Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010

We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd.     

Dissolved inorganic carbon evolution in neutral discharge from mine tailings piles

We measured the concentrations of dissolved inorganic carbon (DIC) and major ions and the stable carbon isotope ratios of DIC (δ¹³C_DIC) in two creeks discharging from carbonate‐rich sulphide‐containing mine tailings piles. Our aim was to assess downstream carbon evolution of the tailings discharge as it interacted with the atmosphere. The discharge had pH of 6.5–8.1 and was saturated with respect to carbonates. Over the reach of one creek, the DIC concentrations decreased by 1.1 mmol C/l and δ¹³C_DIC increased by ~4.0‰ 200 m from the seep source. The decrease in the DIC concentrations was concomitant with decreases in the partial pressure of CO_2(aq) because of the loss of excess CO_2(aq) from the discharge. The corresponding enrichment in the δ¹³C_DIC is because of kinetic isotope fractionation accompanying the loss of CO_2(g). Over the reach of the other creek, there was no significant decrease in the DIC concentrations or notable changes in the δ¹³C_DIC. The insignificant change in the DIC concentrations and the δ¹³C_DIC is because the first water sample was collected 160 m away from the discharge seep, not accessible during this research. In this case, most of the excess CO_2(aq) was lost before our first sampling station. Our results indicate that neutral discharges from tailings piles quickly lose excess CO_2(aq) to the atmosphere and the DIC becomes enrich in ¹³C. We suggest that a significant amount of carbon cycling in neutral discharges from tailings piles occur close to the locations where the discharge seeps to the surface. Copyright © 2015 John Wiley & Sons, Ltd.     

Precipitation variability assessment of northeast China: Songhua River basin

Variability in precipitation is critical for the management of water resources. In this study, the research entropy base concept was applied to investigate spatial and temporal variability of the precipitation during 1964–2013 in the Songhua River basin of Heilongjiang Province in China. Sample entropy was applied on precipitation data on a monthly, seasonally, annually, decade scale and the number of rainy days for each selected station. Intensity entropy and apportionment entropy were used to calculate the variability over individual year and decade, respectively. Subsequently, Spearman’s Rho and Mann–Kendall tests were applied to observe for trends in the precipitation time series. The statistics of sample disorder index showed that the precipitation during February (mean 1.09, max. 1.26 and min. 0.80), April (mean 1.12, max. 1.29 and min. 0.99) and July (mean 1.10, max. 1.20 and min. 0.98) contributed significantly higher than those of other months. Overall, the contribution of the winter season was considerably high with a standard deviation of 0.10. The precipitation variability on decade basis was observed to increase from decade 1964–1973 and 1994–2003 with a mean value of decadal apportionment disorder index 0.023 and 0.053, respectively. In addition, the Mann–Kendall test value (1.90) showed a significant positive trend only at the Shangzhi station.     

Evaluation of Land Suitability for Urban Land‐Use Planning: Case Study Dhaka City

The aim of this research is evaluation of land suitability for urban land‐use planning. Four factors and fourteen criteria were selected for suitability analysis and land‐use planning. Factors and criteria were defined based on literature survey, experts’ opinions, local contexts and availability of data. GIS‐based Analytical Hierarchy Process (AHP) was used as a Multi‐criteria Decision Making model. The study was conducted on a selected area of Dhaka city, which is one of the fastest growing mega‐cities of the world. The research result shows that highly suitable area (13%) should be used for urban residential zone; moderately suitable area (35%) should be designated as mixed use zone; low suitable area (42%) should be reserved for agricultural use and open spaces; and not suitable area (10%) should be protected from any types of activities except agriculture. The research approached an urban land‐use planning at a regional scale.     

An Agent‐Based Simulation of Residential Location Choice of Tenants in Tehran,Iran

Residential location choice modeling is one of the substantial components of land use and transportation models. While numerous aggregated mathematical and statistical approaches have been developed to model the residence choice behavior of households, disaggregated approaches such as the agent‐based modeling have shown interesting capabilities. In this article, a novel agent‐based approach is developed to simulate the residential location choice of tenants in Tehran, the capital of Iran. Tenants are considered as agents who select their desired residential alternatives according to their characteristics and preferences for various criteria such as the rent, accessibility to different services and facilities, environmental pollution, and distance from their workplace and former residence. The choice set of agents is limited to their desired residential alternatives by applying a constrained NSGA‐II algorithm. Then, agents compete with each other to select their final residence among their alternatives. Results of the proposed approach are validated by comparing simulated and actual residences of a sample of tenants. Results show that the proposed approach is able to accurately simulate the residence of 59.3% of tenants at the traffic analysis zone level.