利用GIS对伊拉克Wasit和Dhi Qar省浅水井选定化学性质的建模和变异性

IF 0.4 Q4 SOIL SCIENCE
B. Al-humairi, N. Rahal, A. Jebur
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引用次数: 1

摘要

进行这项研究是为了模拟浅井水的几种化学性质,并调查伊拉克瓦西特省和济加尔省不同地区这些性质的空间变异性。选择了11口井来评估其水质及其对农业、土木工程和人类应用和用途的适用性。样本于2018年1月从瓦西特省的贾兹纳(1、2、3和4)、Karthiya、Badra、Dujaili、Shaikhsaad、Muwafaqiya、Hay和济加尔省的Fajr采集。对水样进行化学分析,以测量钠(Na1+)、钙(Ca2+)、镁(Mg2+)的浓度、pH、电导率(Ec)和总溶解固体(TDS)。对结果进行了几个描述性统计——最小值(Min.)、最大值(Max)、标准差(std)、偏度(偏斜)、峰度(Kurt.)和变异系数(CV%)。使用Data Fit(9.3)软件生成数学模型,根据化学性质预测钠吸附率(SAR)和可交换钠百分比(ESP)。SAR和ESP的预测值使用几个验证指标进行验证,包括确定因子R2、均方根误差(RMSE)、绝对均方误差(MAE)、相对误差(RE)、相关系数(R)和标准误差(s)。GIS程序用于绘制所研究的化学性质图。结果表明,SAR模型(SAR=a 1×Na 1+a 2×Ca 2+a 3×Mg 2+a 4×ESP+a 5×X东+a 6×Y北+a 7)具有(R2=0.999,SEE=5.30,RMSE=0.000,MAE=0.000和RE=0.000),ESP模型(ESP=Exp(a 1×Na1+a 1×Ca 2+a 3×Mg 2+a 1 4×X东+a 5×Y北+a 6)具有(R 2=0.9827,SEE=5.55,RMSE=0.037,MA E=0.026和RE=0.003)对于预测所选井的SAR和ESP值而言是最好的。确定了井水水质指数(WWQI),因此将该水归类为差水。因此,研究井的水被认为不适合作为饮用水和灌溉水供人类饮用;除了Fajr井被发现非常适合灌溉。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling and variability of selected chemical properties of shallow water wells using GIS in Wasit and Dhi Qar provinces/Iraq
This study was conducted to model several chemical properties of shallow well waters and to investigate the spatial variability of these properties in different regions over two provinces in Iraq - Wasit and Dhi-Qar. Eleven wells were chosen to evaluate the quality of their water and its suitability for agricultural, civil engineering and human applications and uses. Samples were taken in January 2018 from Giazna (1, 2, 3, and 4 ), Karthiya, Badra, Dujaili, Shaikhsaad, Muwafaqiya, Hay, in Wasit province and from Fajr in Dhi-Qar province. The water samples were subjected to chemical analysis to measure the concentrations of sodium (Na 1+ ), calcium (Ca 2+ ), magnesium (Mg 2+ ), pH, electrical conductivity (Ec), and total dissolved solids (TDS). Results were undergone several descriptive statistics Minimum (Min.), Maximum (Max.), standard deviation (std), skewness (skew.), and Kurtosis, (Kurt.) and coefficient of variation (CV%). Mathematical models were generated using Data Fit (9.3) software to predict sodium adsorption ratio (SAR) and exchangeable sodium percentage (ESP) depending on chemical properties. The predicted values of SAR and ESP were validated using several validation indices including the factor of determination R 2 , root mean squared error (RMSE), absolute mean error (MAE), relative error (RE), correlation coefficient (r) and standard error (s). A GIS program was used to map the studied chemical properties. The results showed that the SAR model (SAR = a 1 × Na 1+ + a 2 × Ca 2+ + a 3 × Mg 2+ + a 4 × ESP + a 5 × X east + a 6 × Y north + a 7 ) which with (R 2 =0.999, SEE=5.30, RMSE=0.000, MAE=0.000, and RE=0.000) and the ESP model (ESP = Exp(a 1 × Na 1+ + a 2 × Ca 2+ + a 3 × Mg 2+ + a 4 × X east + a 5 × Y north + a 6 )) which with ( R 2 =0.9827, SEE=5.55, RMSE=0.037,MAE=0.026 and RE=0.003) were the best for predicting SAR and ESP values for the selected wells. The Well water quality index (WWQI) was determined and accordingly the water was classified as poor. As a result, the water of the studied wells was considered unsuitable for human consumption as drinking water and irrigation; except the well of Fajr which was found critically suitable for irrigation purposes.
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来源期刊
Soil & Environment
Soil & Environment SOIL SCIENCE-
CiteScore
1.10
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