Predicting Freshwater Critical Loads of Acidification at the Catchment Scale: An Empirical Model

Current applications of the critical loads concept are geared primarily toward targeting emission control strategies at a national and international level. Maps of critical loads for freshwaters have been produced in grid form based on water samples of representative sites within each grid square. However, the water chemistry data required to calculate freshwater critical loads are not always readily available at a national level and maps are therefore limited to catchments where such data exist. This paper describes the development of an approach that uses nationally available secondary data to predict freshwater critical loads for catchments lacking the appropriate water chemistry information. An empirical statistical model is calibrated using data from 78 catchments throughout Scotland. Water chemistry for each catchment has been determined. Each catchment is characterized according to a number of attributes. Redundancy analysis of these data shows clear relationships between catchment attributes and the critical load derived from the water chemistry. The key variables that explain most of the variation in critical load relate to soil, geology and land use within the catchment. Using these variables as predictors in a regression analysis, the critical load can be predicted across a broad gradient of sensitivity (R² _adj=0.81). The predictive power of the model was maintained when different combinations of explanatory variables were used. This accords the approach a degree of flexibility in that model parameterization can be geared toward availability of secondary data. There are limitations with the model as presently calibrated. However, the approach offers considerable scope for environmental managers to undertake national inventories of catchment sensitivity and specific assessments of individual catchments.     

Mapping the Potential Sensitivity of Surface Waters to Acidification Using Measured Freshwater Critical Loads as an Indicator of Acid Sensitive Areas

Environmental organisations in the UK have shown increasing interest in freshwater critical loads and acid sensitivity maps as a means of assessing pollution at the local and regional level. These maps can be used to identify sensitive areas when considering catchment management plans. The use of national data sets to map the sensitivity of freshwaters to acidification, highlighted the problems of relating national datasets to smaller, localised areas. The study described here investigated the use of detailed large-scale maps to predict the sensitivity of surface waters to acidification for two river catchments. Three large-scale acid sensitivity maps were produced and validated using measured freshwater critical loads. In addition, a score system relating to the buffering capacity for each soil and geology type was devised. The score value was found to have a better correlation with water chemistry and freshwater critical loads than the acid sensitivity maps. The study concluded that it was not necessary to use the largest scale data available in order to improve predictions of sensitive areas.     

The use of catchment attributes to predict surface water critical loads: A preliminary analysis

Current applications of the critical loads concept are geared primarily towards targeting emission control strategies at a regional and international level. Freshwater critical maps in the UK have been produced at a resolution of 10 km grid squares and do not take into account variations of water chemistry within the mapping unit. They are therefore of limited use at the catchment scale. This paper assesses the potential for the development ofn empirical statistical model to predict catchment critical loads using readily available secondary data. Multivariate statistical analysis of existing critical loads chemistry data together with data obtained from the Institute of Terrestrial Ecology (ITE) identifies strong relationships between surface water chemistry composition and a variety of site-specific catchment attributes, particularly rainfall, altitude and site sensitivity. Although there were problems with the data used, particulaly in terms of noise, collinearity and spatial resolution, the strength of the relationships indicates that accurate prediction of catchment scale critical loads should be possible using a higher resolution, catchment specific dataset.     

Predicting freshwater critical loads from national data on geology,soils and land use

Using information on geology, soils and land use, a map has been generated for Great Britain which indicates five classes of sensitivity of surface waters to acidification. This map has been used for designing sampling strategies for mapping critical loads of acidity for freshwaters. This paper evaluates the freshwater sensitivity map using a data set of water chemistry collected as part of the UK critical loads programme. Discriminant analysis was used to predict five critical load classes from information on geology and soil sensitivity for freshwater sites. This showed geology and soil information can correctly predict approximately 50% of all critical loads classes. In addition, 77% of sites fall within one critical loads class of that predicted. Predictions may be improved by including other variables eg altitude and geographical location. Differences between lake, stream and reservoir sites are also examined. Ranges of critical loads values were determined for each of the five classes of surface water sensitivity. While a trend in critical load values was evident between classes, there was significant overlap. A simplified sensitivity map with only three classes related more closely to critical loads values. The paper demonstrates the usefulness of the surface water sensitivity map for assessing acidification at a national scale, but highlights the difficulties of predicting critical loads for individual sensitive catchments using national data.     

Validation of the UK critical loads for freshwaters: Site selection and sensitivity

Critical loads maps for UK freshwaters have been produced on a 10×10 km grid square basis, and used to map critical load exceedances under various deposition scenarios. A single lake or stream site was selected to represent the most sensitive water body in each grid square using predefined criteria. In the UK a major programme of data screening and validation has been undertaken in order to address issues of accuracy and validity. A major part of this validation exercise, the within-square variability study, is designed to test the extent to which the site chosen for mapping represents the most sensitive water body within each grid square or mapping unit. Sampling of all lake sites in thirty-two randomly chosen 10 × 10 km grid squares has shown that in two thirds of cases, the selection exercise has identified a site in the lowest critical load class within a square. However, up to a third of all sites selected to represent grid squares could be replaced by more sensitive sites with a critical load smaller by at least one Skokloster class. The mean overestimate of diatom model critical loads for sulphur in the within-square variability study is 0.188 keq ha^–1 yr^–1. This means that current critical load maps show overestimates for some grid squares. In order to determine where the most sensitive site has not been identified, further work on catchment scale classification of freshwater sensitivity is being carried out.     

Variation in Freshwater Critical Loads Across Two Upland Catchments in the UK: Implications for Catchment Scale Management

In the UK the "critical loads" approach has been used to derive maps based on the 10km × 10km national grid. However, this grid based approach is inappropriate for catchment scale management and these maps cannot be used for "stock at risk" assessments of the number of water bodies or lengths of streams in a given area that may be vulnerable to acidification. Critical loads are determined across two large river catchments in England (The Duddon) and Wales (The Glaslyn). High resolution, digital datasets are used to characterise the attributes of each subcatchment in terms of land cover, soil, geology, topography and topology. Empirical models used to examine the relationship between these attributes and critical loads indicate that the former can be used to account for significant variation in the latter. However, these relationships can vary from catchment to catchment. Thus, although this approach provides the potential for identifying sensitive surface waters on a catchment wide basis, it is likely that models will need to be parameterised on a catchment specific basis.     

Uncertainty in predicting weathering rate and environmental stress factors with the profile model

The PROFILE model is a steady state soil chemistry model which is used to calculate soil weathering rate. The model has also been used to calculate critical loads of acidity and N to forest soils, using the ratio of Ca+Mg+K to total inorganic aluminium in the soil solution as criterion, and to surface waters, using the ANC leached from the soil column as criterion. An uncertainty analysis of the PROFILE model was performed by Monte Carlo analysis, varying input parameter errors individually and simultaneously in ranges of ±10–100%, depending on parameter. The uncretainty in calculation of weathering rate, ANC leaching and ratio of Ca+Mg+K to inorganic Al in the soil solution was studied for three Nordic sites. Furthermore, the effect of uncertainty in estimates of critical load for forest soils was assessed. The analysis shows that the weathering rate can be calculated with high precision, provided that the errors of input parameter are within the range that has been reported in the literature. The model tend to be less sensitive to errors in input parameters for the range of conditions where forest damage is most likely to occur. Critical loads of acid deposition for one site calculated on the basis of the model varies within a largest range of ±40%. A study of one geographical grid included in the Swedish critical loads assessment shows that with the number of calculation points in the grid, the distribution of critical loads will stay stable independently of stochastic errors.     

The use of critical load exceedances in abatement strategy planning

Critical loads for sulphur and nitrogen are defined to produce effective control strategies over Europe, such as those of the new sulphur protocol. To determine the critical load exceedances on the European scale it is necessary to simplify and generalize. The spatial variation on a scale smaller than the 150 × 150 km EMEP grid squares is considered for critical loads, via a cumulative frequency distribution and the 95 percentile for the grid square is determined. The deposition is assumed to be uniform over the area and the exceedance over the 95 percentile critical load is determined. In reality, the spatial variation is considerable for critical loads as well as for deposition. Calculations based on the frequency of local critical load exceedances have been made for two grid squares in southern Sweden. Local critical loads for acidity are compared to local deposition. Deposition variations due to pollution gradients within the square and to ecosystem structure have been considered. The results are similar for the two squares. The calculations based on local exceedances on 50×50 km grid squares and consideration to landuse variability, indicate that in order to protect 95% of the ecosystems in the square, emission reductions 25% greater than the large-scale European approach are needed. The effect of enhanced deposition at forest edges is of relatively small importance for the total exceedance.     

Dynamic Modelling of Spatially Variable Catchment Hydrochemistry for Critical Loads Assessment

Concern about acidification in upland areas has brought about the need to model the stream hydrochemical response to deposition and land-use changes and calculate critical loads. Application of dynamic models such as MAGIC are preferable to steady-state methods, since they are able to produce an estimate of the time scale required to meet some water chemistry target given a reduction in acid deposition. These models typically consider annual changes in stream chemistry at one point. However, in order to protect biota from 'acid episodes', quantification of temporal variability needs to encompass event responses; in addition spatial variability across the catchment also needs to be considered. In this paper, modelling of both spatial and temporal variability is combined in a new framework which enables quantification of catchment hydrochemical variability in time and space. Both low and high flow hydro-chemical variability are quantified in terms of statistical distributions of ANC (Acid Neutralisation Capacity). These are then input as stochastic variables to an EMMA (End-Member Mixing Analysis) model which accounts for temporal variability and ANC is hence predicted as a function of time and space across the whole catchment using Monte-Carlo simulation. The method is linked to MAGIC to predict future scenarios and may be used by iteration to calculate critical loads. The model is applied to the headwaters of the River Severn at Plynlimon, Wales, to demonstrate its capabilities.     

Estimating uncertainty in the current critical loads exceedance models

The critical loads approach to quantifying areas at risk of damage requires deposition and critical loads data at the same spatial scale to calculate exceedance. While maps of critical loads for soil acidification are available at a 1 km scale no monitoring networks in Europe measure wet and dry inputs at this scale and, further, the models currently used to estimate deposition incorporate a number of assumptions which are not valid at the 1 km scale. Simulations of 1 km deposition from 20 km data show that the uncertainty introduced by using 20 km scale estimates of deposition is small, except in mountain areas where it can give misleading results, but a major problem is the uncertainty in estimates of deposition at the 20 km scale produced by the current models.     

不同布点密度条件下土壤有机碳的空间变异特性

选择福建省漳州市三个不同尺度的典型区,在格网法采样的基础上设计6种不同分类方法和4种格网密度,研究不同尺度下高效表征耕地土壤有机碳空间变异的样点布设方式。研究结果表明:市级尺度(漳州市)高效的样点布设方法为结合地貌类型和土壤类型信息的分类格网法,样点密度以接近6 km×6 km为最节省的采样方法。县级(龙海市)尺度按土壤类型与格网法相结合的方法是高效的布点方式,土壤类型若仅划分到土类,格网密度需接近1 km×1 km;若土壤类型划分到亚类或土属,格网密度可放宽到2 km×2 km。乡镇级(程溪镇)最适合的样点布设方法是未分类格网法。由于土壤类型信息是表征土壤有机碳空间变异最重要的影响因素,因此建议在县级以上尺度进行土壤有机碳空间变异研究时应考虑到土壤类型的影响。     

Effects of Site Selection Strategy on Freshwater Critical Load Exceedances in Wales

Critical loads are used in international negotiations to reduce acid deposition resulting from emissions of sulphur and nitrogen compounds within Europe. For freshwater ecosystems, the First-order Acidity Balance (FAB) model is used to generate national maps of critical loads and exceedances for both sulphur (S) and nitrogen (N). In Wales, two survey datasets have been used to calculate critical loads and exceedances; one based on water bodies selected to be "most-sensitive" to acidification within a 10 km grid and the other based on a random selection of standing waters. Both datasets indicate that critical loads were exceeded in 1990 in a significant proportion of Welsh lakes and streams; 36% of sites in the grid-based survey and 31% of sites in the random survey. However, implementation of the Gothenburg Protocol would protect all but 6% of sites in the grid-based survey and all sites in the random survey. Assessment of the relative success of the Gothenburg Protocol in protecting Welsh freshwater ecosystems therefore depends on the site selection strategy employed.     

The effects of scale and resolution in developing percentile maps of critical loads for the UK

Critical loads are estimated in the UK by the Department of Environment's Critical Loads Advisory Group and sub-groups. The Mapping and Data Centre at ITE Monks Wood acts as the National Focal Centre for the UNECE programme for mapping critical loads. The centre is responsible for the generation of UK data sets and their application for national and European purposes. To make effective use of these data, it is necessary to draw upon other environmental data and examine the issues of scale, uncertainty and the way that data are presented. This paper outlines the methodologies which have been employed to derive national maps. Early critical load maps were not vegetation specific, but now critical loads for acidity and for nutrient nitrogen for soils, critical levels maps for ozone and sulphur dioxide, and sulphur deposition maps, have been generated on a vegetation or ecosystem specific basis. These have been used to derive a number of different types of critical load and exceedance maps. The results show the importance of the method selected and the data used for the interpretation. The visualisation of critical loads and the corresponding exceedance data is an important aspect in producing information for pollution abatement strategies.     

Identification of key soil and terrain properties that influence the spatial variability of soil moisture throughout the growing season

Combining soils and terrain information is the key to understanding hydrological processes at a landscape scale. Increasing the scale of soil maps has been shown to allow the spatial patterns of soil moisture to be more fully represented in the landscape, but soil data are often only available at reconnaissance scales (e.g. 1:250 000). It is widely acknowledged that soil hydrological properties vary within the landscape and there are widely available digital terrain models at a 10-m grid resolution in the UK. The aim of this study was to investigate soil moisture variations and how soil and terrain data can be used in combination to explain the spatial variation in soil moisture contents. Field monitoring of surface soil moisture content on eight occasions in three different fields in Bedfordshire (UK) was undertaken between April and July in 2004 and 2005. Between 100 and 120 points were sampled in each survey using a Delta-T ML2x™ Theta Probe. The results from regression models show that up to 80% of the variation in surface soil moisture can be explained using 1:10 000 soil series maps and terrain variables. Short-wave radiation on a sloping surface (SWRSS), calculated by SRAD, and a topographic wetness index combined explained a maximum of 44% of the variation. The results show that the terrain effect on soil moisture is modified by soils. The additional variation explained by adding 1:10 000 soil series information to terrain variables was up to 50% and adding 1:25 000 soil series information increased the variation explained by up to 29%. The interactions in the variation explained by soils and landscape indices at different scales tie in with the concept of hydropedology. It also has implications for data requirements for modelling soil hydrological response and associated soil functions.     

Identification of sediment source and sink areas in a Himalayan watershed using GIS and remote sensing

Erosion is a natural geomorphic process occurring continually over the Earth's surface and it largely depends on topography, vegetation, soil and climatic variables, and therefore, exhibits pronounced spatial variability due to catchment heterogeneity and climatic variation. This problem can be circumvented by discretizing the catchment into approximately homogeneous sub‐areas using GIS. In this study, the remote sensing and GIS techniques (through Imagine®8.6 and ArcGIS®9.1 software) were used for derivation of spatial information, catchment discretization, data processing etc. for the Himalayan Chaukhutia watershed (India). Various thematic layers for different factors of USLE were generated and overlaid to compute spatially distributed gross soil erosion maps for the watershed using 18‐year rainfall data. The concept of transport limited accumulation was formulated and used in ArcGIS® for generating the transport capacity maps. Using these maps, the gross soil erosion was routed to the catchment outlet using hydrological drainage paths, for derivation of transport capacity limited sediment outflow maps. These maps depict the amount of sediment rate from a particular grid in spatial domain and the pixel value of the outlet grid indicates the sediment yield at the outlet of the watershed. Up on testing, the proposed method simulated the annual sediment yield with less than ±40% error. Copyright © 2009 John Wiley & Sons, Ltd.     

Critical loads of acid deposition on Scottish soils

The impact of acid deposition, attributable to sulphur and nitrogen pollutants, on the soils of Scotland has been analysed using a critical loads approach. The critical load of a soil (as an indicator of ecological damage) is calculated from the soil parent material controlling weathering and soil development. Using existing soil survey information national maps for critical loads of acidity and the sulphur fraction are presented for soils under natural and semi-natural ecosystems. The results show that highly sensitive soils, that is those derived from quartzite and granite are limited in occurrence. However, there are large areas of sensitive soils predominantly to the north and west of the Midland Valley and in the Southern Uplands, in receipt of acid deposition in excess of their critical load. Enhanced soil acidification should be widespread in these areas and consequently the ecosystems which they support will be adversely affected. The least sensitive soils, overlying limestone or marl, are restricted in occurrence and are confined to the major deposits of marine alluvium. The results of the analysis may be used to help policy makers derive emission abatement strategies in the context of the European Sulphur protocol renewal in 1993. In Scotland the maps may be used to aid the planning of large scale afforestation.     

Soil Factors and their Influence on Within-field Crop Variability, Part I: Field Observation of Soil Variation

A fundamental component of adopting the concept of precision farming in practice is the ability to measure spatial variation in soil factors and assess the influence of this on crop variability in order to apply appropriate management strategies. The aim of this study was to appraise potential methods for measuring spatial variability in soil type, nutrient status and physical properties in practical farming situations. Five fields that are representative of more than 30% of soils used for arable production in England and Wales were selected for use as case studies. Maps of soil type were generated from a conventional hand-auger survey on a 100 m grid and the excavation of targeted soil profile pits. These were compared with those refined using a mechanised soil coring device and scans of electromagnetic inductance (EMI) carried out while the soil could reasonably be considered to be at, or near, field-capacity moisture content. In addition, soil sampling for nutrient analyses was conducted on a 50 m grid to examine the spatial variation in nutrient status. Conventional methods for sampling soil were found to be appropriate for identifying soil types at specific locations within the field sites, however, they were time-consuming to perform which placed an economic and therefore a practical limitation on the sampling density possible. The resulting data were considered to be too sparse for demarcating soil-type boundaries for use in the context of precision farming. The location of soil boundaries were refined by using the mechanised soil corer, however, the limitation of this was found to be the time required to analyse the soil cores produced. Maps of soil variation generated from EMI scans conducted at field capacity appear to reflect the underlying variation in soil type observed in maps generated using the mechanised soil corer and, therefore, this approach has potential as a cost-effective, data-rich, surrogate for measures of soil variability. Results from analyses of soil samples for measurement of nutrient status indicated that whilst there was considerable variation in macro- and micro-nutrient levels in each field, with the exception of pH, these levels were above commonly accepted agronomic limits. Results, however, did demonstrate the potential for addressing variation in critical factors such as pH at specific locations, however, there is a need to develop protocols for targeting sampling in order to reduce costs.     

Effects of Data Uncertainty in the Swedish Critical Load Assessment for Forest Soils

The effects of input data uncertainty on the critical loads andexceedance estimates for Swedish forest soils was assessed usingMonte Carlo simulations of the PROFILE model. The study focuseson the effects of data uncertainty on the 5%-ile critical loadat 150 × 150 km resolution and the 95%-ile exceedance at150 × 150 km and 50 × 50 km resolution.The results indicate that datauncertainty limits the possibility to differentiate grid cellson 150 × 150 km resolution. The confidence interval for agiven percentile can generally be reduced if the uncertaintiesin calculated critical loads are addressed simultaneously forall sites in a grid cell. The resulting best estimates of the5%-ile critical load were found to be lowered, therebyadvocating larger deposition reductions to comply with a givengap closure of exceedance. The results further indicate that thenumber of sites within the grid cells is important for the rangeof the confidence interval for a given percentile.Re-aggregation of exceedance estimate in 50 × 50 km gridcells showed that differentiation may be improved as compared to150 × 150 km resolution. For 70% of the grid cells on 50× 50 km resolution, the confidence interval forcalculated exceedance covers both negative and positive values.     

不同取样方式下土壤质地空间插值的精度分析

为研究土壤质地的合理取样方式,进而研究其空间变异情况,为田间施肥及灌溉提供依据,本试验利用地统计学方法和GIS技术,在重庆市彭水县重庆烟草试验站,利用289个表层土样,研究了16 m间距的栅格取样法(对照,253个土样,扣除36个验证样点)、34 m间距的栅格取样法(115个土样)和随机取样法(115个土样)3种取样方式下土壤质地的空间插值精度。3种土壤颗粒指标中粉粒占68.43%,砂粒含量最少,占12.68%,黏粒含量略高于砂粒。砂粒和黏粒具有中等强度的变异性,粉粒具弱变异性,且数据符合正态分布。地统计分析显示,在分析该区域土壤质地时,采用栅格取样方法应适当增大取样间距,而采用随机取样方法可适当缩小取样间距。交叉检验显示,土壤质地成分在3种取样方式下的插值精度均以对照最大,栅格取样次之,随机取样最小。综合考虑插值误差、样品采集和分析成本及时效性等因素,本研究建议在该区域进行土壤质地空间变异规律分析为生产服务时应采用随机取样。     

短距离样点对土壤呼吸空间变异预测精度的影响

不同采样设计会对土壤呼吸空间变异特征的预测精度产生重要影响。本研究选取黄淮海平原北部潮土区1 km×1 km夏玉米样地,在7×7单元规则格网(样点间距167 m)、完全随机(样点平均间距433 m)以及3×3单元规则格网+完全随机(样点平均间距405m)3种布点方式的基础上,保持样本总量(49)不变,以占总样点2%～14%的短距离样点(样点间距4m)随机替换原方案相应样点个数的方法优化布点方式,应用普通克里金法插值,以均方根误差(RMSE)和确定系数(R2)作为验证指标,检验基于3种布点方式设置的短距离样点对土壤呼吸空间变异预测精度的影响。结果表明:研究区土壤呼吸平均速率为2.65μmol·m?2·s?1,空间分布均呈西高东低,表现出中等程度变异。采样设计对土壤呼吸空间分布的预测精度影响显著,基于3种布点方式设置短距离样点可提高预测精度7%～13%。无短距离样点替换时,规则格网+完全随机的布点方式最优,比完全随机布点和规则格网布点的空间插值预测精度分别提高10%和22%;设置短距离样点替换后,在最优布点方式(规则格网+完全随机)中,对土壤呼吸空间变异的预测精度可再提高4%～7%,其中短距离样点个数占样本总量10%对土壤呼吸空间变异预测精度的提高最为明显。研究发现,基于相同的样本数量设置短距离样点可增加区域范围内样点密度,提高土壤呼吸空间变异预测精度及试验结果的可靠性。因此,在黄淮海平原北部潮土区100 hm2尺度的夏玉米样地中,规则格网+完全随机+10%短距离样点的布点方式是预测土壤呼吸空间变异最适宜的采样布点方式。