Healthy Waters Basin Appraisal

Provide advice and technical support to DERM in the development of the Healthy Headwaters Program.

Enhancing economic input to the CQSS2 Project report. Commissioned by the Fitzroy Basin Association.

The Fitzroy Basin is the second largest catchment area in Australia covering 143,00 km² and is the largest catchment for the Great Barrier Reef lagoon (Karfs et al., 2009). The Great Barrier Reef is the largest reef system in the world; it covers an area of approximately 225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland Coast (Haynes et al., 2007). The prime determinant for the changes in water quality have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al., 2009). In response to the depletion of water quality in the reef, in 2003 a Reef Water Quality plan was developed by the Australian and Queensland governments. The plan targets as a priority sediment contributions from grazing cattle in high risk catchments (The State of Queensland and Commonwealth of Australia, 2003). The economic incentive strategy designed includes analysing the costs and benefits of best management practice that will lead to improved water quality (The State of Queensland and Commonwealth of Australia, 2003).

Natural regeneration and ecological succession in Pinus kesiya watershed plantations in northern Thailand : Implications on plantation management

Establishment of Pinus kesiya Roy. ex Gord. plantations in Thailand began in the 1960s by the Royal Forest Department. The aim was to reforest abandoned swidden areas and grasslands in order to reduce erosion and to produce timber and fuel wood. Today there are about 150, 000 ha of P. kesiya plantations in northern Thailand. Most of these plantations cannot be harvested due to a national logging ban. Previous studies have suggested that Pinus kesiya plantations posses a capability as a foster environment for native broadleaved tree species, but little is known about the extent of regeneration in these plantations. The general aim of the study was to clarify the extent of forest regeneration and interactions behind it in Pinus kesiya plantations of the Ping River basin, northern Thailand. Based on the results of this study and previous literature, forest management proposals were produced for the area studied. In four different pine plantation areas, a total of seven plantations were assessed using systematic data collection with clustered circular sample plots. Vegetation and environmental data were statistically analysed, so as to recognise the key factors affecting regeneration. Regeneration had occurred in all plantations studied. Regeneration of broadleaved trees was negatively affected by forest fire and canopy coverage. A high basal area of mature broadleaved trees affected the regeneration process positively. Forest fire disturbance had a strong effect also on plantation structure and species composition. Because of an unclear future forest management setting as regards forest laws in Thailand, a management system that enables various future utilisation possibilities and emphasises local participation is recommended for P. kesiya watershed platations of northern Thailand.

Lake sediment research as a part of lake management - case studies and implications from southern Finland

In Finland one of the most important current issues in the environmental management is the quality of surface waters. The increasing social importance of lakes and water systems has generated wide-ranging interest in lake restoration and management, concerning especially lakes suffering from eutrophication, but also from other environmental impacts. Most of the factors deteriorating the water quality in Finnish lakes are connected to human activities. Especially since the 1940's, the intensified farming practices and conduction of sewage waters from scattered settlements, cottages and industry have affected the lakes, which simultaneously have developed in to recreational areas for a growing number of people. Therefore, this study was focused on small lakes, which are human impacted, located close to settlement areas and have a significant value for local population. The aim of this thesis was to obtain information from lake sediment records for on-going lake restoration activities and to prove that a well planned, properly focused lake sediment study is an essential part of the work related to evaluation, target consideration and restoration of Finnish lakes. Altogether 11 lakes were studied. The study of Lake Kaljasjärvi was related to the gradual eutrophication of the lake. In lakes Ormajärvi, Suolijärvi, Lehee, Pyhäjärvi and Iso-Roine the main focus was on sediment mapping, as well as on the long term changes of the sedimentation, which were compared to Lake Pääjärvi. In Lake Hormajärvi the role of different kind of sedimentation environments in the eutrophication development of the lake's two basins were compared. Lake Orijärvi has not been eutrophied, but the ore exploitation and related acid main drainage from the catchment area have influenced the lake drastically and the changes caused by metal load were investigated. The twin lakes Etujärvi and Takajärvi are slightly eutrophied, but also suffer problems associated with the erosion of the substantial peat accumulations covering the fringe areas of the lakes. These peat accumulations are related to Holocene water level changes, which were investigated. The methods used were chosen case-specifically for each lake. In general, acoustic soundings of the lakes, detailed description of the nature of the sediment and determinations of the physical properties of the sediment, such as water content, loss on ignition and magnetic susceptibility were used, as was grain size analysis. A wide set of chemical analyses was also used. Diatom and chrysophycean cyst analyses were applied, and the diatom inferred total phosphorus content was reconstructed. The results of these studies prove, that the ideal lake sediment study, as a part of a lake management project, should be two-phased. In the first phase, thoroughgoing mapping of sedimentation patterns should be carried out by soundings and adequate corings. The actual sampling, based on the preliminary results, must include at least one long core from the main sedimentation basin for the determining the natural background state of the lake. The recent, artificially impacted development of the lake can then be determined by short-core and surface sediment studies. The sampling must be focused on the basis of the sediment mapping again, and it should represent all different sedimentation environments and bottom dynamic zones, considering the inlets and outlets, as well as the effects of possible point loaders of the lake. In practice, the budget of the lake management projects of is usually limited and only the most essential work and analyses can be carried out. The set of chemical and biological analyses and dating methods must therefore been thoroughly considered and adapted to the specific management problem. The results show also, that information obtained from a properly performed sediment study enhances the planning of the restoration, makes possible to define the target of the remediation activities and improves the cost-efficiency of the project.

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)