The connection of the Ob river flow variability with meteorological parameters in different parts of its catchment area is considered. Areas of the prevailing influence of the air temperature and different types of precipitation on Ob runoff fluctuations were identified. The long-term series of average annual water discharge in the Salekhard hydrometric station for the period 1936–2015 is reconstructed. The reconstructed series reproduces the measured interannual fluctuations and long-term trends of the average annual water discharge and found it to be good.
There are several factors that need to be monitored to fully understand agricultural contributions to environmental degradation as well as the effectiveness of implementing sustainable practices. This study did so by sampling cow ponds from different locations in northern Virginia with different cattle exclusion methods to evaluate the phosphorus levels in each aquatic system. Through comparing these sites, there were conclusions shown through a statistical analysis to summarize both the current health of agricultural ponds compared to government recommended criteria and the effectiveness of varying forms of clean water practices. The data collection came from samples taken at six cattle farm ponds in northern Virginia that were collected in November 2021 and January 2022. The samples were compared using an ANOVA statistical analysis, which compared sample results by location. The findings of this study showed that all the test sites were above the recommended value by the EPA for the total P concentrations. There was also statistical significance shown through some of the locations, which provided partial credibility to the efficiency of clean water practices. These studies are important to both the overall issue of clean water in agricultural industry regions as well as the specific situation of Virginia agricultural practices. Currently under a voluntary stream exclusion program, there is potential for mandates to be put in place without a shown improvement in water quality by 2025. Taking progressional measurements into consideration it is clear that there is still a way to go to meet federal satisfaction. This study opens up the door for future research regarding the progress of clean water restoration efforts as well as the monitoring of agricultural impacts on overall regional water quality.
This paper investigates when a runoff election is desirable and when a plurality result is good enough. A runoff election increases the likelihood that the Condorcet winner will be elected but also entails additional costs. The metric for determining whether a runoff election is desirable will be the probability that the winner of the plurality election would win an ensuing runoff. Statistical models of voter behavior are developed that estimate this probability, which are verified with runoff-election data from United States elections. The models allow governments to make more informed choices in creating rules to decide when to hold runoff elections. Adapted from the source document.
"Global construction data is vital for contractors, governments, international organisations, policy makers, academic researchers and statisticians. As the global population of the world expands, the sustainability of the built environment rises up the political agenda and the need to manage infrastructure and buildings in both urban and rural contexts becomes ever more pressing. How much more can the built environment grow and how can it be managed sustainably? This edited volume is about finding a possible way through the inconsistencies between national construction data sets to devise a consistent approach to national construction data to further the global sustainability agenda and inform policy making. This search begins in Part 1, which looks at the methods and definitions used in construction statistics in different countries. Part 2 considers examples of dealing with different types of construction data from the cost of materials, measuring work on high rise buildings and existing stock. In Part 3 the authors consider construction data internationally, beginning with the problem of comparing data in different countries using exchange rates and purchasing power parities (PPPs), comparing innovation processes in different countries and looking at the provision of building design internationally. In the final section, the international theme is continued by comparing accounting practices and company performance in different countries, and concludes with an international comparison of construction industries"--
Successful modeling of hydro-environmental processes widely relies on quantity and quality of accessible data and noisy data might effect on the functioning of the modeling. On the other hand in training phase of any Artificial Intelligence (AI) based model, each training data set is usually a limited sample of possible patterns of the process and hence, might not show the behavior of whole population. Accordingly in the present article first, wavelet-based denoising method was used in order to smooth hydrological time series and then small normally distributed noises with the mean of zero and various standard deviations were generated and added to the smoothed time series to form different denoised-jittered training data sets, for Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling of daily rainfall – runoff process of the Oconee River watershed located in USA. To evaluate the modeling performance, the outcomes were compared with the results of multi linear regression (MLR) and Auto Regressive Integrated Moving Average (ARIMA) models. Comparing the achieved results via the trained ANN and ANFIS models using denoised-jittered data showed that the proposed data processing approach which serves both denoising and jittering techniques could improve performance of the ANN and ANFIS based rainfall-runoff modeling of the Oconee River Watershed up to 13% and 11% in the verification phase.
