Mojtaba Naghdyzadegan Jahromi

• Shiraz University

Addressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to the depletion of saline lakes, it is crucial to i...

Timely and accurate crop yield estimation is important for adjusting agronomic management and ensuring agricultural sustainability. Machine learning (ML) algorithms provide new opportunities to integrate agronomic information with ground-based and satellite data and develop flexible yield predictive models. In particular, satellite-based vegetation...

Iran imported around 1.3 million tons of barley in 2017. Accordingly, conducting researches under low organic matter soils and limited water resources is important to enhance barley products and improve economic conditions. Field experiments were performed to evaluate the effect of different levels of irrigation water (0, 50, 75 and 100% of crop wa...

During the past decades, consistent efforts have been undertaken to model the Earth's hydrological cycle. Multiple mathematical models have been designed to understand, predict, and manage water resources, particularly under the context of climate change. A variable that has traditionally received limited attention by the hydrological community—but...

The abundance of information and data necessitates the formulation of a new paradigm for a more robust and efficient water management system using artificial intelligence and automated data processing. In particular, the observational data from satellites have been extensively used in monitoring agricultural and natural resources from local to glob...

Hydrology is the science of studying the natural flow of water and the effect of human activity on the water. Hydrological modeling is essential for the management and conservation of water. In recent decades, machine learning (ML) has been applied efficiently in hydrology. In this study, the application of ML in four subfields of hydrology, includ...

Despite the rapidly increasing number of studies on methods to identify pest infestation using remote sensing techniques, novel methods are still emerging. Tortrix viridana and Tibicina plebejus are among the most destructive pests in oak forests in regions with Mediterranean climates. This study assessed classification models and compared their ef...

Changing climate and human interference with natural phenomena are causing unprecedented changing patterns in hydro-climatic variables. These changes can manifest as dynamic changes of the stochastic properties of the datasets over time, which pose challenges for conventional time-series modeling. These datasets are dynamic in nature, even when tre...

When it comes to projecting the potential effects of climate change on hydro-climatic variables using time-series models, the conventional approach has been to examine correlations with exogenous variables. Establishing correlations among endogenous and exogenous variables, however, cannot guarantee that there is a cause-effect relationship among t...

Studying the earth's climatic and environmental system requires precise land cover (LC) information, particularly over forested areas to accurately account for the carbon budget. This study's objective was to evaluate the accuracy of the moderate resolution imaging spectroradiometer (MODIS) LC product (MCD12Q1) over a forested area covering Norther...

In order to support sustainable forest management, it is essential to estimate the extent and change of forest cover and to evaluate the environmental and socio-economic impacts of forest dynamics. It is challenging, however, to calculate forest area on a large scale using traditional statistical survey methods. Access to satellite images make it f...

This study was conducted to estimate the optimal amounts of water and nitrogen of barley production under water‐ and land‐limited conditions. Two years of field experiments were performed with two treatments using a spilt plot design with three replications. The treatments included four levels of irrigation regimes (0, 50, 75 and 100% of water requ...

A simple Landsat-MODIS (Moderate Resolution Imaging Spectroradiometer) fusion model was used to generate 30-m resolution evapotranspiration (ET) maps for the 2010 growing season over a heterogeneous sparse vegetation, agricultural region using the METRIC (mapping evapotranspiration with internalized calibration) algorithm. The fusion model performa...