Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
195,396
result(s) for
"River water"
Sort by:
Managing basin interdependencies in a heterogeneous, highly utilized and data scarce river basin in semi-arid Africa : the case of the Pangani River Basin, Eastern Africa
\"For integrated water resources management both blue and green water resources in a river basin and their spatial and temporal distribution have to be considered. This is because green and blue water uses are interdependent. In sub-Saharan Africa, the upper landscapes are often dominated by rainfed and supplementary irrigated agriculture that rely on green water resources. Downstream, most blue water uses are confined to the river channels, mainly for hydropower and the environment. Over time and due to population growth and increased demands for food and energy, water use of both green and blue water has increased. This book provides a quantitative assessment of green-blue water use and their interactions. The book makes a novel contribution by developing a hydrological model that can quantify not only green but also blue water use by many smallholder farmers scattered throughout the landscape. The book provides an innovative framework for mapping ecological productivity where gross returns from water consumed in agricultural and natural vegetation are quantified. The book provides a multi-objective optimization analysis involving green and blue water users, including the environment. The book also assesses the uncertainty levels of using remote sensing data in water resource management at river basin scale.\" --Back cover.
Book
River water quality shaped by land–river connectivity in a changing climate
River water quality is crucial to ecosystem health and water security, yet its deterioration under climate change is often overlooked in climate risk assessments. Here we review how climate change influences river water quality via persistent, gradual shifts and episodic, intense extreme events. Although distinct in magnitude, intensity and duration, these changes modulate the structure and hydro-biogeochemical processes on land and in rivers, hence reshaping land–river connectivity and the quality of river waters. To advance understanding of and forecasting capabilities for water quality in future climates, it is essential to perceive land and rivers as interconnected systems. It is also vital to prioritize research under climate extremes, where the dynamics of water quality often challenge existing theories and models and call for shifts in conceptual paradigms.River water quality affects water security and is expected to degrade under climate change—an issue that has garnered limited attention. Here the authors review the impacts of climate change and climate extremes on water quality, highlighting the pivotal role of land–river connectivity.
Journal Article
Evaluation of heavy metal risk potential in Bogacayi River water (Antalya, Turkey)
This study analyzed 25 river water samples collected from the Bogacayi River in Antalya, Turkey, to evaluate the potential risk of pollution by heavy metals. Concentrations of As, Ba, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Se, Sr, and V were determined by inductively coupled plasma mass spectrometry (ICP-MS). The method was validated prior to analysis in terms of linearity, limit of detection (LOD), limit of quantification (LOQ), and recovery. In addition, a certified standard (SPS-SW2 surface water) was used to verify method trueness. Method validation data and results obtained from the certified material suggested that the method could be applied to determine elemental compositions of the samples. Although various concentrations of As, Ba, Cd, Cr, Cu, Mn, Ni, Pb, and Sr were found in the samples, no Hg, V, Co, and Se concentrations were found. The highest concentration of Pb, Cd, and As was found in the samples from the 22nd, 16th, and 5th sampling stations, respectively. Concentrations of the studied elements were aligned from high to low as Sr > Ba > Ni > Cr > Cu > Mn > Pb > As > Cd. To evaluate the risk potential of metallic pollution, the data were used to calculate the heavy metal pollution index (HPI). The HPI values were found to be in the range from 7.81 to 43.97 (mean 25.48). Samples from upstream seemed to show lower risk potentials (<15) than those from downstream (>30); however, all HPI values were lower than 100, which is the critical HPI value for drinking safety.
Journal Article
Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models
River water temperature is a key control of many physical and bio-chemical processes in river systems, which theoretically depends on multiple factors. Here, four different machine learning models, including multilayer perceptron neural network models (MLPNN), adaptive neuro-fuzzy inference systems (ANFIS) with fuzzy c-mean clustering algorithm (ANFIS_FC), ANFIS with grid partition method (ANFIS_GP), and ANFIS with subtractive clustering method (ANFIS_SC), were implemented to simulate daily river water temperature, using air temperature (
T
a
), river flow discharge (
Q
), and the components of the Gregorian calendar (
CGC
) as predictors. The proposed models were tested in various river systems characterized by different hydrological conditions. Results showed that including the three inputs as predictors (
T
a
,
Q
, and the
CGC
) yielded the best accuracy among all the developed models. In particular, model performance improved considerably compared to the case where only
T
a
is used as predictor, which is the typical approach of most of previous machine learning applications. Additionally, it was found that
Q
played a relevant role mainly in snow-fed and regulated rivers with higher-altitude hydropower reservoirs, while it improved to a lower extent model performance in lowland rivers. In the validation phase, the MLPNN model was generally the one providing the highest performances, although in some river stations ANFIS_FC and ANFIS_GP were slightly more accurate. Overall, the results indicated that the machine learning models developed in this study can be effectively used for river water temperature simulation.
Journal Article
Ganga rejuvenation : governance challenges and policy options
\"This book focuses on governance and management issues in the much publicized 'Ganga Rejuvenation Project', led by the Indian Prime Minister Mr. Narendra Modi. Attempts over the past three decades to clean up and rejuvenate one of the world's greatest rivers have proved futile. The major reasons for the lack of success are absence of long-term planning, poor co-ordination and failure to sustain whatever little infrastructure for water and sewage treatment could be developed. Focusing on these broad aspects, the book explores spaces for better governance through active community participation, knowledge management, prospects of Public-Private-Partnership, e-governance, youth education, waterfront development, lessons from past failures, comparative international analogies, utilization of external aid and global expertise in successful implementation of a sustainable long-term plan for a river basin's integrated development of both the economy and environment. A host of activities, such as, improving pollution monitoring systems, new development plans for tourism enhancement; river dredging and sewering riparian cities are already being carried in the hope of quick results. The Government of India has also appointed a task force for preparation of a long-term strategy. However, substantial knowledge gaps persist especially with regard to governance. This book aims to address the governance and policy issues and will be a very timely contribution to cleaning as well as rejuvenating Ganga, a river that is lifeline of millions of people.\"--Back cover.
Book
Assessing the impact of land use and land cover on river water quality using water quality index and remote sensing techniques
The impact of land use on water quality is becoming a global concern due to the increasing demand for freshwater. This study aimed to assess the effects of land use and land cover (LULC) on the surface water quality of the Buriganga, Dhaleshwari, Meghna, and Padma river system in Bangladesh. To determine the state of water, water samples were collected from twelve locations in the Buriganga, Dhaleshwari, Meghna, and Padma rivers during the winter season of 2015 and collected samples were analysed for seven water quality indicators: pH, temperature (Temp.), conductivity (Cond.), dissolved oxygen (DO), biological oxygen demand (BOD), nitrate nitrogen (NO
3
-N), and soluble reactive phosphorus (SRP) for assessing water quality (WQ). Additionally, same-period satellite imagery (Landsat-8) was utilised to classify the LULC using the object-based image analysis (OBIA) technique. The overall accuracy assessment and kappa co-efficient value of post-classified images were 92% and 0.89, respectively. In this research, the root mean squared water quality index (RMS-WQI) model was used to determine the WQ status, and satellite imagery was utilised to classify LULC types. Most of the WQs were found within the ECR guideline level for surface water. The RMS-WQI result showed that the “fair” status of water quality found in all sampling sites ranges from 66.50 to 79.08, and the water quality is satisfactory. Four types of LULC were categorised in the study area mainly comprised of agricultural land (37.33%), followed by built-up area (24.76%), vegetation (9.5%), and water bodies (28.41%). Finally, the Principal component analysis (PCA) techniques were used to find out significant WQ indicators and the correlation matrix revealed that WQ had a substantial positive correlation with agricultural land (
r
= 0.68,
P
< 0.01) and a significant negative association with the built-up area (
r
= − 0.94,
P
< 0.01). To the best of the authors’ knowledge, this is the first attempt in Bangladesh to assess the impact of LULC on the water quality along the longitudinal gradient of a vast river system. Hence, we believe that the findings of this study can support planners and environmentalists to plan and design landscapes and protect the river environment.
Journal Article
An Economic Model of Transboundary Water Agreements With Groundwater and Surface Water Interaction: Application to a US River Basin With a History of Conflict
This study examines the connection between groundwater and surface water in the design of transboundary compacts. A steady‐state hydro‐economic model is developed and applied to a river basin in the United States. Simulations demonstrate that when a water compact is designed to govern only surface water, the assigned allocations are nonbinding and lead to decreased river‐flow in the downstream region. When the compact is designed to govern surface water and groundwater usage combined, however, the assigned allocations are binding and changes in them can increase overall net benefits, with the extent dependent on flexibility in compact design.
Journal Article