Great Bay Estuary Restoration Compendium

Single species approaches to natural resource conservation and management are now viewed as antiquated and oversimplified for dealing with complex systems. Scientists and managers who work in estuaries and other marine systems have urged adoption of ecosystem based approaches to management for nearly a decade, yet practitioners are still struggling to translate the ideas into practice. Similarly, ecological restoration projects in coastal systems have typically addressed one species or habitat. In recent years, efforts to focus on multiple species and habitats have increased. Our project developed an integrated ecosystem approach to identify multi-habitat restoration opportunities in the Great Bay estuary, New Hampshire. We created a conceptual site selection model based on a comparison of historic and modern distribution and abundance data, current environmental conditions, and expert review. Restoration targets included oysters and softshell clams, salt marshes, eelgrass beds, and seven diadromous fish species. Spatial data showing the historical and present day distributions for multiple species and habitats were compiled and integrated into a geographic information system. A matrix of habitat interactions was developed to identify potential for synergy and subsequent restoration efficiency. Output from the site selection models was considered within this framework to identify ecosystem restoration landscapes. The final products of these efforts include a series of maps detailing multi-habitat restoration opportunities extending from upland freshwater fish habitat down to the bay bottom. A companion guidance document was created to present project methods and a review of restoration methods. The authors hope that this work will help to stimulate and inform new restoration projects within the Great Bay estuarine system, and that it will serve as a foundation to be updated and improved as more information is collected

Hydrologic Modeling to Examine Land Use Change Impacts (1970’s and 2005) on the Sediment Yield and Flow Regime in Cayuga Creek, Niagara County, New York

This research aims to assess the water quality and the land use change impacts on sediment concentration and flow regime in Cayuga Creek, Niagara County, NY for two land use periods, 1970’s and 2005. The 1970’s land use, classified by the USGS, had a significant error. Therefore, the scenario of sediment yield and discharge level to land use change is more of a “what if” since the 1970’s land use was classified incorrectly. The Soil and Water Assessment Tool (SWAT)was used to simulate flows and sediment concentrations for the two land use scenarios using the same rainfall data at the upstream and downstream sites. The modeling results indicated that the discharges at the downstream site were higher than those at the upstream site for both 1970’s and 2005 land uses. The sediment concentration was higher at the downstream site than the upstream site for 1970’s land use and the result was in an opposite direction for 2005 land use. Hydrolab Datasonde 4a’s were installed at an upstream and downstream site for a ten week period in order to assess water quality. The parameters monitored were: dissolved oxygen, pH, conductivity, turbidity, and temperature. Grab samples were taken in order to examine total suspended solids levels and establish a relationship with turbidity

Water Resources Management and Modeling

Hydrology is the science that deals with the processes governing the depletion and replenishment of water resources of the earth's land areas. The purpose of this book is to put together recent developments on hydrology and water resources engineering. First section covers surface water modeling and second section deals with groundwater modeling. The aim of this book is to focus attention on the management of surface water and groundwater resources. Meeting the challenges and the impact of climate change on water resources is also discussed in the book. Most chapters give insights into the interpretation of field information, development of models, the use of computational models based on analytical and numerical techniques, assessment of model performance and the use of these models for predictive purposes. It is written for the practicing professionals and students, mathematical modelers, hydrogeologists and water resources specialists

The Effect of Hydrology on Soil Erosion

This Special Issue includes manuscripts about soil erosion and degradation processes and the accelerated rates due to hydrological processes and climate change. The new research included in this issue focuses on measurements, modeling, and experiments in field or laboratory conditions developed at different scales (pedon, hillslope, and catchment). This Special Issue received investigations from different parts of the world such as Ethiopia, Morocco, China, Iran, Italy, Portugal, Greece, and Spain, among others. We are happy to see that all papers presented findings characterized as unconventional, provocative, innovative, and methodologically new. We hope that the readers of the journal Water can enjoy and learn about hydrology and soil erosion using the published material, and share the results with the scientific community, policymakers, and stakeholders to continue this amazing adventure, facing plenty of issues and challenges

Translate Data Into Meaning: integration of meteorology and geomatics to generate meaningful information for decision makers

A variety of actors at all scales and acting in different domains such as emergency management, agriculture, sports and leisure and commercial activities, are becoming more aware of the challenges and opportunities that meteorological data analysis poses for their operational goals. The increasing availability of meteorological data coupled with a rapid improvement in technology led to the widespread dissemination of the weather information to a variety of users on a regular basis. Particularly through the internet and mobile application all users, despite their varied background, can access to big amount of data with a high potential to gather essential input that can significantly help their decisions. At the same time, simply creating and disseminating information without context does not necessarily offer an added value to sèecific users. One of the main issues is related to the scientific approach of weather analysis and to the representation of results, which are hardly understandable for non-technical users and therefore not easily usable to make decisions. As a result, there are several researches aiming at finding new ways of supporting decision making by supplying easy to use information. The main objective of this thesis is therefore to provide guidance on how to identify and characterize the needs for meaningful and usable information among various users of meteorology, including members of the public, emergency managers, other government decision makers, and private-sector entities, both direct users and intermediaries. In particular a methodology for the integration of meteorological data and GIS capabilities is investigated and applied to three different end users having similarities and differences. Scientific analysis, results and cartographic products are adapted to specific requirements, experience and perceptions of the three different users

Sustainable Reservoir Management Approaches under Impacts of Climate Change - A Case Study of Mangla Reservoir, Pakistan

Reservoir sedimentation is a major issue for water resource management around the world. It has serious economic, environmental, and social consequences, such as reduced water storage capacity, increased flooding risk, decreased hydropower generation, and deteriorated water quality. Increased rainfall intensity, higher temperatures, and more extreme weather events due to climate change are expected to exacerbate the problem of reservoir sedimentation. As a result, sedimentation must be managed to ensure the long-term viability of reservoirs and their associated infrastructure. Effective reservoir sedimentation management in the face of climate change necessitates an understanding of the sedimentation process and the factors that influence it, such as land use practices, erosion, and climate. Monitoring and modelling sedimentation rates are also useful tools for forecasting future impacts and making management decisions. The goal of this research is to create long-term reservoir management strategies in the face of climate change by simulating the effects of various reservoir-operating strategies on reservoir sedimentation and sediment delta movement at Mangla Reservoir in Pakistan (the second-largest dam in the country). In order to assess the impact of the Mangla Reservoir's sedimentation and reservoir life, a framework was developed. This framework incorporates both hydrological and morphodynamic models and various soft computing models. In addition to taking climate change uncertainty into consideration, the proposed framework also incorporates sediment source, sediment delivery, and reservoir morphology changes. Furthermore, the purpose of this study is to provide a practical methodology based on the limited data available. In the first phase of this study, it was investigated how to accurately quantify the missing suspended sediment load (SSL) data in rivers by utilizing various techniques, such as sediment rating curves (SRC) and soft computing models (SCMs), including local linear regression (LLR), artificial neural networks (ANN) and wavelet-cum-ANN (WANN). Further, the Gamma and M-test were performed to select the best-input variables and appropriate data length for SCMs development. Based on an evaluation of the outcomes of all leading models for SSL estimation, it can be concluded that SCMs are more effective than SRC approaches. Additionally, the results also indicated that the WANN model was the most accurate model for reconstructing the SSL time series because it is capable of identifying the salient characteristics in a data series. The second phase of this study examined the feasibility of using four satellite precipitation datasets (SPDs) which included GPM, PERSIANN_CDR, CHIRPS, and CMORPH to predict streamflow and sediment loads (SL) within a poorly gauged mountainous catchment, by employing the SWAT hydrological model as well as SWAT coupled soft computing models (SCMs) such as artificial neural networks (SWAT-ANN), random forests (SWAT-RF), and support vector regression (SWAT-SVR). SCMs were developed using the outputs of un-calibrated SWAT hydrological models to improve the predictions. The results indicate that during the entire simulation, the GPM shows the best performance in both schemes, while PERSIAN_CDR and CHIRPS also perform well, whereas CMORPH predicts streamflow for the Upper Jhelum River Basin (UJRB) with relatively poor performance. Among the best GPM-based models, SWAT-RF offered the best performance to simulate the entire streamflow, while SWAT-ANN excelled at simulating the SL. Hence, hydrological coupled SCMs based on SPDs could be an effective technique for simulating streamflow and SL, particularly in complex terrain where gauge network density is low or uneven. The third and last phase of this study investigated the impact of different reservoir operating strategies on Mangla reservoir sedimentation using a 1D sediment transport model. To improve the accuracy of the model, more accurate boundary conditions for flow and sediment load were incorporated into the numerical model (derived from the first and second phases of this study) so that the successive morphodynamic model could precisely predict bed level changes under given climate conditions. Further, in order to assess the long-term effect of a changing climate, a Global Climate Model (GCM) under Representative Concentration Pathways (RCP) scenarios 4.5 and 8.5 for the 21st century is used. The long-term modelling results showed that a gradual increase in the reservoir minimum operating level (MOL) slows down the delta movement rate and the bed level close to the dam. However, it may compromise the downstream irrigation demand during periods of high water demand. The findings may help the reservoir managers to improve the reservoir operation rules and ultimately support the objective of sustainable reservoir use for societal benefit. In summary, this study provides comprehensive insights into reservoir sedimentation phenomena and recommends an operational strategy that is both feasible and sustainable over the long term under the impact of climate change, especially in cases where a lack of data exists. Basically, it is very important to improve the accuracy of sediment load estimates, which are essential in the design and operation of reservoir structures and operating plans in response to incoming sediment loads, ensuring accurate reservoir lifespan predictions. Furthermore, the production of highly accurate streamflow forecasts, particularly when on-site data is limited, is important and can be achieved by the use of satellite-based precipitation data in conjunction with hydrological and soft computing models. Ultimately, the use of soft computing methods produces significantly improved input data for sediment load and discharge, enabling the application of one-dimensional hydro-morphodynamic numerical models to evaluate sediment dynamics and reservoir useful life under the influence of climate change at various operating conditions in a way that is adequate for evaluating sediment dynamics.:Chapter 1: Introduction Chapter 2:Reconstruction of Sediment Load Data in Rivers Chapter 3:Assessment of The Hydrological and Coupled Soft Computing Models, Based on Different Satellite Precipitation Datasets, To Simulate Streamflow and Sediment Load in A Mountainous Catchment Chapter 4:Simulating the Impact of Climate Change with Different Reservoir Operating Strategies on Sedimentation of the Mangla Reservoir, Northern Pakistan Chapter 5:Conclusions and Recommendation

Nonpoint Source Pollution Control Using a Multi-Objective Optimization Tool for Best Management Practices Selection and Spatial Placement in the Lower Bear River Watershed, Utah

This dissertation presents a set of approaches to help address water quality problems related to total phosphorus loads in water bodies. Water quality degradation is caused by many nonpoint sources such as agricultural runoff, fertilizers applications, and bank erosion. Three studies present methodologies for water quality protection from degradation in watersheds. The first study demonstrates the application of a watershed simulation tool that can quantify flows in the watershed, the amount of released pollutants and identify the areas contributing to the pollutants’ release in the watershed. The second study presents a simple combination tool that can pair potential management practices with the identified nonpoint sources areas to generate cost-effective combinations of management practices for reducing excess phosphorus loading to water bodies. The last study develops an optimization framework that recommends the area optimum sizes that are available for implementing management practices. These studies were applied to real-case problems to reduce excess nutrients within the Lower Bear River Watershed in northern Utah and expected to improve the management of nutrient control plans under the allocated funds

To pave or not to pave: A social landscape analysis of land use decision-making in the Lamprey River watershed

Seacoast New Hampshire\u27s population has quadrupled in four decades resulting in sprawl and increased impervious surfaces which threaten the ecological health of Great Bay. Calls for watershed-based strategies addressing growth and land use planning abound. This study addresses these challenges by examining the question of whether there is a potential for watershed base land use decision-making. Using constructivist grounded theory, this study explores the social landscape of land use decision-making in a case study of the towns of the Lamprey River watershed. The qualitative methods include semi-structured interviews with GIS based maps and content analysis in NVivo software. Results include a proposed theoretical framework which characterizes the social landscape of land use decision-making concerning community, conflict and temporo-spatial scaling. Challenges and opportunities are also identified in moving towards watershed based land use decision-making. Conclusions represent a mix of optimistic and pessimistic themes regarding current land use decision-making and suggested recommendations necessary to move towards watershed-scaled land use planning