Trace metals in interstitial waters from sandstones: acidic inputs to shallow groundwaters

There is some evidence from southern Britain that shallow groundwaters in non-carbonate lithologies may be affected by acidic deposition. To investigate this, interstitial water profiles down to 12 m have been obtained from unsaturated sands or semi-consolidated sandstones from the Folkestone Beds (Lower Greensand) of Surrey and the Sherwood Sandstone of the West Midlands. The pH of the interstitial waters generally increased with depth and reflected an increase in the base saturation of the exchange complex. Beneath the highly acidic surface soil horizons (pH 3.0-3.5), interstitial waters with a pH of 4.0-4.5 were found down to depths of several metres. The pH progressively increased to around pH 5.5 because of base cation desorption and the weathering of silicate minerals. High concentrations of aluminium (10-20 mg litre(-1)) and other metals (Fe, Mn, Cu, Ni, Co, Zn, Be) were found in the interstitial water in the upper unsaturated zone. Most metal concentrations were strongly pH-dependent but also reflected the geochemical characteristics of the parent sands or sandstones. H+ and trace element concentrations were slightly higher beneath areas of afforestation than beneath heathland. The downward fluxes of solutes have been estimated using rainfall-derived chloride as a non-reactive solute. The profiles retain a record of 10-20 years input allowing the past inputs from SO4 and other species to be estimated using solute/chloride ratios. Cation exchange sites are probably depleted over a period of decades and there can be a significant decrease in the unsaturated zone pH as a result of increased or sustained acidic deposition. The shallow groundwater environment (0-15 m) in non-carbonate terrains is therefore a sensitive environment where high metal concentrations may be generated and may ultimately lead to water quality problems in shallow water supplies.     

A review of the drivers of 200 years of wetland degradation in the Mekong Delta of Vietnam

This paper examines the anthropogenic factors that have contributed to wetland loss and degradation in the Mekong Delta, Vietnam from 1816 AD to present. Our analysis is framed over five historical periods and highlights the role that seven drivers of wetland degradation have played in the Mekong Delta, including: resettlement and economic development policies; population growth and urbanization; demand for food and reclaiming wetland for agriculture; construction of canals construction of dykes flood protection systems; expansion of travel systems (waterway and roads); and exploitation of wetland natural resources. Of these, government policies for resettlement and economic development seem to have had the greatest impact on wetland loss and degradation in the Mekong Delta throughout the course of history. As a result of these factors, only 0.068 million hectares of the original 4.0 million hectares of the Mekong Delta currently remains as primary swamp forest ecosystem. History suggests that future management of the Mekong Delta should take a holistic approach that includes a better understanding of the implications of past decisions on wetland loss.     

Applying Statistical Causal Analyses to Agricultural Conservation: A Case Study Examining P Loss Impacts

Estimating the effect of agricultural conservation practices on reducing nutrient loss using observational data can be confounded by factors such as differing crop types and management practices. As we may not have the full knowledge of these confounding factors, conventional statistical meta‐analysis methods can be misleading. We discuss the use of two statistical causal analysis methods for quantifying the effects of water and soil conservation practices in reducing P loss from agricultural fields. With the propensity score method, a subset of data was used to form a treatment group and a control group with similar distributions of confounding factors. With the multilevel modeling method, data were stratified based on important confounding factors, and the conservation practice effect was evaluated for each stratum. Both methods resulted in similar estimates of the conservation practice effect (total P load reduction avg. ~70%). In addition, both methods show evidence of conservation practices reducing the incremental increase in total P export per unit increase in fertilizer application. These results are presented as examples of the types of outcomes provided by statistical causal analyses, not to provide definitive estimates of P loss reduction. The enhanced meta‐analysis methods presented within are applicable for improved assessment of agricultural practices and their effects and can be used for providing realistic parameter values for watershed‐scale modeling.     

Predicting the biological condition of streams: use of geospatial indicators of natural and anthropogenic characteristics of watersheds

We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments.     

Incorporating stakeholder decision support needs into an integrated regional Earth system model

A new modeling effort exploring the opportunities, constraints, and interactions between mitigation and adaptation at regional scale is utilizing stakeholder engagement in an innovative approach to guide model development and demonstration, including uncertainty characterization, to effectively inform regional decision making. This project, the integrated Regional Earth System Model (iRESM), employs structured stakeholder interactions and literature reviews to identify the most relevant adaptation and mitigation alternatives and decision criteria for each regional application of the framework. The information is used to identify important model capabilities and to provide a focus for numerical experiments. This paper presents the stakeholder research results from the first iRESM pilot region. The pilot region includes the Great Lakes Basin in the Midwest portion of the United States as well as other contiguous states. This geographic area (14 states in total) permits cohesive modeling of hydrologic systems while also providing strong gradients in climate, demography, land cover/land use, and energy supply and demand. The results from the stakeholder research indicate that, for this region, iRESM should prioritize addressing adaptation alternatives in the water resources, urban infrastructure, and agriculture sectors, including water conservation, expanded water quality monitoring, altered reservoir releases, lowered water intakes, urban infrastructure upgrades, increased electric power reserves in urban areas, and land use management/crop selection changes. For mitigation in this region, the stakeholder research implies that iRESM should focus on policies affecting the penetration of renewable energy technologies, and the costs and effectiveness of energy efficiency, bioenergy production, wind energy, and carbon capture and sequestration.     

Evaluation of a Watershed Model for Estimating Daily Flow Using Limited Flow Measurements1

Abstract: The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash‐Sutcliffe model Efficiency (NSE) and mean relative error values of daily flow estimations were 0.66 and 15% for calibration, and 0.56 and 4% for validation, respectively. Also, further evaluation of the model’s estimation of flow at multiple locations was conducted with parametric paired t‐test and nonparametric sign test at a 95% confidence level. Among the five main stem stations, four stations were statistically shown to have good agreement between predicted and measured flows. SWAT underestimated the flow of the fifth main stem station possibly because of the existence of complex flood control measures near to the station. SWAT estimated the daily flow at one tributary station well, but with relatively large errors for the other two tributaries. The spatial pattern of predicted flows matched the measured ones well. Overall, it was concluded from the graphical comparisons and statistical analyses of the model results that SWAT was capable of reproducing continuous daily flows based on limited flow data as is the case in the UOC watershed.     

EFFECTS OF CLIMATE CHANGE ON WATER RESOURCES IN THE DELAWARE RWER BASIN1

ABSTRACT: The effects of potential climate change on water resources in the Delaware River basin were determined. The study focused on two important water-resource components in the basin: (1) storage in the reservoirs that supply New York City, and (2) the position of the salt front in the Delaware River estuary. Current reservoir operating procedures provide for releases from the New York City reservoirs to maintain the position of the salt front in the estuary downstream from freshwater intakes and ground-water recharge zones in the Philadelphia metropolitan area. A hydrologic model of the basin was developed to simulate changes in New York City reservoir storage and the position of the salt front in the Delaware River estuary given changes in temperature and precipitation. Results of simulations indicated that storage depletion in the New York City reservoirs is a more likely effect of changes in temperature and precipitation than is the upstream movement of the salt front in the Delaware River estuary. In contrast, the results indicated that a rise in sea level would have a greater effect on movement of the salt front than on storage in the New York City reservoirs. The model simulations also projected that, by decreasing current mandated reservoir releases, a balance can be reached wherein the negative effects of climate change on storage in the New York City reservoirs and the position of the salt front in the Delaware River estuary are minimized. Finally, the results indicated that natural variability in climate is of such magnitude that its effects on water resources could overwhelm the effects of long-term trends in precipitation and temperature.     

生态环境与洪旱灾害

作者将自然运动与人类活动、生态环境与气候结合起来研究，求索洪旱灾害之谜，着重探讨了其中多种生态环境因素。由大灾后的反思，找出灾害加剧的人为原因是：人中激增、生态危机、水利失修等，提出必须加强防灾减灾的对策研究。     

A Biological Assessment of Streams in the Eastern United States Using a Predictive Model for Macroinvertebrate Assemblages1

Abstract: A predictive model (RIVPACS‐type) for benthic macroinvertebrates was constructed to assess the biological condition of 1,087 streams sampled throughout the eastern United States from 1993‐2003 as part of the U.S. Geological Survey’s National Water‐Quality Assessment Program. A subset of 338 sites was designated as reference quality, 28 of which were withheld from model calibration and used to independently evaluate model precision and accuracy. The ratio of observed (O) to expected (E) taxa richness was used as a continuous measure of biological condition, and sites with O/E values <0.8 were classified as biologically degraded. Spatiotemporal variability of O/E values was evaluated with repeated annual and within‐site samples at reference sites. Values of O/E were regressed on a measure of urbanization in three regions and compared among streams in different land‐use settings. The model accurately predicted the expected taxa at validation sites with high precision (SD = 0.11). Within‐site spatial variability in O/E values was much larger than annual and among‐site variation at reference sites and was likely caused by environmental differences among sampled reaches. Values of O/E were significantly correlated with basin road density in the Boston, Massachusetts (p < 0.001), Birmingham, Alabama (p = 0.002), and Green Bay, Wisconsin (p = 0.034) metropolitan areas, but the strength of the relations varied among regions. Urban streams were more depleted of taxa than streams in other land‐use settings, but larger networks of riparian forest appeared to mediate biological degradation. Taxa that occurred less frequently than predicted by the model were those known to be generally intolerant of a variety of anthropogenic stressors.