水环境质量预报预警大数据平台研究

构建基于水环境模型的水质预报预警大数据平台是一项复杂的系统工程,主要面临模型的规模计算及其引发的模拟结果规模存储、规模分析的挑战.相关挑战极大地限制了水环境质量预报预警业务的深入开展,但目前国内外关于此方面的研究极少.为此,提出了水环境质量预报预警大数据平台框架.该框架以水环境模型体系为基础,以大数据集群计算体系为核心...     

Assessing the influence of nutrient reduction on water quality using a three-dimensional model: case study in a tidal estuarine system

A coupled three-dimensional hydrodynamic and water quality model has been developed and applied to the Danshuei River estuarine system and adjacent coastal sea. The water quality model considers various species of nitrogen, phosphorus, organic carbon, and phytoplankton as well as dissolved oxygen and is driven by a three-dimensional hydrodynamic model. The hydrodynamic and water quality models were validated with observations of water surface elevation, velocity, salinity distribution, and water quality parameters. Statistical error analysis shows that predictions of hydrodynamics, salinity, dissolved oxygen, and nutrients from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict water quality conditions as a result of a reduction in nutrient loadings based on different engineering strategies. The simulated results revealed that the dissolved oxygen concentration would increase significantly and would be higher than 2 mg/L in the main stream and in three tributaries to meet the minimum statutory requirement for dissolved oxygen. Active estuarine management focused on the reduction of anthropogenic nutrient loads is needed for improvement in water quality.     

Measuring Water Storage Fluctuations in Lake Dongting, China, by Topex/Poseidon Satellite Altimetry

Although satellite radar altimetry was developed and optimized for open oceans, it has been used to monitor variations in the level of inland water-bodies such as lakes and rivers. Here, for the first time, we have further used the altimetry-derived variation of water level for estimating the fluctuation of water storage as an addition to the present in situ water storage estimation systems to be used in remote areas and in emergency situation such as in the events flooding monitoring and for studying the effect of climate change. Lake Dongting, the second largest lake in China, influenced frequently by flooding, was, therefore, chosen to demonstrate the potential of the technique. By using the concept of an “assumed reference point”, we converted Topex/Poseidon satellite altimetry data on water level variations in Lake Dongting to “water level” data. The “water level” time-series data and in situ water storage were used to establish a rating curve. From the rating curve, we converted data on “water level” derived from seven years (1993–1999) of Topex/Poseidon data to actual water storage in Lake Dongting. The result reveals that the seasonal and annual fluctuations of water storage occurred during the 1990s with a more frequent flooding at the late 1990s' especially the flooding in whole catchment level in 1998 and 1999. The study supports the usefulness of satellite altimetry for dense and continuous monitoring of the temporal variations in water dynamic in moderate to large lakes.     

A Compartmental Model for Stable Time-Dependent Modeling of Surface Water and Groundwater

Water resource system planners make decisions that guide water management policy. The fundamental tools for assessing management and infrastructure strategies are combined hydro-economic models of river basins (RBHE models). These models have improved the economic efficiency of water use in situations of competition for scarce water resources. In RBHE models, a groundwater model is coupled with surface water models of the various water resources. Today, the groundwater models used in an RBHE model can be of two types: cell models or numerical models. Cell models are easy to use, but they are too simple to realistically describe the geology and hydrology of the area under investigation. Numerical models, in contrast, are closer to the physical behavior of the aquifer. However, the vast quantity of data to be analyzed makes them impractical for many management scenarios. Moreover, the calibrations of these high-resolution models are generally difficult and sensitive to the variation of parameters, especially when boundary conditions are dynamic. This is the case when dynamic river data or dynamic surface lake data are present. In this work, a compartmental cell model is built on the hydrogeology of the aquifer. In this approach, the hydrogeology of the aquifer and the dynamic boundary conditions are treated with separate models. A general mathematical formulation is presented where the calibration stage, the validation stage, and the prediction stage are formulated as a series of sub-model calibrations and solved using a general least squares routine. With this approach, it becomes possible to treat both the water level and the pumping rate in each cell as variables to be predicted. In most of the models, the pumping rates are known and the goals of the computation are to estimate the groundwater level. However, when for political or technical reasons access to some of the wells is difficult, the pumping rates are only partially known. Then, both groundwater levels and pumping rates are variables to be predicted by the groundwater model. A computer program was developed using MATLAB, with a Visual Basic graphical user interface using COM technology to access the advanced mathematical libraries. The approach was implemented with a real case study of the Yarkon–Taninim aquifer in Israel. The results indicate that the method is more stable than the classical approach.     

An expert system for water quality modelling

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.     

Hydrodynamic characterization of Corpus Christi Bay through modeling and observation

Christi Bay is a relatively flat, shallow, wind-driven system with an average depth of 3–4 m and a mean tidal range of 0.3 m. It is completely mixed most of the time, and as a result, depth-averaged models have, historically, been applied for hydrodynamic characterization supporting regulatory decisions on Texas coastal management. The bay is highly stratified during transitory periods of the summer with low wind conditions. This has important implications on sediment transport, nutrient cycling, and water quality-related issues, including hypoxia which is a key water quality concern for the bay. Detailed hydrodynamic characterization of the bay during the summer months included analysis of simulation results of 2-D hydrodynamic model and high-frequency (HF) in situ observations. The HF radar system resolved surface currents, whereas an acoustic Doppler current profiler (ADCP) measured current at different depths of the water column. The developed model successfully captured water surface elevation variation at the mouth of the bay (i.e., onshore boundary of the Gulf of Mexico) and at times within the bay. However, large discrepancies exist between model-computed depth-averaged water currents and observed surface currents. These discrepancies suggested the presence of a vertical gradient in the current structure which was further substantiated by the observed bi-directional current movement within the water column. In addition, observed vertical density gradients proved that the water column was stratified. Under this condition, the bottom layer became hypoxic due to inadequate mixing with the aerated surface water. Understanding the disparities between observations and model predictions provides critical insights about hydrodynamics and physical processes controlling water quality.     

Prediction of Leachate Level in Kimpo Metropolitan Landfill Site by Total Water Balance

Kimpo metropolitan landfill has received various kinds of wastessince January 1992. The leachate level was measured to be 10.3 m in May 1995 and the level increased to 12.2 m in August 1996. Therefore, to prove the reason for the increasing leachate level, we calibrated hydraulic conductivity of each waste andintermediate layer using the HELP (Hydrologic Evaluation ofLandfill Performance) model. The leachate generation data measured from February 1993 to October 1995 was used in the model calibration. As a result of a model calibration, we obtained anaverage infiltration ratio and used this in analysis of the total water balance to predict elevation of leachate level. Main causes of the elevation of the leachate level were the high water content of the waste and the degradation of the leachate-drainage system caused by the subsidence of a naturalbarrier layer.     

Precipitation Modeling by Polyhedral RCMARS and Comparison with MARS and CMARS

Climate change is becoming an ever important issue due to the possibility that it may result in extreme weather events such as floods or droughts. Consequently, precipitation forecasting has similarly gained in significance as it is a useful tool in meeting the increasing need for the efficient management of water resources as well as in preventing disasters before they happen. In the literature, there are various statistical and computational methods used for this purpose, including linear and nonlinear regression, kriging, time series models, neural networks, and multivariate adaptive regression splines (MARS). Among them, MARS stands out as the better performing precipitation modeling method. In this article, we used a recently developed method called robust conic mars (RCMARS), based on MARS (also on CMARS), to forecast precipitation owing to its ability to model complex uncertain data. In CMARS, which was developed as a powerful alternative to MARS, the model complexity is penalized in the form of Tikhonov regularization and studied as a conic quadratic programming. In RCMARS, on the other hand, CMARS is refined further by including the existence of uncertainty in the future scenarios and robustifying it with a robust optimization technique. To evaluate the performance of the RCMARS method, it was applied to build a precipitation model constructed as an early warning system for the continental Central Anatolia Region of Turkey, where drought has been a recurrent phenomenon for the last few decades. Furthermore, the performance of the RCMARS precipitation model was also compared to that of MARS and CMARS. The results indicated that RCMARS builds more accurate, precise, and stable precipitation models compared to those of MARS and CMARS. In addition to these advantageous features of the RCMARS precipitation model, it also provided a good fit to the data. As a result, we propose its use in precipitation forecasting for the region studied.     

Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010

Drought is a complex natural phenomenon that can cause reduced water supplies and can consequently have substantial effects on agriculture and socioeconomic activities. The objective of this study was to gain a better understanding of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China. The Vegetation Condition Index (VCI) dataset calculated from NOAA/AVHRR images from 1982 to 2010 was used to analyse the spatial-temporal variation characteristics of vegetative drought in China. This study also examined the trends in meteorological factors and their influences on drought using monitoring data collected from 686 national ground meteorological stations. The results showed that the VCI appeared to slowly rise in China from 1982 to 2010. From 1982 to 1999, the VCI rose slowly. Then, around 2000, the VCI exhibited a severe fluctuation before it entered into a relatively stable stage. Drought frequencies in China were higher, showing a spatial distribution feature of “higher in the north and lower in the south”. Based on the different levels of drought, the frequencies of mild and moderate drought in four geographical areas were higher, and the frequency of severe drought was higher only in ecologically vulnerable areas, such as the Tarim Basin and the Qaidam Basin. Drought was mainly influenced by meteorological factors, which differed regionally. In the northern region, the main influential factor was sunshine duration, while the other factors showed minimal effects. In the southern region and Tibetan Plateau, the main influential factors were sunshine duration and temperature. In the northwestern region, the main influential factors were wind velocity and station atmospheric pressure.     

Research on the drought index of irrigation district with multi-time scales

The empirical mode decomposition method is applied to analyze fluctuating periods and local features of the annual drought index and the drought index in the irrigation and non-irrigation periods from 1956 to 2010 in the Yinchuan irrigation district. In order to understand the uncertainty between these variables, the set pair analysis method is used to present the identity, discrepancy, and contrary of the drought index with multi-time scales. The results reveal that the annual drought index and the drought index in the irrigation and non-irrigation periods have a complex relationship which may be related to El Niño, the air–sea intersection, and the long period of solar activity. The drought index in the irrigation and non-irrigation periods presents mainly the contrary and the discrepancy; the fluctuating shapes of the annual drought index and drought index in the irrigation period are the same on their different period levels. The original annual drought index and its intrinsic mode function components have a certain connection degree; they mainly present the discrepancy.     

Climate Change Impacts and Human Settlements in Africa: Prospects for Adaptation

Climate change impacts on African human settlements arise from a number of climate change-related causes, notably sea level changes, impacts on water resources, extreme weather events, food security, increased health risks from vector home diseases, and temperature-related morbidity in urban environments.Some coastlines and river deltas of Africa have densely populated low-lying areas, which would be affected by a rise in sea level. Other coastal settlements will be subjected to increased coastal erosion. Recent flooding in East Africa highlighted the vulnerability of flood plain settlements and the need to develop adaptive strategies for extreme weather events management and mitigation. In the semi arid and arid zones many settlements are associated with inland drainage water sources. Increases in drought will enhance water supply related vulnerabilities. Inter-basin and international water transfers raise the need for adequate legal frameworks that ensure equity among participating nations.Similarly, water supply and irrigation reservoirs in seasonal river catchments might fail, leading to poor sanitation in urban areas as well as food shortage. Hydroelectric power generation could be restricted in drought periods, and where it is a major contributor to the energy budget, reduced power generation could lead to a multiplicity of other impacts. States are advised to develop other sources of renewable energy.Temperature changes will lead to altered distribution of disease vectors such as mosquitoes, making settlements currently free of vector borne diseases vulnerable. Rapid breeding of the housefly could create a menace associated with enteric disorders, especially in conditions of poor sanitation.The dry savannahs of Africa are projected as possible future food deficit areas. Recurrent crop failures would lead to transmigration into urban areas. Pastoralists are likely to undertake more trans-boundary migrations and probably come into conflict with settled communities.Adaptive measures will involve methods of coastal defences (where applicable), a critical review of the energy sector, both regionally and nationally, a rigorous adherence to city hygiene procedures, an informed agricultural industry that is capable of adapting to changing climate in terms of cropping strategies, and innovations in environment design to maximise human comfort at minimum energy expenditure. In the savannah and arid areas water resource management systems will be needed to optimise water resource use and interstate co-operation where such resources are shared.Climate change issues discussed here raise the need for state support for more research and education in impacts of climate change on human settlements in Africa.     

Effects of selective withdrawal on hydrodynamics and water quality of a thermally stratified reservoir in the southern side of the Mediterranean Sea: a simulation approach

This study uses a multidisciplinary approach to simulate the spatial and temporal patterns of hydrodynamics and water quality in a thermally stratified reservoir in the southern side of the Mediterranean Sea in response to water withdrawal elevation using the 2D water quality and laterally averaged hydrodynamic model CE-QUAL-W2. The withdrawal elevation controls largely the transfer of heat and constituents in the dam in particular during thermal stratification. Fifteen scenarios of withdrawal elevation are possible. To identify the most effective scenarios, a hierarchical clustering technique was performed and only four scenarios were clustered. Deep withdrawals deepen the hypoxia, increase the thickness of the metalimnion, and weaken the stratification stability, which facilitate the vertical transfer of heat and dissolved oxygen mainly. Surface withdrawals, however, shrink the metalimnion and tend to strengthen the stratification, resulting in less transfer of matter from the epilimnion to the hypolimnion. Most of the bottom sediment is overlaid by the hypolimnion. The oxygen depletes significantly and waters become anoxic at a few meters depth. For all scenarios, the reservoir experiences a summer hypolimnetic anoxia, which lasts from 42 to 80 days and seems to decrease as withdrawal elevation increases. At the end of stratification, waters below the withdrawal elevation showed a noticeable release of iron, nutrients, and suspended sediments that increases with depth and near-bottom turbulence. Attention should be drawn to shallower withdrawals because they accumulate nutrients and silts continuously in the reservoir, which may deteriorate water quality. Based on these results, a withdrawal elevation rule is presented. This rule may be adjusted to optimize water withdrawal elevation for dams in the region with similar geometry.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

A Review of Public Domain Water Quality Models for Simulating Dissolved Oxygen in Rivers and Streams

The review discusses six major public domain water quality models currently available for rivers and streams. These major models, which differ greatly in terms of processes they represent, data inputs requirements, assumptions, modeling capability, their strengths and weaknesses, could yield useful results if appropriately selected for the desired purposes. The public domain models, which are most suitable for simulating dissolved oxygen along rivers and streams, chosen in this review are simulation catchment (SIMCAT), temporal overall model for catchments (TOMCAT), QUAL2Kw, QUAL2EU, water quality analysis simulation program (WASP7), and quality simulation along rivers (QUASAR). Each of these models is described based on a consistent set of criteria-conceptualization, processes, input data, model capability, limitations, model strengths, and its application. The results revealed that SIMCAT and TOMCAT are over-simplistic but useful to quickly assess impact of point sources. The QUAL2Kw has provision for conversion of algal death to carbonaceous biochemical oxygen demand (CBOD) and thus more appropriate than QUAL2EU, where macrophytes play an important interaction. The extensive requirement of data in WASP7 and QUASAR is difficult to justify the time and costs required to set up these complex models. Thus, a single model could not serve all wide range of functionalities required. The choice of a model depends upon availability of time, financial cost and a specific application. This review may help to choose appropriate model for a particular water quality problem.     

Modelling Wetland Bird Response to Water Level Changes in the Lake Ontario – St. Lawrence River Hydrosystem

Lake Ontario and St. Lawrence River (LOSL) wetland bird abundance and diversity are greatly influenced by lake and river hydrology. Our study used an interdisciplinary ecosystem approach, blending avian and plant ecology, ecohydraulic, statistical ecology and modelling to evaluate potential impacts of water level fluctuations on indicator species representative of the wetland breeding bird assemblages in the entire LOSL freshwater system. Multi-year (2000–2003) bird surveys captured bird distribution and density in wetland habitats under varying degrees of water inandation, depth and fluctuation. Analyses revealed strong associations between estimated breeding pair densities and plant communities, water depth, and degree of water level fluctuation during the breeding season for a suite of wetland bird species using marsh, wet meadow, shrub swamp and treed swamp habitats. These quantitative associations were used to develop wetland bird performance indicators for use in a LOSL water regulation review study. Several bird species also nest at or near the water surface and are thus vulnerable to nest flooding or stranding. Changes to the seasonal hydrology of Lake Ontario and St. Lawrence River that result in an increased frequency or magnitude of these nest failure events may have a significant impact on regional population sustainability. Long term nest record databases were analyzed to create nesting flooding and stranding probability equations based on water level increases and decreases during the breeding season. These species-specific nesting relationships were incorporated into a reproduction index.Many breeding bird species were strongly associated with specific wetland plant communities. Predicted habitat suitability, as measured by estimated breeding pair density, can also change significantly within a specific wetland plant community based solely on changes in water depth during the breeding season. Three indicator species, Black Tern, Least Bittern and Virginia Rail were selected as key environmental performance indicators for alternate regulation plan comparisons.Water regulation criteria should be such that the long term diversity and abundance of wetland plant communities and frequency of spring flooding in marsh habitats during breeding are not reduced. Magnitude and frequency of water level change during the nesting season (May–July) can also adversely impact reproductive success of many wetland bird species. As such, regulation criteria that increase the seasonal magnitude and frequency of water level change may be detrimental to the long term viability of certain regional breeding bird populations.     

True and false positive rates in maximum contaminant level tests

The U.S. Environment Protection Agency (EPA) is promulgating a revised national primary drinking water regulation (NPDWR) which includes a monthly sample size and maximum contaminant level (MCL) for total coliform bacteria in public water systems. No previous quantification has been made of the coliform content that must be present in the sampled water in order for an MCL to be exceeded. This paper presents a method for evaluating the coliform level an MCL will detect with likelihood P.Our approach is to treat an MCL as a decision rule, with Type I (false positive) and Type II (false negative) error rates. The stringency of an MCL is quantified as the mean coliform level in the sampled system that it will detect with likelihood P. MCLs are contrasted on stringency by comparing the mean coliform level each targets for detection, with fixed error rates.Interim rules (NIPDWR), in effect since 1975, are shown to vary widely on the coliform content each targets for detection, that is, on stringency. Yes/no decisions on contamination have not been decided based on mean coliform content. Coliform levels permitted in monitored public water systems have been determined by the particular MCL used for testing. The same coliform level will test positively with one MCL 90 times in 100 yet be guaranteed 95% nondetection by a second MCL.EPA's reasonably safe standard for drinking water is reformulated on our stringency criteria. Its proposed monthly MCL is evaluated on its capability for maintaining this standard. Smaller systems will not provide its users this level of protection under the new rule.In addition, our evaluation of the safe water standard on stringency and the rationale for a monthly MCL require that coliform levels be identically distributed (i.d.) across month and sampled system. Empirical data strongly refute this model and question the utility of a monthly MCL.This work suggests an alternative, single sample MCL, with repeat sampling for verification, which can be configured to provide monitoring to discover mean coliform values at any level, in any size of system, at minimal extra cost.     

A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity

Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors — thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance — or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human “footprint” and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.     

运行方式对人工快渗系统水质净化效果的影响

以天然砂作为主要渗滤介质,建立污水处理人工快速渗滤系统(CRI).分别以洗浴污水、生活污水和受污染河水作为研究对象,在相同的水力负荷条件下,用两种不同的运行方式(定期投配一定量的污水、淹水和落干交替运行)对不同水质的污染物去除效果进行了对比研究.结果表明,通过缩短淹水周期,加大系统淹水和落干的频率,可以明显改善CRI系统的污染物去除效果.     

Assessing Multi-site Drought Connections in Iran Using Empirical Copula

Drought is a multi-dimensional natural hazard with stochastic characteristics usually related to each other. Separate univariate statistical models cannot capture the important relationships among drought characteristics, that is, severity and duration. In this study, an empirical copula is employed to construct a bivariate model of droughts, where droughts are defined as continuously negative standardized precipitation index (SPI) periods with one SPI value reaching ?1 or less. Bivariate frequency analyses in terms of recurrence intervals are performed using the established empirical copula-based bivariate drought model. The inter-connection among different regions of droughts is explored by a lower tail dependence coefficient. A nonparametric estimation based on an empirical copula is employed pairwisely to calculate the lower tail dependence coefficient among stations. The proposed method is applied to six rainfall gauge stations in Iran to explore drought properties of single sites as well as the inter-connection among multi-sites. The results show that greater mean drought severity and duration are associated with the least arrival rate of drought events, which occurs at the Ahwaz station. The tail dependence analysis reveals that distance between stations is not a key parameter. Generally, the Ahwaz and Isfahan stations have the highest probability of simultaneous droughts among the six stations.     

对旱情的理性思考和构建新的监测、抗旱理念

对旱灾造成的损失,不能仅从农业粮食减产单方面估算,而应把旱灾造成的隐性损失科学评估出来。据此提出,抗旱要处理好农业用水、工业用水和城市用水及生态用水的关系,真正实现水资源的可持续利用,并应建立自动化的干旱监测和快速评估系统,以保证及时掌握旱情,将旱灾损失减至最小。