scholarly journals Water Resource Management through Understanding of the Water Balance Components: A Case Study of a Sub-Alpine Shallow Lake

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3124
Author(s):  
Marzia Ciampittiello ◽  
Claudia Dresti ◽  
Helmi Saidi
Keyword(s):  
Resource Management ◽  
Surface Water ◽  
Water Balance ◽  
Water Resource ◽  
Water Resource Management ◽  
Water Inflow ◽  
Water Balance Components ◽  
Hydrological Balance ◽  
Volume Variation ◽  
Groundwater Source

Water availability is a crucial factor for the hydrological balance of sub-alpine shallow lakes and for their ecosystems. This is the first study on water balance and water management of Lake Candia, a small sub-alpine, shallow morainic lake. The aims of this paper are to better understand the link between surface water and groundwater. The analyses carried out included: (i) evaluation of water balance, (ii) identification of trends for each component of water balance, (iii) detection of the presence of a break point or change in the behavior of each component, and (iv) regression analyses of the terms of hydrological balance and their relative importance. The analyses revealed a high variability mainly regarding the groundwater component, and very good correlation between rainfall and volume variation, between rainfall and the water inflow, and between groundwater source and outflow. Volume variation is linked with rainfall, outflow, groundwater source, and surface water inflow. Despite the fact that the groundwater component does not seem to have a great importance relative to direct rainfall on the lake, it is necessary to study the component with careful resource management policies that point toward the protection of the water resource, sustainable uses, and protection of the Lake Candia ecosystem.

scholarly journals How is Baseflow Index (BFI) impacted by water resource management practices?

2021 ◽  
Author(s):  
John P. Bloomfield ◽  
Mengyi Gong ◽  
Benjamin P. Marchant ◽  
Gemma Coxon ◽  
Nans Addor
Keyword(s):  
Resource Management ◽  
Surface Water ◽  
Water Resource ◽  
Water Resource Management ◽  
Management Practices ◽  
Explanatory Power ◽  
Minor Importance ◽  
Groundwater Abstraction ◽  
Large Sample ◽  
Water Abstraction

Abstract. Water resource management (WRM) practices, such as abstractions and discharges, may impact baseflow. Here the CAMELS-GB large-sample hydrology dataset is used to assess the impacts of such practices on baseflow index (BFI) using statistical models of 429 catchments from Great Britain. Two complementary modelling schemes, multiple linear regression (LR) and machine learning (random forests, RF), are used to investigate the relationship between BFI and two sets of covariates (natural covariates only and a combined set of natural and WRM covariates). The LR and RF models show good agreement between explanatory covariates. In all models, the extent of fractured aquifers, clay soils, non-aquifers, and crop cover in catchments, catchment topography and aridity are significant or important natural covariates in explaining BFI. When WRM terms are included, groundwater abstraction is significant or the most important WRM covariate in both modelling schemes and discharge to rivers is also identified as significant or influential, although natural covariates still provide the main explanatory power of the models. Surface water abstraction is a significant covariate in the LR model but of only minor importance in the RF model. Reservoir storage covariates are not significant or are unimportant in both the LR and RF models for this large-sample analysis. Inclusion of WRM terms improves the performance of some models in specific catchments. The LR models of high BFI catchments with relatively high levels of groundwater abstraction show the greatest improvements, and there is some evidence of improvement in LR models of catchments with moderate to high discharges. However, there is no evidence that the inclusion of the WRM covariates improves the performance of LR models for catchments with high surface water abstraction or that they improve the performance of the RF models. These observations are used to formulate a conceptual framework for baseflow generation that incorporates WRM practices. It is recommended that information on WRM, particularly groundwater abstraction, should be included where possible in future large-sample hydrological data sets and in the analysis and prediction of BFI and other measures of baseflow.

scholarly journals How is Baseflow Index (BFI) impacted by water resource management practices?

2021 ◽  
Vol 25 (10) ◽  
pp. 5355-5379
Author(s):  
John P. Bloomfield ◽  
Mengyi Gong ◽  
Benjamin P. Marchant ◽  
Gemma Coxon ◽  
Nans Addor
Keyword(s):  
Resource Management ◽  
Surface Water ◽  
Water Resource ◽  
Water Resource Management ◽  
Low Flow ◽  
Minor Importance ◽  
Groundwater Abstraction ◽  
Large Sample ◽  
Water Abstraction ◽  
Wide Range

Abstract. Water resource management (WRM) practices, such as groundwater and surface water abstractions and effluent discharges, may impact baseflow. Here the CAMELS-GB large-sample hydrology dataset is used to assess the impacts of such practices on Baseflow Index (BFI) using statistical models of 429 catchments from Great Britain. Two complementary modelling schemes, multiple linear regression (LR) and machine learning (random forests, RF), are used to investigate the relationship between BFI and two sets of covariates (natural covariates only and a combined set of natural and WRM covariates). The LR and RF models show good agreement between explanatory covariates. In all models, the extent of fractured aquifers, clay soils, non-aquifers, and crop cover in catchments, catchment topography, and aridity are significant or important natural covariates in explaining BFI. When WRM terms are included, groundwater abstraction is significant or the most important WRM covariate in both modelling schemes, and effluent discharge to rivers is also identified as significant or influential, although natural covariates still provide the main explanatory power of the models. Surface water abstraction is a significant covariate in the LR model but of only minor importance in the RF model. Reservoir storage covariates are not significant or are unimportant in both the LR and RF models for this large-sample analysis. Inclusion of WRM terms improves the performance of some models in specific catchments. The LR models of high BFI catchments with relatively high levels of groundwater abstraction show the greatest improvements, and there is some evidence of improvement in LR models of catchments with moderate to high effluent discharges. However, there is no evidence that the inclusion of the WRM covariates improves the performance of LR models for catchments with high surface water abstraction or that they improve the performance of the RF models. These observations are discussed within a conceptual framework for baseflow generation that incorporates WRM practices. A wide range of schemes and measures are used to manage water resources in the UK. These include conjunctive-use and low-flow alleviation schemes and hands-off flow measures. Systematic information on such schemes is currently unavailable in CAMELS-GB, and their specific effects on BFI cannot be constrained by the current study. Given the significance or importance of WRM terms in the models, it is recommended that information on WRM, particularly groundwater abstraction, should be included where possible in future large-sample hydrological datasets and in the analysis and prediction of BFI and other measures of baseflow.

scholarly journals Response of Surface Water Quality Characteristics to Socio-economic Factors in Eastern-Central China

2021 ◽  
Author(s):  
Maoqing Duan ◽  
Shilu Zhang ◽  
Junyu He ◽  
MIngxia Xu ◽  
Yuanyuan Gao ◽  
...  
Keyword(s):  
Water Quality ◽  
Resource Management ◽  
Surface Water ◽  
Influencing Factors ◽  
Water Resource ◽  
Quality Index ◽  
Water Resource Management ◽  
Surface Water Quality ◽  
Ccme Wqi

Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was as follows: 61.7% of the water was classified under Class I–III; and 5%, 8.6%, and 12.2% of the water was classified under Class IV, V, and inferior V, respectively. The main standard items are DO, CODMn, COD, BOD5, NH3-N, and TP. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the water quality of surface water at the provincial boundaries of 27 provinces were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China

scholarly journals Groundwater monitoring system and groundwater policy in relation to unified water resource management in Korea

Water Policy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 211-222
Author(s):  
Lae-Soo Kang ◽  
Se-Yeong Hamm ◽  
Jae-Yeol Cheong ◽  
Hang-Tak Jeon ◽  
Jae Hyun Park
Keyword(s):  
Climate Change ◽  
Resource Management ◽  
Surface Water ◽  
Water Resources ◽  
Water Resource ◽  
Groundwater Monitoring ◽  
Water Resource Management ◽  
Social Issues ◽  
Groundwater Resources ◽  
Monitoring Stations

Abstract The demand for water resources is consistently increasing due to industrialization and urbanization. Water resource management can become difficult because of climate change and social issues. Due to the difficulty in securing stable water resources, reasonable utilization and management of water is crucial for the sustainable development of groundwater resources that are an efficient alternative to surface water. For groundwater management, the National Groundwater Information Management Service (GIMS) Center for K-Water measures groundwater data hourly (groundwater level, water temperature, and electrical conductivity) at national groundwater monitoring stations and analyzes the long-term variation of groundwater with regard to climate change. According to the Groundwater Act (1993), auxiliary groundwater monitoring stations for groundwater use and water quality are activated by local governments. The observed data after the calibration process are provided for utilization by citizens, industries, schools, institutes, and government policies through annual reports on groundwater monitoring by the GIMS Center. In 2018, the Korean government merged water resources affairs that were once divided between the Ministry of Environment and the Ministry of Land, Infrastructure, and Transport. The change will be favorable for effective management of the surface water and groundwater resources as well as ensuring both quality and quantity.

scholarly journals A Bipartite Techno-Policy Model for River Based Water Resource Management for Sustainable Future with Special Reference To Haora River in Tripura, India

2021 ◽  
Author(s):  
Nami Prasad ◽  
Prabir Barman ◽  
Jayanta GHOSH ◽  
Prantik Roy
Keyword(s):  
Water Quality ◽  
Resource Management ◽  
Surface Water ◽  
Water Resource ◽  
Water Policy ◽  
Water Resource Management ◽  
Biological Properties ◽  
The State ◽  
Aquatic Life ◽  
Policy Model

Abstract Surface water serves most of the water requirements to sustain lives on earth. Of all fresh water on earth, only 1.2% is making up of surface water and the rest is confined in ice and ground. As the rivers provide for the significant sources of surface water, there is a need for river-based water resource management to meet global water quality challenge. Haora River that originated in the India’s north-eastern state of Tripura and meets ultimately with the Titas River in the Bangladesh carries a significant impact on life in and around the river both on the Indian side and Bangladesh side. Thus, study emphasizes the test of water quality of the river and corresponding impact therefor based on a detail explanation of the monitoring data obtained through published sources, laboratory analysis of samples and relevant field observations. ANOVA revealed year wise significant variations in physicochemical and biological properties of the river water tested except for pH. Abnormalities were mostly observed in the values of T, DO, BOD, PO4-P and FC. Water Quality Index (WQI) revealed water quality status of the river fall under the category of very poor to unfit, and require proper treatment before the water is being used for drinking and other domestic purposes. Adversities in the water are also found to be affecting the aquatic life and overall river ecosystem. Cause and effect analogy of these abnormalities were established for taking corrective measures. Existing statutory law to prevent and control such anomalies have been found lacking enforcement in the state of Tripura. The broad-based state level water policy to protect and improve water resources has also been found lacking in the state. The study recommends policy level interventions at the earliest considering the specific measures suggested in this study.

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