scispace - formally typeset
A

Assefa M. Melesse

Researcher at Florida International University

Publications -  319
Citations -  11181

Assefa M. Melesse is an academic researcher from Florida International University. The author has contributed to research in topics: Surface runoff & Drainage basin. The author has an hindex of 51, co-authored 285 publications receiving 8379 citations. Previous affiliations of Assefa M. Melesse include Haramaya University & University of North Dakota.

Papers
More filters
Journal ArticleDOI

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques.

TL;DR: The commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters, including chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygendemand (COD).
Journal ArticleDOI

Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management

TL;DR: In this paper, the authors applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change.
Journal ArticleDOI

Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: A case study at Mehran Region, Iran

TL;DR: In this paper, the application of random forest (RF) and maximum entropy (ME) models for groundwater potential mapping is investigated at Mehran Region, Iran and the results of the GPMs were quantitatively validated using observed groundwater dataset and the receiver operating characteristic (ROC) method.
Journal ArticleDOI

Suspended sediment load prediction of river systems: An artificial neural network approach

TL;DR: A multilayer perceptron (MLP) ANN with an error back propagation algorithm, using historical daily and weekly hydroclimatological data (precipitation P ( t ), current discharge Q ( t ), antecedent discharge Q( t −1), and antecient sediment load SL ( t − 1) ), is used to predict the suspended sediment load at the selected monitoring stations.
Journal ArticleDOI

A Coupled Remote Sensing and Simplified Surface Energy Balance Approach to Estimate Actual Evapotranspiration from Irrigated Fields

TL;DR: In this paper, the authors developed and implemented a simplified surface energy balance (SSEB) model to monitor and assess the performance of irrigated agriculture in Afghanistan using a combination of 1-km thermal data and 250-m Normalized Difference Vegetation Index (NDVI) data, both from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor.