Geophysical Assessment of Groundwater Potential: A Case Study from Mian Channu Area,Pakistan

An integrated study using geophysical method in combination with pumping tests and geochemical method was carried out to delineate groundwater potential zones in Mian Channu area of Pakistan. Vertical electrical soundings (VES) using Schlumberger configuration with maximum current electrode spacing (AB/2 = 200 m) were conducted at 50 stations and 10 pumping tests at borehole sites were performed in close proximity to 10 of the VES stations. The aim of this study is to establish a correlation between the hydraulic parameters obtained from geophysical method and pumping tests so that the aquifer potential can be estimated from the geoelectrical surface measurements where no pumping tests exist. The aquifer parameters, namely, transmissivity and hydraulic conductivity were estimated from Dar Zarrouyk parameters by interpreting the layer parameters such as true resistivities and thicknesses. Geoelectrical succession of five‐layer strata (i.e., topsoil, clay, clay sand, sand, and sand gravel) with sand as a dominant lithology was found in the study area. Physicochemical parameters interpreted by World Health Organization and Food and Agriculture Organization were well correlated with the aquifer parameters obtained by geoelectrical method and pumping tests. The aquifer potential zones identified by modeled resistivity, Dar Zarrouk parameters, pumped aquifer parameters, and physicochemical parameters reveal that sand and gravel sand with high values of transmissivity and hydraulic conductivity are highly promising water bearing layers in northwest of the study area. Strong correlation between estimated and pumped aquifer parameters suggest that, in case of sparse well data, geophysical technique is useful to estimate the hydraulic potential of the aquifer with varying lithology.     

Biodegradation by Co‐inoculated Bacteria and Fungi Alleviates Adverse Effects of Red‐S3B on Growth and Nitrogen Uptake of Wheat

Textile wastewater contains huge quantities of nitrogen (N)‐containing azo‐dyes. Irrigation of crops with such wastewater adds toxic dyes into our healthy soils. One of the ways to prevent their entry to soils could be these waters after the dyes' biodegradation. Therefore, the present study was conducted to evaluate the impact of textile dyes on wheat growth, dye degradation efficiency of bacteria‐fungi consortium, and alleviation of dye toxicity in wheat by treatment with microbial consortium. Among dyes, Red‐S3B (3.19% N) was found to be the most toxic to germination and growth of seven‐day‐old wheat seedlings. Shewanella sp. NIAB‐BM15 and Aspergillus terreus NIAB‐FM10 were found to be efficient degraders of Red‐S3B. Their consortium completely decolorized 500 mg L^?1 Red‐S3B within 4 h. Irrigation with Red‐S3B‐contaminated water after treatment with developed consortium increased root length, shoot length, root biomass, and shoot biomass of 30‐day‐old wheat seedlings by 47, 18, 6, and 25%, respectively, than untreated water. Moreover, irrigation after microbial treatment of dye‐contaminated water resulted in 20 and 51% increase in shoot N content and N uptake, respectively, than untreated water. Thus, co‐inoculation of bacteria and fungi could be a useful bioremediation strategy for the treatment of azo‐dye‐polluted water.     

Seismic activity prediction using computational intelligence techniques in northern Pakistan

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar’s statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.     

Investigation of fractured rock aquifer in South China using electrical resistivity tomography and self-potential methods

Assessment of fractured rock aquifers in many parts of the world is complicated given their strong heterogeneity. Delineation of the subsurface geological formation in the weathered terrain is essential for groundwater exploration. To achieve this goal, 2D electrical resistivity tomography(ERT) and self-potential(SP) in combination with joint profile method(JPM) and boreholes have been carried out to delineate the subsurface geological units, detect the fracture/fault zones in hard rock, monitor the groundwater flow, and estimate the groundwater reserves contained within the weathered terrain at a complex heterogeneous site of Huangbu, South Guangdong of China. The integration of resistivity images with the borehole lithology along three profiles delineates three subsurface distinct layers namely topsoil cover, weathered and unweathered layers. The incorporation of ERT and SP with JPM reveal five fractures/faults, i.e., F_1, F_2, F_3, F_4 and F_5. 2D ERT models interpret the less resistive anomalies as the fractures/faults zones, and high resistive anomalies as the fresh bedrock. The inversion program based on the smoothness-constraint is used on the resistivity field data to get more realistic three layered model. SP measurements are obtained along the same electrical profiles which provide the negative anomalies clearly indicating the groundwater preferential flow pathways along the fracture/fault zones. Hydraulic parameters namely hydraulic conductivity and transmissivity were determined to estimate the groundwater resources contained within the fractures/faults. The integrated results suggest that the fractures/faults zones are most appropriate places of drilling for groundwater exploration in the investigated area. Geophysical methods coupled with the upfront borehole data provides better understanding about the conceptual model of the subsurface geological formations. The current investigation demonstrates the importance of the integrated geophysical methods as a complementary approach for groundwater assessment in the hard rock weathered areas.     

青藏高原中部色林错湖泊沉积物色度反映末次冰盛期以来区域古气候演化

色林错湖位于青藏高原内部,是西藏第一大咸水内陆湖。研究区剖面选自色林错第三湖泊阶地,利用常用气候替代指标色度,结合粒度、碳酸盐含量［CaCO³（%）］、矿物分析和全有机质（TOC）等进行对比分析,同时采用¹⁴C测年方法对剖面进行准确的年代划分,初步探讨了末次冰盛期以来色林错湖泊沉积物色度增强机制的差异性。研究表明： a^*、b^*与中粗粒砂、磁化率具有较好的相关性;亮度L^*与CaCO³（%）具较好相关性;因而沉积物色度变化可反应区域古气候变化。同时对湖泊沉积物矿物分析发现,影响色度变化的制色矿物主要是针铁矿,且以还原环境为主。红度a^*高值与亮度L^*低值对应气候暖湿气候环境,沉积物粒度较粗,碳酸盐含量低,有机质含量高,磁化率较高值;反之,红度a^*低值,L^*高值,粒度较细,碳酸盐含量高,有机质含量低,磁化率低值,对应干冷气候。在17.4～15.5 cal ka BP阶段,对应干冷的气候特点;在15.5～10.4 cal ka BP阶段,对应温暖湿润的气候;在10.4～5.2 cal ka BP阶段,整体属于温暖湿润的气候特点;其中,在9.7～9.4 cal ka BP和8.75～8.5 cal ka BP为两个重要的冷事件,属于干湿的气候特点;在5.2～1.2 cal ka BP阶段,反映了干冷的气候特征;在4.3～4.0 cal ka BP,3.3～3.0 cal ka BP和2.4～1.75 cal ka BP,反映了干旱温暖的气候特点;在1.2 cal ka BP以后,色林错湖湖水迅速下降。     

社区化新零售的布局选址与优化发展研究——以南京市盒马鲜生为例

社区化新零售是新兴的商业模式,也是商业与社区互动的重要场域,值得从城市空间视角深入探究。基于南京市盒马鲜生及相关兴趣点(point of interest,POI)与兴趣面(area of interest,AOI)数据,综合运用空间分析、定量统计、实地调研等方法,解析盒马鲜生的服务类型及对象、空间布局特征、区位选址因素,并提出优化发展建议。研究发现：① 南京市盒马鲜生服务对象以社区为主,酒店、写字楼为辅;服务客户以具有一定经济基础和消费能力的中青年人群为主。② 空间布局总体呈现南—北走向的主城区+近郊区的“5+7三组团”格局,均为“点”状门店+不规则“面”状服务区相结合的“中心—外围”结构,实际配送范围与3 km缓冲区存在差异。③ 区位选址主要受社区密度和交通环境的影响,对商圈、地价具有依赖性,竞争对手对门店选址影响较小;主要位于社区与道路密度中高值区、商圈边缘地带、主干道两侧及地价中等区域,并利用面状服务区延伸服务范围,获取更多潜在目标客户群。最后从消费群体、运营成本、品牌竞争3个方面探索其区位选址的影响机制,并基于区位选址特征提出优化发展建议。     

Impact of grazing on soil,vegetation and ewe production performances in a semi-arid rangeland

Controlled grazing is considered a good management strategy to maintain or increase the live weight of livestock and to reduce vegetation degradation of rangelands. The present study investigated soil characteristics, aboveground vegetation biomass dynamics and controlled grazinginduced changes in the live weight of local ewes in the semi-arid rangeland of Ahmadun, Ziarat, Balochistan province of Pakistan. An area of 115 ha was protected from livestock grazing in April 2014. In June 2015, soil characteristics within 0-30 cm depth i.e. soil organic matter (SOM), mineral nitrogen, pH and texture in controlled and uncontrolled grazing sites were assessed. Aboveground vegetation biomass measured in early (June) and late summer (August) in 2015 and 2016. The nutritional value i.e. crude protein, phosphorus (P), neutral detergent fiber (NDF), acid detergent fiber (ADF), calcium (Ca), magnesium (Mg) and potassium (K) of dominant plant species were assessed at the beginning of experiment in 2015. Vegetation cover of controlled and uncontrolled grazing sites was also measured during the two years of the study period using the VegMeasure software. From June to November in 2015 and 2016, controlled and uncontrolled livestock grazing sites were grazed on a daily basis by local ewes with a stocking rate of 2 and 1 head ha-1 respectively. Results reveal that the organic matter contents of coarse-textured, slightly alkaline soil of the study site were in the range of 9.4 - 17.6 g kg-1 soil and showed a strong positive correlation with aboveground vegetation biomass. The biomass of plants was 56.5% and 33% greater at controlled than uncontrolled grazing site in 2015 and 2016 respectively and plant cover was also higher at controlled than uncontrolled grazing site in both years. The nutrient contents were significantly (P<0.05) lower in grasses than shrubs. In both years, the controlled grazing increased the weight gain of ewes about two folds compared to the uncontrolled grazing. The results indicate that controlled grazing improved the vegetation biomass production and small ruminant productivity.     

Projection of future streamflow of the Hunza River Basin,Karakoram Range (Pakistan) using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.     

A Seismic Hazard Map Based on Geology and Shear-wave Velocity in Rawalpindi–Islamabad,Pakistan

The ‘twin cities' district of Rawalpindi–Islamabad is among the most endangered seismic regions in Pakistan,with the seismic hazard assessed(0.32 g) to intensity IX MMI for a 475-year return period. A seismic hazard map for Rawalpindi–Islamabad is presented herein, based on 85 shear-wave velocity(VS) profiles obtained through geophysical H/V measurements and from the geological map of the region. Relationships between the average top thirty-meter shear-wave velocities(VS30) and surficial geological units have been determined. The peak ground acceleration(PGA) maps for 150,475 and 2475-year return periods were converted into a seismic intensity map. Intensity increments for different soils were used to compute PGA values for 150, 475 and 2475-year return periods. Sites located on softer ground experienced a higher degree of damage from moderate earthquakes. Due to the presence of soft clay or lique?able soil and lateral spreading, a few locations may be classified as hybrid sites class C and D. This map is a critical step in facilitating code-based site classification and seismic design throughout Rawalpindi–Islamabad. Although the seismic hazard map based on seismic intensities is no longer used in engineering geology, it is still important in seismological analysis and for civil protection purposes.