The objective of this work is the development of a new approach for the estimation of water requirements for the most
important crops located at Karla Watershed, central Greece. Satellite-based energy balance for mapping
evapotranspiration with internalized calibration (METRIC) was used as a basis for the derivation of actual
evapotranspiration (ET) and crop coefficient (ETrF) values from Landsat ETM+ imagery. MODIS imagery has been also
used, and a spatial downscaling procedure is followed between the two sensors for the derivation of a new NDVI product
with a spatial resolution of 30 m x 30 m. GER 1500 spectro-radiometric measurements are additionally conducted during
2012 growing season. Cotton, alfalfa, corn and sugar beets fields are utilized, based on land use maps derived from
previous Landsat 7 ETM+ images. A filtering process is then applied to derive NDVI values after acquiring Landsat
ETM+ based reflectance values from the GER 1500 device. ETrF vs NDVI relationships are produced and then applied
to the previous satellite based downscaled product in order to finally derive a 30 m x 30 m daily ETrF map for the study
area. CropWat model (FAO) is then applied, taking as an input the new crop coefficient values with a spatial resolution
of 30 m x 30 m available for every crop. CropWat finally returns daily crop water requirements (mm) for every crop and
the results are analyzed and discussed.
The overall objective of this work is the development of a District Information System (DIS) which could be used by stakeholders for the purposes of a district day-to-day water management as well as for planning and strategic decisionmaking. The DIS was developed from a GIS-based modeling approach, which integrates a generic crop model and a hydraulic model of the transport/distribution system, using land use maps generated by Landsat TM imagery. The main sub-objectives are: (i) the development of an operational algorithm to retrieve crop evapotranspiration from remote sensing data, (ii) the development of an information system with friendly user interface for the data base, the crop module and the hydraulic module and (iii) the analysis and validation of management scenarios from model simulations predicting the respective behavior. The Lake Karla watershed is used in this study, but the overall methodology could be used as a basis for future analysis elsewhere. Surface Energy Balance Algorithm for Land (SEBAL) was used to derive monthly actual evapotranspiration (ET) values from Landsat TM imagery. Meteorological data from the archives of the Institute for Research and Technology, Thessaly (I.RE.TE.TH) has also been used. The methodology was developed using high quality Landsat TM images during 2007 growing season. Monthly ET values are used as an input to CROPWAT model. Outputs of CROPWAT model are then used as input for WEAP model. The developed scenario is based on the actual situation of the surface irrigation network of the Local Administration of Land Reclamation (LALR) of Pinios for the year of 2007. The DIS is calibrated with observed data of this year and the district parameterization is conducted based on the actual operation of the network. The operation of the surface irrigation network of Pinios LALR is simulated using Technologismiki Works, while the operation of closed pipe irrigation network of Lake Karla LALR is simulated using Watercad. Four alternative scenarios have been tested with the DIS: reduction of channel losses, alteration of irrigation methods, Introduction of greenhouse cultivation, and operation of the future Lake Karla network. The results of the simulation for the historical period indicate that the water pumped from Pinios LALR is not enough to serve irrigation requirements. The spatial and temporal variation of the unmet and unsatisfied water demand has been estimated. Simulation of the four alternative scenarios indicated that the alteration of irrigation methods scenario mainly increases the efficiency of the irrigation network.
An integrated modeling system, developed in the framework of “Hydromentor” research project, is applied to evaluate
crop water requirements for operational water resources management at Lake Karla watershed, Greece. The framework
includes coupled components for operation of hydrotechnical projects (reservoir operation and irrigation works) and
estimation of agricultural water demands at several spatial scales using remote sensing. The study area was sub-divided
into irrigation zones based on land use maps derived from Landsat 5 TM images for the year 2007. Satellite-based
energy balance for mapping evapotranspiration with internalized calibration (METRIC) was used to derive actual
evapotranspiration (ET) and crop coefficient (ETrF) values from Landsat TM imagery. Agricultural water needs were
estimated using the FAO method for each zone and each control node of the system for a number of water resources
management strategies. Two operational strategies of hydro-technical project development (present situation without
operation of the reservoir and future situation with the operation of the reservoir) are coupled with three water demand
strategies. In total, eight (8) water management strategies are evaluated and compared. The results show that, under the
existing operational water resources management strategies, the crop water requirements are quite large. However, the
operation of the proposed hydro-technical projects in Lake Karla watershed coupled with water demand management
measures, like improvement of existing water distribution systems, change of irrigation methods, and changes of crop
cultivation could alleviate the problem and lead to sustainable and ecological use of water resources in the study area.
The objective of this work is the investigation of the specific relationships between actual evapotranspiration based crop coefficients and vegetation indices adapted to Karla Watershed, central Greece. Surface Energy Balance Algorithm for Land (SEBAL) was used to derive monthly actual evapotranspiration (ET) and ETrF values during the growing season of 2012. The methodology was developed using medium resolution Landsat 7 ETM+ images. Meteorological data from the archive of the Institute for Research and Technology, Thessaly (I.RE.TE.TH) have also been used. Fields with cotton, wheat, alfalfa, corn and sugar beets are utilized. During the same period, in-situ radiometric measurements were generated with the use of the field spectro-radiometer GER1500 giving specific spectral signatures for each crop. Filtering of reflectance values with the use of relative spectral responses (RSR) gives the opportunity to match the spectral measurements with Landsat ETM+ bands and compute VI like NDVI, SAVI, EVI and EVI2 using the same remote sensing formulas as the ETM+ conventional procedures. New relationships are derived and NDVI, SAVI, EVI and EVI2 are tested separately for each crop. Special attention is given to the constant L inside the SAVI relationship. The main advantage of the new approach is that is more crop specific and it less time consuming because there is no need for atmospheric correction.
In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to derive daily actual evapotranspiration (ETa) distributions from Landsat and MODIS images separately. The study area is the Lake Karla basin in Thessaly, Central Greece. Meteorological data from the archive of Center for Research and Technology, Thessaly (CERETETH) have also been used. The methodology was developed using satellite and ground data for the period of summer 2007. Landsat and MODIS imagery were combined in order to have data with high temporal and spatial resolution (downscaling). The downscaling technique applied is the output downscaling with regression between images. This technique disaggregates imagery by applying linear regression between two MODIS products to the previous or subsequent Landsat product. After the calculation of a first order linear regression between two MODIS-derived ETa maps the next step is the regression to the ETa map derived from the prior Landsat image to predict the disaggregated subsequent Landsat ETa map. The results are satisfactory, giving the general trend of ETa derived from the original SEBAL procedure.
KEYWORDS: LIDAR, Floods, Clouds, Data modeling, Spatial resolution, Data processing, Laser scanners, Geographic information systems, Bridges, Imaging systems
Spatial resolution of river and riverine area is an important aspect of hydraulic flood modeling that affects the accuracy of flood extent. This study compares the accuracy of Digital Elevation Models (DEMs) produced from three methods of land surveying measurements and their effect on the results of river flow modeling and mapping of floodplain. Four data sets have been used for the creation of the DEMs: Light Detection and Ranging (LiDAR) point cloud data (raw data and processed), classic land surveying and digitization of elevation contours from 1:5000 scale topographic maps. LiDAR offers advantages over traditional methods for representing a terrain. Optech ILRIS-3D (Intelligent Laser Ranging and Imaging System) is a land based LiDAR system and has been used in this study. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. In this study, geomorphologic filters, GIS operations and expert knowledge have been applied to produce the bare earth DEM. The HEC-GeoRAS and HEC-RAS software have been used as pre- and post-processing tools to prepare model inputs, simulate of river flow, and delineate flood inundation maps. The methodology has been applied in the suburban part of Xerias river at Volos-Greece, where typical hydrologic and hydraulic methods for ungauged watersheds have been used for flood modeling and inundation mapping. The results show that flood inundation area is significantly affected by the accuracy of DEM spatial resolution and could have significant impact on the delineation and mapping of flood hazard areas.
The use of actual evapotranspiration derived by satellite data at watershed scale in water balance modelling of forested mountainous watersheds is studied. Mean monthly maximum composites of the Normalized Difference Vegetation Index (NDVI), derived from the National Oceanic and Atmospheric Administration’s (NOAA) / Advanced Very High Resolution Radiometer (AVHRR) were correlated with monthly actual evapotranspiration rates estimated by a water balance model. The water balance model was applied to three mountainous and forested watersheds of Central Thessaly in Greece and the actual basin-wide evapotranspiration was estimated using two methods for the estimation of basin wide precipitation and two methods of potential evapotranspiration. The derived values of actual evapotranspiration were then correlated to NDVI data, and the developed equations were validated temporally and spatially. The actual evapotranspiration estimates, derived from NDVI and used in the water balance model, resulted in equally accurate simulations of monthly runoff when compared with the simulations acquired from the classical application of water balance model.
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