Publications by authors named "Ali Danandeh Mehr"

Mangroves play a crucial role in filtering pollutants from water and sediments. However, excessive accumulation of potentially toxic elements (PTEs) has harmful effects on marine organisms. This article investigates the concentration and distribution of PTEs in water, sediment, and the roots of endangered mangrove species in Chabahar Bay, a subtropical coastal wetland.

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Existing artificial neural networks (ANNs) have attempted to efficiently identify underlying patterns in environmental series, but their structure optimization needs a trial-and-error process or an external optimization effort. This makes ANNs time consuming and more complex to be applied in practice. To alleviate these issues, we propose a stabilized ANNs, called SANN.

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As global climate change poses a challenge to crop production, it is imperative to prioritize effective adaptation of agricultural systems based on a scientific understanding of likely impacts. In this study, we applied an integrated watershed modeling framework to examine the impacts of projected climate on runoff, soil moisture, and soil erosion under different management systems in Central Oklahoma. The proposed model uses measured climate data and three downscaled ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) at the water resources and erosion watershed to understand the impact of climate change and various climate conditions under three management systems: (1) continuous winter wheat (Triticum aestivum) under conventional tillage (WW-CT; baseline system), (2) continuous winter wheat under no-till (WW-NT), and (3) cool and warm season forage cover crop mixes under no-till (CC-NT).

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The accumulation of pollutants in the sediment along surface water may negatively affect riparian zones and increase ecological risk. This article investigates the effects of metal sediments on riparian soil via field monitoring and ICP-OES analysis. To this end, pollution levels, seasonal changes, and potential sources of the pollutants were determined for the Melen River watershed, Turkey.

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This study investigates the impact of pneumatophores (the aerial roots of Avicenna marina) on water flow rate, retention time, contact time, and consequently on nutrient absorption through the sediment in sub-tropical salt marshes. The goal is to realize how the density of mangroves in salt marshes influences the kinematic factors of streamflow at estuaries. To this end, a field experiment was carried out to assess nutrient and organic compound levels in the sediment and water samples, spanning six sampling stations along the Chabahar River discharging to the Chabahar Bay, Iran.

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Hydrocarbons, originating from oil and gas industries, are considered a potential risk for Nayband Bay, a natural marine park with extended mangroves, located on the north coastlines of the Persian Gulf, Iran. This paper determines the potential sources and spatial distribution of hydrocarbons, especially aliphatic hydrocarbons (AHCs), in Nayband Bay through the simultaneous application of three indices in the coastline surface sediments. To this end, a field study was conducted in the inter-tidal coastal zones and wetlands.

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To reduce the problem of sedimentation in open channels, calculating flow velocity is critical. Undesirable operating costs arise due to sedimentation problems. To overcome these problems, the development of machine learning based models may provide reliable results.

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It is well documented that standalone machine learning methods are not suitable for rainfall forecasting in long lead-time horizons. The task is more difficult in arid and semiarid regions. Addressing these issues, the present paper introduces a hybrid machine learning model, namely multiple genetic programming (MGP), that improves the predictive accuracy of the standalone genetic programming (GP) technique when used for 1-month ahead rainfall forecasting.

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