scholarly journals ANALISIS KEBERLANJUTAN SUMBER DAYA IKAN KARANG FAMILI CAESIONIDAE DI KAWASAN KONSERVASI TAMAN NASIONAL KARIMUNJAWA

2019 ◽  
Vol 20 (1) ◽  
pp. 57-67
Author(s):  
Ernik Yuliana ◽  
Nurhasanah Nurhasanah ◽  
Idha Farida
Keyword(s):  
Water Quality ◽  
National Park ◽  
Suspended Solids ◽  
Stakeholder Analysis ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Data ◽  
Water Quality Data ◽  
Fish Resources ◽  
Spawning Potential Ratio

Reef fish resources are the main catch in Karimunjawa National Park. The fishing activities are feared to have an impact on the sustainability of fish resources inside and outside the conservation area. The purpose of this study is to analyze of the sustainability of reef fish resources (Family Caesionidae) in marine protected area. The study was conducted in Karimunjawa National Park (TNKJ) in Jepara Regency, Central Java, April-September 2017. Data collection was carried out by survey, observation, and deep interview methods, including primary data. Coral fish of the Caesionidae family, which were the object of research, were Caesio cuning and Caesio caerulaurea. Data collection on fish length and weight was carried out six times sampling (for six months). Examples of fish taken from three collectors in Karimunjawa Village. Water quality data was taken for analysis of pH, total dissolved solids (TDS), temperature, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), and salinity. Data analysis using FISAT II program and estimation of spawning potential ratio (SPR) using length-based spawning potential ratio analysis. To analyze management aspects of reef fishes, stakeholder analysis was carried out. The research results indicated that Caesio cuning and Caesio caerulaurea had exploitation rate values ​​of 0.69 and 0.61, in the condition of over exploited. The spawning potential ratio (SPR) value are 0.14 and 0.25 (the capacity of adult fish that is ready naturally to spawn is very small). Water quality data is below the water quality standard for marine biota, indicated that the waters of the Karimunjawa National Park was sustainable. The results of stakeholder analysis indicated that there are four parties who are the subject of management. They were fisheries management authorities and Non-Governmental Organizations (NGOs) as work partners of the management authority.   Ikan karang merupakan sumber daya ikan yang menjadi tangkapan utama nelayan di Taman Nasional Karimunjawa. Penangkapan ikan tersebut dikhawatirkan berdampak pada keberlanjutan sumber daya ikan di dalam dan luar kawasan konservasi. Tujuan studi ini adalah menganalisis keberlanjutan sumber daya ikan karang Famili Caesionidae di kawasan konservasi. Studi dilakukan di Taman Taman Nasional Karimunjawa (TNKJ) Kabupaten Jepara, Jawa Tengah, April-September 2017. Pengumpulan data dilakukan dengan metode survei, observasi, dan wawancara dengan mengumpulkan data primer. Ikan karang Famili Caesionidae yang menjadi objek penelitian adalah Caesio cuning dan Caesio caerulaurea. Pengambilan data panjang dan bobot ikan dilakukan empat kali sampling (selama empat bulan). Contoh ikan diambil dari tiga pengepul di Desa Karimunjawa. Data kualitas air diambil untuk analisis pH, total dissolved solids (TDS), suhu, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), dan salinitas. Analisis data menggunakan program FISAT II dan pendugaan spawning potential ratio (SPR) menggunakan analisis length-based spawning potential ratio. Untuk menganalisis aspek pengelolaan, dilakukan analisis stakeholder. Hasil penelitian menunjukkan bahwa Caesio cuning dan Caesio caerulaurea mempunyai nilai laju eksploitasi berturut-turut 0,69 dan 0,61, berada pada kondisi over exploited. Nilai spawning potential ratio (SPR) berturut-turut adalah 0,14 dan 0,25 (kapasitas ikan dewasa yang siap memijah di alam sangat sedikit). Data kualitas air berada di bawah baku mutu perairan untuk biota laut, menunjukkan perairan TNKJ dalam kondisi berlanjut. Hasil analisis stakeholder menunjukkan ada empat pihak yang menjadi subjek pengelolaan, dan semuanya adalah pemegang otoritas pengelolaan perikanan dan Lembaga Swadaya Masyarakat (LSM) sebagai partner kerja otoritas pengelola.

scholarly journals URBAN GROWTH AND WATER QUALITY IN THIMPHU, BHUTAN

2013 ◽  
pp. 82-95 ◽  
Author(s):  
Nandu Giri ◽  
O. P. Singh
Keyword(s):  
Water Quality ◽  
Urban Area ◽  
Water Samples ◽  
Urban Areas ◽  
Forest Cover ◽  
Rapid Development ◽  
Oxygen Demand ◽  
Capital City ◽  
Quality Data ◽  
Water Quality Data

Detailed study was undertaken in 2008 and 2009 on assessment of water quality of River Wang Chhu which flows through Thimphu urban area, the capital city of Bhutan. The water samples were examined at upstream of urban area, within the urban area and its downstream. The water samples were analyzed by studying the physico-chemical, biological and benthic macro-invertebrates. The water quality data obtained during present study are discussed in relation to land use/land cover changes(LULC) and various ongoing human activities at upstream, within the each activity areas and it’s downstream. Analyses of satellite imagery of 1990 and 2008 using GIS revealed that over a period of eighteen years the forest, scrub and agricultural areas have decreased whereas urban area and road network have increased considerably. The forest cover, agriculture area and scrub decreased from 43.3% to 42.57%, 6.88% to 5.33% and 42.55% to 29.42%, respectively. The LULC changes effect water quality in many ways. The water temperature, pH, conductivity, total dissolved solids, turbidity, nitrate, phosphate, chloride, total coliform, and biological oxygen demand were lower at upstream and higher in urban area. On the other hand dissolved oxygen was found higher at upstream and lower in urban area. The pollution sensitive benthic macro-invertebrates population were dominant at upstream sampling sites whereas pollution tolerant benthic macro-invertebrates were found abundant in urban area and its immediate downstream. The rapid development of urban infrastructure in Thimphu city may be posing serious threats to water regime in terms of its quality. Though the deterioration of water quality is restricted to a few localized areas, the trend is serious and needs proper attention of policy planners and decision makers. Proper treatment of effluents from urban areas is urgently needed to reduce water pollution in such affected areas to check further deterioration of water quality. This present study which is based on upstream, within urban area and downstream of Thimphu city can be considered as an eye opener.

scholarly journals Time series modeling of biochemical oxygen demand at the upstream catchment of Feitsui Reservoir, Taiwan

2016 ◽  
Vol 47 (5) ◽  
pp. 1069-1085 ◽  
Author(s):  
Yung-Chia Chiu ◽  
Chih-Wei Chiang ◽  
Tsung-Yu Lee
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Biochemical Oxygen Demand ◽  
Oxygen Demand ◽  
Quality Data ◽  
Series Data ◽  
Water Quality Data ◽  
Inference System ◽  
Feitsui Reservoir ◽  
Upstream Catchment

The adaptive neuro fuzzy inference system (ANFIS) has been proposed to model the time series of water quality data in this study. The biochemical oxygen demand data collected at the upstream catchment of Feitsui Reservoir in Taiwan for more than 20 years are selected as the target water quality variable. The classical statistical technique of the Box-Jenkins method is applied for the selection of appropriate input variables and data pre-processing of using differencing is implemented during the model development. The time series data obtained by ANFIS models are compared to those obtained by autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs). The results show that the ANFIS model identified at each sampling station is superior to the respective ARIMA and ANN models. The R values at all sampling stations of the training and testing datasets are 0.83–0.98 and 0.81–0.89, respectively, except at Huang-ju-pi-liao station. ANFIS models can provide accurate predictions for complex hydrological processes, and can be extended to other areas to improve the understanding of river pollution trends. The procedure of input selection and the pre-processing of input data proposed in this study can stimulate the usage of ANFIS in other related studies.

scholarly journals A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mochamad A. Pratama ◽  
Yan D. Immanuel ◽  
Dwinanti R. Marthanty
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Quality Management ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River’s water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

Effects of sampling frequency on estimation accuracies of annual loadings for water quality parameters in different sized watersheds

2020 ◽  
Vol 55 (3) ◽  
pp. 261-277
Author(s):  
Lin Gao ◽  
Junyu Qi ◽  
Sheng Li ◽  
Glenn Benoy ◽  
Zisheng Xing ◽  
...  
Keyword(s):  
Water Quality ◽  
Suspended Solids ◽  
Nitrate Nitrogen ◽  
Sampling Frequency ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Estimation Errors ◽  
Water Quality Data ◽  
Novel Approach

Abstract Potential errors or uncertainties of annual loading estimations for water quality parameters such as suspended solids (SS), nitrate-nitrogen (NO3-N), ortho-phosphorus (Ortho-P), potassium (K), calcium (Ca), and magnesium (Mg) can be greatly affected by sampling frequencies. In this study, annual loading estimation errors were assessed in terms of the coefficient of variation, relative bias, and probability of potential errors that were estimated with statistical samples taken at a series of sampling frequencies for a watershed in northwestern New Brunswick, Canada, and one of its sub-watersheds. Results indicate that annual loading estimation errors increased with decreasing sampling frequency for all water quality parameters. At the same sampling frequencies, the estimation errors were several times greater for the smaller watershed than those for the larger watershed, possibly due to the flushing nature of streamflows in the smaller watershed. We also found that low sampling frequency tended to underestimate the annual loadings of water quality parameters dominated by stormflow events (SS and K) and overestimate water quality parameters dominated by baseflow (Mg and Ca). These results can be used by hydrologists and water quality managers to determine sampling frequencies that minimize costs while providing acceptable estimation errors. This study also demonstrates a novel approach to assess potential errors when analyzing existing water quality data.

Study on Tieling City's water environmental carrying capacity

2015 ◽  
Vol 16 (1) ◽  
pp. 52-60 ◽  
Author(s):  
Limin Hou ◽  
Qiang Yue ◽  
Xiangzheng Hu ◽  
Tong Wang ◽  
Liusuo Wang ◽  
...  
Keyword(s):  
Water Quality ◽  
Economic Development ◽  
Carrying Capacity ◽  
Oxygen Demand ◽  
Quality Data ◽  
Quality Model ◽  
Water Quality Data ◽  
Environmental Carrying Capacity ◽  
Definition Of ◽  
Water Environmental Carrying Capacity

The water environmental carrying capacity (WECC) of a city can demonstrate a balance between the level of exploitation of the local water resources and the population growth and concomitant socio-economic development. To begin with, the definition of WECC was elaborated. Combined with hydraulic, hydrologic and water quality data, a one-dimensional water quality model was subsequently applied to simulate the water pollutants (chemical oxygen demand (COD)) in Tieling City. Then, a multi-objective model was applied to explore WECC. Economy, demography, and contaminant were selected as goals, taking into account the constraints of macroeconomic aggregates, water supply, water quality, and population. The results showed WECC could nearly carry all planned gross domestic product (GDP), population in the planning years 2015, 2020, and 2025 with the maximum COD of 30,681.7 t, but not for the condition of maximum COD of 15,709.0 t. That is, COD overload would occur if GDP and population develop as planned. Some measures must be taken to improve WECC in Tieling City, which are valuable for supporting the adjustment and planning for social-economic development.

scholarly journals Investigation of the Soan River Water Quality Using Multivariate Statistical Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Zakaullah ◽  
Naeem Ejaz
Keyword(s):  
Water Quality ◽  
River Water ◽  
Water Quality Management ◽  
Oxygen Demand ◽  
River Water Quality ◽  
Quality Data ◽  
Spatiotemporal Pattern ◽  
Multivariate Statistical ◽  
Water Quality Data

Evaluating the quality of river water is a critical process due to pollution and variations of natural or anthropogenic origin. For the Soan River (Pakistan), seven sampling sites were selected in the urban area of Rawalpindi/Islamabad, and 18 major chemical parameters were examined over two seasons, i.e., premonsoon and postmonsoon 2019. Multivariate statistical approaches such as the Spearman correlation coefficient, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the water quality of the Soan River based on temporal and spatial patterns. Analytical results obtained by PCA show that 92.46% of the total variation in the premonsoon season and 93.11% in the postmonsoon season were observed by only two loading factors in both seasons. The PCA and CA made it possible to extract and recognize the origins of the factors responsible for water quality variations during the year 2019. The sampling stations were grouped into specific clusters on the basis of the spatiotemporal pattern of water quality data. The parameters dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), turbidity, and total suspended solids (TSS) are among the prominent contributing variations in water quality, indicating that the water quality of the Soan River deteriorates gradually as it passes through the urban areas, receiving domestic and industrial wastewater from the outfalls. This study indicates that the adopted methodology can be utilized effectively for effective river water quality management.

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