利用地理信息系统和指数评价孟加拉国Kalihati Upazila地下水灌溉适宜性

Md. Touhidul Islam, Nilima Das, Nusrat Jahan, Md. Sifat Siddik, Khalid Mahmud, A.K.M. Adham
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引用次数: 0

摘要

这项研究的目的是评估孟加拉国Kalihati Upazila地区用于灌溉的地下水质量,该地区的作物生长严重依赖地下水,特别是在干旱时期。采用水化学分析与地理信息系统(GIS)相结合的方法,研究了水体理化属性及其空间分布特征。对15份不同地点的地下水样品进行了钠吸附比(SAR)、可溶性钠百分比(SSP)、残余碳酸钠(RSC)、镁吸附比(MAR)、电导率(EC)、总溶解固形物(TDS)、总硬度(TH)、凯利比(KR)、渗透率指数(PI)和潜在盐度(PS)等参数的测定。地下水pH值在5.51 ~ 7.53之间,呈微酸性至中碱性,适合灌溉。EC范围在115.7 ~ 458 μS/cm之间,大部分属于“优秀”或“良好”类别。地下水在TDS低于182 ppm、SAR值较低时表现出灌溉适宜性,但不同的RSC和MAR值表明存在局部水质问题。根据灌溉水质指标,所有样品均在“允许”范围内。然而,地理信息系统生成的地图显示了整个研究区域地下水质量的差异。相关矩阵揭示了各因素之间的显著联系。Piper图和Gibbs图均显示受地质构造影响的Ca-HCO3地下水类型普遍存在。总体而言,该研究证实了地下水灌溉的适宜性,但由于存在一些不确定因素,建议进行定期评估。总而言之,研究发现水化学分析、GIS制图和相关矩阵揭示了地下水质量和空间趋势,为可持续水资源管理和农业发展提供了可能。
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Utilizing geographic information system and indexing to evaluate irrigation suitability of groundwater in Kalihati Upazila, Bangladesh
The aim of this research was to evaluate groundwater quality for irrigation in Kalihati Upazila, Bangladesh, a region that is significantly reliant on groundwater for crop development, especially during dry periods. By combining hydrochemical analysis and Geographic Information System (GIS), the research examined the physicochemical attributes and their spatial distribution. Fifteen groundwater samples from various locations were analyzed to measure parameters such as sodium adsorption ratio (SAR), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium adsorption ratio (MAR), electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), Kelly's ratio (KR), permeability index (PI), and potential salinity (PS). The pH of the groundwater ranged between 5.51 and 7.53, indicating slightly acidic to moderately alkaline conditions suited for irrigation. The EC ranged between 115.7 and 458 μS/cm, mostly falling into the "excellent" or "good" categories. Groundwater displayed irrigation suitability with TDS below 182 ppm and low SAR values, but variable RSC and MAR values indicated localized water quality issues. Based on the irrigation water quality index, all samples were within the "permissible" range. However, GIS-generated maps showed disparities in groundwater quality across the study area. Correlation matrices revealed significant links between various factors. Both the Piper and Gibbs diagrams displayed a prevalent Ca-HCO3 groundwater type influenced by geological formations. Overall, the study confirmed groundwater's appropriateness for irrigation while recommending periodic evaluations due to a few uncertainties. In conclusion, the study found that hydrochemical analysis, GIS mapping, and correlation matrices reveal groundwater quality and spatial trends, allowing for sustainable water resource management and agricultural advancement.
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