea,with significant evaporation,orographic,and amount effects.The values of the stable isotope composition of NO3–corresponded toδ15N-NO3–andδ18O-NO3–values produced by the nitrification process of manure or septic waste and soil NH4+.The FA performed on the hydrochemical parameters and isotope data resulted in three main factors,with Factor 1,Factor 2,and Factor 3,accounting for 50%,21%,and 11%of the total variance,respectively.Factor 1 was considered human-induced factor,named"pollution factor",whereas Factor 2,named"conservative fingerprint factor",and Factor 3,named"hardness factor",were considered natural factors.This study will help local researchers manage groundwater sustainably in the study area and other similar arid and semiarid areas in the world.

Source identification of nitrate in the upper aquifer system of the Wadi Shueib catchment area in Jordan based on stable isotope composition

Groundwater forms the main freshwater supply in arid and semi-arid areas,and contamination of this precious resource is complicated by the slow rate of recharge in these areas.Nitrate contamination of groundwater is a global water quality problem,as it entails threat to human health as well as aquatic ecosystems.Source identification of contamination is the cornerstone and a prerequisite for any effective management program of water quality.Stable isotope composition of the dissolved nitrate(δ^(15)N-NO_(3)-andδ^(18)O-NO_(3)-)has been applied to identify NO_(3)-sources and the main transformation processes in the upper aquifer system(A1/2,A4,and B2/A7 aquifers)in the Wadi Shueib catchment area,Jordan.Moreover,the stable isotope compositions of the groundwater(δ^(2)H-H_(2)O andδ^(18)O-H_(2)O)in conjunction with the groundwater hydrochemistry were integrated to investigate the origin and evolution of the groundwater.Results revealed that groundwater in the study area is fresh and hard-very hard water,and mainly a Ca-Mg-Cl type.NO_(3)-concentration was in the range of 7.0-74.0 mg/L with an average of 37.0 mg/L.Most of the samples showed concentration higher than the natural background concentration of NO_(3)-(5.0-10.0 mg/L).Theδ^(2)H-H_(2)O andδ^(18)O-H_(2)O values indicated that the groundwater is meteoric,and of Mediterranean origin,with a strong evaporation effect.Theδ^(15)N-NO_(3)-values ranged between 6.0‰and 11.3‰with an average of 8.7‰,and theδ^(18)O-NO_(3)-values ranged between 1.6‰and 5.9‰with an average of 3.4‰.These values are in conformity with the stable isotope composition of nitrate derived the nitrification of wastewater/manure,and soil NH4.Nitrification and denitrification are the main transformation processes affecting nitrogen species.Statistical analysis revealed no significant differences in theδ^(2)H-H_(2)O andδ^(18)OH_(2)O values,andδ^(15)N-NO_(3)-andδ^(18)O-NO_(3)-values for the three aquifers(A1/2,A4,and B2/A7),indicating that the groundwater of these aquifers has the same origin,and a common source of pollution.

Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data

We propose a multi-sensor multi-spectral and bi-temporal dual-polarimetric Synthetic Aperture Radar(SAR) data integration scheme for dry/wet snow mapping using Sentinel-2 and Sentinel-1 data which are freely available to the research community. The integration is carried out by incorporating the information retrieved from ratio images of the conventional method for wet snow mapping and the multispectral data in two different frameworks. Firstly, a simple differencing scheme is employed for dry/wet snow mapping, where the snow cover area is derived using the Normalized Differenced Snow Index(NDSI). In the second framework, the ratio images are stacked with the multispectral bands and this stack is used for supervised and unsupervised classification using support vector machines for dry/wet snow mapping. We also investigate the potential of a state of the art backscatter model for the identification of dry/wet snow using Sentinel-1 data. The results are validated using a reference map derived from RADARSAT-2 full polarimetric SAR data. A good agreement was observed between the results and the reference data with an overall accuracy greater than 0.78 for the different blending techniques examined. For all the proposed frameworks, the wet snow was better identified. The coefficient of determination between the snow wetness derived from the backscatter model and the reference based on RADARSAT-2 data was observed to be 0.58 with a significantly higher root mean square error of 1.03 % by volume.

An Integrated Method for the Selection of Optimum Locations for Landfilling Utilizing GIS: A Case Study of the State of Kuwait

With the rise of urbanization, change in lifestyles, and food habits, the amount of Municipal Solid Waste (MSW) has been rapidly increasing with the composition constantly changing. Landfilling is the common approach for waste management in Kuwait, and around 90% of municipal wastes are disposed in landfill sites. Therefore, this study focused on the integration of different methods for the process of allocating optimum sites for MSW landfills, in four main stages. The first stage focused on utilizing the gap analysis method for the identification of effective criteria for landfill site selection, by comparing the criteria in Kuwait with the World Bank guidelines, US EPA, and Australia EPA, to suggest the best criteria for landfill site selection. These criteria were applied in the second and third stages to determine suitable locations for landfill sites using the Geographical Information System (GIS). In the last stage, the suitable areas were evaluated by studying the socioeconomic aspects such as distance to waste generation center, the proximity of existing roads, and lifespan to select optimum locations for landfilling. The results indicated that only one site with a total area of 12 km2 was considered optimum for MSW landfill sites in Kuwait. Therefore, moderate suitability areas were indicated to support and provide decision makers with more options. The moderately suitable sites are also suitable for landfilling, but they need to be designed carefully in order to avoid negative impacts on the environment and human health. Therefore, we conclude that there is an urgent need to apply the integrated waste management system in Kuwait, as well as to develop a long-term strategic plan.

Flood Resilient Cities: A Syntactic and Metric Novel on Measuring the Resilience of Cities against Flooding, Gothenburg, Sweden

Flooding is one of the most destructive natural disasters which have rapidly been growing in frequency and intensity all over the world. In this view, assessment of the resilience of the city against such disturbances is of high necessity in order to significantly mitigate the disaster effects of flooding on the city structures and the human lives. The aim of this paper is to develop a method to assess the resilience of a river city (the city of Gothenburg in Sweden), which is prone to flood Hazard, against such disturbances. By simulating flood inundation with different return periods, in the first step, the areas of impact are determined. To assess the resilience, two different methods are followed. One is a syntactic method grounded in the foreground network in space syntax theory and the other is based on measuring accessibility to the essential amenities in the city. In the first method, similarity and sameness parameters are defined to quantitatively measure the syntactic resilience in the city. In the next step, accessibility to amenities and the minimum distance to amenities before and after each disturbance is measured. The results, in general, show that such disturbances affect the city structure and the resilience of the city differently. For instance, the city is more resilient after flooding according to accessibility measures. This clearly means that the answer to the question of resilience is mainly dependent on “resilience of what and for what.”

A novel solution for outlier removal of ICESat altimetry data： a case study in the Yili watershed, China

Due to the influence of cloud and saturated waveforms, ICESat data contain many contaminated elevation data that cannot be directly used in examining surface elevation and change. This study provides a novel solution for removing bad data and getting clean ICESat data for land applications by using threshold values of reflectivity, saturation, and gain directly from ICESat＇s GLAS （Geoscience Laser Alteimeter System） 01, 05, and 06 products. It is found that each laser campaign needs different threshold compositions to assure qualified ICESat data and that bad data removal rates range from 9.6% （laser 2A） to 62.3% （laser 2B） for the test area in the Yili watershed, China. These thresholds would possibly be used in other regions to extract qualified ICESat footprints for land applications. However, it is recommended to use the steps proposed here to further examine the transferability of threshold values for other regions of different elevations and climate regimes. As an example, the resulting ICESat data are applied to examine lake level changes of two lakes in the study area.

Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data

Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.