The paper presents an adaptive neuro-fuzzy inference system (ANFIS) based modeling approach to predict the monthly global solar radiation (MGSR) in Bhubaneswar. Comparisons of the predicted and measured value of monthly global solar radiation (GSR) on a horizontal surface are presented. The input parameters of the model used in this paper are sunshine duration, temperature, humidity, clearness ...

The rapid growth of the economy in China has caused dramatic growth in the industrial and agricultural development in the Yellow River (YR) watershed. The hydrology of the YR has changed dramatically due to the climate changes and water management practices, which have resulted in a great variation in the fluxes of riverine nutrients carried by the YR. To study these changes dissolved nutrients...

Extreme droughts and high temperatures have becomemore frequent in the last two decades, increasing fire risk in the Amazon. The overarching goal of this study is to shed light on the influence of temperature and rainfall on fire occurrence for the 1998–2013 period. We use a Poisson regression to model satellite-based monthly fire counts across the Brazilian Amazon as a function of observed rai...

BACKGROUND In June of 2010, an antenatal ultrasound program to perform basic screening for high-risk pregnancies was introduced at a community health care center in rural Uganda. Whether the addition of ultrasound scanning to antenatal visits at the health center would encourage or discourage potential patients was unknown. Our study sought to evaluate trends in the numbers of antenatal visits ...

For developing countries like Pakistan, the paucity of reliable solar radiation data necessitates the development of empirical models. To develop such a model one could use various parameters. In this study, linear regression models are developed to estimate the monthly average daily global radiation using cloudiness data for Karachi, Pakistan for the period of 20 years (1990-2010). The results...

This paper presents the results of a study that simulates historic average discharges by means of an Artificial Neural Network, within a variety of input data combinations. A cluster of small area watersheds in Eastern Serbia was selected for the study. The input data considered were: climatic data (precipitation, average air temperatures, vapor pressure and air humidity), physiographic, hydrog...

Sediment and nutrient concentrations in surface water in agricultural regions are strongly influenced by agricultural activities. In the Corn Belt, recent changes in farm management practices are likely to affect water quality, yet there are few data on these linkages at the landscape scale. We report on trends in concentrations of N as ammonium (NH(4)) and nitrate (NO(3)), soluble reactive pho...

rainfall spatial analysis methods are very helpful since there are not enough rainfall gauge stations and watersheds are scattered in large extent. there are many different methods for estimating average precipitation such as; arithmetic method and thiessen polygon. however, the arrangement and location of data and their correlations are not considered by classic methods. thus, geostatistical t...

According to the water resources and climate change and challenges of Urmia Lake basin, which is the discharge and final destination of North West Rivers, a model was presented. Due to climate change and water resources in river basin such as rainfall, climate change in basin that has direct impact on evaporation over water catchment areas and lake water, this model can be provided. In addition...

[1] A salient characteristic of river discharge is its temporal variability. The time series of flow at a point on a river can be viewed as the superposition of a smooth seasonal cycle and an irregular, random variation. Viewing the random component in the spectral domain facilitates both its characterization and an interpretation of its major physical controls from a global perspective. The po...