Browsing by Author "Mengistu, Michael Ghebrekidan."

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Comparison between satellite-based and cosmic ray probe soil moisture estimates : a case study in the Cathedral Peak catchment.
(2015) Vather, Thigesh.; Chetty, Kershani Tinisha.; Mengistu, Michael Ghebrekidan.; Everson, Colin Stuart.
Abstract available in PDF file.
Developing a method to estimate the water use of South African natural vegetation using remote sensing.
(2016) Ramjeawon, Manish Roshenlal.; Toucher, Michele Lynn.; Mengistu, Michael Ghebrekidan.
The scarcity of water is a growing concern throughout the world. It is essential to accurately determine the quantity and quality of this valuable resource to aid in water resource planning and management. For this purpose a hydrological baseline is required to compare against the water use of other land uses. Currently, the Acocks (1988) Veld Type is the baseline land cover used for hydrological studies. However, there are several shortcomings associated with this baseline land cover that may be overcome by using the recently released natural land cover map produced by South African National Biodiversity Institute (SANBI) 2012. A barrier to the use of the SANBI (2012) vegetation map is that, the water use parameters have not been determined for the various vegetation units defined. Vegetation water use can be determined by estimating the total evaporation (ET). There are a number of in-situ methods available to estimate ET. However, these methods estimate ET based on point or line averaged measurements which are only representative of local scales and cannot be extended to large areas because of land surface heterogeneity. The application of remote sensing energy balance models has the potential to overcome these limitations. Remote sensing has the ability to produce large spatial scale estimates of ET. It can also provide information at remote sites where it is difficult to install instruments. The focus of this study was to develop a method to estimate ET for natural vegetation of South Africa using remote sensing. The Surface Energy Balance System (SEBS) model in conjunction with Landsat 7 ETM+ and 8 OLI/TRS images was first used to validate point-based ET from various biomes across the country. The results from the study indicate a fair comparison between the in-situ ET data and the evaporation estimates produced using the SEBS model with coefficient of determination value of 0.66 being achieved and a RMSE of 1.74 mm.day-1. The highest RMSE was attained for the Ingeli forest site whilst the lowest belonged to the Nama Karoo site of 2.2 mm.day-1 and 0.5 mm.day-1, respectively. The SEBS model was able to estimate ET which mimics the trend of in-situ ET well. However, the model tends to over-estimate ET in comparison to in-situ ET data. Following the validation of the in-situ and SEBS ET, the SEBS model was applied to model ET for a year. For this investigation, cloud free Landsat 8 OLI/TRS images was obtained for each biome for the period between 1 July 2014 to 31 June 2015. The highest ET value of 8.7 mm/day was obtained from the Forest biome on the 12 January 2015 and the lowest ET estimate of 0.09 mm/day was on the 17 January 2015 for the Nama Karoo biome. The Forest biome recorded the highest mean ET value of 4.9 mm/day whilst the lowest mean ET value was 0.71 mm/day attained from the Nama Karoo biome. Satellite derived ET using the SEBS model produced reliable estimates when compared to in- situ ET. The spatial and temporal resolution of ET can be achieved using remote sensing. The ET estimates from SEBS compared well to the in-situ ET measurements and followed the seasonal trend, however an over-estimation of ET was present in some cases. Overall, remote sensing proves a viable option to estimate ET over large areas. This method can be applied to derive the water use which can be used to determine water use parameters.
The effect of spatial resolution in remote sensing estimates of total evaporation in the uMgeni catchment.
(2014) Shoko, Cletah.; Clark, David John.; Bulcock, Hartley Hugh.; Mengistu, Michael Ghebrekidan.
The estimation of total evaporation plays a vital role in water resources monitoring and management, especially in water-limited environments. In South Africa, the increasing water demand, due to population growth and economic development, threatens the long-term water supply. This, therefore, underscores the need to account for water by different consumers, for well-informed management, allocation and future planning. Currently, there are different methods (i.e. ground-based and remote sensing-based methods), which have been developed and implemented to quantify total evaporation at different spatial and temporal scales. However, previous studies have shown that ground-based methods are inadequate for understanding the spatial variations of total evaporation, within a heterogeneous landscape; they only represent a small area, when compared to remotely sensed methods. The advent of remote sensing therefore provides an invaluable opportunity for the spatial characterization of total evaporation at different spatial scales. This study is primarily aimed at estimating variations of total evaporation across a heterogeneous catchment in KwaZulu-Natal, South Africa, using remote sensing data. The first part provides an overview of total evaporation, its importance within the water balance and consequently in the management of water resources. It also covers various methods developed to estimate total evaporation, highlighting their applications, limitations, and finally, the need for further research. Secondly, the study determines the effect of sensor spatial resolution in estimating variations of total evaporation within a heterogeneous uMngeni Catchment. Total evaporation estimates were derived, using multispectral 30 m Landsat 8 and 1000 m MODIS, based on the Surface Energy Balance (SEBS) model. The results have shown that different sensors, with varying spatial resolutions, have different abilities in representing variations of total evaporation at catchment scale. It was found that Landsat-based estimates were significantly different (p < 0.05) from MODIS. The study finally estimates spatial variations of total evaporation from Landsat 8 and MODIS datasets for the uMngeni Catchment. It was found that the Landsat 8 dataset has greater potential for the detection of spatial variations of total evaporation, when compared to the MODIS dataset. For instance, MODIS-based daily total evaporation estimates did not show any significant difference across different land cover types (One way ANOVA; F1.924 = 1.412, p= 0.186), when compared to the 30 m Landsat 8, which yielded significantly different estimates between different land cover types (One way ANOVA; F1.993= 5.185, p < 0.001). The validation results further indicate that Landsat-based estimates were more comparable to ground-based eddy covariance measurements (R2 = 0.72, with a RMSE of 32.34 mm per month (30.30% of the mean)). In contrast, MODIS performed poorly (R2 = 0.44), with a RMSE of 93.63 mm per month (87.74% of the mean). In addition, land cover-based estimates have shown that, not only does the land cover type have an effect on total evaporation, but also the land cover characteristics, such as areal extent and patchiness. Overall, findings from this study underscore the importance of the sensor type, especially spatial resolution, and land cover type characteristics, such as areal extent and patchiness, in accurately and reliably estimating total evaporation at a catchment scale. It is also evident from the study that the spatial and temporal variations in SEBS inputs (e.g., LAI, NDVI and FVC) and energy fluxes (e.g., Rn) calculated by SEBS for the two sensors can affect the spatial and temporal variations in total evaporation estimates. For instance, spatial variations in total evaporation reflected similar spatial variations in Rn. Areas with high NDVI, FVC and LAI (which denotes dense vegetation cover) tend to have higher total evaporation estimates, compared to areas with lower vegetation cover. In addition, the MODIS sensor at 1000 m spatial resolution showed lower estimates of SEBS inputs with less variability across the catchment. This resulted in lower total evaporation estimates, with less variability, compared to the 30 m Landsat 8. In addition, with regard to inputs derived from remote sensing, it was found that the spatial variations in total evaporation are not determined by individual variables (e.g., LST), but are influenced by a combination of many biophysical variables, such as LAI, FVC and NDVI. These findings lay a foundation for a better approach to estimate total evaporation using remote sensing for use in the management and allocation of water.
Heat and energy exchange above different surfaces using surface renewal.
(2008) Mengistu, Michael Ghebrekidan.; Savage, Michael John.
The demand for the world’s increasingly scarce water supply is rising rapidly, challenging its availability for agriculture and other environmental uses, especially in water scarce countries, such as South Africa, with mean annual rainfall is well below the world’s average. The implementation of effective and sustainable water resources management strategies is then imperative, to meet these increasingly growing demands for water. Accurate assessment of evaporation is therefore crucial in agriculture and water resources management. Evaporation may be estimated using different micrometeorological methods, such as eddy covariance (EC), Bowen ratio energy balance (BR), surface renewal (SR), flux variance (FV), and surface layer scintillometry (SLS) methods. Despite the availability of different methods for estimating evaporation, each method has advantages and disadvantages, in terms of accuracy, simplicity, spatial representation, robustness, fetch, and cost. Invoking the shortened surface energy balance equation for which advection and stored canopy heat fluxes are neglected, the measurement of net irradiance, soil heat flux, and sensible heat flux allows the latent energy flux and hence the total evaporation amount to be estimated. The SR method for estimating sensible heat, latent energy, and other scalars has the advantage over other micrometeorological methods since it requires only measurement of the scalar of interest at one point. The SR analysis for estimating sensible heat flux from canopies involves high frequency air temperature measurements (typically 2 to 10 Hz) using 25 to 75 ìm diameter fine-wire thermocouples. The SR method is based on the idea that parcel of air near a surface is renewed by an air parcel from above. The SR method uses the square, cube, and fifth order of two consecutive air temperature differences from different time lags to determine sensible heat flux. Currently, there are three SR analysis approaches: an ideal SR analysis model based on structure function analysis; an SR analysis model with finite micro-front period; and an empirical SR analysis model based on similarity theory. The SR method based on structure function analysis must be calibrated against another standard method, such as the eddy covariance method to determine a weighting factor á which accounts for unequal heating of air parcels below the air temperature sensor height. The SR analysis model based on the finite micro-front time and the empirical SR analysis model based on similarity theory need the additional measurement of wind speed to estimate friction velocity. The weighting factor á depends on measurement height, canopy structure, thermocouple size, and the structure function air temperature lag. For this study, á for various canopy surfaces is determined by plotting the SR sensible heat flux SR H against eddy covariance EC H estimates with a linear fit forced through the origin. This study presents the use of the SR method, previously untested in South Africa, to estimate sensible heat flux density over a variety of surfaces: grassland; Triffid weed (Chromolaena odorata); Outeniqua Yellow wood (Podocarpus Falcatus) forest; heterogeneous surface (Jatropha curcas); and open water surface. The sensible heat flux estimates from the SR method are compared with measurements of sensible heat flux obtained using eddy covariance, Bowen ratio, flux variance, and surface layer scintillometer methods, to investigate the accuracy of the estimates. For all methods used except the Bowen ratio method, evaporation is estimated as a residual using the shortened energy balance from the measured sensible heat and from the additional measurements of net irradiance and soil heat flux density. Sensible heat flux SR H estimated using the SR analysis method based on air temperature structure functions at a height of 0.5 m above a grass canopy with a time lag r = 0.5 s, and á =1 showed very good agreement with the eddy covariance EC H , surface layer scintillometer SLS H , and Bowen ratio BR H estimates. The half-hourly latent energy flux estimates obtained using the SR method SR ë E at 0.5 m above the grass canopy for a time lag r = 0.5 s also showed very good agreement with EC ë E and SLS ë E . The 20-minute averages of SR ë E compared well with Bowen ratio BR ë E estimates. Sensible heat and latent energy fluxes over an alien invasive plant, Triffid weed (C. odorata) were estimated using SR , EC , FV and SLS methods. The performance of the three SR analysis approaches were evaluated for unstable conditions using four time lags r = 0.1, 0.4, 0.5, and 1.0 s. The best results were obtained using the empirical SR method with regression slopes of 0.89 and root mean square error (RMSE) values less than 30 W m-2 at measurement height z = 2.85 and 3.60 m above the soil surface for time lag r = 1.0 s. Half-hourly SR H estimates using r = 1.0 s showed very good agreement with the FV and SLS estimates. The SR latent energy flux, estimated as a residual of the energy balance ë ESR , using time lag r = 1.0 s provided good estimates of EC ë E , FV ë E , and SLS ë E for z = 2.85 and 3.60 m. The performance of the three SR analysis approaches for estimating sensible heat flux above an Outeniqua Yellow wood stand, were evaluated for stable and unstable conditions. Under stable conditions, the SR analysis approach using the micro-front time produced more accurate estimates of SR H than the other two SR analysis approaches. For unstable conditions, the SR analysis approach based on structure functions, corrected for á using EC comparisons produced superior estimates of SR H . An average value of 0.60 is found for á for this study for measurements made in the roughness sublayer. The SR latent energy flux density estimates SR ë E using SR H based on structure function analysis gave very good estimates compared with eddy covariance ( EC ë E ) estimates, with slopes near 1.0 and RMSE values in the range of 30 W m-2. The SR ë E estimates computed using the SR analysis approach using the micro-front time also gave good estimates comparable to EC ë E . The SR and EC methods were used to estimate long-term sensible heat and latent energy flux over a fetch-limited heterogeneous surface (J. curcas). The results show that it is possible to estimate long-term sensible heat and latent energy fluxes using the SR and EC methods over J. curcas. Continuous measurements of canopy height and leaf area index measurements are needed to determine á . The weighting factor á was approximately 1 for placement heights between 0.2 and 0.6 m above the Jatropha tree canopy. The daily sensible heat and latent energy flux estimates using the SR analysis gave excellent estimates of daily EC sensible heat and latent energy fluxes. Measurements of sensible heat and estimates of the latent energy fluxes were made for a small reservoir, using the SR and EC methods. The SR sensible heat flux SR H estimates were evaluated using two air temperature time lags r = 0.4 and 0.8 s at 1.0, 1.3, 1.9, 2.5 m above the water surface. An average á value of 0.175 for time lag r = 0.4 s and 0.188 for r = 0.8 s was obtained. The SR H and EC H estimates were small (-40 to 40 W m-2). The heat stored in water was larger in magnitude (-200 to 200 W m-2) compared to the sensible heat flux. The SR and EC latent energy fluxes were almost the same in magnitude as the available energy, due to the small values of the sensible heat fluxes. The daily evaporation rate ranged between 2.0 and 3.5 mm during the measurement period. The SR method can be used for routine estimation of sensible heat and latent energy fluxes with a reliable accuracy, over a variety of surfaces: short canopies, tall canopies, heterogeneous surface, and open water surface, if the weighting factor á is determined. Alternatively, the SR method can be used to estimate sensible heat flux which is exempt from calibration using the other two SR analysis approaches, with additional measurement of wind speed for estimating friction velocity iteratively. The advantages of the SR method over other micrometeorological methods are the relatively low cost, easy installation and maintenance, relatively low cost for replicate measurements. These investigations may pave the way for the creation of evaporation stations from which real-time and sub-hourly estimates of total evaporation may be obtained relatively inexpensively.
The use of infrared thermometry for irrigation scheduling of cereal rye (Secale cereale L.) and annual ryegrass (Lolium multiflorum Lam.)
(2003) Mengistu, Michael Ghebrekidan.; Savage, Michael John.; Everson, Colin Stuart.
Limited water supplies are available to satisfy the increasing demands of crop production. It is therefore very important to conserve the water, which comes as rainfall, and water, which is used in irrigation. A proper irrigation water management system requires accurate, simple, automated, non-destructive method to schedule irrigations. Utilization of infrared thermometry to assess plant water stress provides a rapid, nondestructive, reliable estimate of plant water status which would be amenable to larger scale applications and would over-reach some of the sampling problems associated with point measurements. Several indices have been developed to time irrigation. The most useful is the crop water stress index (CWSI), which normalizes canopy to aIr temperature differential measurements, to atmospheric water vapour pressure deficit. A field experiment was conducted at Cedara, KwaZulu-Natal, South Africa, to determine the non-water-stressed baselines, and CWSI of cereal rye (Secale cereale L.) from 22 July to 26 September 2002, and aImual (Italian) ryegrass (Lolium multiflorum Lam.) from October 8 to December 4, 2002, when the crops completely covered the soil. An accurate measurement of canopy to air temperature differential is crucial for the determination of CWSI using the empirical (Idso et al., 1981) and theoretical (Jackson et al., 1981) methods. Calibrations of infrared thermometers, a Vaisala CS500 air temperature and relative humidity sensor and thermocouples were performed, and the reliability of the measured weather data were analysed. The Everest and Apogee infrared thermometers require correction for temperatures less than 15 QC and greater than 35 QC. Although the calibration relationships were highly linearly significant the slopes and intercepts should be corrected for greater accuracy. Since the slopes of the thermocouples and Vaisala CS500 air temperature sensor were statistically different from 1, multipliers were used to correct the readings. The relative humidity sensor needs to be calibrated for RH values less than 25 % and greater than 75 %. The integrity of weather data showed that solar irradiance, net irradiance, wind speed and vapour pressure deficit were measured accurately. Calculated soil heat flux was underestimated and the calculated surface temperature was underestimated for most of the experimental period compared to measured canopy temperature. The CWSI was determined using the empirical and theoretical methods. An investigation was made to determine if the CWSI could be used to schedule irrigation in cereal rye and annual rye grass to prevent water stress. Both the empirical and theoretical methods require an estimate or measurement of the canopy to air temperature differential, the non-waterstressed baseline, and the non-transpiring canopy to air temperature differential. The upper (stressed) and lower (non- stressed) baselines were calculated to quantify and monitor crop water stress for cereal rye and annual ryegrass. The non-water-stressed baselines were described by the linear equations Te - Ta = 2.0404 - 2.0424 * VPD for cereal rye and Te - Ta = 2.7377 - 1.2524 * VP D for annual ryegrass. The theoretical CWSI was greater than the empirical CWSI for most of the experimental days for both cereal rye and annual ryegrass. Variability of empirical (CWSI)E and theoretical (CWSI)T values followed soil water content as would be expected. The CWSI values responded predictably to rainfall and irrigation. CWSI values of 0.24 for cereal rye and 0.29 for annual ryegrass were found from this study, which can be used for timing irrigations to alleviate water stress and avoid excess irrigation water. The non-water-stressed baseline can also be used alone if the aim of the irrigator is to obtain maximum yields. However the non-water-stressed baseline determined using the empirical method cannot be applied to another location and is only valid for clear sky conditions. And the non-water-stressed baseline determined using theoretical method requires computation of aerodynamic resistance and canopy resistances, as the knowledge of canopy resistance, however the values it can assume throughout the day is still scarce. The baseline was then determined using a new method by Alves and Pereira (2000), which overcomes these problems. This method evaluated the infrared surface temperature as a wet bulb temperature for cereal rye and annual ryegrass. From this study, it is concluded that the infrared surface temperature of fully irrigated cereal rye and annual ryegrass can be regarded as a surface wet bulb temperature. The value of infrared surface temperature can be computed from measured or estimated values of net irradiance, aerodynamic resistance and air temperature. The non-water-stressed baseline is a useful concept that can effectively guide the irrigator to obtain maximum yields and to schedule irrigation. Surface temperature can be used to monitor the crop water status at any time of the day even on cloudy days, which may greatly ease the task of the irrigator.