Browsing by Author "Tumbo, S. D."

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Accuracy of Giovanni and Marksim software packages for generating daily rainfall data in selected bimodal climatic areas in Tanzania
(Tanzania Journal of Agricultural Sciences, 2014) Kahimba, F. C.; Tumbo, S. D.; Mpeta, E.; Yonah, I. B.; Timiza, W.; Mbungu, W.
Agricultural adaptation to climate change requires accurate, unbiased, and reliable climate data. Availability of observed climatic data is limited because of inadequate weather stations. Rainfall simulation models are important tools for generating rainfall data in areas with limited or no observed data. Various weather generators have been developed that can produce time series of climate data. Verification of the applicability of the generated data is essential in order to determine their accuracy and reliability for use in areas different from those that were used during models development. Marksim and Giovanni weather generators were compared against 10 years of observed data (1998-2007) for their performance in simulating rainfall in four stations within the northern bimodal areas of Tanzania. The observed and generated data were analyzed using climatic dialog of the INSTAT program. Results indicated that during the long rain season (masika) Giovanni predicted well the rainfall amounts, rainy days, and maximum dry spells compared to Marksim model. The Marksim model estimated seasonal lengths much better than the Giovanni model during masika. During short rain season (vuli), Giovanni was much better than Marksim. All the two software packages had better predictions during masika compared to vuli. The Giovanni model estimated probabilities of occurrence of rainfall much better (RMSE = 0.23, MAE = 0.18, and d =0.75) than Marksim (RMSE = 0.28, MAE = 0.23, and d = 0.63). The Marksim model over-predicted the probabilities of occurrence of dry spells greater than seven days (MBE = 0.17) compared to the Giovanni model (MBE = 0.01). In general the Giovanni model was more accurate than the Marksim model in most of the observed weather variables. The web based Giovanni model is better suited to the northern bimodal areas of Tanzania. The Marksim model produced more accurate climatic data when the long-term average climate data are used as input variables. This study recommends the use of rainfall data generated using Giovanni software over Marksim, for areas receiving bimodal rainfall regimes similar to the northern bimodal areas of Tanzania.
Adoption and scaling-up of conservation agriculture in Tanzania: Case of Arusha and Dodoma regions
(Scientific Research, 2014-02-21) Kahimba, F. C.; Mutabazi, K. D.; Tumbo, S. D.; Masuki, K. F.; Mbungu, W. B.
A study was conducted to assess the adoption and scaling-up of Conservation Agriculture in Arumeru district, Arusha region, northern Tanzania and Chamwino and Dodoma Urban districts in Dodoma region, Central Tanzania. The study employed structured questionnaire survey and key informant interviews as the main data collection methods. Data analysis was done descriptively to determine factors that influence the adoption. Results showed that farmers in Arusha have highly adopted terraces, minimum tillage and cover cropping whereas their counterparts in Dodoma have highly adopted large planting pits, minimum tillage, and rippers. The intensity of adoption in Arusha is higher for the wealthy compared to the poor while in Dodoma the wealth status was not a factor that influenced adoption of the Conservation Agriculture (CA) technologies. The process of technology adoption should include the use of various participatory methods including farmer field schools, experimental plots, farmer exchange visits, and training of trainers among others. Use of farmer groups, incentives, and support instruments such as Savings and Credit Co-operative Society (SACCOS) or warehouse receipts systems are also important to ensure that farmers realize some acceptable profits from their efforts. Involvement of various stakeholders is also very important including local governments and agricultural change agents at national, regional, district, ward and village levels. Hence, the intention to promote CA technologies should not only look at the economic importance, but also its socio-economic importance to the local people in the area. Their desire to adopt and out-scale a technology should be among the most important investment factors that the government and development partners should consider.
Application of self-organizing-maps technique in downscaling GCMs climate change projections for Same, Tanzania
(2010) Tumbo, S. D.; Mpeta, E.; Mbillinyi, B. P.; Kahimba, F. C.; Mahoo, H. F.; Tadross, M.
High resolution surface climate variables are required for end-users in climate change impact studies; however, information provided by Global Climate Models (GCMs) has a coarser resolution. Downscaling techniques such as that developed at the University of Cape Town, which is based on Self-Organizing Maps (SOMs) technique, can be used to downscale the coarse-scale GCM climate change projections into finer spatial resolutions; but that must be combined with verification. The SOM downscaling technique was employed to project rainfall and temperature changes for 2046-2065 and 2080-2100 periods for Same, Tanzania. This model was initially verified using downscaled NCEP reanalysis and observed climate data set between 1979 and 2004, and between NCEP reanalysis and GCM controls (1979 - 2000). After verification, the model was then used to downscale climate change projections of four GCMs for 2046-2065 (future-A) and 2080-2100 (future-B) periods. These projections were then used to compute changes in the climate variables by comparing future-A and B to the control period (1961-2000). Verification results indicated that the NCEP downscaled climate data compared well with the observed data. Also, comparison between NCEP downscaled and GCM downscaled showed that all the four GCM models (CGCM, CNRM, IPSL, and ECHAM) compared well with the NCEP downscaled temperature and rainfall data. Future projections (2046-2065) indicated 56 mm and 42 mm increase in seasonal total rainfall amounts for March-April-May (MAM) and October-November-December (OND) (23% and 26% increase), respectively; and a temperature increase of about 2°C for both seasons. Furthermore, it was found that during MAM there will be a decrease in dry spells by 2 days, and an increase in seasonal length by 8 days, while for OND, there will be also 2 days decrease in dry spells, and 40 days increase in the seasonal length. The results for future-B shows a 4°C rise in temperature, and 46.5% and 35.8% increase in rainfall for MAM and OND, respectively. The results imply a better climatic future for the area because of the increase in the amount of rainfall and decrease in dry spells. However, it is suggested that further investigations are required to see if the projected changes will have real positive effects in agricultural production and also identify better agronomic practices that will take advantage of the opportunities.
Characterization of sounds in maize produced by internally feeding insects: Investigations to develop inexpensive devices for detection of prostephanus truncatus (Coleoptera: Bostrichidae) and sitophilus zeamais (Coleoptera: Curculionidae) in small-scale storage facilities in Sub-Saharan Africa
(Florida Entomological Society, 2015) Kiobia, D. O.; Tumbo, S. D.; Cantillo, J.; Rohde, B. B.; Mallikarjunan, P. K.; Mankin, R. W.
Infestations by Prostephanus truncatus Horn (Coleoptera: Bostrichidae) and Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae) are prevalent in small-scale Zea mays L. storage facilities in Tanzania and other regions of sub-Saharan Africa. It is especially difficult to detect these species’ larvae, which feed unseen inside the grain kernels. An electronic device that acoustically detects and reliably indicates the presence of such larvae could assist pest managers in maintaining the quality of the stored maize. A study was conducted in a sound- and vibration-controlled environment to estimate the amplitudes and spectral ranges of signals that an inexpensive electronic system would encounter while detecting insects in maize storage facilities. Larva-infested wheat kernels from a laboratory colony of Sitophilus oryzae (L.), a species similar in size and behavior to S. zeamais, were placed in a pouch and inserted near the side or the bottom of a bag of maize. An acoustic probe was inserted into the bag, and recordings were made at multiple positions, 5–35 cm from the pouch. Numerous sounds of 4 different types were detected over a range of frequencies extending to 7 kHz, well within the signal-processing capabilities of currently available low-cost microcontroller platforms. Larval sound impulses were detected frequently within 25 cm from the pouch, but not at 35 cm. However, adjustable-length probes could be used to reach within 30 cm of all maize kernels in the types of containers commonly used in regional storage facilities. Thus, there is considerable potential to develop an inexpensive sensor/ microcontroller system useful for managing stored product insect pests in sub-Saharan Africa.
A decision support system for enhancing crop productivity of smallholder farmers in semi-arid agricultureA decision support system for enhancing crop productivity of smallholder farmers in semi-arid agriculture
(2013) Churi, A. J.; Mlozi, M. R. S; Tumbo, S. D.; Casmir, R.; Mahoo, M. R. S
This study aimed at investigative decision support systems for assisting strategic and tactical decision making of smallholder farmers to reduce climate risks and increase crop productivity of semi-arid areas. Specifically, the study assessed farm-level decisions used by the farmers for reducing climate risks; examined information communication and knowledge sharing strategies for enhancing decision making and designed a system for assisting the farmers in selecting appropriate options for improving crop productivity. Development of DSS was governed by design science where prototyping approach was used to allow complete participation of end-users. The proposed architecture allows difference agricultural actors participate in communicating agricultural information and sharing of knowledge with smallholder farmers. The DSS was implemented and assessed by farmers as a useful tool for accessing information and advisories in agricultural systems. More research is recommended to enable simple and affordable mobile phones be used by farmers to access wealth of agricultural knowledge and policies from research centres and government resources.
Determinants of farm-level adoption of water systems innovations in dryland areas: The case of Makanya watershed in Pangani river basin, Tanzania
(2005) Masuki, K.F. G.; Mutabazi, K. D; Tumbo, S. D.; Rwehumbiza, F. B.; Mattee, A. Z.; Hatibu, N.
Water system innovations such as rainwater harvesting involve abstraction of water in the upper catchments. Increasing adoption of rainwater harvesting in the riparian catchments could have hydrological impacts on downstream flows in the river basin, but it is assumed to have overall gains and synergies when efficient use of rainwater is optimized at farm-level. This paper examines the main determinants of adoption of water system innovations with specific emphasis on the intensity of adoption and adoption lag, using a cross-sectional sample of 234 farmers in the Makanya watershed. Censored Tobit models were used to estimate the coefficients of intensity of adoption and adoption lag of water system innovations. Group networking, years spent in formal education, age of respondent, location and agricultural information pathways were found to be major determinants of intensity of adoption at farm-level. It was also found that intensity of adoption and frequency of attendance to collective action are strong determinants of adoption lag of water system innovation in Makanya watershed. Empirical knowledge of the determinants of adoption of water system innovations is critical for an effective scaling out of best practices of water harvesting in the Basin.
Determination of suitability levels for important factors for identification of potential sites for rainwater harvesting
(2016) Tumbo, S. D.; Mbillinyi, B. P.; Mahoo, H. F.; Mkiramwinyi, F. O.
Indigenous and scientific knowledge for locating potential sites for water harvesting technologies do exists, however, a simple and integrated tool to assist farmers’ support agencies, is missing. A geographic information system (GIS)-based decision support system (DSS) can be a valuable tool for such a task. However, pre-requisite for such DSS are the factors and their suitability levels, which are not well developed. This paper focused on development of suitability levels for most important factors/parameters for identification of such sites, which are soil texture, soil depth, drainage, topography and land use or cover. Specific suitability levels were obtained using both the analysis of existing RWH technology at Makanya river catchment and through literature review. Results of field survey together with literature review showed that suitability levels of factors differ with different RWH technologies. For example, suitable levels/areas for water reservoirs (ndiva) are steep slopes (>30o) with clay soils whereas suitable sites for stone terraces are moderately steep slopes (18o – 30o) with sandy loam soils. It was also found that most RWH technologies are located at a distance between 0 and 125m from cropland.
Enhancing response farming for strategic and tactical management of risks of seasonal rainfall variability
(2014) Admassu, H.; Mahoo, H. F.; Rwehumbiza, F. B. R.; Tumbo, S. D.; Mogaka, H.
Seasonal rainfall variability, particularly the uncertainty with respect to the direction and extent that variability will assume in a given season, forms the greatest source of risk to crop production in semi-arid areas of Ethiopia. Equipping vulnerable communities, in advance, with the expected date of onset of a cropping season, is crucial for smallholder farmers to better prepare to respond and manage the uncertainties. Therefore, rainfall prediction, particularly development of models that can foretell the date of onset of next cropping season is crucial in facilitating strategic agronomic planning and tactical management of in-season risks. A twenty-four-year climatic data study was conducted for Melkassa Agricultural Research Centre (MARC) in semi arid Ethiopia, to develop onset date prediction models that can improve strategic and tactical response farming (RF). A sequential simulation model for a build up of 15 to 25 mm soil water by April 1st, was conducted. Simulation results revealed a build up of soil water up to 25 mm, to be the most risk-wise acceptable time of season onset for planting of a 150-day maize crop. In the context of response farming, this was desirable as it offers the opportunity for farmers to consider flexible combination production of maize (Zea mays L.) varieties of 120 and 90 days in the event of failure of earliest sown 150-day maize crop. Thus, to allow for flexible combination production of the three maize varieties, predictive capacity was found crucial for April onset of the next crop season. Accordingly, based on the consideration of pre-onset rainfall parameters, the first effective rainfall date varied considerably with the date of onset of rainfall. Regression analyses revealed the first effective rainfall date to be the best predictor of the date of onset (R2 = 62.5%), and a good indicator of the duration of next season (R2 = 42.4%). The identified strategic predictor, the first effective rainfall date, enabled prediction of time of season onset and season length by a lead time of two to three months. This markedly improved Stewart’s RF. The date of onset of the next crop season was also found to be a useful predictor of season duration (R2 = 87.3%). Strategic agronomic planning should be adjusted according to the first effective rain date, and tactically according to what date of rainfall onset informs us about expectations in the duration and total season water supply.
Evaluation of a variable rate controller for aldicarb application around buffer zones in citrus groves
(2007-01-25) Tumbo, S. D.; Miller, W. M.; Salyani, M.; Sweeb, R.; Buchanon, S.
Advances in precision farming technologies have facilitated controlled application of agrochemicals and documentation procedures to follow environmental regulations. This paper details evaluation of a commercial variable rate (VR) controller for preventing aldicarb applications in the buffer zones around potablewater wells of citrus groves. The controllerwas coupled to two common drive mechanisms, a ground-driven electric clutch-engaged (GDEC) and pulse-width-modulation motor-driven (PWMM). The evaluation involved determination of dynamic performance of the VR application system through quantification of reaction times and rate transition distances and determination of appropriate “look-ahead” times for each of the drive mechanisms. Without a look-ahead (zero) setting, the mean midpoint reaction distances were about 1.8 and 3.6m for the GDEC and PWMM mechanisms, respectively, at 7.0-km/h ground speed. For the GDEC, a look-ahead time of 1 s gave the mean midpoint reaction distances of −0.06 and 0.04m during step-up and step-down of the rate, respectively. For PWMM, the best look-ahead times were 1 and 2 s during step-up and step-down of the rate, respectively.However, since the prototype unit could not accommodate two look-ahead times, the compromise look-ahead time for both step-up and -down was 2 s. Validation in the actual buffer zone showed that, at 95% confidence level, the buffer zone should be increased by 2.5 or 3.3m in commercial applications using GDEC or PWMM systems, respectively.
A gendered analysis of perception and vulnerability to climate change among smallholder farmers: the case of Same district, Tanzania
(2015-02-16) Mnimbo, T. S.; Mbwambo, J.; Kahimba, F. C.; Tumbo, S. D.
Climate change affects women and men differently. However, there are few location-specific studies that can support interventions or policy development that can tackle this issue. To help build that body of knowledge, this article looks at gender-differentiated vulnerability among smallholder farmers in one sub-Saharan African country: Tanzania. Data were collected through household questionnaires, key informant interviews, and focus group discussions in Same District, northern Tanzania. Results revealed notable inequalities distributed across genders. Women bear the biggest burden from climate change impacts. For example, women shoulder 63% of productive tasks, such as ploughing and crop sowing, compared to 28% by men. On the other hand, resource ownership and expenditure are male dominated. The results highlight the need for governments and NGOs to address gender disparities in policies designed to strengthen the capacity of households to cope with vulnerability to climate change impacts.
GIS-based decision support system for identifying potential sites for rainwater harvesting
(Physics and Chemistry of the Earth, 2007) Mbilinyi, B. P.; Tumbo, S. D.; Mahoo, H. F.; Mkiramwinyi, F. O.
Identification of potential sites for rainwater harvesting (RWH) is an important step towards maximizing water availability and land productivity in the semi-arid areas. However, selection of appropriate sites for different RWH technologies on a large scale presents a great challenge, since the necessary biophysical data and infrastructure are often lacking. This paper presents a geographic information system (GIS)-based decision support system (DSS) that uses remote sensing (RS), limited field survey to identify potential sites for RWH technologies. The input into the DSS include maps of rainfall, slope, soil texture, soil depth, drainage and land use/cover and the outputs are maps showing potential sites of water storage systems (ndiva), stone terraces, bench terraces and borders. The Model Builder in the Arc View GIS was used as a platform for the DSS. Two sites in the Makanya watershed, in Kilimanjaro Region, Tanzania, were used for testing and validation of the DSS. The results reflect specific suitability levels of parameters and weight of factors; for example, near streams (drainage) with slope ranges from moderately steep to steep (10 –30 ) are potential sites for ndiva locations whereas moderately undulating to steep slopes (5 –30 ) with unstable soils are potential sites for stone terraces. Moderately undulating slopes (5 –10 ) with clay, silt clay and sandy clay soils are potential sites for bench terrace and gently undulating slopes (2 –5 ) with clay, silt clay and sandy clay soils are potential sites for borders. The results from testing and validation of the developed DSS indicated that the tool can be used reliably to predict potential sites for RWH technologies in semi-arid areas. Most of predicted RWH technologies during testing were found within very highly and highly suitable locations (41.4% and 40%, respectively) also in validation 36.9% of RWH technologies were found within the moderately suitable followed by very highly suitable and highly suitable both with 23.6%. Despite the good results, it is recommended that more work be carried out to refine the model and to include other pertinent ancillary data like socio-economic factors to increase its usefulness.
Identification of suitable indices for identification of potential sites for rainwater harvesting
(Tanzania Journal of Agricultural Sciences, 2014) Tumbo, S. D.; Mbillinyi, B. P.; Mahoo, H. F.; Mkilamwinyi, F. O.
Although indigenous and scientific knowledge for locating potential sites for water harvesting technologies do exist, a simple and integrated tool to assist farmers’ support agencies, is missing. A geographic information system (GIS)-based decision support system (DSS) can be a valuable tool for such a task. However, key to such DSS are the factors and their suitability levels, which are not well developed. This study therefore focused on the development of suitability levels for most important factors/parameters for identification of such sites. The factors included rainfall, soil texture, soil depth, drainage, topography and land use or cover. Specific suitability levels were derived from analysis of existing RWH technologies in Makanya river catchment. Results showed that suitability levels of factors differ with different RWH technologies. Suitable areas for ndiva is on steep slopes (18o-30o) with clay soils, stone terraces is on moderately steep slopes (10o – 18o) with sandy clay loam soils, bench terraces (5o-18o slopes, clay or silt clay soils) and “boda” (2o-5o slopes, slit clay or clay soils). It was also found that ndiva, “boda”, stone terrace and bench terrace are located at a distance within 125m from cropland. Testing of the developed parameters using ArcView-based DSS framework showed that 81.4% RWH technologies were located in the very high and high suitability levels, indicating the usefulness of the developed parameters and their suitability levels.
Impact of projected climate change on agricultural production in semi-arid areas of Tanzania: A case of Same district
(2012) Tumbo, S. D.; Kahimba, F. C.; Mbilinyi, B. P.; Rwehumbiza, F. B.; Mahoo, H. F.; Mbungu, W. B.; Enfors, E.
Sub-Saharan Africa is one of the most vulnerable regions in the World to climate change because of widespread poverty and limited adaptive capacity. The future climate change is likely to present an additional challenge to the agricultural sector. Therefore, the effects of climate change on the current agronomic management practices were investigated using Same District, Tanzania as a case study area. APSIM software was used to investigate the response of maize (Zea mays L.) yield to different agronomic management practices using current and future (2046 - 2065) climate data. The climate change projections data from global climate models were downscaled using self-organising maps technique. Under the conventional practices, results show that during long rainy season (from March to May) there is yield decline of 13% for cultivar Situka, no change for cultivar Kito and increase of 10% and 15% for cultivars Sc401 and TMV1, respectively. Under the recommended practices, cultivars TMV1 and Sc401 are projected to register a 10% yield increase whereas cultivars Situka and Kito are projected to register a decrease of 10% and 45%, respectively. Also, under both conventional and recommended management practices, results showed that during short rainy season (from October to December/January) all cultivars are projected to register between 75% and 146% increase in maize yields. This implies that future climate change is going to have positive effects on current management practices during short rainy seasons and it will have negligible impact during long rainy seasons.
Impacts of climate variability and change on rainfed sorghum and maize: Implications for food security policy in Tanzania
(Canadian Center of Science and Education, 2015-04-15) Msongaleli, B. M.; Rwehumbiza, F.; Tumbo, S. D.; Kihupi, N.
Concern about food security has increased because of a changing climate, which poses a great threat to food crop productivity. Climate change projections from the Coupled Model Inter-comparison Project phase 5 (CMIP5) and crop models were used to investigate the impacts of climate change on rain-fed cereal production. Calibrated and evaluated crop models simulated maize and sorghum yields over time periods and scenarios across central zone Tanzania with and without adaptation. Simulation outputs without adaptation showed predominant decrease and increase in maize and sorghum yields, respectively. The results showed that maize yields were predicted to decline between 1% and 25% across periods, representative concentration pathways (RCPs) and global circulation models (GCMs). However, sorghum yields were on average predicted to increase between 5% and 21%. Overall when adaptation is incorporated toward mid-century, yields are projected to increase for both crops. The yield projections variation between cereal crops highlights the importance of location and crop specific climate change impact assessments. Despite the uncertainties in predicting the impacts of climate change on rainfed crops, especially on cereals (maize and sorghum) which are important staple food crops in semi-arid Tanzania, the findings of this study enable policy makers to develop plans aimed at sustainable food security. In conclusion, the results demonstrate the presumption that sorghum productivity stands a better chance than maize under prospects of negative impacts from climate change in central zone Tanzania.
Integrated assessment of climate change impacts and adaptation in agriculture: the case study of the Wami River Sub-basin, Tanzania
(Springer Nature Switzerland AG, 2020) Tumbo, S. D.; Mutabazi, K. D.; Mourice, S. K.; Msongaleli, B. M.; Wambura, F. J.; Mzirai, O. B.; Kadigi, I. L.; Kahimba, F. C.; Mlonganile, P.; Ngongolo, H. K.; Sangalugembe, C.; Rao, K. P. C.; Valdivia, R. O.
This study evaluates the impacts of climate change and an adaptation strategy on agricul- ture in the Wami River sub-basin in Tanzania. This study uses the Agricultural Model Improvement and Inter-comparison Project (AgMIP) framework that integrates climate, crops and economic models and data using a novel multi-model approach for impact assess- ment of agricultural systems under current and future conditions. This study uses five Global Circulation Models (GCMs) from the fifth phase of the Coupled Model Inter-comparison Project (CMIP5), two crop simulation models, and one economic impact assessment model. In this study, a representative agricultural path- ways (RAP) that characterises future condi- tions following ‘business-as-usual’ trends was developed and used to model future agricul- tural systems in the Wami River sub-basin. Results show that by mid-century, the maxi- mum and minimum temperatures will increase by 1.8–4.1 °C and 1.4–4.6 °C, respectively. Rainfall is predicted to be variable with some places projected to increase by 12%, while in other areas it is projected to decrease by 14– 28%. Maize yields under these conditions are projected to decrease by 5.3–40.7%. Results show that under current conditions, 50–60% of farm households are vulnerable to losses due to climate change. The impacts of climate change on poverty and per capita income are also projected to be negative. Under the current production system, poverty rates were pro- jected to increase by 0.8–15.3% and per-capita income to drop by 1.3–7.5%. Future socio-economic conditions and prices offset the negative impacts of climate change. Under future conditions, the proportion of households vulnerable to loss is estimated to range from 25 to 50%. Per-capita income and poverty rates are expected to improve under the future climate change conditions. Poverty rates would decrease between 1.9 and 11.2% and income per-capita would increase between 2.6 and 18.5%. The proposed future adaptation pack- age will further improve household liveli- hoods. This integrated assessment of climate change projections using the improved meth- ods and tools developed by AgMIP has con- tributed to a better understanding of climate change and adaptation impacts in a holistic manner.
Integrated catchment characteristics, runoffwater reservoir capacities and irrigation - requirement for bean productivity
(2013) Singa, D. D.; Tumbo, S. D.; Mahoo, H. F.; Rwehumbiza, F. B. R.; Lowole, M. W.
Crop production in semi-arid Sub-Saharan Africa (SSA) is limited by over-reliance on rainfall, which is erratic and inadequate. Rainwater conservation and irrigation are needed to avert drought effects and dry spells, and extend crop production activities to dry seasons. A study was conducted from 2011 to 2013 at Ukwe area in Malawi, to determine the size of seasonal open surface reservoir and crop field in relation to catchment characteristics among smallholder farming communities, using beans as a case study crop. There is positive linear relationship between seasonal harvested watershed runoff and rainfall (over 75%). Based on the catchment characteristics and crop water requirement, catchment/cultivated area ratio was 2.1. Harvested runoff water is linearly related to seasonal rainfall amount. About 6000 m3 of water was required to irrigate a hectare of beans. Total volume harvested was estimated to support six-fold the current field area at bean water productivity of 0.7 g L-1. It is possible to determine dry season bean water productivity based on integrated effects of catchment characteristics, runoff water reservoir capacities and irrigation water requirement.
Investigation of laser and ultrasonic ranging sensors for measurements of citrus canopy volume
(American Society of Agricultural Engineers, 2002) Tumbo, S. D.; Salyani, M.; Whitney, J. D.; Wheaton, T. A.; Miller, W. M.
This study compared ultrasonic and laser measurements of citrus canopy volume with manual measurement methods. Fifteen trees with different canopy heights and volumes were used. Manual and ultrasonic measurements provided dimensions for computing the canopy volume whereas laser measurements gave information that could be used to compute a ‘laser canopy volume index.’ Ultrasonic and laser methods agreed with manual methods (R2 > 0.85, RMSE < 2.15 m3). Laser showed better prediction of canopy volume than the ultrasonic system because of the higher resolution. Ultrasonic or laser sensors can be used for automatic mapping and quantification of the canopy volumes of citrus trees.
Investigation of sorghum yield response to variable and changing climatic conditions in semi-arid central Tanzania: Evaluating crop simulation model applications
(2013) Msongaleli, B.; Rwehumbiza, F. B. R.; Tumbo, S. D.; Kihupi, N.
Combination of global circulation models (GCMs), local-scale climate variability and crop simulation models were used to investigate rain-fed sorghum yield response under current and future climate in central Tanzania. Decision Support System for Agrotechnology Transfer (DSSAT) v.4.5 and Agricultural Production Systems Simulator (APSIM) v 7.4 were calibrated and evaluated to simulate sorghum (Sorghum Bicolor L. Moench) var. Tegemeo in 2050s compared to baseline. Simulated median yields from both crop models for the baseline (1980-2010) agree with the trend of yield over the years realistically. The models predicted yields of sorghum in the range from 818 to 930 kg ha-1 which are close to the current national average of 1000 kg ha-1. Simulations by both models using downscaled weather data from two GCMs (CCSM4 and CSIRO-MK3) under the Fifth Coupled Model Intercomparison Project (CMIP5) and Representative Concentration Pathway (RCP 4.5) by mid-century show a general increase in median sorghum yields. Median sorghum yields will increase by 1.1% - 7.0% under CCSM4 and by 4.0% - 12.5% under CSIRO-MK3. Simulations for both current and future periods were run based on the present technology, current varieties and current agronomy packages. This examination of impacts of climate change revealed that increase in sorghum yield will occur despite further projected declines or increase in rainfall and rise in temperature. Modifying management practices through adjustment of sowing dates and the choice of cultivars between improved and local are seemingly feasible options under future climate scenarios depending on the GCM and the direction of the management practice. Our simulation results show that current improved sorghum cultivars would be resilient to projected changes in climate by 2050s, hence bolstering the evidence of heat and drought tolerance in sorghum crop, thus justifying its precedence as an adaptation crop under climate change. We conclude that despite the uncertainty in projected climate scenarios, crop simulation models are useful tools for assessing possible impacts of climate change and management practices on sorghum.
Land cover transition in Northern Tanzania
(2016-10-10) Tumbo, S. D.; Kahimba, F.C.; Ouedraogo, I.; Barron, J.
Land conversion in sub-Saharan Africa has profound biophysical, ecological, political and social consequences for human well-being and ecosystem services. Understanding the process of land cover changes and transitions is essential for good ecosystem management policy that would lead to improved agricultural production, human well-being and ecosystems health. This study aimed to assess land cover transitions in a typical semi-arid degraded agro-ecosystems environment within the Pangani river basin in northern Tanzania. Three Landsat images spanning over 30 years were used to detect random and systematic patterns of land cover transition in a landscape dominated by crop and livestock farming. Results revealed that current land cover transition is driven by a systematic process of change dominated by the following: (i) transition from degraded land to sparse bushland (10·8%); (ii) conversion from sparse bushland to dense bushland in lowland areas (6·0%); (iii) conversion from bushland to forest (4·8%); and (iv) conversion from dense bushland to cropland in the highlands (4·5%). Agricultural lands under water harvesting technology adoption show a high degree of persistence (60–80%) between time slices. This suggests that there is a trend in land-use change towards vegetation improvement in the catchment with a continuous increase in the adoption of water harvesting technologies for crop and livestock farming. This can be interpreted as a sign of agricultural intensification and vegetation regrowth in the catchment.
Maize cultivar specific parameters for decision support system for agrotechnology transfer system (DSSAT) application in Tanzania
(2013) Mourice, S. K.; Rweyemamu, C. L.; Tumbo, S. D.; Amuri, N.
In order to develop basis for tactical or strategic decision making towards agricultural productivity improvement in Tanzania, a new approach in which crop models could be used is required. Since most crop models have been developed elsewhere, their adaptation, improvement and/or use outside their domain of development requires a great deal of data for estimating model parameters to allow their use. Cultivar specific parameters for maize varieties in Tanzania have not been determined before and consequently, crop modelling approaches to address biophysical resource management challenges have not been effective. An overall objective of this study was to evaluate DSSAT (v4.5) Cropping System Model (CSM) using four adapted maize cultivars namely Stuka, Staha, TMV1 and Pioneer HB3253. The specific objectives were; to determine maize crop growth and development indices under optimum conditions, to estimate maize cultivar parameters, and to evaluate DSSAT CSM for simulating maize growth under varied nitrogen fertilizer management scenarios. The results indicate that maize cultivars did not differ significantly in terms of the number of days to anthesis, maturity, or grain weight except final aboveground biomass. Also there was no difference between variables with respect to growing seasons. The cultivar specific parameters obtained were within the range of published values in the literature. Model evaluation results indicate that using the estimated cultivar coefficients, the model simulated well the effects of varying nitrogen management as indicated by the agreement index (d-statistic) closer to unity. Also, the cultivar coefficients which are difficult to measure physically were sensitive to being varied indicating that the estimated values were reasonably good. Therefore, it can be conclude that model calibration and evaluation was satisfactory within the limits of test conditions, and that the model fitted with cultivar specific parameters that can be used in simulation studies for research, farm management or decision making.