Average Monthly Water Research Articles

Temporal variabilities and correlation of runoff in the Ural River

The article deals with the study of intra-annual discharge distribution of the Ural River basin runoff. Norms, coefficients of variation, and average standard deviations of monthly, seasonal and annual runoff, as well as maximum and minimum flow and the tendencies of its changes, were determined for rivers in the area. The average and maximum water discharge spring high water and the ratio of maximum and minimum monthly and the annual runoff were calculated. Based on the wavelet transform method applied to the river flow data of the area under study, a cyclical pattern of water availability was identified. Moreover, the closeness of the correlation between average monthly expenditures and annual average water consumption, as well as the average monthly water costs was revealed. The statistical significance of the detected correlations was defined.

A Hybrid Seasonal Box Jenkins-ANN Approach for Water Level Forecasting in Thailand

Every year, many basins in Thailand face the perennial droughts and floods that lead to the great impact on agricultural segments. In order to reduce the impact, water management would be applied to the critical basin, for instance, Yom River basin. An importing task of management is quantitative prediction of water that is stated by water level. This study proposes the hybridized forecasting models between the stochastic approaches, seasonal autoregressive integrated moving average (SARIMA) models and machine learning approach, artificial neural network (ANN). The proposed hybrid model is called seasonal autoregressive integrated moving average and artificial neural network or SARIMANN model for average monthly water level (AMWL) time series of Yom River basin. The study period is from April 2007 to March 2020, over thirteen hydrological years. The forecasting performance is the minimum values of root mean squared error (RMSE) and mean absolute percentage error (MAPE) between SARIMA models, ANN models, and SARIMANN models. Results indicated that: The three models reveal the similarity of RMSE and MAPE for both four water level measurement stations for wet and dry seasons. The forecasting performance is the minimum values of RMSE and MAPE of three models. The SARIMA model is the best approach for Y.31 Station [Wet Season], Y.20 Station [Wet Season], Y.37 Station [Wet Season], Y.31 Station [Dry Season], Y.20 Station [Dry Season], and Y.1C Station [Dry Season, while the best method for Y.37 Station [Dry Season] is ANN model, furthermore the SARIMANN model is the best approach for Y.1C Station [Wet Season]. All methods have delivered the similar results in dry season, while both SARIMA and SARIMANN are better than ANN in wet season by RMSE for all stations. Even though the downstream is affected by many disturbances, it is still more accurate than the upstream. This is the visible evidence to indicate that the stochastic based models, SARIMA and SARIMANN proposed in this study are appropriate for the high fluctuation series. Furthermore, the dry season forecasting is more accurate than the wet season.

The Impact of the Uncertain Input Data of Multi-Purpose Reservoir Volumes under Hydrological Extremes

The topic of uncertainties in water management tasks is a very extensive and highly discussed one. It is generally based on the theory that uncertainties comprise epistemic uncertainty and aleatoric uncertainty. This work deals with the comprehensive determination of the functional water volumes of a reservoir during extreme hydrological events under conditions of aleatoric uncertainty described as input data uncertainties. In this case, the input data uncertainties were constructed using the Monte Carlo method and applied to the data employed in the water management solution of the reservoir: (i) average monthly water inflows, (ii) hydrographs, (iii) bathygraphic curves and (iv) water losses by evaporation and dam seepage. To determine the storage volume of the reservoir, a simulation-optimization model of the reservoir was developed, which uses the balance equation of the reservoir to determine its optimal storage volume. For the second hydrological extreme, a simulation model for the transformation of flood discharges was developed, which works on the principle of the first order of the reservoir differential equation. By linking the two models, it is possible to comprehensively determine the functional volumes of the reservoir in terms of input data uncertainties. The practical application of the models was applied to a case study of the Vír reservoir in the Czech Republic, which fulfils the purpose of water storage and flood protection. The obtained results were analyzed in detail to verify whether the reservoir is sufficiently resistant to current hydrological extremes and also to suggest a redistribution of functional volumes of the reservoir under conditions of measurement uncertainty.

Factors influencing water consumption in public schools in Southern Brazil

The purpose of this research is to identify factors influencing water consumption in schools in the city of Joinville, Southern Brazil, in order to understand and monitor water consumption. Twenty-six (26) public elementary, middle, and high schools in the state public educational system were selected for this research study. Data were collected on water usage, through in situ water-related measurements and through questionnaires answered by the principals from each school. The collected data made it possible to characterize the schools and perform a preliminary diagnosis of water usage. Descriptive analysis of water consumption and per capita water consumption was performed. Average monthly water consumption was 111.45 m3/school/month, and the average per capita water consumption was 8.833 L/student/day. Multiple linear regression analysis was employed to forecast schools’ monthly water consumption. Correlation analysis and the stepwise method were used to choose the variables, and the results showed that the significant variables for monthly water consumption were the number of students and the number of toilets in use. These results contribute to understanding factors influencing the water consumption at schools, as there have been few studies performed regarding the subject on this typology of buildings. In addition, the results can be used to forecast and monitor consumption, contributing to water saving in the school environment.

Hydrological-stenobiontic method for determining environmental flows from reservoir

In the practice of using river resources accumulated in reservoirs, there is a typical problem of unreasonably large water intake for industrial-household needs to the detriment of the aquatic ecosystem. An important tool for balancing these links is to provide environmental flows based on a comprehensive analysis of river functioning patterns. And in terms of a progressing negative impact of reservoirs on the integrity of river ecosystems, the choice of indicator hydrobiota for the calculation of environmental flows should be considered insufficiently substantiated. The solution of this problem, by filling the appropriate methodological niche, allowed substantiating the hydrological-stenobiontic method for determining environmental flows. The developed solutions are based on the minimum possible values of tolerance of aquatic ecosystems stenobionts to water velocity. Five groups of macrozoobenthos represent relevant target organisms. The hydrological calculations presented in the paper are based on the data of daily water flow rate for 80 years and the results of field studies of the river channel depth in the low water period. On this basis, it was determined that for lowland parts of rivers, the flow velocity in the tailwater of reservoirs should be at least 0.2 m/s. Comparison of the curve of the average monthly water velocity dynamics of 95 % runoff availability with the minimum corresponding requirements of stenobionts allowed determining the most threatening period of the year for the aquatic ecosystem – summer low water. For a reservoir in the lowland parts of the river, based on the developed method, the calculations substantiate an increase in the minimum volume of environmental flows by 40 % relative to the current one. It is also estimated that the average annual and average second volumes of environmental flows should be about 38 % of the respective river runoff. The obtained results are close to those found on rivers in China, Iran and the United States in the framework of a comprehensive analysis of hydrological, hydraulic and hydrobiological parameters of the aquatic ecosystem

High performance approach for water level forecasting in Yom River basin of Thailand

Analyses of average monthly water level (AMWL) time series (April 2007 - March 2020) at four water level measurement stations (Y.31, Y.20, Y.1C, Y.37) for wet and dry seasons in the Yom River basin of Thailand. Using Box-Jenkins method, eight best-fit seasonal ARIMA models for one hydrological year forecasting for wet and dry seasons of AMWL were selected; among from twenty-four possible models, by minimum values of AIC, SBIC RMSE, and MAPE. Besides, The comparisons with two benchmark models, Holt-Winters’ Seasonal additive method, and Seasonal Naive method were applied. Results indicated that: The four selected SARIMA models for wet seasons of Y.31, Y20, Y1C, and Y.37 are SARIMA(1,1,1)(1,0,0)[6], SARIMA(1,1,1)(1,0,0)[6], SARIMA(1,1,2)(1,0,0)[6], and SARIMA(1,1,1)(1,0,0)[6], respectively. While the models for dry seasons are SARIMA(0,1,1)(2,0,0)[6], SARIMA(1,1,1)(1,0,1)[6], SARIMA(1,1,1)(2,0,0)[6], and SARIMA(1,0,0)(1,0,1)[6]. The forecasting performance are the minimum values of RMSE and MAPE between SARIMA and the benchmark models. The SARIMA model is the best approach for Y.31 Station [Wet Season], Y.31 Station [Dry Season], and Y.37 Station [Dry Season], while the best method for Y.20 Station [Wet Season], Y.1C Station [Wet Season], Y.37 Station [Wet Season], Y.20 Station [Dry Season], and Y.1C Station [Dry Season] is Holt-Winters’ seasonal additive method. The upstream station (Y.31 station) has higher accuracy than the downstream station (Y.37 station) due to human activities that disturb hydrological changes. Furthermore, the dry season forecasting is more accurate than the wet season.

Customer Satisfaction and the Willingness to Pay for Cleaner Water to Sustain Clean Water Supply in Bengkulu City, Indonesia

Clean water is a basic human need. One of the drinking water supply systems is held by a regional drinking water company. Business profits of regional drinking water companies are crucial things that allow companies to continue to exist in business and expanding the service to supply clean water to the wider community. Ensuring availability and sustainable provision of clean water is important since it has been targeted in Goal 6 of Sustainable Development Goals. The existence and continuity of business activities are very inseparable from service quality and customer satisfaction. Therefore, customer satisfaction and willingness to pay for clean water supply are essential factors for the company's continuity and the sustainable management of clean water for the community. The study aimed to determine the level of customer satisfaction for the provision of clean water and to uncover the factors affecting the community's willingness to pay to improve clean water delivered. The method for getting customer satisfaction index used Structural Equation Modelling and indexing. Contingent valuation method and logistic regression were employed for analyzing willingness to pay and uncover the factors affecting it. The results showed that the overall customer satisfaction level was moderately satisfied with a Customer Satisfaction Index of 66 with priority improvements to increase customer satisfaction, especially on attributes of turbidity conditions of water, water quality assurance, and water price level. The result indicated that fifty-six percent of the respondents are willing to pay for cleaner water. The only factor influencing the willingness to pay for the cleaner water supplied is the average monthly water bill

An efficiency dynamic seasonal regression forecasting technique for high variation of water level in Yom River Basin of Thailand

<abstract> The Yom River Basin is one of 25 river basins in Thailand. The Yom River Basin experiences perennial droughts and floods that heavily impact the agricultural sector. In order to reduce the impact, water management, including water level estimation, must be applied to critical basins like the Yom River Basin. An important task of management is the quantitative prediction of water levels. Four different modeling approaches were applied to forecast the average monthly water level (AMWL) data from four water level measurement stations for the wet season (May–October) and dry season (November–April) from 2007 to 2020. The forecast patterns obtained from the four approaches were similar to the observed historical values, except the upstream in wet season and downstream in dry season. Furthermore, the artificial neural network (ANN) approach overestimated forecasts for almost every station in both seasons. All four approaches were more accurate in the dry season than the wet season. This study proposed a forecasting method called dynamic seasonal regression (DSR), which was obtained by combining multiple linear regression (MLR) and the autoregressive integrated moving average (ARIMA) model of the random error from MLR. DSR was more efficient than ANN, seasonal-ARIMA (SARIMA) and a hybridized SARIMA and ANN approach (SARIMANN). On average, for all stations in wet and dry seasons, DSR reduced RMSE by over 40.86%, 9.10% and 23.07% with respect to ANN, SARIMA and SARIMANN, and MAPE by over 35.01%, 13.02% and 15.96% with respect to ANN, SARIMA and SARIMANN. The RMSE of upstream was higher than the RMSE downstream in the wet season for all methods, and the MAPE of upstream was lower than the downstream in both seasons for all methods. Moreover, the RMSE of upstream was lower than the downstream in the dry season for all methods except the ANN method. </abstract>

ДОСЛІДЖЕННЯ ДЕФІЦИТІВ ВОДНОСТІ ТА ІНДЕКСІВ ПОСУХИ ДЛЯ ЗОНИ НЕДОСТАТНЬОЇ ВОДНОСТІ УКРАЇНИ

The study of the formation of water deficits on rivers in the zone of the insufficient water content of Ukraine is presented in the article. To determine the deficits, the “threshold” method was used, which involves comparing the daily water discharges in the low water period with the values of the minimum runoff of a given probability of exceeding. Long-term data of average daily and average monthly minimum water discharges during the winter and summer-autumn period on rivers located in different areas of river basins and significantly differing in the catchment area, namely the Southern Bug River – Oleksandrivka (A = 46200 km2), Kinska River – Pologi (A = 353 km2), Obitichna River – Primorsk (A = 1300 km2) for the observation period from 1953 to 2018 inclusive was used. In cases where runoff values ​​were less than Q90% or Q97%, they were considered deficient (90%) or extremely deficient (97%). The dynamics of deficits in time are analyzed, and the number of such events by decades, frequency, average volume, duration, and intensity are determined. The chronological course of runoff volumes and deficits (90%) is graphically presented. Analyzing the obtained diagrams, it can be noted that naturally, the largest water deficit was observed in low-water years (below normal), and accordingly, the lack of deficit is characteristic of multi-water periods (above normal). Additionally, extreme deficits were also estimated (97%) for the Southern Bug River – Oleksandrivka township. The study also presents the results of the calculation of various drought indices. For the rivers of the study area, using the DrinC drought calculator were calculated – the river runoff drought index (SDI), standardized precipitation index (SPI), agricultural standardized precipitation index (aSPI), drought research index (RDI), effective drought research index (eRDI) , and its relationship with water discharges during the summer-autumn period was analyzed. Long-term data of average monthly water discharges at 6 hydrological gauge (Kodyma river – Katerynka river, Ingul river – Novogorozhene river, Ingul river – Sednivka village, Kinska river – Polohy town, Kilchen river- Oleksandrivka Persha village, Kalchyk river – Kremenivka village) were used as initial information and as also average monthly air temperature and monthly precipitation at 6 meteorological stations (Odessa, Kherson, Kropyvnytskyi, Zaporizhia, Dnipro, and Mariupol). Analyzing the obtained results, it can be noted that drought indices provide an opportunity to study climatic and hydrological trends, characterize drought, assess the severity of drought, and promote early assessment of the effects of drought. In particular, the SDI index correlates well with water discharges, which opens up opportunities for forecasting runoff in the dry period.

High performance approach for water level forecasting in Yom River basin of Thailand

Analyses of average monthly water level (AMWL) time series (April 2007 - March 2020) at four water level measurement stations (Y.31, Y.20, Y.1C, Y.37) for wet and dry seasons in the Yom River basin of Thailand. Using Box-Jenkins method, eight best-fit seasonal ARIMA models for one hydrological year forecasting for wet and dry seasons of AMWL were selected; among from twenty-four possible models, by minimum values of AIC, SBIC RMSE, and MAPE. Besides, The comparisons with two benchmark models, Holt-Winters’ Seasonal additive method, and Seasonal Naïve method were applied. Results indicated that: The four selected SARIMA models for wet seasons of Y.31, Y20, Y1C, and Y.37 are SARIMA(1,1,1)(1,0,0)[6], SARIMA(1,1,1)(1,0,0)[6], SARIMA(1,1,2)(1,0,0)[6], and SARIMA(1,1,1)(1,0,0)[6], respectively. While the models for dry seasons are SARIMA(0,1,1)(2,0,0)[6], SARIMA(1,1,1)(1,0,1)[6], SARIMA(1,1,1)(2,0,0)[6], and SARIMA(1,0,0)(1,0,1)[6]. The forecasting performance are the minimum values of RMSE and MAPE between SARIMA and the benchmark models. The SARIMA model is the best approach for Y.31 Station [Wet Season], Y.31 Station [Dry Season], and Y.37 Station [Dry Season], while the best method for Y.20 Station [Wet Season], Y.1C Station [Wet Season], Y.37 Station [Wet Season], Y.20 Station [Dry Season], and Y.1C Station [Dry Season] is Holt-Winters’ seasonal additive method. The upstream station (Y.31 station) has higher accuracy than the downstream station (Y.37 station) due to human activities that disturb hydrological changes. Furthermore, the dry season forecasting is more accurate than the wet season.

Сток рек Ленского бассейна на территории Забайкальского края и его связь с атмосферными осадками

The objective of the article is assessment of many-year changes of the Lena River basin rivers’ runoff on the territory of Trans-Baikal Kray and its correlation with atmospheric precipitation as a leading factor of the water flow formation. Studying of the rivers’ water regime and determination of their water content cycles is especially relevant in view of extreme climate changes over the past decades and the necessity to elaborate a strategy of sustainable social/economic development of regions in contemporary conditions. However, the Lena River basin hydrological characteristics within the boundaries of Trans-Baikal Kray have been studied insufficiently. Methods. The analysis was carried out according to the data on the average monthly water consumption over the period from 1976 to 2018. To analyze the current climatic conditions we have used air temperature and atmospheric precipitation observation data from six meteorological stations. When used Pearson correlation analysis we have revealed correlation between the runoff at the posts under study and its within-year dynamics, as well as have calculated the connection with atmospheric precipitation. We have revealed many-year tendencies of the water flow by calculation and analysis of linear trends computed by the least-squares method and by plotting differential integral curves. Results. More than 80 % of river runoff is formed during the spring-summer period, at that the total winter (December-March) runoff on the average is less than 2 % of the annual runoff. In the studied sections of large rivers (Chara, Olekma), the average annual water discharge varies from 3.20 to 54.5 m3/s, small (Karenga, Bugarikhta, Kuanda) – from 10.2 m3/s up to 47.3 m3/s. The greatest consistency of water discharges is noted for the spring (April-June) and summer (July-September) hydrological seasons, since it is due to the distribution of atmospheric precipitation during the year, with which their significant correlation was revealed. During the study period, the full cycle in the sections of the studied rivers was not traced, which most likely indicates its longer duration relative to other rivers of the Trans-Baikal Kray. At present, we observe the high-water phase of the hydrological cycle.

SIMULATION OF THE AUTUMN-WINTER RUNOFF OF THE ANADYR RIVER

. Runoff during the autumn-winter low-water period is of great importance in the life of river ecosystems. In this work, the goal is to construct a mathematical model of the curves of daily water discharge during the autumn-winter low-water period (September-April) on the Anadyr River near the village Snezhny (catchment area 106 000 km2 ). Anadyr River is the largest waterway of the Chukotka. The river is used by public utilities, river transport in summer and road transport in winter. Pacific salmon spawn in this river every year. The conditions for the survival of salmon eggs in winter are influenced by the water content of the rivers. The basin under consideration is located in a zone of subarctic climate and continuous permafrost. Therefore, the autumn-winter low-water period on the Anadyr River lasts from September to April during this period, 4–6 % of the annual runoff occurs. Based on the average annual monthly water discharges for September-April, the averaged runoff depletion curve was calculated in relative ordinates, which is approximated by an exponential function. Based on this curve, you can predict daily water discharges from September 15th to April 15th of the following year. Verification calculations for the years of winters with different water content showed that the mathematical model works satisfactorily. Based on the data on the runoff of other hydrological stations in the Anadyr catchment, the study can be continued to derive a basin formula, which can be used to predict the daily water discharges of the autumn-winter low-water period on any unexplored river.

Baseline Water Temperature: Estimation of the Annual Cycle of Surface Water Temperature in Lakes in North-Central Poland over the 1951–1968 Period

Water temperature is an important ecological variable that affects the functioning of lakes. Unfortunately, for many lakes there are no long-term observations enabling the assessment of changes in water temperatures. This makes it difficult to include this aspect in research into the biology, ecology and chemistry of such lakes. This paper presents a literature review related to changes of surface water temperatures in lakes and in particular describing the response of water temperatures and stratification to changing climate in Polish lakes. On this basis, a model based on the available data on water temperature in 931 Polish lakes in the years 1951–1968 was proposed, which allows to estimate the baseline water temperature on any day of the year. This model is calculated using the complementary error peak function on the 0–3 m water temperature dataset, which provides the best reduction of diurnal temperature fluctuations. It can be an alternative to the average temperature of surface waters, which are calculated on the basis of systematically collected data. Based on the average water temperature data obtained from 56 thermal profiles in 10 lakes in 2010–2019, the equation was analogically calculated. The average monthly water temperatures in June, July, August and September and the change in water temperature (0.24–0.30 °C decade−1) in the period 1951–1968/2010–2019 were estimated then. Similar regional or single lake trends have been found in studies by other authors covering a similar or longer period of time. The proposed method, which is suitable for simulating temperatures, especially in summer, enables the determination of the value of changes in surface water temperature in Polish lakes when only thermal profiles data from different dates are available, which can be especially helpful when analyzing hydrobiological results.

მდინარის ჩამონადენის განსაზღვრა ჰიდროლოგიური მონაცემების დეფიციტის პირობებში მდ. მტკვრის ჰესების კასკადის მაგალითზე

The article discusses a method for determining water discharge at intake points under the conditions of lack of hydrological data. As an example is given the calculation of the river flow at intake points of the hydroelectric power chain cascade on the river Mtkvari (Chitakhevi HPP, ZAHPP, Ortachala HPP). The data taken from the hydrological stations of ,,Likani,, and „Tbilisi“ are multiplied by the adaptation coefficient, which is obtained by dividing catchment areas of Chitakhevi HPP ZAHPP and Ortachala HPP. The method allows to receive continuous average monthly and annual water discharge at the intake points of Chitakhevi HPP, ZAHPP, Ortachala HPP, instead of incomplete hydrological data. Additionally, the impact of Zhinvali reservoir is taken into account in the calculation of river flow at intake points of the ZAHPP and Ortachala HPP. Also its effect on natural water inflow of river Mtkvari is established. The calculation results show that since of the operation of Zhinvali HPP the average annual water inflow of the river Mtkvari is decreased by 10% at the intake points of the ZAHPP and Ortachala HPP. Using the calculation results it is possible to determine the river flow for existing and planned HPPs on the section of Chitakhevi-Ortachala. The method also helps to determine the design parameters of these HPPs more accurately that is important for effective and safe operation of HPPs on the river Mtkvari during different levels of water flow.

Variability of hydrometeorological situation during fish kill events in the summer seasons of 2010–2018 in the Sea of Azov

Hydrometeorological situations during the fish kill events that took place in the Belosaray, Obitochny and Kazantip Bays in the summer seasons of 2010–2018 have been analyzed. Average monthly background water and air temperatures and wind velocity are considered, as well as their average daily values before, during and after a fish kill event. It is shown that background characteristics of water temperature and wind velocity influenced the development of a fish kill event more directly and definitely than air temperature, which influence was only indirect. In the majority of cases, hydrometeorological situation, leading to fish kill event, developed according to the typical pattern with increasing air and water temperature and decreasing wind activity. In the northern bays, the Belosaray and Obitochny Bays, fish kill events were recorded during the first half of summer season, and in the southern bay, the Kazantip Bay, they occurred in the second half of it. Since 2012, due to significant decrease in vertical thermohaline stability and increase in water homogeneity, no significant fish kill events were recorded under various temperature and wind conditions. Satellite imaging of sea surface temperature confirmed typical course of fish kill event development: the temperature increased in the pre-event period and then, after the event, stayed high in the southern bays and decreased in the northern ones.

Deducing the digital evaporation loss model of high dam reservoir

Evaporation is the most negative phenomenon, causing huge losses in the water capacities of reservoirs. For example, evaporation at the High Dam (HD) reservoir (the water resources bank of Egypt that supplies Egypt with about 97% of its freshwater needs) which is characterized by its large water surface area (about 6000 km2 at water level 178 A.M.S.L). This reservoir, due its geographical location, is exposed to a range of climatic factors which increase evaporation rate annually, and consequently, increase the total loss of its capacity (about 10 Billion m3 of the HD reservoir capacity is lost annually due to evaporation phenomenon). Many organizations rely on an evaporation chart that gives the value of evaporation loss according to some climate variables. With respect to the problem of malfunctions of some stations, or in case of lack of data for any reason, it is important to have a digital evaporation loss model that gives the missed evaporation loss in the High Dam reservoir directly, according to two factors; the given month and the average monthly water level. This paper will explain how to get benefit from the available data of hydro-meteorological stations distributed within the High Dam reservoir, to predict the digital evaporation loss surface using the GIS prediction and conversion tools.

Opisthorchis felineus as the basis for the reconstruction of migrations using archaeoparasitological materials

This article shows the potential of reconstruction of human migrations based on archaeoparasitological data. On the example of the territory of Western Siberia and based on the characteristics of the biology and ecology of the intermediate hosts of Opisthorchis felineus, it was determined, if we want to reconstruct migrations related to the territory of Siberia in antiquity, we can be fairly confident in using only natural factors. They are independent of anthropogenic influence and determine favorable or unfavorable conditions for the functioning of the focus of Opisthorchis felineus. In particular, the occurrence of mollusks as intermediate hosts, the average monthly water temperature in summer, and the occurrence of permafrost can be considered as the main factors that can be used to reconstruct human migrations in antiquity.Collectively, our findings suggest that the presence or absence of Opisthorchis felineus eggs in the samples gathered at Western Siberian archaeological sites can be a basis for the reconstruction of migrations in earlier times. This approach can be applied to other foci of Opisthorchis felineus situated in the European part of Eurasia and of territories endemic for other Opisthorchidae (Clonorchis sinensis, Opisthorchis viverrini) situated in of Eurasia. This likelihood is contingent on accumulating more biological materials, such as mapping zones, with or without intermediate hosts; the occurrence of infection of the final hosts; environmental and climatic conditions; and, even more important, archaeoparasitological data.

İçme Suyu Olarak Belediye Şebeke Suyunun Tüketici Tercihlerindeki Yerinin Belirlenmesi: Iğdır İli Örneği

Bu çalışmada Iğdır ilinde hanehalkının en uygun içme suyu tipini tespit etmek amaçlanmıştır. Bu amacı gerçekleştirmek için Iğdır ili Merkez ilçede yaşayan 17-75 yaş aralığında 400 bireyle yüz-yüze görüşme yapılmıştır. Çalışmada tüketici ve ailesine yönelik sosyo- ekonomik ve demografik sorular ile içme ve kullanma suyu tüketimine yönelik sorular sorulmuştur. Anket sayısının belirlenmesinde ana kitle oranlarına dayalı basit tesadüfi örnekleme yöntemi ile en uygun içme suyu tipinin belirlenmesinde Analitik Hiyerarşi Süreci (AHS) yöntemi kullanılmıştır. Çalışma sonuçlarına göre içme suyu olarak hanelerin %38’i şişe suyunu, %35’i arıtma cihazlı şebeke suyunu, %13’ü mahalle çeşmesi veya kaynak suyunu, %13’ü arıtma cihazı olmadan belediye şebeke suyunu, %1'i de arıtma cihazlı kaynak suyunu kullandığı belirlenmiştir. Hanehalkı için aylık ortalama su faturası 40.14 TL ve şişe su harcaması 86.42 TL’dir. Günlük kişi başına içilen su miktarı 2.27 L olup 1.03 L’si şişe sudur. Hanehalkının %32.36’sı şişe suyu, %27.56’sı arıtılmış suyu, %21.27’si çeşme ve kuyu gibi kaynak sularını ve %18.80 ise belediye şebeke suyunu fiyat, hijyen, mineral, tat ve ulaşım kriterlerine göre tercih ettikleri tespit edilmiştir. Bu çalışmanın sonuçlarının Iğdır iline içme ve kullanma suyu arz eden belediye yetkililerine ve içme suyu sağlayan arıtma cihazı ve şişe su pazarlayan firmalara yol göstereceği düşünülmektedir.

Simulation of Transmission of Drinking Water Sources to Reservoirs: Case Study PDAM Tirta Jati, Cirebon, Indonesia

Population dynamics have very important effects on ecosystems, including those related to water availability. The availability of clean water is closely related to the condition of the population in an area. Every human being must drink 8 (eight) glasses of water per day. Plants and animals also need water. So it can be said that water is one source of life. Regional Water Supply Company (PDAM) is a company whose ownership is held by the regional head as the operator of drinking water supply for the community. Companies are encouraged to utilize developing technology to manage their drinking water assets effectively and efficiently so they can improve services to the community. EPANET 2.0 is one tool that is suitable for connecting piping network models. Quantum Geographic Information System (QGIS) is a model simulating hydraulics which parameters can be launched through a processing stage. The master network system model created in QGIS was included in EPANET 2.0 for rasterization. Then enter the required data such as pipe length, height of each node, water flow per tapping, pipe roughness coefficient, and peak hour factor. The results of the analysis in the form of pipe hydraulics, such as pipe speed and pressure from each node are used as a basis for network development plans. The ratio of the total population per family in Sumber District in 2018 is 6 people/head of the family. The population in the administrative area served by PDAM is 22,560 people. Domestic water needs can be calculated based on data on average water usage per month recorded at PDAM Tirta Jati, Cirebon Regency. The number of domestic customers was 2,446 in August 2019 with an average monthly water consumption of 15.02 m3/unit. Based on analysis using Epanet and QGIS, parameter data for pipe flow rates are 0.63 - 1.05 meters/second. While the result for water pressure in the pipe is 140.95 meters at node 274.

The hydrological and water level data in Yom River basin of Thailand

Yom River basin located in Northern Thailand, faces perennial droughts and floods with great impact on agriculture and the economy in the surrounding landscape. Therefore, the purpose of the present study is to study the hydrological nature of the Yom River basin, by descriptive statistics analysis using daily water level data from four water level measurement stations, from April 1, 2007, to March 31, 2020. The lower part of Mae Nam Yom river is almost half of the Yom River basin area. The water allocation plan in 2019-2020 for six reservoirs suggests usable water of 116.5 million m 3 , with the water allocated at the beginning of the rainy season more than during the dry season. During the dry season most of the water was allocated for agriculture. In most areas of Yom River basin, there are droughts and floods happened not more than 3 times in the last 10 year. The daily water level data of all four water level measurement stations showed relatively clear seasonal variations. The daily water level peaked every hydrological year during the rainy season. The average annual water level was the highest in 2011 (258.92 ± 1.09, 183.26 ± 1.64, 145.56 ± 1.89, and 96.20 ± 2.17 m(MSL)), and the lowest in 2015, except at the Y.1C station in 2019 (258.01 ± 0.49, 182.10 ± 0.61, 144.01 ± 1.24, and 94.50 ± 0.56, m(MSL)). The average monthly water level started to rise since May, with its highest peak value is in September (259.67 ± 0.86, 184.27 ± 1.14, 146.21 ± 1.39, and 97.09 ± 1.57 m(MSL)). The average monthly water level is low from December to April (dry season), the lowest values are from February to March (257.82 ± 0.19, 181.65 ± 0.12, 143.91 ± 0.32, and 94.31 ± 0.20, m(MSL)).