Annual Load Research Articles

Effects of cascading reservoirs on streamflow and sediment load with machine learning reconstructed time series in the upper Yellow River basin

Large reservoirs are widely built along rivers for flood control, hydropower generation, water supply for industry and agricultural production, and recreation. Many large reservoirs/dams built to provide multiple functions for local people are strongly influenced by the downstream flow and sediment discharge in the upstream of the Yellow River, China. In this study, we assessed the changes in the river flow and sediment discharge in responses to the construction of cascade reservoirs/dams by using continuously hydrological time series observed at six stations during 1956–2018. The temporal change in the streamflow was insignificant, but the sediment load decreased dramatically due to the trapping effects of the cascade reservoirs. The change points were detected in 1969 and 1986, which were consistent with the timing of the construction of gigantic reservoirs. We then applied the abrupt changing points to divide the whole time series into a reference period (1956–1968) and two changing periods (1969–1986 and 1987–2018). The linear regression and three machine learning models were employed to reconstruct the natural streamflow and sediment load at the downstream station, before quantifying their responses to cascade reservoirs. The annual mean streamflow and sediment load decreased by 21% and 84%, respectively, after constructing the Longyangxia and Liujiaxia reservoirs. Cascade reservoirs contributed 85.39% and 94.91% to the decreases in the streamflow and sediment discharge, respectively. Hydrological regimes have been greatly altered by the 13 cascade reservoirs, with seasonal redistribution of the streamflow and flood peak reduction because their high trapping efficiencies exceed 95%. These findings indicate that large and medium sized reservoirs have drastically altered the streamflow and sediment load, thereby intensely influencing the fluvial processes in the upstream of the Yellow River.

The effect of aboveground biomass harvesting on nutrients removal in a constructed wetland treating municipal sewage

The study was performed at the constructed wetland treating municipal sewage from 200 population equivalent. The aim of the study was to evaluate the role of Phalaris arundinacea and Phragmites australis harvesting on nutrient removal. The highest phosphorus concentrations in leaves were found in the re-grown P. arundinacea in October (3.12 m g−1), followed by those in June (2.68 mg g−1) and July (2.67 mg g−1). Phosphorus concentrations in P. australis leaves were higher in July (2.14 mg g−1) than in September (1.79 m g−1). Phosphorus concentrations in stems were lower and varied between 1.07 mg g−1 in P. australis in September and 2.21 mg g−1 in P. arundinacea regrowth in October. Nitrogen leaf concentrations varied between 21.0 mg g−1 in P. arundinacea in June and 33.7 mg g−1 in P. arundinacea regrowth in October. In stems, the highest concentration was observed in P. australis in July (18.6 mg g−1) while the lowest N concentration was measured in July in P. arundinacea (3.8 mg g−1). The results showed that there was no difference between nutrients standing stock in a single harvested of P. arundinacea as compared to double harvested biomass. There was a significant higher biomass and consequently higher standing stock in P. arundinacea in the inflow zone as compared to outflow zone. Biomass and nutrients standing stocks in P. australis were significantly higher than that in P. arundinacea. The phosphorus sequestered in the aboveground biomass represented 6.3% of the inflow P load and phosphorus in the harvested biomass represented 44% of removed P load. For nitrogen, the respective values represented 14% and 41.6%. The data indicate that to remove 20% of the inflow annual load via biomass cutting, the inflow load should not exceed 20 g P m−2 yr−1 and 300 g N m−2 yr−1.

Economic analysis of annual load loss due to voltage sags in industrial distribution networks with distributed PVs

In an industry, analysis of load disconnection indices is essential to determine the annual economic loss because of the high cost of load interruptions. With the interconnection of PVs in modern industrial networks, this analysis gets more complicated due to controls associated with PV inverters for reactive power support. Hence, the paper proposes a unique method for such analysis that relies on dynamic simulation to calculate load disconnections. The dynamic simulation allows the integration of the voltage tolerance curve of loads and controls associated with PVs making the scenarios more realistic. The indices are determined by employing statistical experiments which account for annual variability of daily solar and load profiles with the least possible runs of dynamic simulation. The proposed method is applied to calculate load disconnection indices for an IEEE 399-1997 industrial distribution system. A comparative analysis of the cost of disconnection under a variety of solar penetration and operation scenarios is presented. Network planners and reliability engineers can potentially utilize the proposed method to identify PV inverter controls, placement, and size effects on the annual load disconnection indices due to voltage sags.

Multi-objective optimization of latent energy storage in buildings by using phase change materials with different melting temperatures

Technologies based on phase change materials (PCMs) are promising solutions to reduce energy consumption in buildings and related greenhouse gas emissions. However, the performance of passive PCMs in buildings is highly dependent on the melting temperatures employed, as well as the climate where the building is located. Therefore, the present contribution describes an optimization-based method to design passive latent energy storage in buildings by using PCMs with different melting temperatures. To achieve this goal, a multi-objective genetic algorithm is coupled with the building energy models developed in EnergyPlus to find the best trade-off between annual heating and cooling loads. A small office is chosen as a case study to evaluate the energy performance of the buildings incorporating the proposed PCM approach. Three different PCM layers are added to the ceilings and the external and internal walls of the building, and their parametric models are developed in EnergyPlus to optimize the melting temperature and thickness of each PCM layer simultaneously. Moreover, a method to select climate-representative locations according to the ASHRAE 169-2020 climate classification and within the WMO Region VI (Europe) is proposed and applied, resulting in eight well-representative locations. An optimization-based design is carried out for each selected location and the performances of the optimized building designs are systematically compared to the ones of the baseline models. The optimization results achieved show that regardless of the climate zone analyzed, using several PCMs with different melting temperatures instead of a single one, is preferred. Moreover, the best performance of PCMs is attained in climate zones where both the heating and cooling loads are present. Thus, the highest saving regarding the annual total loads of 11.7% is achieved in zone 5A (Cold), while the lowest one of 2.3% is obtained in zone 1B (Very hot).

Optimizing building surface retro-reflectivity to reduce energy load and CO2 emissions of an enclosed teaching building

Abstract Building surface reflectivity determines the amount of reflected solar radiation, which indirectly affects the cooling and heating load of a building. Therefore, optimizing building surface retro-reflectivity is an effective method to reduce energy load and CO2 emissions of buildings. To analyse the optimization potential of building surface retro-reflectivity, the effect of surface reflectivity on daily, monthly and yearly energy load, as well as CO2 emissions of an educational building were simulated based on the Energyplus software. The numerical results showed that for daily energy load in four typical seasons, there was a positive correlation between the daily energy load and building surface reflectivities in January, April and October and a negative correlation in July. For monthly energy load, the building cooling and heating loads were the highest in January and August, respectively. For annual energy load, the higher the reflectivity, the lower the cooling load and the higher the heating load. When the building surface reflectivity was 0.7, the annual energy load was the least, with a value of 148.23 kWh/m2. In addition, the CO2 emission was also the lowest, with a value of 24.79 kg/m2. According to the relation between building surface reflectivities and retro-reflectivities, the optimal retro-reflectivity was 0.47.

Optimizing Hybrid Power for Manpura Island: A Case Study in Bangladesh

In the remote and isolated island Manpura in southern Bangladesh, located within the Bhola district and surrounded by the Meghna River, most communities rely on farming and fishing for their livelihoods. Due to its isolation, the island is not connected to the mainland's electrical grid. In this study, a freestanding green hybrid energy system was proposed for the Manpura island using HOMER software to meet the electricity needs of its 17,016 households. The average load for the system is 9,149.87 kWh per day, with an annual peak load of 2,112.6 kW. The system would utilize PV panels, hydrokinetic energy, biogas, wind turbines, storage, and a converter, with a total Net Present Cost (NPC) of 23,796,260.00 and a Cost of Energy (COE) of $0.5515. This hybrid energy systems would provide a sustainable and cost-effective long-term power solution for the island while preserving its natural beauty.

Techno-Economic and Environmental Study of Optimum Hybrid Renewable Systems, including PV/Wind/Gen/Battery, with Various Components to Find the Best Renewable Combination for Ponorogo Regency, East Java, Indonesia

Nowadays, hybrid renewable systems can be the best solution for meeting electricity demand, especially where grid extension and environmental issues are important. This study aimed to find the best combination of the typical components used in East Java, Indonesia. In this regard, four types of photovoltaic (PV) panels, four types of wind turbines, and two types of batteries were selected, and the HOMER software simulated all possible combinations of the systems, including 32 scenarios (Sen). Then, considering the most important 15 parameters, such as pollutant emissions and economic values, the results were analyzed and sorted by the multicriteria decision-making (MCDM) method to find the best scenario for the case-study region. The results showed that SunPower E20-327 as PV, Eocycle EO10 10 kW as wind turbine, and Generic 1 kWh Li-Ion as the battery could be the best selection to design a hybrid renewable system for the case-study region since it can fulfill both economic and environmental needs. The cost of energy (COE) of the best-designed system and net present cost (NPC) are 0.24 ($/kWh) and 1.64 million $, respectively, where the renewable fraction (RF) is 55.1% and the scaled annual average load is 1126 kWh/day. The results of the sensitivity analysis on the best scenario’s parameters (where the capital cost of PV, battery, and wind turbine changes from 0.6 to 1.2, from 0.7 to 1.2, and from 0.7 to 1.4 of the current price, and diesel price from 0.5 to 1.1 ($/L)) showed that the RF, COE, and NPC values ranged between 51% to 93%, 0.2 to 0.3 ($/kWh), and 1.4 to 2.1 (million $), respectively.

Analysis of annual load variability in the Polish electric power system

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informujące swoich czytelników o najnowszych osiągnięciach naukowych i nowoczesnych rozwiązaniach technicznych w Polsce i na świecie, popularyzuje problemy techniczne oraz poszerza wiedzę i kulturę techniczną.

Multivariate Extreme Wind Loads: Copula-Based Analysis

A probabilistic approach is developed to estimate multivariate extreme wind loads by introducing copula theory. Three major concerns are addressed: (1) the characterization of pairwise dependence among extreme load coefficients, (2) the construction of a probability model of multivariate extreme load coefficients, and (3) the probabilistic estimation of multivariate extreme wind loads with randomness of the mean wind speed (i.e., wind climate change). Theoretical and numerical analyses are carried out with the aid of wind tunnel data. The results show that using rank dependence (Kendall’s tau and Spearman’s rho) is more appropriate than using Pearson correlation coefficient in defining dependence for extreme load coefficients. The Gaussian copula is convenient for deriving the joint distribution of multivariate extreme load coefficients but is not applicable for high-dimensional problems. In contrast, the vine copula is flexible and can provide a better estimate of the joint distribution function without dimension limitations. Multivariate annual maximum wind loads can be estimated via either first- or full-order methods. Dependence of the extreme load coefficients and randomness of the wind speed are both found having effects on the dependence of extreme wind loads. Moreover, the procedure of simulating multivariate annual maximum wind loads is presented to facilitate the use in practical problems.

Medium- and long-term power load forecasting model

Power load is an important part of power system, and power load forecasting has an important impact on power system analysis, design and control. With the development of smart micro grid, load forecasting has gradually become an important module in the energy management system, It is “source, network, load and storage” “An important link in energy flow matching. The staged combined demand forecasting model of power grid based on neural network and polynomial regression is adopted, and judgment conditions are added to the neural network. If the training sample data does not converge in the neural network training process, the neural network forecasting is terminated, and the data is automatically transferred to the polynomial regression model to obtain the forecasting results. This method can be initially used for annual and monthly load forecasting. It is an intelligent micro grid The planning of has laid a certain technical foundation.

Comparison of Newly Proposed and Existing Design Approach for Saturated Buffers

Highlights More diverted flow to the buffer does not necessarily mean more nitrate load removal. A design approach should incorporate a nitrate removal component to maximize nitrate load removal. The newly proposed design follows a process-based approach to estimate the annual site-specific nitrate removal. The newly proposed design provided more consistent nitrate load removal regardless of the site conditions. Neglecting exit head loss in the design process leads to an overestimation of diverted flow and nitrate load removal. Abstract. A saturated buffer (SB) is a conservation drainage practice that removes nitrate from subsurface drainage discharge. The reported wide range of nitrate load removal necessitates improvements in design approaches for more consistent performance. There are two SB design approaches: Illinois Natural Resources Conservation Service (Design 1) and McEachran et al. (2020) (Design 2). We proposed a new Design 3 that builds on the previous two designs. In Design 3, the nitrate load removal was simulated for buffer widths ranging from 3 to 30 m with a 0.3-m interval, and the buffer width that maximized the annual nitrate load reduction over the long term was chosen as the SB design. The objective of this study was to identify the best design approaches for maximizing nitrate load removal based on field data. Daily drainage discharge data from two field sites in Michigan were used to design a hypothetical SB length and width for each approach. The designs were compared by applying an identical method to estimate the nitrate load removal for each hypothetical SB system. The method extends Designs 1 and 2 by incorporating a hydrological and nitrate removal component. The results showed that using the minimum recommended buffer width of 9.1 m and the minimum 5% SB design capacity of Design 1 resulted in 25% to 35% of diverted flow to the buffer and 14% to 16% nitrate load removal at the two field sites. However, Design 1 resulted in the lowest nitrate removal compared to Designs 2 and 3 (i.e., 0.3% to 3.4% lower). Designs 2 and 3 consistently provided maximum nitrate load removal regardless of the site conditions, whereas the performance of Design 1 was inconsistent. In conclusion, Designs 2 and 3 were equally good and resulted in higher nitrate load removal compared to Design 1. Keywords: Conservation practice, Exit head loss, Nitrate, Subsurface drainage, Tile drainage, Water quality.

Nitrogen and phosphorus leaching losses under cropping and zone-specific variable-rate irrigation

Context Agricultural land use is intensifying globally. Irrigation and other farm practices associated with intensification, such as cultivation, grazing, and fertiliser application, can increase nutrient losses. Variable rate irrigation (VRI) systems manage irrigation to spatially variable soils and different crops (zones). We lack knowledge on nutrient losses under zone-specific irrigation for mixed-cropping systems (combined crop and livestock grazing). Aims This study evaluated drainage, nitrogen, and phosphorus leaching losses under zone-specific irrigation for a temperate mixed-cropping system. Methods The study site had sheep grazing and crops including peas, beans, wheat, turnips, plantain, and ryegrass-white clover pasture. It had a variable-rate centre-pivot irrigator for two soil zones (free draining Zone 1; poorly drained Zone 2). Drainage flux meters (DFMs) collected drainage leachate, and samples for measurement of nitrogen (N) and phosphorus (P) concentrations. Soil water balance data and statistical modelling evaluated nutrient leaching losses over 5 years. Key results The mean leaching load of NOx-N (nitrate + nitrite) across 5 years was 133 (s.d. 77) and 121 (s.d. 97) kg N/ha/year for Zone 1 and Zone 2, respectively. Similarly, the mean leaching load of reactive P across all years was 0.17 (s.d. 0.30) and 0.14 (s.d. 0.14) kg P/ha/year for Zone 1 and Zone 2, respectively. The nitrogen concentrations and loads generally had greater uncertainty in Zone 2. Conclusions The DFMs worked well for the free draining sandy soil. However, fewer samples were collected in the silt soil, requiring the statistical modelling developed in this study. This study gave a reasonable estimate of annual leaching load means, but the indicators of their within-year variation were not reliable, partly due to differences in sampling frequency. With some exceptions, there was generally more NOx-N leaching from the free draining Zone 1. VRI provided a system to control irrigation-related drainage and leaching in these soil zones. Implications Drainage flux meters are more reliable in well-drained than in poorly drained soil. Given the lack of published studies, this study has improved knowledge of nutrient losses under zone-specific irrigated mixed-cropping systems in a temperate climate.

Two possible methods of examining environmental load at macro and micro levels

The concept of carbon footprint and the application of the calculation methods thereof have become part of the discourse on sustainable economy. Measuring CO2 emissions at macrolevels has become more important in the field of environment and economy in the 21st century. Determining the local environmental impact of microeconomic actors has also come to the fore. This study uses the timeseries data analysis method at two levels. At the macro level, the disparity of distribution of GDP produced and the associated CO2 emissions by continent are analysed, and the study seeks to answer the question whether there is an increasing or decreasing trend in inequality. In the case of microeconomic actors, the study focuses on the built environment: buildings account for 40% of global energy consumption and 1/3 of greenhouse gas emission, so this proportion represents a key responsibility for decision-makers of built environments. For micro-level analysis, the experiences related to determining the annual carbon load of a central unit of a higher education institution are summarized. The data collection and time series analysis show the direct CO2 emissions of the institution and the emissions of the energy inputs used for operation. In addition to presenting time series data, the study seeks to answer the question whether growing and widespread post-COVID-19 online solutions can have a long-term impact on the composition of the environmental load of the examined higher education service centre.

Emission load analysis of land transportation on urban roads in Jember regency, Indonesia (a case study of Sultan Agung Road)

Jember Regency is located in East Java with a population density of 2,536,729 people in 2020. The higher population in Jember will be proportional to the high transportation activity. This will cause problems regarding air pollution due to vehicle exhaust emissions in Jember Regency. The aims of this study are to estimate the annual emission load of air pollutants on a segment of Jember City's urban roads and to recommend emission reduction strategies. The selection of strategies is conducted by considering experts’ judgments through the Analytic Hierarchy Process (AHP). Sultan Agung Road in Jember City was the target of this study because it is a national road in the middle of a busy shopping area around it. The results of this study show that the emission burden generated from the land transportation sector on Sultan Agung Road in Jember Regency includes 177.486 tons of CO/year; 48.638 tons of HC/year; 9.481 tons of NO2/year; 2.534 tons of PM10/year; 1,245.15 tons of CO2 /year and 0.421 tons of SO2 /year. Three strategies recommended by the experts to reduce emissions are BRT (Bus Rapid Transit) Operational Development, The use of Solar Cells in Public Street Lighting, and Smart Driving.

Hybrid solar thermal and heat pump systems in industry: Model based development of globally applicable design guidelines

Solar thermal heating systems and heat pumps are key technologies for decarbonizing low temperature industrial heat demand. Fluctuating solar irradiance, limited heat source capacity or limited availability of renewable electricity often limit the potential of the single technologies. To maximize the share of renewable heat supply, the combination of both technologies is a promising option. This study takes the first steps towards filling the research gap of missing guidelines for preliminary design or feasibility studies. A simulation tool based on idealized component models is used to compare technical and economic performance for 30,240 parameter combinations, that define various global reference applications, system designs, and economic frameworks. The heat sink and source temperatures, and the energy prizes have the highest impact on the economic performance. The potential for technical optimization is small. If the fraction of both heat generators together is close to 100 %, SCOP differences between different hydraulic concepts are neglectable. The most viable option for optimizing the system's LCOH is to reduce the heat pump capacity to about the half of the annual peak load. Due to recent increases in energy prices, a complete decarbonization is economically feasible without subsidies for most of the applications studied.

PSO-BP-Based Optimal Allocation Model for Complementary Generation Capacity of the Photovoltaic Power Station

To improve the operation efficiency of the photovoltaic power station complementary power generation system, an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed. Particle Swarm Optimization and BP neural network are used to establish the forecasting model, the Markov chain model is used to correct the forecasting error of the model, and the weighted fitting method is used to forecast the annual load curve, to complete the optimal allocation of complementary generating capacity of photovoltaic power stations. The experimental results show that this method reduces the average loss of photovoltaic output prediction, improves the prediction accuracy and recall rate of photovoltaic output prediction, and ensures the effective operation of the power system.

Design and technological scheme of a multifunctional seeding unit

Currently, the vast majority of agricultural producers in the Southern Federal District with a total area of arable land up to 50-70 hectares cultivate three main crops, namely grain ears, usually winter wheat, and row crops – corn for grain and sunflower. Grain ear crops are sown in the usual ordinary way, and row crops use the dotted method. These key agrotechnological features lead to the need to use different sowing machines equipped with different types of sowing units. Since the vast majority of agricultural producers of the Southern Federal district with a total area of arable land up to 50-70 hectares do not use monoculture in the structure of crops, this leads to a low annual load of these seeders. This is through deductions for depreciation, maintenance service and repairs inevitably affect the final cost of production. It should also be noted that often, due to the high cost of sowing machines, small agricultural producers are not able to purchase the required agricultural machinery, in addition, this is most often not economically feasible. The use of hired units does not allow sowing in the specified agrotechnical terms, which significantly reduces their productivity and quality parameters. The use of specialized seeders leads to an increase in metal consumption and multi-marking on the farm. This problem can be solved by using a multifunctional seeding machine (MSU). This will make it possible to abandon the use of specialized seeders and perform sowing of grain and row crops with the same machine by carrying out conversion for a specific crop. We have de-scribed the design scheme of the MSU and the principle of its operation. The technical result of the development is also presented and the way to achieve is described.

LONG-TERM TREND OF NITROGEN AND PHOSPHORUS TRANSPORT IN 12 TROPICAL COASTAL WATERSHEDS IN NORTHEAST BRAZIL

Multiple environmental problems are caused by the accumulation of nitrogen (N) and phosphorus (P) in river water on its way to the ocean. The objective of this work was to determine the N and P loads in 12 hydrographic basins that flow into estuaries along the northeastern coast of Brazil using established methods. Additionally, natural and anthropogenic loads trends in the hydrographic basins of 12 tropical rivers in northeastern Brazil over 27 years (1990-2016) were evaluated. The results indicated an annual average increase of +1.1% in population density, while precipitation showed no significant trend. The anthropogenic loads were 21 and 112 times higher than natural inputs for N and P, respectively. Anthropogenic sources accounted for ~ 96% of all contributions. The positive trends of these loads (mainly wastewater) represented an annual average increase of 1.1% for N and 1.2% for P, for all river basins included in this study. These percentages represent average annual loads of 251 t N yr-1 and 54.8 t P yr-1. The time series of N and P in the study region showed trends that point to a constant increase, implying a greater contribution of these loads to the adjacent coastal region year after year.

TRANSPORT AND TECHNOLOGICAL MODULE WITH ELECTRIC WHEEL DRIVE

Agriculture of the Russian Federation suffers huge losses due to the lack of the necessary equipment to work on soils with low load-bearing capacity. As a result, harvesting of winter crops takes more than 40 days, and crop losses amount to 42 percent. When applying fertilizers, about 40 percent of the soil surface is compacted by the wheels of agricultural machinery. Compaction of the soil leads to the appearance of large and dense blocks of earth during plowing. Tractors of traction classes 1,4-5 are used as part of the tractor fleet of peasant farms. Such a nomenclature of tractor types leads to additional costs associated with low annual loading of tractors, over-compaction of soils, tractors of high traction classes. (Research purpose) The research purpose is justifying the use of a transport and technological module with an electric wheel drive. (Materials and methods) Gave a schematic diagram of a modular power-technological means and a kinematic scheme of the wheel drive of a transport and technological module. (Results and discussion) We have developed a transport and technological module with an electric drive of the driving wheels from the generator, which in turn rotates due to the tractor power take-off shaft connected by a cardan transmission. It was determined that the electronic control unit and wheel speed sensors are responsible for the necessary kinematic correspondence between the driving wheels of the tractor and the transport and technological module. It was found that this eliminates the need for a synchronous power take-off shaft on the tractor and, as a result, makes the technological module universal. (Conclusions) It was shown that the use of a transport and technological module with an electric wheel drive serves as an effective way to solve the problem of ballasting and makes it possible to improve the technological properties of a second-generation tractor. It was stated that the use of a transport and technological module with an electric wheel drive will allow the tractor to be used to perform transport work requiring a large traction force on soils with low load-bearing capacity, such as the transportation of forests, manure in the spring and autumn thaw and others.

Hydrological transport pathways of dissolved organic nitrogen and their seasonal changes in an agricultural watershed

The role of dissolved organic nitrogen (DON) in the eutrophication of surface water and the potential risk to drinking water safety as a precursor of disinfection by-products is gradually emphasized. Therefore, accurate estimates of watershed DON load fluxes and identifying thresholds of streamflow that cause abrupt changes in riverine DON concentration are important. Here, we adopted the load estimator model (LOADEST) and nonparametric change-point analysis (nCPA) to comprehensively investigate the variation of DON load from 2011 to 2016 in different seasons in the Fengyu River watershed, Southwest China. Results indicated that the wet season is the hot moment of DON loss, and the average cumulative load reaches 14.1 t, accounting for 72.5 % of the annual load. Meanwhile, baseflow is the main pathway of DON export, accounting for about 74.4 % of the stream export load. Furthermore, the abrupt threshold of streamflow on DON concentration is 2.03 m3/s to 2.15 m3/s. When the stream flow is below 2.15 m3/s, the concentration of river DON increases rapidly and poses a great threat to human drinking water safety. This study will provide a scientific basis for regulating DON at the watershed scale and water quality protection in drinking water source areas.