M. Spiliotopoulos

Early cotton yield assessment by the use of the NOAA/AVHRR derived Vegetation Condition Index (VCI) in Greece

Satellite data can significantly contribute to agricultural monitoring. The reflected radiation, as recorded by satellite sensors, provides an indication of the type, density and condition of canopy. A widely used index for vegetation monitoring is the Normalized Difference Vegetation Index (NDVI) derived from the National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) data provided in high temporal resolution. An extension of the NDVI is the Vegetation Condition Index (VCI). VCI is a tool for monitoring agrometeorological conditions, providing a quantitative estimation of weather impact to vegetation. The primary objective of this paper is the quantitative assessment of the cotton yield before the end of the growing season by examining the weather effects as they are depicted by the VCI. The study area comprises several cotton producing areas in Greece. Ten-day NDVI maximum value composites (MVC) are initially utilized for the period 1982–1999. The correlation between VCI images as extracted from NDVI and the 10-day intervals during the growing season is examined to identify the critical periods associated mostly with the yield. Empirical relationships between VCI and yield are developed. The models are tested on an independent dataset. The results show that an early estimation of the cotton yield trend is feasible by the use of the VCI.

Early cotton production assessment in Greece based on a combination of the drought Vegetation Condition Index (VCI) and the Bhalme and Mooley Drought Index (BMDI)

A new methodological approach is presented for quantifying the meteorological effects on cotton production during the growing season in Greece. The proposed Bhalme and Mooley Vegetation Condition Index (BMVCI) is based on the Vegetation Condition Index (VCI) extracted by National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. In this approach the VCI data is processed with the Bhalme and Mooley methodology to assess the accumulated meteorological effects on cotton from April to August. The resulting index is at the same scale as the Z-Index, which is the classification of the Palmer Drought Severity Index (PDSI) extensively used for drought monitoring. For this study 16 years of data are examined to illustrate that the weather development as identified from satellite data with the use of BMVCI confirm unfavourable conditions for cotton production. For the validation of BMVCI an empirical relationship between the cotton production and the BMVCI values is derived. The resultant high correlation coefficient refers to very encouraging results and confirms the usefulness of the proposed integrated methodological approach as an effective tool for early assessment of the cotton production in Greece.

A 2D Cellular Automaton Biofilm Detachment Algorithm

A cellular-automaton based two-dimensional biofilm detachment module is developed. The module is an improvement of previously presented methodologies for modeling biofilm detachment under the influence of hydrodynamic forces of the moving fluid in which biofilm develops. It uses biofilm mechanical properties that are variable in time and space and are determined by the percentage of each biofilm solid substance—active biomass, extracellular polymeric substance (EPS) and residual dead biomass—and pores that are contained in each cellular automaton compartment in the biofilm column. A methodology is presented that estimates wall shear stresses applied on the biofilm by the fluid for different hydrodynamic conditions and an association with the biofilm mechanical properties is created to predict its detachment. The module is applied in samples created by the UMCCA model [Laspidou and Rittmann, Water Res 38 (2004), 3362-3372].

A spatial downscaling procedure of MODIS derived actual evapotranspiration using Landsat images at central Greece

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.

Remotely-Sensed innovative approach for the cumulative meteorological effects on cotton production

In this study an innovative approach for investigating the accumulated meteorological effects on cotton production during the growing season is presented. The quantification of the meteorological effects is based on the incorporation of the Bhalme and Mooley Drought Index (BMDI) methodology into the Vegetation Condition Index (VCI) extracted by NOAA/AVHRR data. The resulted Bhalme and Mooley Vegetation Condition Index (BMVCI) uses the same scale as the Z-Index of the Palmer Drought Severity Index (PDSI) for drought monitoring. The study area consists of the country of Greece. Eighteen years of NOAA/AVHRR data are examined and processed with the BMVCI to examine the unfavourable conditions for cotton production. For the validation of BMVCI an empirical relationship between the cotton production and the BMVCI values is derived. The method is developed based on the first sixteen years time series data and validated utilizing the following two years. The resultant high correlation coefficient and the approximation of the production for the validated years refer to very favourable results and confirms the usefulness of this integrated methodological approach as an effective tool to assess cotton production in Greece.

Numerical Investigation of Wind Driven Circulation and Horizontal Dispersion in the Surface Layer of a Re-flooded Shallow Lake

The re-flooded lakes with unique natural and cultural values that are under threat from anthropogenic pressure, consist a very important section of fresh water resources management in the Mediterranean. Lake Karla, positioned in the eastern part of Thessaly (Greece), is an example of a lake ecosystem, which was dried in the 60s to provide additional agricultural land; its restoration was launched in 2000 under the 3rd Community Support Framework. The object of the present paper is the study of the effect of the inflows, the wind action and the Coriolis action on the water circulation and the horizontal dispersion of the lake, using a three-dimensional hydrodynamic model. A number of wind directions have been tested upon the lake’s circulation, while in addition to winds other parameters, like inflow and Coriolis force, have been accounted for. Conservative computational tracers were used to assess the rate of horizontal dispersion from various locations in Lake Karla. The simulations indicated that in the coastal strip, the direction of the current corresponded to the wind direction. The horizontal dispersion rate is higher in the central region of the lake and it is not influenced by the presence of the inflow from Pinios River and the Coriolis action. The research in this paper will be useful in determining the horizontal transport of waterborne materials in the lake body which plays a major role in determining its biochemical status.

Estimation of crop water requirements using remote sensing for operational water resources management

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.

Identification of the key variables that can be estimated using remote sensing data and needed for Water Footprint (WF) assessment

Accurate assessment of water use is an important issue in a globally changing climate and environment, where water is becoming a scarce but essential resource. The concept ‘Water Footprint’ (WF) of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. This indicator provides valuable information for a global assessment of how water resources are used. Remote sensing (RS) provides physically-based, worldwide, and consistent spatial information over space and time, and has been used in hydrological applications in order to estimate relevant variables at different temporal and spatial scales. The paper focuses on exploring and exploiting the potential of using RS techniques and data for WF assessment in agriculture. Based on recent papers initiated in this research topic the investigation focuses on how variables needed in the calculation of water footprint are obtained (based on non RS and on RS approaches), on identifying the inputs required for estimating the WF of crops and whether it is feasible to integrate various RS approaches. The results of this study demonstrate the usefulness of satellite data for water footprint assessment, which were obtained by the Remote Sensing Working Group in the framework of the ESSEM COST Action ES1106, “Assessment of EUROpean AGRIculture WATer use and trade under climate change” (EURO-AGRIWAT).

Development of a district information system for water management planning and strategic decision making

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.

A new remote sensing procedure for the estimation of crop water requirements

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.