Models for preserving species diversity with backup coverage

The problem of selecting land for preservation of species has been a rich and active area of research over the past two decades. Typically, reserve selection models have tried to maximize species diversity by preserving areas that contain the greatest number of species. However, several studies have shown that seldom do these species-rich areas contain the rarest species most in need of protection. Most reserve selection models seek to maximize diversity by choosing parcels so that all species are covered by or represented in at least one parcel. This approach would usually be expected to result in coverage by a single parcel for the rarest species, especially for those that do not coincide with more abundant species. It is precisely these rare species, however, that would be lost or whose survivability would be most challenged, if the single parcels in which they are represented became unavailable due to some unforeseen event. In this paper, we introduce to reserve selection models the concept of secondary, or backup, coverage of species. Briefly stated, a species is said to have backup representation in the system of reserves if it is covered by, or represented in, two or more parcels. Having backup coverage guarantees that every species is still covered in the event that a natural or man-made catastrophe makes a given parcel uninhabitable. The results show that backup coverage can be obtained at little additional cost (as expressed by the number of parcels selected). Bi-objective formulations that trade-off primary with backup coverage show that backup coverage can be guaranteed for larger numbers of species with little reduction in primary coverage.     

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.     

Relationship between landscape characteristics and surface water quality

The effects of landscape characteristics on surface water quality were evaluated in terms of land-use condition, soil type and slope. The case area, the Chichiawan stream in the Wulin catchment in Taiwan, is Formosan landlocked salmon's natural habitat. Due to the agriculture behavior and mankind's activities, the water and environmental quality has gradually worsened. This study applied WinVAST model to predict hydrological responses and non-point source pollution (NPSP) exports in the Wulin catchment. The land-use condition and the slope of land surface in a catchment are major effect factors for watershed responses, including flows and pollutant exports. This work discussed the possible variation of watershed responses induced by the change of land-use condition, soil type and slope, etc. The results show that hydrological responses are highly relative to the value of Curve Number (CN); Pollutant exports have large relation to the average slope of the land surface in the Wulin catchment.     

Effect of spatial variability of storm on the optimal placement of best management practices (BMPs)

It is significant to design best management practices (BMPs) and determine the proper BMPs placement for the purpose that can not only satisfy the water quantity and water quality standard, but also lower the total cost of BMPs. The spatial rainfall variability can have much effect on its relative runoff and non-point source pollution (NPSP). Meantime, the optimal design and placement of BMPs would be different as well. The objective of this study was to discuss the relationship between the spatial variability of rainfall and the optimal BMPs placements. Three synthetic rainfall storms with varied spatial distributions, including uniform rainfall, downstream rainfall and upstream rainfall, were designed. WinVAST model was applied to predict runoff and NPSP. Additionally, detention pond and swale were selected for being structural BMPs. Scatter search was applied to find the optimal BMPs placement. The results show that mostly the total cost of BMPs is higher in downstream rainfall than in upstream rainfall or uniform rainfall. Moreover, the cost of detention pond is much higher than swale. Thus, even though detention pond has larger efficiency for lowering peak flow and pollutant exports, it is not always the determined set in each subbasin.     

Method for automatic determination of soybean actual evapotranspiration under open top chambers (OTC) subjected to effects of water stress and air ozone concentration

The present study describes an operational method, based on the Katerji et al. (Eur J Agron 33:218-230, 2010) model, for determining the daily evapotranspiration (ET) for soybean inside open top chambers (OTCs). It includes two functions, calculated day par day, making it possible to separately take into account the effects of concentrations of air ozone and plant water stress. This last function was calibrated in function of the daily values of actual water reserve in the soil. The input variables of the method are (a) the diurnal values of global radiation and temperature, usually measured routinely in a standard weather station; (b) the daily values of the AOT40 index accumulated (accumulated ozone over a threshold of 40 ppb during daylight hours, when global radiation exceeds 50 Wm(-2)) determined inside the OTC; and (c) the actual water reserve in the soil, at the beginning of the trial. The ensemble of these input variables can be automatable; thus, the proposed method could be applied in routine. The ability of the method to take into account contrasting conditions of ozone air concentration and water stress was evaluated over three successive years, for 513 days, in ten crop growth cycles, excluding the days employed to calibrate the method. Tests were carried out in several chambers for each year and take into account the intra- and inter-year variability of ET measured inside the OTCs. On the daily scale, the slope of the linear regression between the ET measured by the soil water balance and that calculated by the proposed method, under different water conditions, are 0.98 and 1.05 for the filtered and unfiltered (or enriched) OTCs with root mean square error (RMSE) equal to 0.77 and 1.07 mm, respectively. On the seasonal scale, the mean difference between measured and calculated ET is equal to +5% and +11% for the filtered and unfiltered OTCs, respectively. The ability of the proposed method to estimate the daily and seasonal ET inside the OTCs is therefore satisfactory following inter- and intra-annual tests. Finally, suggestions about the applications of the proposed method for other species, different from soybean, were also discussed.     

Spatial Prediction of Stream Temperatures Using Top-Kriging with an External Drift

Top-kriging is a method for estimating stream flow and stream flow-related variables on a river network. Top-kriging treats these variables as emerging from a two-dimensional spatially continuous process in the landscape. The top-kriging weights are estimated by a family of variogram models (regularisations) for different catchment areas (kriging support), which accounts for the different scales and the nested nature of the catchments. This assures that kriging weights are distributed to both hydrologically connected and unconnected sites of the stream network according to the data situation: top-kriging gives most weight to close-by sites at the same river system, but when the next hydrologically connected site is far away, more weight is given to a close-by site at an adjacent river system. The distribution of weights is in contrast to ordinary kriging and stream distance-based kriging which does not account for both spatial proximity and network connectivity. We extend the top-kriging method by incorporating an external drift function to account for the deterministic patterns of the spatial variable. We test the method for a comprehensive Austrian stream temperature dataset. The drift is modelled by exponential regression with catchment altitude. Top-kriging is then applied to the regression residuals. The variogram used in top-kriging is fitted by a semiautomatic optimisation procedure. A leave-one-out cross-validation analysis shows that the model performs well for the study domain. The residual mean squared error (cross-validation) decreases by 20 % when using top-kriging in addition to the regression model. For regions where the observed stream temperatures deviate from the expected value of the drift model, top-kriging corrects these regional biases. By exploiting the topological information of the stream network, top-kriging is able to improve the local adjustment of the drift model for the main streams and the tributaries.     

Changes in water level,land use,and hydrological budget in a semi-permanent playa lake,Southwest Spain

Medina playa lake, a Ramsar site in western Andalusia, is a brackish lowland lake of 120 ha with an average depth of 1 m. Water flows into Medina from its 1,748-ha watershed, but the hydrology of the lake has not previously been studied. This paper describes the application of a water budget model on a monthly scale over a 6-year period, based on a conceptual hydrological model, and considers different future scenarios after calibration to improve the understanding of the lake’s hydrological functioning. Climatic variables from a nearby weather station and observational data (water-level evolution) were used to develop the model. Comparison of measured and predicted values demonstrated that each model component provided a reasonable output with a realistic interaction among the components. The model was then used to explore the potential consequences of land-use changes. Irrigation of olive groves would significantly reduce both the hydroperiod (becoming dry 15% of the time) and the average depth of the lake (water level <0.5 m 40% of the time). On the other hand, removal of an artificial overflow would double the average flooded surface area during high-water periods. The simulated water balance demonstrates that the catchment outputs are dominated by lake evaporation and surface outflow from the lake system to a creek. Discrepancies between predicted and observed water levels identify key areas of uncertainty for future empirical research. The study provides an improved basis for future hydrological management of the catchment and demonstrates the wider utility of this methodology in simulating this kind of system. This methodology provides a realistic appraisal of potential land-use management practices on a catchment-wide scale and allows predictions of the consequences of climate change.     

Investigation of impact of environmental changes on precipitation pattern of Pakistan

In this paper, variability in precipitation pattern of Pakistan due to environmental and climatic changes has been studied. Maps have been generated to depict global precipitation variation. Precipitation data of 25 stations of Pakistan have been used. These data were taken from Meteorological Department, Islamabad, Pakistan. The results of two global climate models, namely Australia’s Commonwealth Scientific and Industrial Research’s third generation general circulation model and National Center for Atmospheric Research’s first generation precipitation circulation model for A2 scenario have been applied to investigate the changes. It is observed that precipitation pattern will change significantly in the future. The occurrence of precipitation in all seasons for Pakistan is expected to increase with almost uniform distribution across a season. Average annual precipitation of the country will undergo an increase in the range of +57 to +71 % as compared to average of the base period.     

Siting analyses for water quality sampling in a catchment

Pollution loads discharged from upstream development or human activities significantly degrade the water quality of a reservoir. The design of an appropriate water quality sampling network is therefore important for detecting potential pollution events and monitoring pollution trends. However, under a limited budgetary constraint, how to site an appropriate number of sampling stations is a challenging task. A previous study proposed a method applying the simulated annealing algorithm to design the sampling network based on three cost factors including the number of reaches, bank length, and subcatchment area. However, these factors are not directly related to the distribution of possible pollution. Thus, this study modified the method by considering three additional factors, i.e. total phosphorus, nitrogen, and sediment loads. The larger the possible load, the higher the probability of a pollution event may occur. The study area was the Derchi reservoir catchment in Taiwan. Pollution loads were derived from the AGNPS model with rainfall intensity estimated using the Thiessen method. Analyses for a network with various numbers of sampling sites were implemented. The results obtained based on varied cost factors were compared and discussed. With the three additional factors, the chosen sampling network is expected to properly detect pollution events and monitor pollution distribution and temporal trends.     

Risk assessment for salmon from water quality changes following timber harvesting

Land use activities may affect surface water quantity and quality. Water quality changes (concentration increases) from land use activities that are above background but below the water quality standard or criteria have always been considered benign. Increased public interest and recent legislation and management regarding threatened, or endangered, salmon populations suggest that environmental influences on these populations need to be reevaluated.As one approach, we developed a risk assessment (toxicity and exposure) for salmon from water quality changes following timber harvesting. Toxicity relationships for nitrate-nitrogen (as an LC₅₀) using chloride, suspended sediment, and exposure were developed from the literature and data from the Alsea Watershed Study in the Oregon Coast Range. These relationships were used to predict the probable risk to coho salmon (Oncorhynchus kisutch) to nitrate-nitrogen exposure.The control or reference catchment, Flynn Creek, had higher nitrate-nitrogen concentrations, but showed little likelihood of risk to salmon because of lower suspended sediment concentrations. The treated catchment, Needle Branch (harvested 27 years ago), had lower nitrate-nitrogen concentrations and was expected to have less risk to salmon. However, the risk assessment relationship exhibited sensitivity to suspended sediment concentrations. This smaller catchment had higher suspended sediment transport and thus a higher risk of nitrate-nitrogen exposure to salmon. The suspended sediment transport functions were based on post-treatment monitoring (1966–1973) and are not considered to represent the current situation. These findings are not meant to be categorical, but merely illustrative of this risk assessment application.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

水质自动监测与常规监测结果对比分析

为了系统研究水质自动监测数据与常规监测数据间差异问题,选取15个运行多年的国家地表水水质自动监测站,对p H、溶解氧(DO)、高锰酸盐指数(COD_(Mn))、氨氮(NH_3-N)及总磷(TP)5项监测指标开展了站房外常规监测、站房内常规监测与自动监测的对比实验研究。通过分析监测结果之间相对误差、相对偏差、水质类别变化发现,站房内常规监测、站房外常规监测与自动监测结果之间误差较小;同时通过误差统计分析及直方图分析发现,地表水水质自动监测系统监测结果与站房外常规监测结果之间误差整体属于随机误差(偶然误差)。研究得到了水质自动监测与常规监测数据一致可比的结论,为水质自动监测数据的应用提供了实验基础。     

Ordinal time series model for forecasting air quality index for ozone in Southern California

Air quality index (AQI) for ozone is currently divided into six states depending on the level of public health concern. Generalized linear type modeling is a convenient and effective way to handle the AQI state, which can be characterized as non-stationary ordinal-valued time series. Various link functions which include cumulative logit, cumulative probit, and complimentary log-log are considered, and the partial maximum likelihood method is used for estimation. For a comparison purpose, the identity link, which yields a multiple regression model on the cumulative probabilities, is also considered. Random time-varying covariates include past AQI states, various meteorological processes, and periodic components. For model selection and comparison, the partial likelihood ratio tests, AIC and SIC are used. The proposed models are applied to 3 years of daily AQI ozone data from a station in San Bernardino County, CA. An independent year-long data from the same station are used to evaluate the performance of day-ahead forecasts of AQI state. The results show that the logit and probit models remove the non-stationarity in residuals, and both models successfully forecast day-ahead AQI states with almost 90 % of the chance.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Genetic Algorithm Usage in Water Quality Monitoring Networks Optimization in Gediz (Turkey) River Basin

Selection procedure of the optimum station combination for decreasing the station number from 33 to 14 in water quality monitoring network of Gediz river basin was applied using an optimization method. Gediz basin is one of the important basins and it covers 2.3% of the total surface area of Turkey. The technique includes two stages as the data preparation and the optimization. In the data preparation stage, firstly, alternative station combinations decreased and then station combination scores obtained from assigned selection criteria for point and nonpoint pollution management objectives. Finally, genetic algorithm applied to select the best combination. The results were compared with a prior solution that used dynamic programming as the optimization technique.     

The Development of Biological Objectives for Streams in a Single Catchment: A Case Study on the Catchment of Western Port Bay, Victoria, Australia

Government environment protection policies for waterways have traditionally relied on water quality indicators and their objectives. In this paper we describe the development of biological objectives based on invertebrate indicators for inclusion in a government policy for the catchment of Western Port Bay, Victoria. The first step of defining segments (areas with streams in which the same objectives are applied) was problematic, requiring two different approaches, as follows. Site groups initially based on invertebrate community composition derived using multivariate techniques (ordination and classification) proved to be unsuitable for policy segments. Segment boundaries were subsequently defined using topographical (e.g. boundary of foothills and lowland plains), climate (e.g. rainfall) and land-use (e.g. urban) features. We used information and data from reference sites inside as well outside the catchment to derive specific biological objectives based on aquatic invertebrates for these segments. Objectives were specified for the following four indicators--number of invertebrate families, the SIGNAL index, the AUSRIVAS predictive model and the number of key families.     

Application of Water Quality Indices and Dissolved Oxygen as Indicators for River Water Classification and Urban Impact Assessment

The usefulness of water quality indices, as the indicators of water pollution, for assessment of spatial-temporal changes and classification of river water qualities was verified. Four water quality indices were investigated: WQI (considering 18 water quality parameters), WQI(min) and WQI(m) (considering five water quality parameters: temperature, pH, DO, EC and TSS) and WQI(DO) (considering a single parameter, DO). The water quality indices WQI(min), WQI(m) and WQI(DO) could be of particular interest for the developing countries because of the minimum analytical cost involved. As a case study, water quality indices were used to evaluate spatial and temporal changes of the water quality in the Bagmati river basin (Nepal) for the study period 1999-2003. The results allowed us to determine the serious negative effects of the city urban activity on the river water quality. In the studied section of the river, the water quality index (WQI) was 71 units (classified as good) at the entry station and 47.6 units (classified as bad) at the outlet station. For the studied period, a significant decrease in water quality (mean WQI decrease = 11.6%, p = 0.042) was observed in the rural areas. A comparative analysis revealed that the urban water quality was significantly bad as compared with rural. The analysis enabled to classify the water quality stations into three groups: good water quality, medium water quality and bad water quality. WQI(min) resulted in overestimation of the water quality but with similar trend as with WQI and is useful for the periodic routine monitoring program. The correlation of WQI with WQI(min) and DO resulted two new indices WQI(m) and WQI(DO), respectively. The classification of waters based on WQI(m) and WQI(DO) coincided in 90 and 93% of the samples, respectively.     

Assessment of trace metals pollution in estuarine sediments using SEM-AVS and ERM?CERL predictions

In this paper a PSIAC-based multi-parameter fuzzy pattern recognition (MPFPR) model is proposed and applied for classifying and ranking the potential soil erosion (PSE). In this approach, standard value matrix is used to define the membership degrees of each catchment to each class and the feature values are used for alternative ranking. The characteristic of PSE for each class is expressed by linguistic variables. The proposed method is straightforward, easy to understand, very practical, and its results may easily be interpreted. To assess the performance of the model, the results of PSIAC MPFPR and original PSIAC method are interpreted and compared with the observed data. It is shown that the proposed approach reflects the fuzzy nature of the soil erosion more efficiently and is quite robust for application in real world cases.     

Sensitivity of Simulated Conservation Practice Effectiveness to Representation of Field and In-Stream Processes in the Little River Watershed

Evaluating the effectiveness of conservation practices (CPs) is an important step to achieving efficient and successful water quality management. Watershed-scale simulation models can provide useful and convenient tools for this evaluation, but simulated conservation practice effectiveness should be responsive to parameter values used to represent the practices in the modeling. The objectives of this study were to (1) assess the impacts of a set of conservation practices on hydrology and water quality of a watershed and (2) evaluate the sensitivity of Soil and Water Assessment Tool (SWAT) modeling outputs and simulated conservation practice effectiveness to parameters. The modeling study was conducted in an agricultural watershed, the subwatershed K (16.9 km²) of the Little River Experimental watershed located in the South Atlantic Coastal Plain of the USA. Sensitivity analysis showed that hydrologic response unit (HRU) and watershed-scale simulations for water quality were most sensitive to CN and FILTERW parameters. Load reduction rates as a function of increased aerial coverage of the conservation practices were greatest for total phosphorus (TP), followed by sediment and total nitrogen (TN). The results indicated that conservation practices would have a limited impact on stream flow volume but could have a significant impact on sediment and TP loads within this region. Watershed-scale TN and TP loads were also sensitive to an in-stream nutrient transformation process represented using the QUAL2E algorithm in SWAT. The study clearly demonstrated the most sensitive model parameters and the optimal conservation practices for this watershed.     

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.