- Assefa M. Melesse, Ph. D., P.E., D.WRE
Professor
Department of Earth and Environment, AHC-5-390
Florida International University
11200 SW 8th Street
Miami, FL 33199
Tel. (305) 348-6518; Fax (305) 348-6137
E-mail: melessea@fiu.edu
Homepage: http://faculty.fiu.edu/~melessea/ - Tel. (305) 348-6518; Fax (305) 348-6137
- Dr. Assefa M. Melesse is a Professor of Water Resources Engineering with background in remote sensing and geospatial ... moreDr. Assefa M. Melesse is a Professor of Water Resources Engineering with background in remote sensing and geospatial applications to hydrological modeling. He earned his M.E (2000) and Ph. D (2002) from the University of Florida in Agricultural Engineering with two concentrations (Hydrological Sciences and GIS) and 3 minors (Civil Engineering, Environmental Engineering and Remote sensing). Professor Melesse was an Assistant Professor at Alemaya University, Ethiopia and at the School of Aerospace Sciences, University of North Dakota before he joins FIU. He was tenured and promoted to Associate Professor in 2008 and to Full Professor in 2014. His areas of research and experience include spatially distributed hydrologic modeling, ecohydrology, spatial surface water balance modeling, sediment transport, surface and groundwater interactions modeling, spatial evapotranspiration mapping using remote sensing, water-energy-carbon fluxes coupling and modeling, remote sensing hydrology, climate change impact modeling, river basin management and land cover change detection and scaling. He has also worked on the application of artificial neural network and other statistical learning techniques to hydrology. He has vast experiences in the Nile River basin and the Caribbean islands. Dr. Melesse was a Fulbright Scholar in Ethiopia in 2012. Dr. Melesse has ample experience in river basin runoff modeling employing GIS and data from remote sensing. Dr. Melesse is a registered Professional Engineer (PE) and also Diplomate of Water Resources Engineer (D. WRE) with over 26 years of teaching, research and extension experience both in Ethiopia and USA.edit
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Soil moisture (SM) and groundwater (GW) depletion triggered by anthropogenic and natural climate change are influencing food security via crop production per capita decrease in the Nile River Basin (NRB). However, to the best of our... more
Soil moisture (SM) and groundwater (GW) depletion triggered by anthropogenic and natural climate change are influencing food security via crop production per capita decrease in the Nile River Basin (NRB). However, to the best of our understanding, the causes and impact of SM and GW depletion have not been studied yet comprehensively in the NRB. In this study, GW is derived from the Gravity Recovery and Climate Experiment (GRACE) mission, and SM was estimated using the Triple Collocation Analysis (TCA). SM/GW depletion causes were evaluated via the Land Use Land Cover (LULC) and rainfall/temperature change analysis, whereas impact analysis focused on crop production per capita reduction (food insecurity) during SM depletion. The major findings of this study are 1) TCA analyzed SM show a decreasing trend (-0.06 mm/yr) in agricultural land while increasing (+0.21 mm/yr) in forest land, 2) LULC analysis indicated a vast increment of agricultural land (+9%) and bareland (+9%) although the decreasing pattern of forest (-1.5%) and shrubland (-6.9%) during 1990-2019; 3) the impact of SM depletion on crop production per capita caused food insecurity during a drought year, 4) agriculture drought indices and crop production per capita show high correlations (R2 = 0.86 to 0.60) demonstrated that Vegetation Supply Water Index (VSWI) could provide strategic warning of drought impacts on rainfed agricultural regions. In conclusion, SM and GW depletions are mainly caused by human-induced and climate change factors imposing food insecurity challenges in the NRB coupled with increasing temperature and excessive water extraction for irrigation. Therefore, it is highly recommended to rethink and reverse SM/GW depletion causing factors to sustain food security in NRB and similar basins.
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Land surface energy fluxes are required in many environmental studies, including hydrology, agronomy and meteorology. Surface energy balance models simulate microscale energy exchange processes between the ground surface and the... more
Land surface energy fluxes are required in many environmental studies, including hydrology, agronomy and meteorology. Surface energy balance models simulate microscale energy exchange processes between the ground surface and the atmospheric layer near ground level. Spatial variability of energy fluxes limits point measurements to be used for larger areas. Remote sensing provides the basis for spatial mapping of energy fluxes.
Research Interests: Environmental Engineering, Civil Engineering, Remote Sensing, Evapotranspiration, Land Surface Temperature, and 15 moreEnergy Balance, Soybean, Spatial Distribution, Spatial Variability, Crop Yield, Energy Flux, Simulation Model, Sensible Heat Flux, Hydrological Processes, Latent Heat, Model simulation, Spatial mapping, Latent Heat Flux, remote sensing data, and Root mean square error
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This study presents three global precipitation products and their downscaled versions (CHIRPSv2, TAMSATv3, PERSIANN_CDR, CHIRPS_D, PERSIANNN_CDR_D, and TAMSAT_D) estimated with observed values from 1983 to 2014. Performance evaluation of... more
This study presents three global precipitation products and their downscaled versions (CHIRPSv2, TAMSATv3, PERSIANN_CDR, CHIRPS_D, PERSIANNN_CDR_D, and TAMSAT_D) estimated with observed values from 1983 to 2014. Performance evaluation of global precipitation products and their downscaled versions is important for accurate use of those measured values in water resource management, climate, and hydrological applications, particularly in the data-sparse Wabi Shebelle River Basin, Ethiopia. Categorical and quantitative evaluation index techniques were applied. The spatial downscaled global precipitation products outperformed raw spatial resolution estimates in all statistical indicators. TAMSAT-D had acceptable performance ratings in terms of RMSE, CC, and scatter plots (R2). CHIRPSv2 showed the least performance at a daily timestep. Performance of global precipitation products and their downscaled versions increased when daily data were aggregated to the monthly data. CHIRPS-D performe...
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The size and distribution of Phytoplankton populations are indicators of the ecological status of a water body. The chlorophyll-a (Chl-a) concentration is estimated as a proxy for the distribution of phytoplankton biomass. Remote sensing... more
The size and distribution of Phytoplankton populations are indicators of the ecological status of a water body. The chlorophyll-a (Chl-a) concentration is estimated as a proxy for the distribution of phytoplankton biomass. Remote sensing is the only practical method for the synoptic assessment of Chl-a at large spatial and temporal scales. Long-term records of ocean color data from the MODIS Aqua Sensor have proven inadequate to assess Chl-a due to the lack of a robust ocean color algorithm. Chl-a estimation in shallow and coastal water bodies has been a challenge and existing operational algorithms are only suitable for deeper water bodies. In this study, the Ocean Color 3M (OC3M) derived Chl-a concentrations were compared with observed data to assess the performance of the OC3M algorithm. Subsequently, a regression analysis between in situ Chl-a and remote sensing reflectance was performed to obtain a green-red band algorithm for coastal (case 2) water. The OC3M algorithm yielded ...
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Abstract Flash floods are the highest sediment transporting agent, but are inaccessible for in-situ sampling and have rarely been analyzed by remote sensing technology. Laboratory and field experiments were done to develop linear spectral... more
Abstract Flash floods are the highest sediment transporting agent, but are inaccessible for in-situ sampling and have rarely been analyzed by remote sensing technology. Laboratory and field experiments were done to develop linear spectral unmixing (LSU) remote sensing model and evaluate its performance in simulating the suspended sediment concentration (SSC) in flash floods. The models were developed from continuous monitoring in the laboratory and the onsite spectral signature of river bed sediment deposits and flash floods in the Tekeze River and in its tributary, the Tsirare River. The Pearson correlation coefficient was used to determine the variability of correlations between reflectance and SSCs. The coefficient of determination (R2) and root mean square of error (RMSE) were used to evaluate the performance of the generated models. The results found that the Pearson correlation coefficient between SSCs and reflectance varied based on the level of the SSCs, geological colors, and grain sizes. The performance of the LSU model and empirical remote sensing approaches were computed to be R2 = 0.92, and RMSE = ±0.76 g/l in the Tsirare River and R2 = 0.91, and RMSE = ±0.73 g/l in the Tekeze River and R2 = 0.81, RMSE = ±2.65 g/l in the Tsirare river and R2 = 0.76, RMSE = ±10.87 g/l in the Tekeze River, respectively. Hence, the LSU approach of remote sensing was found to be relatively accurate in monitoring and modeling the variability of SSCs that could be applied to the upper Tekeze River basin.
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Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most widely used approaches to reduce these damages is preparing a landslide... more
Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most widely used approaches to reduce these damages is preparing a landslide susceptibility map (LSM) using suitable methods and selecting the proper conditioning factors. The current study is aimed at comparing four bivariate models, namely the frequency ratio (FR), Shannon entropy (SE), weights of evidence (WoE), and evidential belief function (EBF), for a LSM of Klijanrestagh Watershed, Iran. Firstly, 109 locations of landslides were obtained from field surveys and interpretation of aerial photographs. Then, the locations were categorized into two groups of 70% (74 locations) and 30% (35 locations), randomly, for modeling and validation processes, respectively. Then, 10 conditioning factors of slope aspect, curvature, elevation, distance from fault, lithology, normalized difference vegetation index (NDVI), distance from the river, di...
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The hydrologic response of urbanized watersheds is greatly affected by the extent of fractional impervious surface (FIS) area. Impervious surfaces effect on ecohydrology of watersheds include reduction of infiltration, soil moisture... more
The hydrologic response of urbanized watersheds is greatly affected by the extent of fractional impervious surface (FIS) area. Impervious surfaces effect on ecohydrology of watersheds include reduction of infiltration, soil moisture storage, natural interception and depression storage, base flow and groundwater recharge, increase peak discharge, reduction in time to peak and time of concentration. These effects have important ecological and
Research Interests: Environmental Science, Remote Sensing, Groundwater recharge, Watershed Management, Land Cover, and 13 moreSoil moisture, Economic Impact, Storm, Cost effectiveness, Human impact, North Dakota, Travel Time, Spatial Distribution, River Basin, Chemical Properties, Overland Flow, Geographic Information System, and Surface Runoff
Research Interests: Watershed and Flood Myth
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... 179 Woubet Gashaw and Dagnachew Legesse 10 Soil Erosion Mapping and Hotspot Area Identification Using GIS and Remote Sensing ... 283 Seleshi B. Awulachew, Fasikaw Dessie Wubet, Matthew McCartney, and Yilma Sileshi Shiferaw 15... more
... 179 Woubet Gashaw and Dagnachew Legesse 10 Soil Erosion Mapping and Hotspot Area Identification Using GIS and Remote Sensing ... 283 Seleshi B. Awulachew, Fasikaw Dessie Wubet, Matthew McCartney, and Yilma Sileshi Shiferaw 15 Livestock-Water Productivity in the ...
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Land use/land cover change evaluation and prediction using spatiotemporal data are crucial for environmental monitoring and better planning and management of land use. The main objective of this study is to evaluate land use/land cover... more
Land use/land cover change evaluation and prediction using spatiotemporal data are crucial for environmental monitoring and better planning and management of land use. The main objective of this study is to evaluate land use/land cover changes for the time period of 1991–2022 and predict future changes using the CA-ANN model in the Upper Omo–Gibe River basin. Landsat-5 TM for 1991, 1997, and 2004, Landsat-7 ETM+ for 2010, and Landsat-8 (OLI) for 2016 and 2022 were downloaded from the USGS Earth Explorer Data Center. A random forest machine learning algorithm was employed for LULC classification. The LULC classification result was evaluated using an accuracy assessment technique to assure the correctness of the classification method employing the kappa coefficient. Kappa coefficient values of the classification indicate that there was strong agreement between the classified and reference data. Using the MOLUSCE plugin of QGIS and the CA-ANN model, future LULC changes were predicted. ...
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Abstract Drought prediction is very important in the planning and management of water resources. Karkheh River basin is one of the considerable water resources fields in Iran and it is located in western parts of Iran. In this chapter,... more
Abstract Drought prediction is very important in the planning and management of water resources. Karkheh River basin is one of the considerable water resources fields in Iran and it is located in western parts of Iran. In this chapter, using precipitation data of 7 meteorological stations from 1987 to 2014 and also applying Standard Precipitation Index (SPI) in 1, 3, 6, 9, 12 monthly time scales, dry periods were extracted and results were analyzed. Then forecasting of SPI3 time series was performed using AutoRegressive Integrated Moving Average (ARIMA) models. The result showed that meteorological drought occurred in years 1988, 1990, 1995, 1996, 1998, 2002, 2004, 2005, 2010, and 2011 in the basin. The analysis also indicated that ARIMA (3,3,4) for Aran Station, ARIMA(1,2,3) for Polechehr Station, ARIMA (4,2,4) for Doabmerk Station, ARIMA (0,3,4) for Tang-siab Station, ARIMA (4,2,4) for Dehno Station, ARIMA (0,3,4) for Sarabseyed Ali Station, ARIMA (2,2,4) for Nazarabad Station selected as the appropriate models regarding the minimum corrected Akaike information criterion (AICC). Eventually, the results showed a fairly good agreement between observed and predicted data indicating the linear stochastic models can be used for forecasting of SPI3 time series.
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Abstract This chapter evaluates flood inundation area in Fogera-Dera floodplain under future climate change in Lake Tana basin. Downscaling of the Global Climate Model (GCM) to watershed level was done by Linear Scaling (LS) bias... more
Abstract This chapter evaluates flood inundation area in Fogera-Dera floodplain under future climate change in Lake Tana basin. Downscaling of the Global Climate Model (GCM) to watershed level was done by Linear Scaling (LS) bias correction method. Parameter-efficient semidistributed watershed (PED-W) model was used to simulate streamflow under baseline and future climate projections. Two-dimensional (2D) BASEMENT hydrodynamic model was used for flood inundation area evaluation. Calibration and validation of PED-W indicated very good agreement with R2 = 0.77 and NSE = 0.76 and R2 = 0.77 and NSE = 0.76, respectively, on daily basis. Inundation area increased from 36.76 to 38.4, 41.91, and 46.36 km2 in RCP 2.6 and 40.12, 44.15, and 48.21 km2 in RCP 8.5 for 2020s, 2050s, and 2080s, respectively. Flooding in Dera-Fogera areas would be aggravated under future climate change. Flood monitoring and management systems have to be developed taking into consideration climate change scenarios.
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Abstract River valleys are dynamic living ecosystems of utmost importance for flood attenuation that are shaped by inundation dynamics. Topographic and bathymetric surveys represent pivotal information for accurate and up-to-date... more
Abstract River valleys are dynamic living ecosystems of utmost importance for flood attenuation that are shaped by inundation dynamics. Topographic and bathymetric surveys represent pivotal information for accurate and up-to-date floodplain studies. Both floodplain morphology as well as fluvial river cross section and thalweg profiles are required for inundation modelling and mapping. However, economic and technical limitations hinder their availability in some regions, resulting in challenges to build two dimensional (2D) flood wave routing simulations at proper accuracy and resolution. In this study, we assess the effectiveness of characterizing the fluvial morphology by means of geomorphic methods (GMs). Different GMs, used as surrogates of fluvial bathymetry, are tested and compared to a dataset of surveyed natural cross sections available for the Tiber River basin (Italy). Quantitative flood modelling performances are developed using a validated 150 m flood model, providing inundation extent and floodplain flow depths for the 200 years return period event. The ability (or inefficiency) of surrogating the lack of surveyed fluvial bathymetric data with GMs for supporting large scale hydraulic inundation modelling studies is assessed by testing the following 5 floodplain modelling configurations: (1) rectangular shaped cross section; (2) floodplain-based; (3) global river database; (4) linear regression bathymetric relationship; and (5) and a very coarse 700 grid resolution. In addition, two Global Flood Hazard Mapping (GFHM) products (hydrological, and hydrogeomorphic) were used as part of the large scale floodplain modelling evaluation framework. Results demonstrate that, once the fluvial channel flow area is preserved, all tested GM models produce consistent simulation of inundation depths and extents (Fit index ≥ 0.90). This work provides a quantitative assessment of the validity of the hypothesis stressing that the floodplain conveyance capacity is the driving principle of flood inundation dynamics under extreme flooding scenarios. Understanding the role of geomorphology during extreme magnitude floods may support the idea that under specific conditions, high resolution models and detailed topography/bathymetry are surplus to requirements. This work supports the application of geomorphic approaches over large riparian domains as a parsimonious solution for flood hazard mapping in data scarce regions for applications beyond flood mitigation and forecasting.
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Abstract Reservoir operation is an important part of the planning and management of water resources. It is a complex problem that involves many decision variables, conflicting objectives, and considerable risk and uncertainty that lead to... more
Abstract Reservoir operation is an important part of the planning and management of water resources. It is a complex problem that involves many decision variables, conflicting objectives, and considerable risk and uncertainty that lead to significant challenges for operators when making operational decisions. An operating policy is developed to guide the reservoir operators in decision making of releasing or storing water. The primary purpose of this study is to establish operating guide curves that include the probability of water shortage and water spillage by employing HEC-ResSim model for Ribb reservoir. Ribb reservoir is located in south Gonder zone of Amhara region mainly to irrigate an area of 19,925 ha. This study is to evaluate alternatives of reservoir operations and develop operating guidelines. Simulation was performed based on three defined alternatives. Alt-1, Alt-2, and Alt-3, that is, 100%, 90%, and 80% of the irrigation water demand fulfilled. The input data for the analysis were: inflows, reservoir characteristics, irrigation and domestic water demands, and reservoir water losses. The analysis revealed that the catchment, upstream of Ribb dam could yield 237.12 Mm3 (million cubic meter) of water annually including rainfall on the reservoir. The outputs of the model were the difference in inflow and outflow of the reservoir system. Maximum release is 223.4 Mm3 including domestic and water losses. Storage capacity of the reservoir is 233.7 Mm3 and water losses are 50 Mm3 per year via spilling. The study also assessed the performance of the reservoir using reliability, resilience, and vulnerability (R-R-V) criteria. Based on the outputs, the study provided a reservoir operating guide curves (upper, lower, and operating rule curves). The analysis deduced that the available water source in the Ribb watershed has sufficient capacity to develop the 100% of the irrigable land (19,925 ha). But, in order to increase the reservoir performance (reliability) and for full utilization of the available water source in the watershed, the study proposes additional storage dam. Dry years are likely to occur during El Nino years at a confidence level of 90%. Low and high flow analysis for selected tributaries and flow at the Blue Nile River flow shows different recurrence intervals of the high and low flows.
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Abstract Shared waters are vital resources for human well-being, socio-economic development, and environmental health. Management of shared water resources is a challenging issue to promote peaceful cooperation between neighboring... more
Abstract Shared waters are vital resources for human well-being, socio-economic development, and environmental health. Management of shared water resources is a challenging issue to promote peaceful cooperation between neighboring countries and sustainable development. This chapter first describes shared waters concepts and then presents a framework to manage shared water resources and to find reliable solutions for shared waters problems. Managing shared waters needs fully analyzing a case study, technically assessing the case study, resolving the conflicts and allocation problems, and reaching to a cooperative vision in the case study.
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Abstract Drought is one of the most damaging natural disasters which cause huge losses to agriculture, ecosystem, and society. Natural vegetation which is one of the most important factors for ecosystem health and environmental and land... more
Abstract Drought is one of the most damaging natural disasters which cause huge losses to agriculture, ecosystem, and society. Natural vegetation which is one of the most important factors for ecosystem health and environmental and land resources planning is severely affected by drought. Drought management is therefore essential for sustainable development. This study aimed to investigate the relationship between changes in vegetation and drought, using remote sensing data in Sari, northern part of Iran. These relationships were studied as simultaneous and up to 2-month lag for the month of May during the period 2000–2017. The results indicated that the correlation between vegetation and drought in the lag-time approach was higher than that in the simultaneous approach. The highest correlation occurred between normalized difference vegetation index (NDVI) and standardized precipitation index (SPI). So, NDVI and SPI indices were found to be the best indicators of relationship between vegetation and drought.
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ABSTRACT The generation of scientific information for improved understating of the physical dynamics of a lake is fundamental for guiding lake stakeholders and managers at the local level to implement best management practices and help... more
ABSTRACT The generation of scientific information for improved understating of the physical dynamics of a lake is fundamental for guiding lake stakeholders and managers at the local level to implement best management practices and help design effective management strategies and policies at higher levels. Multitemporal bathymetric information on lakes is very important in hydrology and sediment studies to more clearly indicate environmental changes and to understand the effects of land processes on the hydrology of lakes. Accordingly, the purpose of this study was to map bathymetric charts of Lake Hayq in Ethiopia and to derive morphometric parameters, including depth, volume, area, width and length, and to plot curves illustrating the relationships between these parameters. The bathymetric survey was carried out using a combination of a SonarLite Portable Echo Sounder and Global Positioning System (GPS) to generate three‐dimensional (XYZ) hydrographic data. Surfer 8.01 and ArcGIS 9.3 software program were used for surface, gridding and morphometric analyses. Comparison of the results of this study with a previous study conducted in 1941 indicated the lake has experienced changes in depth and surface area. To reduce the negative impacts of human‐induced activities on the ecohydrology of the lake, and to maintain its ecological integrity, appropriate and integrated lake management practices must be adopted. This will necessitate policy formulation, active lake basin stakeholder involvement and implementation of basin‐wide lake management to ensure sustainable use of the lake and its basin resources.