scholarly journals Water Resource Carrying Capacity Based on Water Demand Prediction in Chang-Ji Economic Circle

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 16
Author(s):  
Ge Wang ◽  
Changlai Xiao ◽  
Zhiwei Qi ◽  
Xiujuan Liang ◽  
Fanao Meng ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Correlation Analysis ◽  
Water Resource ◽  
Carrying Capacity ◽  
Regression Models ◽  
Water Shortage ◽  
Linear Regression Models ◽  
Gray Correlation ◽  
Multiple Linear Regression Models

In view of the large spatial difference in water resources, the water shortage and deterioration of water quality in the Chang-Ji Economic Circle located in northeast China, the water resource carrying capacity (WRCC) from the perspective of time and space is evaluated. We combine the gray correlation analysis and multiple linear regression models to quantitatively predict water supply and demand in different planning years, which provide the basis for quantitative analysis of the WRCC. The selection of research indicators also considers the interaction of social economy, water resources, and water environment. Combined with the fuzzy comprehensive evaluation method, the gray correlation analysis and multiple linear regression models to quantitatively and qualitatively evaluate the WRCC under different social development plans. The developmental trends were obtained from 2017 to 2030 using four plans designed for distinct purposes. It can be seen that the utilization of water resource is unreasonable now and maintains a poor level under a business-as-usual Plan I. Plan II and Plan III show that resource-based water shortage is the most critical issue in this region, and poor water quality cannot be ignored either. Compared with Plan I, the average index of WRCC in Plan IV increased by 51.8% and over 84% of the regions maintain a good level. Strengthening sewage treatment and properly using transit water resources are more conducive to the rapid development of Chang-Ji Economic Circle.

scholarly journals The effects of precipitation, river discharge, land use and coastal circulation on water quality in coastal Maine

2015 ◽  
Vol 2 (7) ◽  
pp. 140429 ◽  
Author(s):  
Charles E. Tilburg ◽  
Linda M. Jordan ◽  
Amy E. Carlson ◽  
Stephan I. Zeeman ◽  
Philip O. Yund
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
River Discharge ◽  
Regression Models ◽  
Mechanistic Model ◽  
Commercial Fishing ◽  
Coastal Circulation ◽  
Linear Regression Models ◽  
Multiple Linear Regression Models

Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18–24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible.

Catastrophe progression method based on M-K test and correlation analysis for assessing water resources carrying capacity in Hubei province

2018 ◽  
Vol 11 (2) ◽  
pp. 556-567
Author(s):  
Fan Song ◽  
Xiaohua Yang ◽  
Feifei Wu
Keyword(s):  
Water Resources ◽  
Correlation Analysis ◽  
Water Resource ◽  
Carrying Capacity ◽  
Supply And Demand ◽  
Hubei Province ◽  
Ecological Environment ◽  
Water Resources Carrying Capacity ◽  
Catastrophe Progression Method ◽  
Catastrophe Progression

Abstract In order to assess the water resources carrying capacity (WRCC) of Hubei province, an improved catastrophe progression method based on M-K test and correlation analysis was established. This model includes evaluation, abrupt change test and correlation analysis. It can make a comprehensive assessment of water resource carrying capacity in a certain area. The evaluation results of this model are clear and can effectively avoid the effects of subjective weight and, in addition, it can also streamline the index system. We applied the model to study the WRCC of Hubei province from 2005 to 2016, considering the supply and demand of water resources, ecological environment, economy and society. The results showed that the WRCC of Hubei province is at the ‘weak’ level, presenting a certain development and utilization potential, but it must be strictly controlled and moderately developed. The WRCC of Hubei province is improving, but must be adjusted by water conservation facilities and long-term management policies to prevent the foreseeable deterioration. Water supply and demand systems and ecological environment systems were found to be the driving factors of WRCC through correlation analysis. This approach gives the decision-makers suggestions about water resource sustainable utilization.

Water Resource Assessment Based on Ecological Footprint in Beijing City, China

2014 ◽  
Vol 1073-1076 ◽  
pp. 445-449
Author(s):  
Li Ping Xu ◽  
Li Wang ◽  
Jin Lin Li
Keyword(s):  
Water Resources ◽  
Water Resource ◽  
Carrying Capacity ◽  
Ecological Footprint ◽  
Water Shortage ◽  
Environmental Water ◽  
Resource Assessment ◽  
Scientific Basis ◽  
Beijing City ◽  
Water Resource Carrying Capacity

Beijing is now facing the intense water shortage problem. Evaluation of regional water resources capacity provides a scientific basis for further water resources utilization and social economic sustainable development. This study mainly focused on assessing the water resource carrying capacity in Beijing during the period from 1980 to 2011. The results indicated that the domestic and environmental water resource ecological footprint showed increasing trend, whereas agricultural and industrial water resource ecological footprint showed decreasing trend. The total water resource ecological footprint increased from 6.5×106 hm2 in 2011 to 6.8×106 hm2 in 2015 and 9.1×106 hm2 in 2020, respectively. Even taking the South-to North water transfer project, the water supply still not meet the serious water demand in Beijing with 10×108 hm3 of water shortage in 2020. Moreover, policies for reducing the water resource ecological footprint and increasing the water resource carrying capacity were put forward.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

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