ANN-based mapping of monthly reference crop evapotranspiration by using altitude, latitude and longitude data in Fars province, Iran

The main goal of this study was to evaluate the different feed-forward back-propagation artificial neural networks’ (ANNs) potential to estimate and interpolate the reference crop evapotranspiration (ET₀) in Fars province of Iran. ET₀ was calculated using the FAO-56 Penman–Monteith method over 24 synoptic stations. Then, altitude, latitude, longitude and the month’s number as inputs and the monthly ET₀ as output (target) were used to train the ANNs. In addition, the three-layered ANNs optimized with different training algorithms including gradient descent back-propagation (gd), gradient descent with adaptive learning rate back-propagation (gda), gradient descent with momentum and adaptive learning rate back-propagation (gdx) and scaled conjugate gradient back-propagation (scg). The results indicated that scg algorithm with architecture (4 2 1) had more satisfactory results with the RMSE and R correlation coefficient equal to 18.538 mm and 0.967 in validation phase, respectively. Based on the mentioned architecture of scg algorithm, and input data form different parts of Fars province and surrounding areas, monthly ET₀ maps were produced and annual one achieved by summation of monthly maps. The maps particularly annual one showed that highest values of ET₀ could be found in the southern and especially southeastern regions, while the lowest values of ET₀ could be seen in the northern parts. Contribution of geographic and topographic variables improved the accuracy and spatial details of the resulting maps. It is interesting to note that the fundamental capability of this model is the usage of just a few parameters for ET₀ mapping. Since ET₀ is a key parameter in water demand planning, therefore, the derived maps could be useful and applicable for many purposes mainly irrigation scheduling in Fars province, Iran.     

Comparison of understorey bird species in relation to edge–interior gradient in an isolated tropical rainforest of Malaysia

Forest fragmentation results in a loss of forest interior and an increase in edge habitat. As a result, these changes may affect the bird species distribution and composition. We studied how understorey bird community composition and habitat variables changed along an edge-to-interior gradient in a fragmented lowland rainforest in Peninsular Malaysia. Birds and environmental variables were recorded at each of the 93 sampling points distributed along the 14 parallel transects that were systematically placed across the gradient of distance from the forest edge to the forest interior. Species composition was different along the edge–interior gradient, although only a few species were strictly confined to either edge or interior habitat. Based on bird–habitat associations along the edge–interior gradient, some of these edge-preferred species occurred in high numbers at the matrix surrounding the patch. In contrast, the interior-specialist group, mainly terrestrial insectivores, avoided the forest edge and was positively associated with humidity, canopy cover, the number of dead trees, percentage of litter cover, and depth of the litter layer. Species endemic to the Sunda subregion were more abundant in the interior of the forest. From a conservation perspective, forest remnants in the lowlands of Peninsular Malaysia that have a deep leaf litter layer, dense canopy cover, high number of dead trees, and high relative humidity are able to support understorey bird species that are sensitive to edge effects. The forest has important conservation value even though it is fragmented and isolated.     

Microplastics in urban waters and its effects on microbial communities: a critical review

Environmental Science and Pollution Research - Microplastic (MP) pollution is one of the emerging threats to the water and terrestrial environment, forcing a new environmental challenge due to the...     

Correction to: Multivariate modeling of agricultural river water abstraction via novel integrated-wavelet methods in various climatic conditions

Environment, Development and Sustainability - The authors would like to apologize for inadvertent mistakes in this article.     

Physical and chemical separation of Ti,rare earth elements,Fe, and Al from red mud by carbothermal reduction,magnetic separation,and leaching

Environmental Science and Pollution Research - In this study, a combination of physical and chemical separation processes was used to recover the metallic components of red mud. At first, the...     

Numerical and artificial intelligence models for predicting the water advance in border irrigation

Environment, Development and Sustainability - The water advance time (Ta) is needed for designing and evaluating surface irrigation systems. This study employed artificial neural networks (ANNs)...     

Multivariate modeling of agricultural river water abstraction via novel integrated-wavelet methods in various climatic conditions

Environment, Development and Sustainability - Water resource management in the agricultural sector is a necessity that profoundly impacts water resources conservation for future generations. With...     

Sample preparation methods for the analysis of microplastics in freshwater ecosystems: a review

Environmental Chemistry Letters - The vast amount of plastic waste emitted into the environment is of increasing concern because there is mounting evidence for various toxic effects of...