Environmental factors and uncertainty in fisheries management in the northern Baltic Sea

The Baltic Sea is a geologically young, large brackish water basin, and few of the species living there have fully adapted to its special conditions. Many of the species live on the edge of their distribution range in terms of one or more environmental variables such as salinity or temperature. Environmental fluctuations are know to cause fluctuations in populations abundance, and this effect is especially strong near the edges of the distribution range, where even small changes in an environmental variable can be critical to the success of a species. This thesis examines which environmental factors are the most important in relation to the success of various commercially exploited fish species in the northern Baltic Sea. It also examines the uncertainties related to fish stocks current and potential status as well as to their relationship with their environment. The aim is to quantify the uncertainties related to fisheries and environmental management, to find potential management strategies that can be used to reduce uncertainty in management results and to develop methodology related to uncertainty estimation in natural resources management. Bayesian statistical methods are utilized due to their ability to treat uncertainty explicitly in all parts of the statistical model. The results show that uncertainty about important parameters of even the most intensively studied fish species such as salmon (Salmo salar L.) and Baltic herring (Clupea harengus membras L.) is large. On the other hand, management approaches that reduce uncertainty can be found. These include utilising information about ecological similarity of fish stocks and species, and using management variables that are directly related to stock parameters that can be measured easily and without extrapolations or assumptions.

Optimal crop planning and conjunctive use of water resources in a coastal river basin

Due to increasing trend of intensive rice cultivation in a coastal river basin, crop planning and groundwater management are imperative for the sustainable agriculture. For effective management, two models have been developed viz. groundwater balance model and optimum cropping and groundwater management model to determine optimum cropping pattern and groundwater allocation from private and government tubewells according to different soil types (saline and non-saline), type of agriculture (rainfed and irrigated) and seasons (monsoon and winter). A groundwater balance model has been developed considering mass balance approach. The components of the groundwater balance considered are recharge from rainfall, irrigated rice and non-rice fields, base flow from rivers and seepage flow from surface drains. In the second phase, a linear programming optimization model is developed for optimal cropping and groundwater management for maximizing the economic returns. The models developed were applied to a portion of coastal river basin in Orissa State, India and optimal cropping pattern for various scenarios of river flow and groundwater availability was obtained.

Simulated water resource impacts and livelihood implications of stakeholder-developed scenarios in the Jaldhaka Basin, India

This paper shows how multidisciplinary research can help policy makers develop policies for sustainable agricultural water management interventions by supporting a dialogue between government departments that are in charge of different aspects of agricultural development. In the Jaldhaka Basin in West Bengal, India, a stakeholder dialogue helped identify potential water resource impacts and livelihood implications of an agricultural water management rural electrification scenario. Hydrologic modelling demonstrated that the expansion of irrigation is possible with only a localized effect on groundwater levels, but cascading effects such as declining soil fertility and negative impacts from agrochemicals will need to be addressed.

Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources

Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

Surface freshwater storage and variability in the Amazon basin from multi-satellite observations, 1993-2007

The amount of water stored and moving through the surface water bodies of large river basins (river, floodplains, wetlands) plays a major role in the global water and biochemical cycles and is a critical parameter for water resources management. However, the spatiotemporal variations of these freshwater reservoirs are still widely unknown at the global scale. Here, we propose a hypsographic curve approach to estimate surface freshwater storage variations over the Amazon basin combining surface water extent from a multi-satellite-technique with topographic data from the Global Digital Elevation Model (GDEM) from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Monthly surface water storage variations for 1993-2007 are presented, showing a strong seasonal and interannual variability, and are evaluated against in situ river discharge and precipitation. The basin-scale mean annual amplitude of similar to 1200 km(3) is in the range of previous estimates and contributes to about half of the Gravity Recovery And Climate Experiment (GRACE) total water storage variations. For the first time, we map the surface water volume anomaly during the extreme droughts of 1997 (October-November) and 2005 (September-October) and found that during these dry events the water stored in the river and floodplains of the Amazon basin was, respectively, similar to 230 (similar to 40%) and 210 (similar to 50%) km(3) below the 1993-2007 average. This new 15 year data set of surface water volume represents an unprecedented source of information for future hydrological or climate modeling of the Amazon. It is also a first step toward the development of such database at the global scale.

Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Water resource records of the Econfina Creek Basin area, Florida

The Econfina Creek basin area in northwestern Florida, which includes Bay County, southeastern Washiigton County, and parts of Calhoun, Gulf, and Jackson counties is shown in figure 1. The basin has an abundant supply of ground water and surface water of good quality. This determination is based on a three-year investigation of the water resources of the basin by the U. S. Geological Survey in cooperation with the Division of Geology, Florida Board of Conservation, during the period from October 1961 through June 1964. The purpose of this report is to assemble the basic data collected during this investigation for those persons interested in water development or management in this basin. (Document has 131 pages.)

Low streamflow in the Myakka River Basin Area in Florida

The Sarasota-Manatee area is a water-short area and the study was undertaken in 1963 in order to determine the storage capability and discharge rates of the Myakka water shed. It was found that many of the streams of the water shed were virtually dry during part of every year. However, the basins of the Myakka lakes, through which the river flows offer some storage potential, that if properly developed would provide a continuance drift of about seven million gallons of water per day of good quality water that would be high in color and temperature upon occasion. With reasonable treatment some of this water could be used to meet the present needs of the rapidly expanding coastal areas. (PDF contains 40 pages.)

Adsorptive Media Investigations and Testing for Improved Performance of Stormwater Treatment Systems in the Tahoe Basin

Retrofit activities, such as improving hydrology and incorporating more advanced treatment methods into systems where feasible, may improve phosphorus (P) removal performance of current Best Management Practices (BMPs). In the recent past, chemical treatment systems such as chemical dosing and the use of adsorptive media have become more prevalent for treating stormwater and hold promise for improving the P removal performance of stormwater treatment BMPs (Bachand et al., 2005; Patel et al., 2005). Our primary objective for this project has been to investigate whether adsorptive media hold any promise for improving P removal performance of stormwater basins and treatment wetlands at Lake Tahoe.... (PDF contains 99 pages)

BMP treatment technologies, monitoring needs, and knowledge gaps: status of the knowledge and relevance within the Tahoe Basin

This Technical memorandum fulfills Task 2 for Agreement 03-495 between El Dorado County and the Office of Water Programs at California State University Sacramento and their co-authors, Bachand & Associates and the University of California Tahoe Research Group: 1) a review of current stormwater treatment Best Management Practices (BMP) in the Tahoe Basin and their potential effectiveness in removing fine particles and reducing nutrient concentrations; 2) an assessment of the potential for improving the performance of different types of existing BMPs through retrofitting or better maintenance practices; 3) a review of additional promising treatment technologies not currently in use in the Tahoe Basin; and 4) a list of recommendations to help address the knowledge gaps in BMP design and performance. ... (PDF contains 67 pages)

Preliminary studies on bamboo floating cage and net enclosure culture in Kainji Lake basin

The main objective of this paper is to introduce bamboo floating cage and net enclosure fish culture technology aimed at producing fish from almost all available inland bodies of water in Nigeria. The experimental approach embarked upon at Kainji Lake Research Institute is discussed. Results obtained from these experiments would help in identifying the inherent problems of this culture system and in determining the urgently needed information that will serve as management and production guidelines for adapting the technology to local conditions of varying ecological characteristics in Nigeria. Ultimately, the project is aimed at increasing the productivity of fishermen/fish farmers and hastening the development of rural communities

Economic analysis of utilizing Kainji gas kiln for fish smoking in the Kainji Lake Basin of Nigeria

Marketing of smoked fish in the Kainji Lake Basin (Nigeria) has been found to be complex, traditional and inefficient. It is also said to be limited in scope due to poor handling and processing techniques, lack of storage facilities and inadequate marketing informations. The invention of Kainji gas kiln has been found suitable to overcoming poor handling and processing techniques. This paper discusses the feasibility of operating Kainji gas kiln commercially supported with adequate storage facilities and competent management hands. The financial indicators of net present value (NPV), 47,481.11, Internal rate of return (IRR) 24% and payback period of 2.3 years that are calculated confirmed that the commercial use of Kainji gas kiln is indeed profitably feasible

Media of communication among fishermen around Kainji Lake basin

The findings are presented of a study conducted in the framework of the Nigerian-German Kainji Lake Fisheries Promotion Project to examine the role and structure of communication in fishing villages around Kainji Lake in Nigeria. The major aim was to be able to utilize the knowledge at a later stage in the project cycle to pass on fisheries extension messages to fishing communities. The study had the following terms of reference: 1) describe the structure and processes of communication of fishermen around Kainji Lake; 2) identify the formal and informal media of communication used by the fishermen to communicate information concerning their job; 3) describe the problems inhibiting usage of the different media identified; 4) ascertain the extent of use of mass media by fishermen around the lake; and, 5) identify acceptable ways by which fisheries information can be repackaged for the use of extension workers. (PDF contains 58 pages)