Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58% of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and three-hour precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions

Using the soil and water assessment tool to simulate the pesticide dynamics in the data scarce Guayas River Basin, Ecuador

Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin

Addressing Uncertainty in TMDLS: Short Course at Arkansas Water Resources Center 2001 Annual Conference

Management of a critical natural resource like water requires information on the status of that resource. The US Environmental Protection Agency (EPA) reported in the 1998 National Water Quality Inventory that more than 291,000 miles of assessed rivers and streams and 5 million acres of lakes do not meet State water quality standards. This inventory represents a compilation of State assessments of 840,000 miles of rivers and 17.4 million acres of lakes; a 22 percent increase in river miles and 4 percent increase in lake acres over their 1996 reports. Siltation, bacteria, nutrients and metals were the leading pollutants of impaired waters, according to EPA. The sources of these pollutants were presumed to be runoff from agricultural lands and urban areas. EPA suggests that the majority of Americans-over 218 million-live within ten miles of a polluted waterbody. This seems to contradict the recent proclamations of the success of the Clean Water Act, the Nation\u27s water pollution control law. EPA also claims that, while water quality is still threatened in the US, the amount of water safe for fishing and swimming has doubled since 1972, and that the number of people served by sewage treatment plants has more than doubled

Models for Analyzing Agricultural Nonpoint-Source Pollution

Mathematical models are useful means of analyzing agricultural nonpoint-source pollution. This review summarizes and classifies many of the available chemical transport and planning and management models. Chemical transport models provide estimates of chemical losses from cropland to water bodies; they include continuous simulation, discrete simulation, and functional models. A limited number of transport models have been validated in field studies, but none has been tested extensively. Planning and management models, including regional impact, watershed planning and farm management models, are used to evaluate tradeoffs between environmental and agricultural production objectives. Although these models are in principle the most useful for policy making, their economic components are much better developed than components for predicting water pollution

Evaluating River Water Quality Modelling Uncertainties at Multiple Time and Space Scales

Maintaining healthy river ecosystems is crucial for sustaining human needs and biodiversity. Therefore, accurately assessing the ecological status of river systems and their response to short and long-term pollution events is paramount. Water quality modelling is a useful tool for gaining a better understanding of the river system and for simulating conditions that may not be obtained by field monitoring. Environmental models can be highly unreliable due to our limited knowledge of environmental systems, the difficulty of mathematically and physically representing these systems, and limitations to the data used to develop, calibrate and run these models. The extensive range of physical, biochemical and ecological processes within river systems is represented by a wide variety of models: from simpler one-dimensional advection dispersion equation (1D ADE) models to complex eutrophication models. Gaining an understanding of uncertainties within catchment water quality models across different spatial and temporal scales for the evaluation and regulation of water compliance is still required. Thus, this thesis work 1) evaluates the impact of parameter uncertainty from the longitudinal dispersion coefficient on the one-dimensional advection-dispersion model and water quality compliance at the reach scale and sub-hourly scale, 2) evaluates the impact of input data uncertainty and the representation of ecological processes on an integrated catchment water quality model, and 3) evaluates the impact of one-dimensional model structures on water quality regulation. Findings from this thesis stress the importance of longitudinal mixing specifically in the sub daily time scales and in-between 10s of meters to 100s of meters. After the sub daily time scale, other biological and ecological processes become more important than longitudinal mixing for representing the seasonal dynamics of dissolved oxygen (DO). The thorough representation of the dominant ecological processes assists in obtaining accurate seasonal patterns even under input data variability. Furthermore, the use of incorrect model structures for water quality evaluation and regulation leads to considerable sources of uncertainty when applying duration over threshold regulation within the first 100s of meters and sub hourly time scale

Identifikation von Schadstoffeinleitungen und angepasstes Design eines Monitoringnetzwerkes in Ästuaren

In the last decades there have been thousands of accidental pollution spills as well as intentional illegal discharges into surface waters all over the world. The identification of pollution source parameters (e.g. the source location) has often proven difficult and heavily depends on measured pollutant concentration data collected after the incident. This thesis investigates how an adapted monitoring design can improve the identification of source parameters after a spill incident, especially in the case of estuaries. Initially, the effect of the spatial and temporal monitoring design on parameter identifiability is analyzed based on a synthetic unidirectional (river) as well as a bidirectional (estuary) test case is carried out. While the transport processes in the river could be represented by an analytical solution of the 2D advection-dispersion-reaction equation, to take into account the tidal dynamics in the estuary, a numerical transport model had to be set up with the Delft3D software suite. The results of the analysis indicate that parameter dependencies exist between different source parameters, which can weaken the identifiability of the individual parameters. However, an appropriate monitoring design can improve parameter identifiability and consequently lead to more reliable parameter estimates. To identify the source parameters after potential pollution incidents, two optimization approaches were selected in this work, which were initially applied to the synthetic bidirectional test case. Both approaches achieved very good results for both perfect and noise perturbed monitoring data. Subsequently, both optimization approaches were transferred to a real-world estuary, the Thi Vai Estuary, located in South Vietnam. To simulate pollution scenarios, a 2D hydrodynamic transport model was set up in Delft3D and calibrated based on monitoring data collected in the EWATEC-COAST research project. The synthetically generated monitoring data of an optimized monitoring network were then used to identify several theoretical spill incidents in the Thi Vai Estuary. Both optimization approaches performed generally well and could correctly identify the source parameters in 80% of the considered scenarios.In den letzten Jahrzehnten kam es weltweit immer wieder zu zahlreichen Unfällen und illegalen Einleitungen, bei denen Schadstoffe in Oberflächengewässer eingeleitet wurden. Die Identifikation der Einleitungsparameter (u.a. des Ortes) stellt hierbei eine große Herausforderung dar und hängt stark von den gesammelten Konzentrationsdaten ab, die nach dem Schadstoffeintrag erhoben wurden. Daher bestand das Hauptziel der Dissertation darin, die Identifikation der Einleitungsparameter im Falle eines Schadstoffeintrags durch ein angepasstes Monitoringdesign insbesondere in Ästuaren zu verbessern. Zunächst wurde, aufbauend auf einen synthetischen Fluss- und Ästuarabschnitt, der Einfluss des räumlichen und zeitlichen Monitoringdesigns auf die Identifizierbarkeit der Einleitungsparameter analysiert. Während die Transportprozesse im Fluss durch eine analytische Lösung der 2D Advektions-Dispersions-Reaktions-Gleichung abgebildet werden konnten, musste für das Ästuar zur Berücksichtigung des Tideeinflusses ein numerisches Transportmodell mit der Software Delft3D aufgebaut werden. Die Ergebnisse der Analyse zeigen, dass zwischen bestimmten Einleitungsparametern Interaktionen bestehen, die die Identifizierbarkeit der einzelnen Parameter schwächen. Ein angepasstes Monitoringdesign kann die Identifizierbarkeit allerdings verbessern und folglich zu einer zuverlässigeren Parameterschätzung führen. Zur Identifikation der Einleitungsparameter nach potentiellen Schadstoffeinträgen wurden in dieser Arbeit zwei verschiedene Optimierungsansätze ausgewählt, die zunächst auf den synthetischen Ästuarabschnitt angewandt wurden. Hier konnten durch beide Ansätze sowohl für perfekte als auch fehlerbehaftete Messdaten sehr gute Ergebnisse erzielt werden. Anschließend wurden beide Optimierungsansätze auf einen realen Ästuar, den Thi Vai Ästuar in Südvietnam übertragen. Zur Simulation verschiedener Einleitungsszenarien wurde ein 2D hydrodynamisches Transportmodell in Delft3D aufgebaut und mit Messdaten, die im Forschungsprojekt EWATEC-COAST erhoben wurden, kalibriert. Die synthetisch generierten Monitoringdaten eines optimalen Monitoringnetzwerkes dienten anschließend zur Identifikation mehrerer theoretischer Einleitungsszenarien. Beide Optimierungsansätze zeigten gute Ergebnisse und konnten die Einleitungsparameter in 80% der betrachteten Szenarien korrekt bestimmen

The use of a water quality model to evaluate the impacts of combined sewer overflows on the lower Hudson River

CSO discharges have long been recognized as a significant source of water pollution. While many sources of water pollution have been controlled over the past 20 years, CSOs continue to be a main environmental concern in several areas, especially in old cities. In the past, most CSO research focused on the CSO control processes, including floatables and suspended solids removal. Few studies have been conducted in the area of the impacts of CSO discharge on the receiving water quality. To achieve this purpose, a powerful water-modeling tool, WASP 6.1, is utilized in this study. The Lower Hudson River is selected as a case study. Data are collected from the US EPA, USGS, NYC DEP, and NJ DEP. After calibration, the receiving water quality model can be used to study the impacts of CSO with a series of scenarios, which include the major factors that would affect the water quality of the receiving water. DO, BOD, ammonia, fecal coliform, and mercury are the reference pollutants discussed in this study. The simulation results are able to predict the effect of various CSO abatement alternatives on water quality and to be used in the water quality management and planning processes

A review on the integration of artificial intelligence into coastal modeling

Author name used in this publication: Kwokwing Chau2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A mathematical model development for simulating in-stream processes of non-point source pollutants.

Doctoral Degree. University of KwaZulu-Natal, Durban.In coming years, chronic water stress is inevitable owing to the unavailability of fresh water. This situation is occasioned by rapid urbanisation, climate change, rising food demand, and production. The increasing rate of water scarcity associated with water pollution problems, makes water quality management an issue of great concern. Rivers owe their existence to the relationship of rainfalls, soil properties and land use within a catchment. The entire hydrological processes that occur in the catchment area has a direct effect on occurrences and quality of the rivers there-in. A principal part of the hydrological cycle is runoff generation. Runoff characterises soil erosion, sediment transport, pollutants and chemicals all otherwise referred to as non-point source pollutants and released into water bodies. Most non-point source pollutants are generated from agricultural fields, informal settlements, mining fields, industrial areas, and roads. These sources produce increased nutrient concentrates (sewage effluent from informal settlements and fertilisers from agricultural fields) and toxic substances which alter the water quality in uncertain quantities. This affects aquatic biota and ultimately human health negatively. Non-point source pollution is a major source of water quality degradation globally and is the single most significant threat to subsurface and surface sources of usable water. Developed countries, unlike many developing countries, have long sought ways to stop the release of non-point source pollution directly into natural rivers through the establishment of best management practices but unfortunately with little success in actual practice. Numerous non-point source models exist which are basically watershed based and are limited to simulate the in-stream processes of non-point source pollution in water channels. Most existing non-point source models are site-specific, cumbersome to manipulate, need high-level operational skills and extensive data sets. Consequently, these models are difficult to use in areas apart from where they were developed and with limited data sets, as is the case with developing countries. Hence, to develop a non-point source pollution model that would adequately and effectively, simulate non-point source pollution in water bodies, towards restoring good river health is needed. This is required to enhance the proper monitoring and remediation of water sources affected by Non-Point Source Pollution especially in areas that have scarce data. Using the concept of the Hybrid Cells in Series model in this study, a hydrodynamic riverine Non-point source pollution model is conceptualized to simulate conservative pollutants in natural rivers. The Hybrid Cells in Series model was conceptualized to address the limitations identified in the classical advection dispersion model which is the foundation for all water quality modelling. The proposed model is a three-parameter model made up of three zones, which describes pure advection through time delay in a plug zone, and advection and dispersion occurring in two other thoroughly mixed zones linked in sequence. The model considers lateral inflow and pollutant loading along the river reach in addition to the point source pollutant entry and flow from upstream stations. The model equation for water quality along with hydrodynamic equation has been solved analytically using Laplace Transform. The derived mathematical formulation is appropriately coded, using FORTRAN programming language. Other components such as hyporheic exchange process and first order kinetic reaction simulations are incorporated to the proposed model. The response of these models matches the numerical solution of the classical Advection Dispersion Equation model satisfactorily when compared. The potential of the proposed model is tested using field data obtained from verifiable existing literature. A performance evaluation at 95 percent confidence is carried out. The correlation results of the observed and simulated data are seen to be in good agreement. The breakthrough curves obtained from the proposed model shows its capability to simulate Non-point source pollution transport in natural rivers effectively. The simplicity of the Hybrid Cells in Series model makes it a viable model for simulating contaminant transport from non-point sources. As the model has been validated using recorded data collected from the field for a specific tracer injection event, it is imperative to carry out investigation on changes in model parameters before, during and after storm events. However, this study adequately addressed and attempted to develop, validate new model components for simulating non-point source pollutant transport processes in stream

A hydroinformatic tool for sustainable estuarine management

Book edited by Harry Edmar Schulz, André Luiz Andrade Simões and Raquel Jahara Lobosco• Short characterization of estuarine systems and the Mondego estuary (Portugal); • Research methods: sampling program description and mathematical integrated modelling (hydroinformatic tool presentation) • Hydrodynamic estuarine modelling, including calibration and validation procedures; • New approach for tidal prism and flow estimation in estuaries, using mathematical modelling. • Estuarine dispersion conditions, including the assessment of saline wedge propagation into the Mondego estuary. • Influence of tides and freshwater discharges on residence time spatial distribution in the Mondego estuary