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1

Predicting Water Quality Parameters in a Complex River System

Kurniawan Isman, Hayder Gasim, Mustafa Hauwa Mohammed

Journal of Ecological Engineering

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2021

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Vol. 22, nr 1

250--257

EN

This research applied a machine learning technique for predicting the water quality parameters of Kelantan River using the historical data collected from various stations. Support Vector Machine (SVM) was used to develop the prediction model. Six water quality parameters (dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia nitrogen (NH3-N), and suspended solids (SS)) were predicted. The dataset was obtained from the measurement of 14 stations of Kelantan River from September 2005 to December 2017 with a total sample of 148 monthly data. We defined 3 schemes of prediction to investigate the contribution of the attribute number and the model performance. The outcome of the study demonstrated that the prediction of the suspended solid parameter gave the best performance, which was indicated by the highest values of the R2 score. Meanwhile, the prediction of the COD parameter gave the lowest score of R2 score, indicating the difficulty of the dataset to be modelled by SVM. The analysis of the contribution of attribute number shows that the prediction of the four parameters (DO, BOD, NH3-N, and SS) is directly proportional to the performance of the model. Similarly, the best prediction of the pH parameter is obtained from the utilization of the least number of attributes found in scheme 1.

2

Bivariate food distribution analysis under parametric copula framework: a case study for Kelantan River basin in Malaysia

Latif Shahid, Mustafa Firuza

Acta Geophysica

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2020

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Vol. 68, no. 3

821--859

EN

Flood is becoming an intensive hydro-climatic issue at the Kelantan River basin in Malaysia. Univariate frequency analysis would be unreliable due to multidimensional behaviour of food, which often demands multivariate fow exceedance probabilities. The joint distribution analysis of multiple interacting food characteristics, i.e. food peak, volume and duration, is very useful for understanding critical hydrologic behaviour at a river basin scale. In this paper, a copula-based methodology is incorporated for multivariate food frequency analysis for the 50-year annual basis food characteristics of Kelantan River basin at Guillemard bridge station in Malaysia. Investigation reveals that the Lognormal (2P), Johnson SB-4P and Gamma-3P are selected as marginal distributions for the food peak fow, volume and duration series. Several bivariate families such as mono-parametric, bi-parametric (i.e. mixed version) and rotated version of Archimedean copulas and also the elliptical copula are introduced to cover a large dependence pattern of food characteristics. The dependence parameter of bivariate copulas is estimated by the method of moments (MOM) based on the inversion of Kendall’s tau and maximum pseudo-likelihood estimator. To analytically validate and recognize most parsimonious copulas, GOF test and Cramer–von Mises distance statistics (Sn) with the parametric bootstrap method are employed. The Gaussian copula is identifed as the most justifable model for joint modelling of the food peak–volume and peak–duration combination for MOM-based parameter estimation procedure. Similarly, the Frank copula is selected as the best-ftted structure for modelling peak–duration combination based on MPL estimators, but the MOM estimator recognized Gaussian copula as most suitable for peak–volume pair. Furthermore, the best-ftted copulas are used for obtaining the joint and conditional return periods of the food characteristics

3

Effect of 2014 massive flood on well water qualities: A case study on Kelantan River basin, Malaysia

Rahman H. A. Ab., Ibrahim N. A., Abdul Hamid A. A., Abdul Hamid T. H. T.

Journal of Water and Land Development

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2018

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no. 38

127--136

EN

The effect of physical and biological qualities of wells after submergence was assessed following December 2014 flood in Kelantan. Studies were carried out on a total of 65 wells from 13 stations around Kelantan River basin in which the wells’ water were sampled for pH, total dissolved solid (TDS), turbidity and microbial contamination. About 95% of the well showed to be contaminated, 7 out of 65 samples (11.1%) showed TDS values >400 μS·cm–1; and 19 samples (29.2%) recorded turbidity beyond 7.0 NTU. Statistical non-parametric tests carried out on independent groups showed that the status of well contamination was neither determined by both degree of submergence nor by the geographical location. Also the physico-chemical parameters are independent of flood inundation. However, TDS and turbidity values changed based on geographical location, at p < 0.05. Well from estuary recorded higher TDS (241.2 μS·cm–1 ±159.5 SD) and turbidity (8.04 NTU ± 6.53 SD) compared to those from inner basin (TDS at 156.3 μS·cm–1± 88.9 SD; turbidity at 2.90 NTU ± 2.46 SD), respectively. The flood water had played significant role in the transmission of existing contaminant, and most of the wells were unsafe for drinking. We concluded that the degree of flood submergence does not necessarily determine the severity of the well contamination in Kelantan, but the existing contamination may exacerbate further the potential risk during post flood period.

PL

Oceniano fizyczne i biologiczne właściwości wód w studniach zalanych w wyniku powodzi w grudniu 2014 r. w basenie rzeki Kelantan. Badania prowadzono łącznie w 65 studniach z 13 stanowisk w basenie rzeki. Analizowano pH, zawartość substancji rozpuszczonych (TDS), mętność i zanieczyszczenie mikrobiologiczne. Zanieczyszczenia wykryto w ok. 95% studni, w 7 z 65 stwierdzono wartości TDS > 400 μS·cm–1, a 19 próbek (29,2%) miało mętność ponad 7,0 NTU. Statystyczne testy dla zmiennych niezależnych wykazały, że poziom zanieczyszczeń nie zależał ani od stopnia zalania, ani od lokalizacji. Fizyczne i chemiczne parametry wody także nie były zależne od zalewu powodziowego, TDS i mętność zmieniały się wraz z położeniem geograficznym z istotnością p < 0,05. W wodzie ze studni z estuarium rzeki wartości TDS i mętność (odpowiednio 241,2 μS·cm–1 ±159,5 SD i 8,04 NTU ±6,53 SD) były większe niż w wodzie ze studni w głębi basenu (TDS 156,3 μS·cm–1 ±88,9 SD, mętność 2,90 NTU ±2,46 SD). Wody powodziowe odgrywały istotną rolę w przenoszeniu zanieczyszczeń. Większość wód studziennych nie nadawała się do picia. Stwierdzono ostatecznie, że stopień zalania studni niekoniecznie determinuje stopień zanieczyszczenia studni, ale występujące zanieczyszczenia mogą zwiększać potencjalne ryzyko po ustąpieniu powodzi.