Sensitivity analysis in groundwater vulnerability assessment based on GIS in the Mahdia-Ksour Essaf aquifer,Tunisia: a validation study

Abstract

The assessment of groundwater vulnerability to pollution has proved to be an effective tool for water resource management, especially in arid and semi-arid regions like Mahdia and Ksour Essaf. The main objective of this study is to assess the aquifer vulnerability by applying the DRASTIC method as well as using sensitivity analysis to evaluate the effect of each DRASTIC parameter on the final vulnerability map. An additional objective is to demonstrate the role of the GIS techniques in the vulnerability assessment. The DRASTIC method assigns a high vulnerability to the coast of the Mahdia-Ksour Essaf. The lowest values are observed in the southern part of the study area. A sensitivity analysis applied in this study suggests that net recharge, aquifer media and depth of groundwater are the key factors determining vulnerability. The model is validated with groundwater quality data and the results have shown strong relationships between modified DRASTIC Vulnerability Index and nitrate and chloride concentrations.

Citation Saidi, S., Bouri, S. & Ben Dhia, H. (2011) Sensitivity analysis in groundwater vulnerability assessment based on GIS in the Mahdia-Ksour Essaf aquifer, Tunisia: a validation study. Hydrol. Sci. J. 56(2), 288–304.     

A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment

Abstract

Groundwater vulnerability assessment based on the DRASTIC index has been widely used since the 1980s to map potential risks of groundwater contamination. However, its applicability and usefulness are affected by two uncertain and subjective factors. One is the discretization of continuous input variables and the other is the assignment of different weights to the index variables. In this study, an entropy-weighted fuzzy-optimization approach was developed to augment and improve the classic DRASTIC method by reducing the uncertainties associated with variable discretization and weight assignment. The modified DRASTIC method was applied to a study site in Shandong, north China. The entropy-weighted fuzzy-optimization approach is shown to provide a more rigorous delineation of the relative vulnerability distribution. Meanwhile, the new approach does not require the use of more parameters. The results suggest that this approach significantly improves and enhances the ability of the classic DRASTIC method in a more systematic and rigorous way.

Editor D. Koutsoyiannis

Citation Yu, C., Zhang, B.X., Yao, Y.Y., Meng, F.H., and Zheng, C.M., 2012. A field demonstration of the entropy-weighted fuzzy DRASTIC method for groundwater vulnerability assessment. Hydrological Sciences Journal, 57 (7), 1420–1432.     

SOM-DRASTIC: using self-organizing map for evaluating groundwater potential to pollution

Groundwater is considered as the most important water resource, especially in arid and semi-arid regions, so it is crucial to impede this source of water to be contaminated. One of the most common methods to assess groundwater vulnerability is DRASTIC method. However, the subjectivity existing in defining DRASTIC weights and ratings as well as inadaptability of the parameters involved in this method with special geology, hydrogeology, land use and climatic conditions have urged researchers to modify this method. In this paper, a new method combining a special type of the neural networks called Self-Organizing Map (SOM) and the traditional DRASTIC model resulting in the hybrid SOM-DRASTIC model is applied to modify and improve DRASTIC Model. The traditional DRASTIC method holds a summation among all negative effects of different factors contributing to vulnerability, while the proposed hybrid method is able of classifying the groundwater vulnerability and deriving the real relation existing between the DRASTIC parameters as the inputs and the vulnerability class as the output of the method. The vulnerability assessment process was performed on the Zayandeh-Rud river basin aquifers in Iran. The SOM-DRASTIC identified the northern parts of the study area as the most vulnerable areas with a drastically fractured structure, while the traditional DRASTIC ranked the western parts as the most vulnerable regions with a high rate of net recharge. The results demonstrate that the proposed method can be used by managers and decision-makers as an alternative robust tool for vulnerability-based classification and land use planning.     

Developing a reliable model for aquifer vulnerability

The assessment of aquifer vulnerability to pollution is crucial for planning a sound management strategy of groundwater quality protection and farmland fertilizer use. This study establishes a reliable model for aquifer vulnerability assessment with an excellent performance for predicting groundwater nitrate-N contamination in the Choushui River alluvial fan, Taiwan based on the DRASTIC method. To promote the prediction performance of aquifer vulnerability assessment, discriminant analysis (DA) was applied to determine the weights of factors in the DRASTIC model by comparing the model results with the observed nitrate-N data. Key factors influencing the presence of groundwater nitrate-N pollution were characterized for different concentration thresholds. The results of analysis reveal that the modified DRASTIC model using DA significantly improves prediction performance for aquifer vulnerability assessment, and groundwater protection zones can be determined correctly based on the modified DRASTIC index. Furthermore, the sensitivity of the factors in the modified DRASTIC model indicates that the depth to the groundwater and aquifer media are critical when the nitrate-N concentration is less than 3 mg/L, while the impact of the vadose zone plays a vital role in controlling nitrate-N pollution of over 5 mg/L.     

Catchment-scale vulnerability assessment of groundwater pollution from diffuse sources using the DRASTIC method: a case study

Abstract

The catchment-scale groundwater vulnerability assessment that delineates zones representing different levels of groundwater susceptibility to contaminants from diffuse agricultural sources has become an important element in groundwater pollution prevention for the implementation of the EU Water Framework Directive (WFD). This paper evaluates the DRASTIC method using an ArcGIS platform for assessing groundwater vulnerability in the Upper Bann catchment, Northern Ireland. Groundwater vulnerability maps of both general pollutants and pesticides in the study area were generated by using data on the factors depth to water, net recharge, aquifer media, soil media, topography, impact of vadose zone, and hydraulic conductivity, as defined in DRASTIC. The mountain areas in the study area have “high” (in 4.5% of the study area) or “moderate” (in 25.5%) vulnerability for general pollutants due to high rainfall, net recharge and soil permeability. However, by considering the diffuse agricultural sources, the mountain areas are actually at low groundwater pollution risk. The results of overlaying the maps of land use and the groundwater vulnerability are closer to the reality. This study shows that the DRASTIC method is helpful for guiding the prevention practices of groundwater pollution at the catchment scale in the UK.

Citation Yang, Y. S. & Wang, L. (2010 Yang, Y. S. and Wang, L. 2010. A review of modelling tools for implementation of the EU Water Framework Directive in handling diffuse water pollution. Water Resour. Manage., 24: 1819–1843.  [Google Scholar]) Catchment scale vulnerability assessment of groundwater pollution from diffuse sources using the DRASTIC method: a case study. Hydrol. Sci. J. 55(7), 1206–1216.     

Application of Groundwater Vulnerability Overlay and Index Methods to the Jijel Plain Area (Algeria)

Today, scientists are deeply concerned by the vulnerability of groundwater reservoirs to pollution. Relatively simple overlay and index methods can be used to produce groundwater vulnerability maps in geographic information system. In addition, this study deals with contamination from nonpoint sources. In this study, two such models, DRASTIC and GOD, were applied in the Jijel Plain area of northeast Algeria and compared with measured groundwater nitrate concentrations. This showed that results from DRASTIC were better than GOD, 69% correlation with nitrate compared to 56%. DRASTIC was better able to identify vulnerable zones along the river valleys. The DRASTIC model was then modified using the nitrate concentrations to optimize the rating score given within each parameter range and sensitivity analysis to change the weighting given for each parameter. These combined changes gave a final Pearson's correlation of 83% with nitrate. This showed that recharge, aquifer type, and topography were the key factors in controlling vulnerability to nitrate pollution.     

A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer,Iran

Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. The objective of this research is (1) to assess the groundwater vulnerability using DRASTIC method and (2) to improve the DRASTIC method for evaluation of groundwater contamination risk using AI methods, such as ANN, SFL, MFL, NF and SCMAI approaches. This optimization method is illustrated using a case study. For this purpose, DRASTIC model is developed using seven parameters. For validating the contamination risk assessment, a total of 243 groundwater samples were collected from different aquifer types of the study area to analyze \( {\text{NO}}_{ 3}^{ - } \) concentration. To develop AI and CMAI models, 243 data points are divided in two sets; training and validation based on cross validation approach. The calculated vulnerability indices from the DRASTIC method are corrected by the \( {\text{NO}}_{3}^{ - } \) data used in the training step. The input data of the AI models include seven parameters of DRASTIC method. However, the output is the corrected vulnerability index using \( {\text{NO}}_{3}^{ - } \) concentration data from the study area, which is called groundwater contamination risk. In other words, there is some target value (known output) which is estimated by some formula from DRASTIC vulnerability and \( {\text{NO}}_{3}^{ - } \) concentration values. After model training, the AI models are verified by the second \( {\text{NO}}_{3}^{ - } \) concentration dataset. The results revealed that NF and SFL produced acceptable performance while ANN and MFL had poor prediction. A supervised committee machine artificial intelligent (SCMAI), which combines the results of individual AI models using a supervised artificial neural network, was developed for better prediction of vulnerability. The performance of SCMAI was also compared to those of the simple averaging and weighted averaging committee machine intelligent (CMI) methods. As a result, the SCMAI model produced reliable estimates of groundwater contamination risk.     

Response of deep groundwater to land use change in desert basins of the Trans‐Pecos region,Texas, USA: Effects on infiltration,recharge, and nitrogen fluxes

Quantifying the effects of anthropogenic processes on groundwater in arid regions can be complicated by thick unsaturated zones with long transit times. Human activities can alter water and nutrient fluxes, but their impact on groundwater is not always clear. This study of basins in the Trans‐Pecos region of Texas links anthropogenic land use and vegetation change with alterations to unsaturated zone fluxes and regional increases in basin groundwater NO₃^? concentrations. Median increases in groundwater NO₃^? (by 0.7–0.9 mg‐N/l over periods ranging from 10 to 50+ years) occurred despite low precipitation (220–360 mm/year), high potential evapotranspiration (~1570 mm/year), and thick unsaturated zones (10–150+ m). Recent model simulations indicate net infiltration and groundwater recharge can occur beneath Trans‐Pecos basin floors, and may have increased due to irrigation and vegetation change. These processes were investigated further with chemical and isotopic data from groundwater and unsaturated zone cores. Some unsaturated zone solute profiles indicate flushing of natural salt accumulations has occurred. Results are consistent with human‐influenced flushing of naturally accumulated unsaturated zone nitrogen as an important source of NO₃^? to the groundwater. Regional mass balance calculations indicate the mass of natural unsaturated zone NO₃^? (122–910 kg‐N/ha) was sufficient to cause the observed groundwater NO₃^? increases, especially if augmented locally with the addition of fertilizer N. Groundwater NO₃^? trends can be explained by small volumes of high NO₃^? modern recharge mixed with larger volumes of older groundwater in wells. This study illustrates the importance of combining long‐term monitoring and targeted process studies to improve understanding of human impacts on recharge and nutrient cycling in arid regions, which are vulnerable to the effects of climate change and increasing human reliance on dryland ecosystems.     

GIS based DRASTIC model for groundwater vulnerability assessment: Case study of the shallow mio-plio-quaternary aquifer (Southeastern Tunisia)

Groundwater is the main source of water in arid regions. Thus, groundwater pollution becomes a major issue due to the increasing contamination, which poses serious and harmful risk to the environment. Groundwater vulnerability maps can be used as a tool to help decision makers to protect groundwater resources from contamination. The vulnerability of the Mio-Plio-Quaternary shallow aquifer (Southeast Tunisia) has been assessed using a DRASTIC model based on Geographic Information System (GIS). The different parameters of the model were collected from several sources and converted into thematic maps using ArcGis©. Each DRASTIC parameter was assigned a weight and rating based on a range of information within the parameter. Groundwater vulnerability map shows a large area (48%) with high risk of pollution. It indicates that the Southern part of the aquifer and the wadi beds are the most susceptible to contamination. The measured nitrate concentration is coherent with the DRASTIC model results.     

Vulnerability evaluation of a coastal aquifer via GALDIT model and comparison with DRASTIC index using quality parameters

In recent years, environmental assessments of groundwater resources have resulted in the development of models that help identify the vulnerable zones. An aquifer is investigated using both GALDIT and DRASTIC indices. The GALDIT model is developed to determine the vulnerability of coastal aquifers in terms of saltwater intrusion whereas the DRASTIC model is generally applicable to all aquifers. Having compared the results of both the GALDIT and DRASTIC models with quality parameters, the salinity model proved to be more appropriate in identifying the vulnerability of coastal aquifers. The results show a Pearson correlation coefficient between TDS and the GALDIT vulnerability map of 0.58 while the corresponding value for the DRASTIC index is 0.48.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Fiori     

Estimation of baseflow nitrate loads by a recursive tracing source algorithm in a rainy agricultural watershed

Baseflow has become an important source of nitrate nonpoint source pollution in many intensive agricultural watersheds. Uncertainties in baseflow nutrient load separation are caused by the effects of hydrometeorological factors on both baseflow recession and baseflow nutrient load recession. These uncertainties have not been addressed well in the existing separating algorithms, which are based on simple baseflow rate–load relationships. In the present study, a recursive tracing source algorithm (RTSA) was developed based on a nonlinear reservoir algorithm and hydrometeorology-corrected baseflow nutrient load recession parameter. This approach was used to reduce the uncertainty of baseflow nitrate load estimation caused by variations in different load recessions under varying climate conditions. RTSA validation in a typical rainy agricultural watershed yielded Nash–Sutcliffe efficiency, root mean square error-observation standard deviation ratio, and R² values of 0.91, 0.30, and 0.91, respectively. The baseflow nitrate–nitrogen (N─NO₃^–) loads from 2003 to 2012 in the Changle River watershed of eastern China were estimated with the RTSA. The results indicated that baseflow nitrate export accounted for 62.0% of the mean total annual N─NO₃^– loads (18.0 kg/ha). The total baseflow N─NO₃^– export was highest in spring (3.6 kg/ha), followed by summer (3.2 kg/ha), winter (2.3 kg/ha), and autumn (2.1 kg/ha). The contribution of baseflow to total nitrate in the stream decreased in the order of winter (69.88%) >spring (66.59%) >autumn (60.36%) >summer (54.04%). The monthly baseflow N─NO₃^– loads and flow-weighted concentrations greatly increased during the research period (Mann–Kendall test, Z_s > 2.56, p < .01). Without proper countermeasures, baseflow nitrate may represent a serious long-term risk for water surfaces in the future.     

Hydrochemical and bacteriological features of the groundwater: southern border of the Rharb basin (Morocco) / Caractérisation hydrochimique et bactériologique des eaux souterraines: bordure méridionale du bassin du Rharb (Maroc)

Abstract

The western reservoirs represent the principal groundwater system in Morocco. Demographic, industrial and agricultural developments during the last decade have markedly altered groundwater quality. The Mamora coastal aquifer system is among the Atlantic systems which are most heavily threatened by pollution. Agricultural and industrial activities, and rapid urban growth contribute to the pollution of the groundwater. Contamination transport is facilitated by a high permeability of the aquifer formations. In order to assess the actual groundwater quality of the Mamora aquifer and to understand the influence of the factors generating the pollution, an extensive multidisciplinary research programme is in progress, with hydrochemistry and microbiology playing essential roles. The present paper concerns the spatial distribution of physico-chemical parameters in the groundwater, subjected to domestic, industrial and agricultural pollution. Fifty-seven samples were analysed for several parameters (Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl^?, SO₄ ^2?, HCO₃ ^?, NO₃ ^?, pH, electrical conductivity and temperature). The microbiological analysis of 143 samples reveals the presence of four kinds of indicator bacteria in the groundwater resources: faecal Streptococci, faecal coliform, Escherichia coli and Clostridium. The physico-chemical results and bacteriological monitoring show that the nitrate and bacteria concentrations exceed the maximum admissible levels, notably around pumping stations in the sectors of Sidi Taibi, Sidi Ahmed Taleb and Aïn Sbaâ. Contamination is generated by uncontrolled anthropogenic activities and accentuated by the high intrinsic vulnerability of the aquifer system. Several parameters appeared to exceed admissibility standards. Measures are recommended to prevent groundwater pollution in the region.     

Nitrate attenuation in soil and shallow groundwater under a bottomland hedgerow in a European farming landscape

In many agricultural areas, hedgerows give rise to strong expectations of reducing the inputs of excess nitrate to the groundwater and rivers. This study aims to analyse the spatial and seasonal influences of a hedgerow on nitrate dynamics in the soil and groundwater. Nitrate (NO₃^?) and chloride (Cl^?) concentrations were measured with spatially dense sampling in the unsaturated soil and in the groundwater along a transect intersecting a bottomland oak (Quercus rubor) hedgerow after the growing season and during the dormant season. We explain NO₃^? dynamics by using Cl^? as an index of tree‐root extension and water transfer. At the end of the growing season, NO₃^? is entirely absorbed by the trees over a large and deep volume corresponding to the rooting zone, where, in contrast Cl^? is highly concentrated due to root exclusion. However, these observed patterns in the soil have no influence on the deep groundwater composition at this season. During the dormant season, water transfer processes feeding the shallow groundwater layer are different upslope and downslope from the hedgerow in relation to the thickness of the unsaturated zone. Upslope, the shallow groundwater is fed by rainwater infiltration through the soil which favours Cl^? dilution. Right under the hedge and downslope, the rapid ascent of the groundwater near the ground surface prevents rainwater input and Cl^? dilution. Under the hedgerow the highest concentrations of Cl^? coincide with the absence of NO₃^? in the shallow groundwater layer and with high concentrations of dissolved organic carbon. The absence of NO₃^? during the dormant season seems to be due to denitrification in the hedgerow rooting zone when it is rapidly saturated by groundwater. Copyright © 2011 John Wiley & Sons, Ltd.     

Nested‐Scale Nutrient Flux in a Mixed‐Land‐Use Urbanizing Watershed

To improve quantitative understanding of mixed‐land‐use impacts on nutrient yields, a nested‐scale experimental watershed study design (n = 5) was applied in a 303(d), clean water act impaired urbanizing watershed of the lower Missouri River Basin, USA. From 2010 to 2013, water samples (n = 858 sample days per site) were analysed for total inorganic nitrogen (TIN‐N), nitrite (NO₂–N) nitrate (NO₃–N), ammonia (NH₃–N), and total phosphorus (TP‐P). Annual, seasonal, and monthly flow‐weighted concentrations (FWCs) and nutrient yields were estimated. Mean nutrient concentrations were highest where agricultural land use comprised 58% of the drainage area (NH₃ = 0.111 mg/l; NO₂ = 0.045 mg/l; NO₃ = 0.684 mg/l, TIN = 0.840 mg/l; TP = 0.127 mg/l). Average TP‐P increased by 15% with 20% increased urban land use area. Highly variable annual precipitation was observed during the study with highest nutrient yields during 2010 (record setting wet year) and lowest nutrient yields during 2012 (extreme drought year). Annual TIN‐N and TP‐P yields exceeded 10.3 and 2.04 kg ha^?1 yr^?1 from the agricultural dominated headwaters. Mean annual NH₃–N, NO₂–N, NO₃–N, TIN‐N, and TP‐P yields were 0.742, 0.400, 4.24, 5.38, and 0.979 kg ha^?1 yr^?1, respectively near the watershed outlet. Precipitation accounted for the majority of the explained variance in nutrient yields (R² values from 0.68 to 0.85). Nutrient yields were also dependent on annual precipitation of the preceding year (R² values from 0.87 to 0.91) thus enforcing the great complexity of variable mixed‐land‐use mediated source‐sink nutrient yield relationships. Study results better inform land managers and best management practices designed to mitigate nutrient pollution issues in mixed‐land‐use freshwater ecosystems. Copyright © 2015 John Wiley & Sons, Ltd.     

Electromagnetic induction prediction of soil salinity and groundwater properties in a Tunisian Saharan oasis

Abstract

Electromagnetic induction measurements (EM) were taken in a saline gypsiferous soil of the Saharan-climate Fatnassa oasis (Tunisia) to predict the electrical conductivity of saturated soil extract (ECe) and shallow groundwater properties (depth, Dgw, and electrical conductivity, ECgw) using various models. The soil profile was sampled at 0.2 m depth intervals to 1.2 m for physical and chemical analysis. The best input to predict the log-transformed soil salinity (lnECe) in surface (0–0.2 m) soil was the EMh/EMv ratio. For the 0–0.6 m soil depth interval, the performance of multiple linear regression (MLR) models to predict lnECe was weaker using data collected over various seasons and years (R _a ² = 0.66 and MSE = 0.083 dS m^-1) as compared to those collected during the same period (R _a ² = 0.97, MSE = 0.007 dS m^-1). For similar seasonal conditions, for the Dgw–EMv relationship, R ² was 0.88 and the MSE was 0.02 m for Dgw prediction. For a validation subset, the R ² was 0.85 and the MSE was 0.03 m. Soil salinity was predicted more accurately when groundwater properties were used instead of soil moisture with EM variables as input in the MLR.

Editor D. Koutsoyiannis; Associate editor K. Heal

Citation Bouksila, F., Persson, M., Bahri, A., and Berndtsson, R., 2012. Electromagnetic induction predictions of soil salinity and groundwater properties in a Tunisian Saharan oasis. Hydrological Sciences Journal, 57 (7), 1473–1486.     

Impact of septic tank systems on local groundwater quality and water supply in the Pearl River Delta,China: case study

Located at southern coast of China, the Pearl River Delta (PRD) is facing serious water problems in both quantity and quality after its rapid urbanization in the last decade. Most remarkably, the local groundwater, that was used to be the source of drinking water before the urbanization was polluted due to poor management of the septic tanks. In order to study the effects of suburban development on local groundwater flow and water quality in the PRD region, Fengcun of Guangzhou has been chosen as the study area. In Fengcun, drinking water was groundwater before the 1990s, but now piped reservoir water is used by each family because the groundwater has been polluted. This study clarifies the source and process of the groundwater pollution from septic tanks using isotopic and geochemical characteristics, especially nitrate (NO₃^?) concentrations. Water samples were collected from the wells and ponds in Fengcun in March and July 2005 and in July 2006. Based on the pe–pH diagram, NO₃^? and ammonium of groundwater are from the effect of human activities, rather than from nitrification and ammonification of N₂. NO₃^? pollution of groundwater is from point sources, and NO₃^? concentrations decrease from northeast to southwest. Groundwater is polluted rapidly by the leakage of septic tanks. NO₃^? concentrations of pollution sources were lower than 20 mg l^?1 in March 2005, but had increased to about 120 mg l^?1 in July 2006. This implies that groundwater protection should be strengthened in rural areas of the PRD. Copyright © 2007 John Wiley & Sons, Ltd.     

Spatial and temporal variations in surface water nitrate concentrations in a mixed land use catchment under humid temperate climatic conditions

Streamwater nitrate (NO^―₃) concentrations along the main stream and at the outlet of several subcatchments within the 114\3 km² Zwalm watershed in Flanders, Belgium, have been monitored regularly since 1991. Land use within the Zwalm catchment is predominantly agricultural, with forested regions in the south and urban concentrations in the north‐east of the catchment. Streamwater NO^―₃ concentrations increased with increases in stream discharge rates, but in general, discharge rate explained only about 30% of the variation in NO^―₃ concentrations. The low R² values were attributed to the observed anticlockwise hysteresis in the NO^―₃ concentration – discharge relationship and to differences in NO^―₃ concentrations between both seasonal flow and various flow regimes, with winter flow explaining 51% of the variation in NO^―₃ concentrations, whereas summer flow explained only 28% of the variation. A hypothesis was formulated in which flow regime accounts for the seasonal variation in NO^―₃ export, postulating that the catchment seasonally alternates between two hydrological stages. The first stage occurs during wet winter periods, when the catchment drains as a single source area, whereas the second stage occurs during dry summer periods, when the groundwater store disconnects into separate subcatchments. This causes NO^―₃ concentration peaks to be more delayed during summer storm events compared with winter storm events. Regarding flow regimes, differences between high and low flow conditions and between increasing and stable/decreasing flow were not as pronounced a differences between seasons. In contrast to the estimation of NO^―₃ concentrations, discharge was a strong predictor (R²= 0\71) of the NO^―₃ flux within the tributaries of the Zwalm catchment. The NO^―₃ concentrations in the main stream increased with decreasing elevation, whereas the seasonal concentration patterns along the main channel were similar to those observed at the outlet. NO^―₃ concentrations varied considerably among catchments and showed a high variability over time, although in general, the variation in NO^―₃ concentration was higher between catchments than within catchments. The impact of land use is clearly reflected in the streamwater NO^―₃ concentrations, although NO^―₃ concentration patterns were also affected by topography and, to a lesser extent, by soil type. A gradual increase in NO^―₃ concentrations at the outlet of the Zwalm catchment could be observed throughout the 1991 – 1998 study period, providing evidence for the general trends of increase in Flanders, which are attributed to the intensification of agricultural activities. Copyright © 2000 John Wiley & Sons, Ltd.     

A fuzzy‐based simulation method for modelling hydrological processes under uncertainty

In this study, a fuzzy‐based simulation method (FBSM) is developed for modelling hydrological processes associated with vague information through coupling fuzzy vertex analysis technique with distributed hydrological model. The FBSM can handle uncertainties existed as fuzzy sets in the hydrological modelling systems, and solutions under an associated number of α‐cut levels can be generated by solving 2ⁿ deterministic models. The lower reach of the Tarim River Basin in China is selected as a study case for demonstrating applicability of the proposed method. The developed model is calibrated and validated against observed groundwater elevation for four wells during the period 2000–2001, and generally performed acceptable for model Nash–Sutcliffe coefficient (R2) and correlation coefficient (R). The R2 is approximately over 0·65 and the correlation coefficient is higher than 0·90. Based on the technique of fuzzy simulation, the uncertainties of two parameters (K_H and LC) are reflected under different α‐cut levels. The results indicate that, under a lower degree of plausibility, the interval between the lower and upper bounds of the groundwater elevation is wider; conversely, a higher degree of plausibility would lead to a narrow interval. The main effect of K_H is more significant than the effect of LC at most well sites. The proposed method is useful for studying hydrological processes within a system containing multiple factors with uncertainties and providing support for identifying proper water resources management strategies. Copyright © 2010 John Wiley & Sons, Ltd.     

Identification of groundwater recharge sources and processes in a heterogeneous alluvial aquifer: results from multi‐level monitoring of hydrochemistry and environmental isotopes in a riverside agricultural area in Korea

We evaluated sources and pathways of groundwater recharge for a heterogeneous alluvial aquifer beneath an agricultural field, based on multi‐level monitoring of hydrochemistry and environmental isotopes of a riverside groundwater system at Buyeo, Korea. Two distinct groundwater zones were identified with depth: (1) a shallow oxic groundwater zone, characterized by elevated concentrations of NO₃^? and (2) a deeper (>10–14 m from the ground surface) sub‐oxic groundwater zone with high concentrations of dissolved Fe, silica, and HCO₃^?, but little nitrate. The change of redox zones occurred at a depth where the aquifer sediments change from an upper sandy stratum to a silty stratum with mud caps. The δ¹⁸O and δ²H values of groundwater were also different between the two zones. Hydrochemical and δ¹⁸O? δ²H data of oxic groundwater are similar to those of soil water. This illustrates that recharge of oxic groundwater mainly occurs through direct infiltration of rain and irrigation water in the sandy soil area where vegetable cropping with abundant fertilizer use is predominant. Oxic groundwater is therefore severely contaminated by agrochemical pollutants such as nitrate. In contrast, deeper sub‐oxic groundwater contains only small amounts of dissolved oxygen (DO) and NO₃^?. The ³H contents and elevated silica concentrations in sub‐oxic groundwater indicate a somewhat longer mean residence time of groundwater within this part of the aquifer. Sub‐oxic groundwater was also characterized by higher δ¹⁸O and δ²H values and lower d‐excess values, indicating significant evaporation during recharge. We suggest that recharge of sub‐oxic groundwater occurs in the areas of paddy rice fields where standing irrigation and rain water are affected by strong evaporation, and that reducing conditions develop during subsequent sub‐surface infiltration. This study illustrates the existence of two groundwater bodies with different recharge processes within an alluvial aquifer. Copyright © 2009 John Wiley & Sons, Ltd.     

Inorganic nitrogen retention in acid‐sensitive lakes in southern Norway and southern Ontario,Canada—a comparison of mass balance data with an empirical N retention model

In‐lake retention of inorganic nitrogen species (nitrate and ammonium) was estimated from mass balances in five acid‐sensitive lakes in southern Norway and eight in southern Ontario, Canada, to evaluate an empirical in‐lake N retention (R_N) model. This model is included in the First‐order Acidity Balance (FAB) model, which currently is used for calculation of critical acid loads and exceedances in many countries. To estimate in‐lake R_N, the FAB model uses a recommended mass transfer coefficient (S_N) of 5 m year⁻¹, which mainly is derived from NO₃⁻ mass balances in Canadian lakes. To date, the in‐lake R_N model has not been evaluated for large parts of Europe. At the Norwegian study sites receiving the highest N deposition (>120 meq m⁻² year⁻¹) the net in‐lake retention of inorganic N (TIN) exceeded the corresponding terrestrial retention by a factor of 1·1–2·6. Despite differences in N loading and hydrology at the Norwegian and Canadian sites, both the mean mass transfer coefficients for NO₃⁻ (S_NO3; 6·5 versus 5·6 m year⁻¹) and TIN (S_TIN; 7·9 versus 7·0 m year⁻¹) were of comparable magnitude. Both mean values and ranges of S_NO3 suggest that the default S_N value presently recommended for FAB model applications seems valid over a large range in N inputs and areal water loads (q_s). However, owing to the relatively few data available for lakes with high q_s values (15–150 m year⁻¹), it is recommended that more lakes within this range be included in future studies to obtain a more precise prediction of in‐lake N retention over a wide q_s gradient. Also, when considering that the FAB model treats all inorganic N leaching from a catchment as NO₃⁻, it seems reasonable to use a default S_TIN value instead of just S_NO3 when estimating in‐lake R_N. In that case, the in‐lake R_N presently calculated by the FAB model might be slightly underestimated. Copyright © 2003 John Wiley & Sons, Ltd.