964 resultados para SUL RIVER-BASIN


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The physicochemical interactions between water, sediment and soil deeply influence the formation and development of the ecosystem. In this research, different freshwater, brackish and saline subaqueous environments of Northern Italy were chosen as study area to investigate the physicochemical processes which occur at the interface between water and sediments, as well as the effects of soil submergence on ecosystem development. In the freshwater system of the Reno river basin, the main purpose was to define the heavy metals hazard in water and sediments of natural and artificial water courses. Heavy metals partitioning and speciation allowed to assess the environmental risk linked to the critical action of dredging canal sediments, for the maintenance of the hydraulic safety of plain lands. In addition, some bioremediation techniques were experimented for protecting sediments from heavy metals contamination, and for giving an answer to the problem of sediments management. In the brackish system of S. Vitale park, the development of hydromorphic and subaqueous soils was investigated. The study of soil profiles highlighted the presence of a soil continuum among pedons subjected to different saturation degrees. This investigation allowed to the identification of both morphological and physicochemical indicators, which characterize the formation of subaqueous soils and describe the soil hydromorphism in transitional soil systems. In the saline system of Grado lagoon, an ecosystem approach was used to define the role of water oscillation in soil characterization and plants colonization. This study highlighted the close relationship and the mutual influence of soil submergence and aeration, tide oscillation and vegetation cover, on the soil development. In view of climate change, this study contribute to understand and suppose how soil and landscape could evolve. However, a complete evaluation of hydromorphic soil functionality will be achieved only involving physiological and biochemical expertise in these kind of studies.

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The sudden independence of Kyrgyzstan from the Soviet Union in 1991 led to a total rupture of industrial and agricultural production. Based on empirical data, this study seeks to identify key land use transformation processes since the late 1980s, their impact on people's livelihoods and the implication for natural resources in the communes of Tosh Bulak and Saz, located in the Sokuluk River Basin on the northern slope of the Kyrgyz Range. Using the concept of the sustainable livelihood approach as an analytical framework, three different livelihood strategies were identified: (1) An accumulation strategy applied by wealthy households where renting and/or buying of land is a key element; they are the only household category capable of venturing into rain fed agriculture. (2) A preserving strategy involving mainly intermediate households who are not able to buy or rent additional agricultural land; very often they are forced to return their land to the commune or sell it to wealthier households. (3) A coping strategy including mainly poor households consisting of elderly pensioners or headed by single mothers; due to their limited labour and economic power, agricultural production is very low and hardly covers subsistence needs; pensions and social allowances form the backbone of these livelihoods. Ecological assessments have shown that the forage productivity of remote high mountain pastures has increased from 5 to 22 per cent since 1978. At the same time forage productivity on pre-mountain and mountain pastures close to villages has generally decreased from 1 to 34 per cent. It seems that the main avenues for livelihoods to increase their wealth are to be found in the agricultural sector by controlling more and mainly irrigated land as well as by increasing livestock. The losers in this process are thus those households unable to keep or exploit their arable land or to benefit from new agricultural land. Ensuring access to land for the poor is therefore imperative in order to combat rural poverty and socio-economic disparities in rural Kyrgyzstan.

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Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

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Groundwater pumping from aquifers in hydraulic connection with nearby streams is known to cause adverse impacts by decreasing flows to levels below those necessary to maintain aquatic ecosystems. The recent passage of the Great Lakes--St. Lawrence River Basin Water Resources Compact has brought attention to this issue in the Great Lakes region. In particular, the legislation requires the Great Lakes states to enact measures for limiting water withdrawals that can cause adverse ecosystem impacts. This study explores how both hydrogeologic and environmental flow limitations constrain groundwater availability in the Great Lakes Basin. A methodology for calculating maximum allowable pumping rates is presented. Groundwater availability across the basin is shown to be constrained by a combination of hydrogeologic yield and environmental flow limitations varying over both local and regional scales. The results are sensitive to factors such as pumping time and streamflow depletion limits as well as streambed conductance. Understanding how these restrictions constrain groundwater usage and which hydrogeologic characteristics and spatial variables have the most influence on potential streamflow depletions has important water resources policy and management implications.