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Browsing School of Agricultural, Earth and Environmental Sciences by Author "Abraha, Michael Ghebrekristos."

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    Estimating solar radiation for water-use and yield simulations under present and projected future climate using Cropsyst.
    (2003) Abraha, Michael Ghebrekristos.; Savage, Michael John.
    Agricultural scientists are faced with the challenge of producing enough food for the increasing world population. Hence the need to develop tools for managing soil and plant systems to increase food production in order to meet the world food demand in the future. Crop simulation models have become promising tools in predicting yield and related components fi'om a set of weather, soil, plant and management data inputs. This study describes the estimation of solar radiant density, a crucial input in crop simulation models; calibration and validation of a soil-plant growth simulator, CropSyst, for management purposes; and generation of weather data for assessment of crop production under possible climate changes in the future. Daily solar radiant density, an input required by most crop simulation models, is infiequently observed in many stations. This may prevent application of crop simulation models for specific locations. Long-term data records of daily minimum and maximum air temperatures, precipitation, sunshine hours and/or solar radiant density were obtained for Cedara, Durban, Seven Oaks and Ukulinga in KwaZulu-Natal, South Africa. Solar radiant density was estimated fi'om sunshine hours using the Angstrom equation and ten other models that involved daily minimum and maximum air temperatures and/or precipitation along with extratelTestrial radiant density. Coefficients for the Angstrom equation and one of the other ten models were specifically developed for South African conditions; the remaining models required fitting coefficients using the available data for all locations. The models were evaluated using (i) conventional statistics that involved, root mean square elTor (RMSE) along with its systematic and unsystematic components, slope, intercept, index of agreement (d), and coefficient of determination (R\ and (ii) a fuzzy expert system that involved a single modular indicator (Ira d) aggregated from the modules of accuracy (aggregation of the indices relative RMSE, model efficiency and I-student probability), con'elation (Pearson's correlation coefficient) and pattem (aggregation of pattem index vs day of year and pattem index vs minimum air temperature). For each index, two functions describing membership to the fuzzy subsets Favourable (F) and Unfavourable (V) were defined. The expelt system calculates the modules according to both the degree of membership and a set of decision rules. Solar radiant density estimated from sunshine hours for the Durban station resulted in R2 , RMSE (MJ m,2) and d index of 0.90, 2.32 and 0.97 respectively. In the absence of observed solar radiant density data, estimations from sunshine hours were used for derivation of coefficients as well as evaluation of the models. For Durban, the performance of the models was generally poor. For Cedara, Seven Oakes and Ukulinga two of the models resulted in a high d index and smallest systematic RMSE. The solar radiant density estimated from each model was also used as an input to simulate maize grain yields using the soil-plant growth simulator, CropSyst. The models were ranked according to their ability to simulate grain yields that match those obtained from using the observed solar radiant density. The rankings according to crop simulation, conventional statistics and expert system were compared. The CropSyst model was also evaluated for its ability to simulate crop water-use of fallow and cropped (oats, Italian ryegrass, rye and maize) plots at Cedara, KwaZulu-Natal, South Africa. Soil characteristics, initial soil water conditions, irrigation and weather data were inputted to CropSyst. Crop input parameters for oats, Italian ryegrass and rye were used, with little modifications, as determined from field experiments conducted at Kromdraai open cast mine, Mpumalanga province, South Africa. Crop input parameters for maIze were either determined fi'om field experiments or taken from CropSyst crop input parameters documentation and adjusted within a narrow specification range of values as dictated by CropSyst. The findings indicated that CropSyst was generally able to simulate reasonably well the water-use of fallow and cropped (oats, Italian ryegI°ass, rye and maize) plots; leaf area index and crop evapotranspiration of rye; and grain yield and developmental stages of maize. The validated CropSyst model was also used to simulate timing and amount of irrigation water, and investigate incipient water stress in oats, Italian ryegrass and rye. The CropSyst model was used to investigate potential effects of future climate changes on the productivity of maize grain yields at Cedara, KwaZulu-Natal, South Africa. The effect of planting date (local planting date, a fortnight earlier and a fortnight later) was also included in the study. A 30-year baseline weather data input series were generated by a stochastic weather generator, ClimGen, using 30 years of observed weather data (l971 to 2000). The generated weather data series was compared with the observed for its distributions of daily rainfall and wet and dry series, monthly total rainfall and its variances, daily and monthly mean and variance of precipitation, minimum and maximum air temperature, and solar radiant density. Four months of the year failed to reproduce distributions of wet and dry series, daily precipitation, and monthly variances of precipitation of the observed weather data series. In addition, Penman-Monteith reference evaporation (ETa) was calculated using the observed and generated data series. Cumulative probability function of ETa calculated using the generated weather data series followed the observed distribution well. Moreover, maize grain yields were simulated using the generated and observed weather data series with local, a fortnight earlier and a fortnight later planting dates. The mean simulated grain yields for the respective planting dates were not statistically different from each other; the grain yields simulated using the generated weather data had significantly smaller variance than the grain yields simulated using the observed weather data series. When the generated weather data series was used an input, the early planting date as compared to the locally practiced and late planting dates resulted in significantly greater simulated grain yields. The grain yields simulated using the observed weather data for the early and local planting dates were not statistically different from each other. The baseline period was modified by synthesized climate projections to create future climatic scenarios. The climate changes considered corresponded to doubling of [C02] from 350 to 700 ~t1 ,-I without air temperature and water regime changes, and doubling of [C02] accompanied by increases in mean air temperature and precipitation changes of 2 (lC and 10%, 2 (le and 20%>, 4 °c and 10%, and 4 (lC and 20% respectively. Solar radiant density was also estimated from daily air temperature range for all scenarios that involved change in mean air temperature. In addition, input crop parameters of radiation-use and biomass transpiration efficiencies were modified for maize, in CropSyst, to accommodate changes in elevated levels of [C02]. Equivalent doubling of [C02], without air temperature or water regime changes, resulted in increased simulated grain yields as compared to the baseline period. Adding 2 QC to the mean daily temperature and 10% to the daily precipitation of a [C02] elevated atmosphere reduced the grain yield but still kept it above the level of the baseline period grain yield. Adding 4 QC to the mean daily temperature and 10% to the daily precipitation fLllther decreased the yield. Increasing the daily precipitation by 20% instead of 10% did not change the simulated grain yield as compared to the 10% increments. Early planting date, for all scenarios, also resulted in higher yields, but the relative increment in grain yield was higher for the late planting dates with scenarios that involved increment in mean air temperature. In general, this study confi1l11ed that doubling of [C02] increases yield but the accompanied increase in mean air temperature reduces yield.
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    Sensible heat flux and evaporation for sparse vegetation using temperature-variance and a dual-source model.
    (2010) Abraha, Michael Ghebrekristos.; Savage, Michael John.
    The high population growth rate and rapid urbanization that the world is experiencing today has aggravated the competition for the already scarce resource ¡V water ¡V between the agricultural sector and the other economic sectors. Moreover, within the agricultural sector, water is increasingly being used for commercial plantations as opposed to growing food crops, threatening food security. Therefore, it is very important that this scarce resource is managed in an efficient and sustainable manner, for now and future use. This requires understanding the process of evaporation for accurate determination of water-use from agricultural lands. In the past, direct measurements of evaporation have proven difficult because of the cost and complexity of the available equipments, and level of expertise involved. This justifies a quest for relatively simple, accurate and inexpensive methods of determining evaporation for routine field applications. Estimation of sensible heat flux (H) from high frequency air temperature measurements and then calculating latent energy flux (ƒÜE) and hence evaporation as a residual of the shortened surface energy balance equation, assuming that closure is met, is appealing in this sense. Concurrent net irradiance (Rn) and soil heat flux (G) measurements can be conducted with relative ease for use in the energy balance equation. Alternately, evaporation can also be mathematically modelled, using single- or multi-layer models depending on vegetation cover, from less expensive routine meteorological observations. Therefore, the ultimate objective of this study is to estimate and model H and ƒÜE, and thereby evaporation, accurately over sparsely vegetated agricultural lands at low cost and effort. Temperature-variance (TV) and surface renewal (SR) methods, which use high-frequency (typically 2 to 10 Hz) air temperature measurements, are employed for estimation of H. The TV method is based on the Monin and Obukhov Similarity Theory (MOST) and uses statistical measures of the high frequency air temperature to estimate H, including adjustments for stability. The SR method is based on the principle that an air parcel near the surface is renewed by an air parcel from above and, to determine H, it uses higher order air temperature differences between two consecutive sample measurements lagged by a certain time interval. Single- and double-layer models that are based on energy and resistance combination theory were also used to estimate evaporation and H from sparse vegetation. Single- and double-layer models that were extended to include inputs of radiometric temperature in order to estimate H were also used. The transmission of solar irradiance to the soil beneath in sparse canopies is variable and depends on the vegetation density, cover and apparent position of the sun. A three-dimensional radiation interception model was developed to estimate this transmission of solar irradiance and was used as a sub-module in the double-layer models. Estimations of H from the TV (HTV), SR (HSR) and double-layer models were compared against H obtained from eddy covariance (HEC), and the modelled ƒÜE (single- and double-layer) were compared with that obtained from the shortened energy balance involving HEC. Besides, long-term ƒÜE calculated from the shortened energy balance using HTV and HSR were compared with those calculated using HEC. Unshielded and naturally-ventilated fine-wire chromel-constantan thermocouples (TCs), 75 ƒÝm in diameter, at different heights above the ground over sparse Jatropha curcas trees, mixed grassland community and bare fallow land were used to measure air temperature. A three-dimensional sonic anemometer mounted at a certain height above the ground surface was also used to measure virtual temperature and wind speed at all three sites. All measurements were done differentially at 10-Hz frequency. Additional measurements of Rn, G and soil water content (upper 60 mm) were also made. The Jatropha trees were planted in a 3-m plant and inter-row spacing in a 50 m ¡Ñ 60 m plot with the surrounding plots planted to a mixture of Jatropha trees and Kikuyu grass. Average tree height and leaf area index measurements were taken on monthly and bimonthly basis respectively. An automatic weather station about 10 m away from the edge of the Jatropha plot was also used to obtain solar irradiance, air temperature and relative humidity, wind speed and direction and precipitation data. Soil water content was measured to a depth of 1000 mm from the surface at 200 mm intervals. Soil and foliage surface temperatures were measured using two nadir-looking infrared thermometers with one mounted directly above bare soil and the other above the trees. The three-dimensional solar irradiance interception model was validated using measurements conducted on different trees and planting patterns. Solar irradiance above and below tree canopies was measured using LI-200 pyranometer and tube solarimeters respectively. Leaf area density (LAD) was estimated from LAI, canopy shape and volume measurements. It was also determined by scanning leaves using either destructive sampling or tracing method. The performance of the TV method over sparse vegetation of J. curcas, mixed grassland community and fallow land was evaluated against HEC. Atmospheric stability conditions were identified using (i) sensor height (z) and Obukhov length (L) obtained from EC and (ii) air temperature difference between two thermocouple measurement heights. The HTV estimations, adjusted and not adjusted for skewness (actual and estimated) of air temperature (sk), for unstable conditions only and for all stability conditions were used. An improved agreement in terms of slope, coefficient of determination (r2) and root mean square error (RMSE), almost over all surfaces, was obtained when the temperature difference rather than the z/L means of identifying stability conditions was used. The agreement between the HTV and HEC was improved for estimations adjusted for actual sk than not adjusted for sk. Improved agreement was also noted when HTV was adjusted using estimated sk compared to not adjusting for sk over J. curcas. The TV method could be used to estimate H for surfaces with varying homogeneity with reasonable accuracy. Long-term water-use of a fetch-limited sparse vegetation of J. curcas was determined as a residual of the shortened surface energy balance involving HTV and HSR and compared with those estimated using HEC. Concurrent measurements of Rn and G were also performed. The long-term water-use of J. curcas trees calculated from the shortened surface energy balance involving HTV and HSR agreed very well when compared with those obtained from HEC. The seasonal HTV and HSR also agreed very well when compared with HEC. Changes in structure of the canopy and environmental conditions appeared to influence partitioning of the available energy into H and ƒÜE. The seasonal total evaporation for the EC, TV and SR methods amounted to 626, 640 and 674 mm respectively with a total rainfall of 690 mm. Footprint analysis also revealed that greater than 80% of the measured flux during the day originates from within the surface of interest. The TV and SR methods, therefore, offer a relatively low-cost means for long-term estimation of H, and ƒÜE, hence the total evaporation, using the shortened surface energy balance along with measurements of Rn and G. Evaporation and biomass production estimations from tree crops requires accurate representation of solar irradiance transmission through the canopy. A relatively simple three-dimensional, hourly time-step tree-canopy radiation interception model was developed and validated using measurements conducted on isolated trees, hedgerows and tree canopies arranged in tramline mode. Measurements were obtained using tube solarimeters placed 0.5 m from each other starting from the base of a tree trunk in four directions, along and perpendicular to the row up to mid-way between trees and rows. Model-simulations of hourly radiant transmittance were in good agreement with measurements with an overall r2 of 0.91; Willmott.s index of agreement of 0.96; and general absolute standard deviation of 17.66%. Agreement between model-estimations and measurements, however, was influenced by distance and direction of the node from the tree trunk, sky conditions, symmetry of the canopy, and uniformity of the stand and leaf distribution of the canopy. The model could be useful in planning and management applications for a wide range of tree crops. Penman-Monteith (PM) equation and the Shuttleworth and Wallace (SW) model, representing single- and dual-source models respectively, were used to determine the total evaporation over a sparse vegetation of J. curcas from routine automatic weather station observations, resistance parameters and vegetation indices. The three-dimensional solar irradiance interception model was used as a sub-module in the SW model. The total evaporation from the sparse vegetation was also determined as a residual of the shortened surface energy balance using measurements of Rn, G and HEC. The PM equation failed to reproduce the .measured. daily total evaporation during periods of low LAI, with improved agreement with increased LAI. The SW model, however, produced total evaporation estimates that agreed very well with the .measured. with a slope of 0.96, r2 of 0.91 and RMSE of 0.45 mm for a LAI ranging from 0 (no leaves) to 1.83 m2 m-2. The SW model also estimated soil evaporation and plant transpiration separately, and about 66 % of the cumulative evaporation was attributed to soil evaporation. These findings suggest that the PM equation should be replaced by the SW model for surfaces that assume a range of LAI values during the growing season. The H was estimated using (i) SW model that was further developed to include surface radiometric temperature measurements; (ii) one-layer model, but linked with a two-layer model for estimation of excess resistance, that uses surface radiometric temperature; and (iii) the SW model (unmodified). The agreement between modelled and measured H, using 10-min data, was in general reasonably good with RMSE (W m-2) of 45.11, 43.77 and 39.86 for the three models respectively. The comparative results that were achieved from (iii) were not translated into the daily data as all models appeared to have a tendency to underestimate H. The resulting RMSEs for the daily H data for the three models were (MJ m-2) 1.16, 1.17 and 1.18 respectively. It appears that similar or better agreement between measured and estimated H can be forged without the need for surface radiometric temperature measurements. The study showed, in general, that high frequency air temperature measurements can be used to estimate H with reasonable accuracy using the simple and relatively low-cost TV and SR methods. Moreover, these methods can be used to calculate ƒÜE, hence ET, as a residual of the shortened surface energy balance equation along with measurements of Rn and G assuming that energy balance closure is met. The simple and low-cost nature of these methods makes replication of measurements easier and their robust nature allows long-term measurements of energy fluxes. The study also showed that H and ƒÜE can be modeled using energy and resistance combination equations with reasonable accuracy. It also reiterated that the SW-type models, which treat the plant canopy and soil components separately, are more appropriate for estimation of H and ƒÜE over sparse vegetation as opposed to the PM-type models.