Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

Emerging Tools for Continuous Nutrient Monitoring Networks: Sensors Advancing Science and Water Resources Protection

Sensors and enabling technologies are becoming increasingly important tools for water quality monitoring and associated water resource management decisions. In particular, nutrient sensors are of interest because of the well‐known adverse effects of nutrient enrichment on coastal hypoxia, harmful algal blooms, and impacts to human health. Accurate and timely information on nutrient concentrations and loads is integral to strategies designed to minimize risk to humans and manage the underlying drivers of water quality impairment. Using nitrate sensors as the primary example, we highlight the types of applications in freshwater and coastal environments that are likely to benefit from continuous, real‐time nutrient data. The concurrent emergence of new tools to integrate, manage, and share large datasets is critical to the successful use of nutrient sensors and has made it possible for the field of continuous monitoring to rapidly move forward. We highlight several near‐term opportunities for federal agencies, as well as the broader scientific and management community, that will help accelerate sensor development, build and leverage sites within a national network, and develop open data standards and data management protocols that are key to realizing the benefits of a large‐scale, integrated monitoring network. Investing in these opportunities will provide new information to guide management and policies designed to protect and restore our nation's water resources.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base‐flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite‐nitrate (NO₂‐NO₃), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO₂‐NO₃ concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed‐use and heavily impacted watersheds.     

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.     

Distribution of Organochlorine Pesticides in the Chao Phraya River, Thailand

Water samples from the Chao Phraya River, the main river in Thailand were collected and analyzed during 1988–1994. Organochlorine pesticides such as HCHs, DDTs, aldrin, dieldrin and chlordanes were determined. Aldrin and dieldrin had high frequencies of occurrence in water samples. The concentration median of the pesticides was approximately one order of magnitude higher than those of total HCHs and DDTs. Levels of aldrin were relatively high in the upstream while levels of DDTs were high in the urban area of Bangkok during 1989–1990. p,p-DDE levels were relatively higher in 1992. No clear trends in the levels of pesticides were observed.     

CADMIUM ACCUMULATION AND TOXICITY IN SUBMERGED PLANT HYDRILLA VERTICILLATA (l.f.) ROYLE

Cadmium accumulation and its toxicity in relation tochlorophyll, protein, cysteine contents and in vivo nitrate reductaseactivity were studied under controlled conditions in Hydrillaverticillata, a submerged commonly occurring macrophyte. Plants weresubjected to six different concentrations of Cd ranging from 1.0 to 25.0 µM for 24, 48, 72 and 168 h. Tissue Cd concentration was maximum (13.71 µmoles/g dw) at 25 µM background concentration. At this concentration, a decrease of approximately 79 and 72% was found in chlorophyll and protein content. In vivo nitrate reductase activity was stimulated at 1.0 µM; however, the activity gradually declined beyond this concentration. Exposure to various cadmium concentrations resulted in an increase in cysteine content of the plant.     

Investigating phosphorus limitation in a fixed bed filter with phosphorus and nitrogen profile measurements

In 2000, the European Union adopted the European Water Framework Directive (WFD) (European Commission, 2000). The WFD focuses on increasingly stringent nutrient standards including ultra low nitrogen (< 2.2 mg N-total/L) and phosphorus concentrations (< 0.15 mg total phosphorus/L) in receiving surface waters and in relevant point sources like wastewater treatment plant (WWTP) effluent. Expansion of WWTPs with advanced post-treatment processes, like effluent filtration, is widely proposed to meet possible future effluent discharge standards. When combining biological nitrate-nitrogen and chemical phosphorus removal in one filter, phosphorus limitation in the denitrifying process may occur. This study investigated where in the filter bed and under which conditions phosphorus limitation occurs. Profile measurements for nitrate, nitrite, and orthophosphorus (PO4-P) combined with chemical oxygen demand (COD) and 02 were conducted. Results showed that the required PO4-P/NOx-N ratio is approximately 0.006 mg/mg after phosphorous precipitation and flocculation. Profile measurements have proven to be an applicable and useful tool. It showed how nitrate and orthophosphorus are removed through the filter bed based on the PO4-P/NOx-N ratio. When orthophosphorus is removed more rapidly and efficiently compared to nitrate, the PO4-P/NOx-N ratio decreases. When PO4-P/NOx-N ratio thresholds are approximately 0.006 mg/mg for a certain period of time and water temperatures varied significantly, orthophosphorus limitation may occur. Changing the filter-bed configuration or decreasing the coagulant dosage can prevent limitation of the denitrifying process because of a phosphorous shortage.     

Factors diminishing the effectiveness of phosphorus loading from municipal effluent: critical information for TMDL analyses

Factors that diminish the effectiveness of phosphorus inputs from a municipal wastewater treatment facility (Metro) in contributing to phosphorus levels and its availability to support algae growth in a culturally eutrophic urban lake (Onondaga Lake, NY) were characterized and quantified. These factors included the bioavailability and settling characteristics of particulate phosphorus from this effluent, the dominant form (70%) of phosphorus in this input, and the plunging of the discharge to stratified layers in the lake. Supporting studies included: (1) chemical and morphometric characterization of the phosphorus-enriched particles of this effluent, compared to particle populations of the tributaries and lake, with an individual particle analysis technique; (2) conduct of algal bioavailability assays of the particulate phosphorus of the effluent; (3) conduct of multiple size class settling velocity measurements on effluent particles; and (4) determinations of the propensity of the discharge to plunge, and documentation of plunging through three-dimensional monitoring of a tracer adjoining the outfall. All of these diminishing effects were found to be operative for the Metro effluent in Onondaga Lake and will be integrated into a forthcoming phosphorus "total maximum daily load" analysis for the lake, through appropriate representation in a supporting mechanistic water quality model. The particulate phosphorus in the effluent was associated entirely with Fe-rich particles formed in the phosphorus treatment process. These particles did not contribute to concentrations in pelagic portions of the lake, due to local deposition associated with their large size. Moreover, this particulate phosphorus was found to be nearly entirely unavailable to support algae growth. While substantial differences are to be expected for various inputs, the effective loading concept and the approaches adopted here to assess the diminishing factors are broadly applicable.     

Impact of Climate Change on Fish Population Dynamics in the Baltic Sea: A Dynamical Downscaling Investigation

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties.