Estimating Conveyance Efficiency and Maize Productivity of Traditional Irrigation Systems in Usa River Catchment, Tanzania

This research article published by Hindawi, 2020Estimating the conveyance efficiency of traditional irrigation schemes systems is very important. It is because of understanding the volume of water lost along with the transportation facility, enhancing water usage and productivity, hence making better decisions about the utilization of water resources. (e objective of the study was to determine water abstraction permit compliances and estimate conveyance efficiency and crop and water productivity of traditional irrigation systems in northern Tanzania. (e task involved measurement of irrigation water flows to determine the amount of water abstraction, inflow (head) and outflow (tail) between the canals to determine the conveyance efficiency of the main, secondary, and tertiary canals of the traditional irrigation systems. Moreover, water and yield obtained at the farm level were determined. Results indicate that approximately 72% of water transported reaches the destined farm which produced maize (Zea mays L) yields of 1054.5 kg/ha, 892.4 kg/ha, and 875.156 kg/ha at downstream, midstream, and upstream which equals 0.41 kg/m3, 0.15 kg/m3, and 0.09 kg/m3, respectively, while about 28% of water is lost along the canals through evaporation, seepage, and deep percolation and overtopping. Consequently, water measured at furrow intakes in total was 3, 500 L/s, equal to 23% more than the permitted amount of 2856.14 L/s at Usa River Catchment. Interventions to minimize water losses starting at the furrow’s intakes are urgently required in the current trend of the increasing demand for water resources for food production and schemes performance. Subsequently, more effective conveyance technologies and water management strategies other than canal lining are required

Farmer's appropriation of system of rice intensification practices in water-scarce irrigation schemes in Northern Tanzania

This research article published by Springer Nature Switzerland AG.,2021The system of rice intensification (SRI), advocates new ways of rice cultivation which challenges farmers’ knowledge and skills to the extent that they are required to learn, experiment and integrate new principles to suit their specific needs and agro-ecological conditions. This study was conducted to evaluate farmers’ appropriation to SRI; first, a survey was conducted to explore farmers’ adjustments of SRI. Second, yield and water productivity of the integrated system were assessed by setting up an experiment in the farmers’ plots. Whereby four treatments representing farmers’ adaptations of SRI practises were assessed: continuous flooding (F1) with two 21 days old seedlings at 15 × 15 cm spacing. The other three were under intermittent irrigation with two 21 days seedlings at 20 × 20 cm (F2), one 21 days seedling at 20 × 20 (F3) and one 15 days seedling at 25 × 25 cm spacing. Yields obtained were 4.8, 8.5, 8.2 and 9.2 tons/ha for F1, F2, F3 and F4, respectively. Water productivity (WP) of 0.15, 0.39, 0.35 and 0.51 kg/m3 was obtained for F1, F2, F3 and F4, respectively. Water saving under SRI practise was 34.3%, 28.9% and 45.1% for F2, F3 and F4, respectively. Two seedlings 21 days old at 20 × 20 cm with intermittent irrigation are recommended for this area as it ensures a sufficient number of plants, relatively higher yields and a reduced considerable amount of irrigation water. The findings show that the integration of SRI into the local rice farming system has the potential to improve yields and water productivity of irrigation schemes

Combining biochar with low rate of chemical fertiliser boosts maize biomass yield, regardless of tillage system, under humid conditions

Biochar application to soils increases biomass and crop yields, especially with rates higher than 100 t ha−1. Yet, there is limited knowledge on the combined effect of biochar and chemical fertiliser under different tillage systems. The objective of this study is to investigate the effect of maize-cob biochar (BC) (rates of 5 and 10 t ha−1) combined with chemical fertiliser micro-dosing (MD) at a rate of 25% of the recommended quantity on total shoot dry matter (DM) and plant height of maize cultivated under flat (F) and tied-ridge (R) practices during a humid season in Tanzania. The results indicate that combining 5 t ha−1 BC with 25% MD increases DM at harvest by 83% (4.16 t ha−1) compared to the control (2.27 t ha−1) and was in the same range as the DM obtained from the treatment with the recommended fertiliser rate (100% FD). The treatments with single applications of 25% MD, 5 t ha−1 BC, and 10 t ha−1 BC only tended to exceed the control of DM yield. Therefore, we recommend that small-scale farmers aiming at DM for livestock or grain yield with limited access to chemical fertilisers to combine biochar with 25% MD, rather than applying biochar or low chemical fertiliser rates alone

Optimizing System of Rice Intensification Parameters Using Aquacrop Model for Increasing Water Productivity and Water Use Efficiency on Rice Production in Tanzania

Producing more rice while using less water is among the calls in water scarce regions so as to feed the growing population and cope with the changing climate. Among the suitable techniques towards this achievement is the use of system of rice intensification (SRI), which has been reported as an approach that uses less water and has high water productivity and water use efficiency. Despite its promising results, the use of SRI practice in Tanzania is limited due to less knowledge with regard to transplanting age, plant spacing, minimum soil moisture to be allowed for irrigation, and alternate wetting and drying interval for various geographical locations. The AquaCrop crop water productivity model, which is capable of simulating crop water requirements and yield for a given parameter set, was used to identify suitable SRI parameters for Mkindo area in Morogoro Region, Tanzania. Using no stress condition on soil fertility, plant spacings ranging from 5 cm to 50 cm were evaluated. Results suggest that the yield and biomass produced per ha increase with decreasing spacing from 50 cm to 20 cm. Preliminary field results suggest that the optimum spacing is round 25 cm. However, the model structure does not take into consideration number of tillers produced. As such, the study calls for incorporation of the tillering processes into AquaCrop model

Assessing the impacts of climate variability and change on agricultural systems in Eastern Africa while enhancing the region’s capacity to undertake integrated assessment of vulnerabilities to future changes in climate - Tanzania

Agriculture is the most important economic sector in Tanzania as it provides the main source of food and employment among others (URT, 2012). More than 80% of population in Tanzania depends on climate sensitive rain fed agriculture as source of livelihood. However, agriculture is characterized by high production risks due to its dependence on unpredictable and highly variable weather, low returns on investment resulting among others from low productivity, rudimentary technology and inefficient marketing system (URT, 2012). Water scarcity and other natural resource constraints will make it even harder to intensify agricultural production (Meridian Institute, 2013). As population increases and climate changes, agricultural productivity improvement demands new approaches which, apart from addressing these challenges, should also aim at protecting both the environment and functioning of ecosystem while enhancing the capabilities of communities to attaining sustainable development. It is in this light under which the Agricultural Model inter-comparison and Improvement Project (AgMIP) was formulated. AgMIP proposes methods and tools that allow integrated assessment of climate change impact by linking climate, crop, and economic modelling (Rosenzweig et al., 2013). Wami River sub-Basin in Tanzania is one of the AgMIP case study sites. Therefore, this study presents the results of the AgMIP integrated climate change impact assessment for Wami River sub-Basin. The objectives for Tanzanian component are as follows:  To generate and corroborate climate data for baseline and future scenarios in the Wami sub-basin; To calibrate and validate crop models and simulate crop growth and development for baseline and future climate (mid-century and end-century) for identified livelihood zones;  To determine the impacts of changes in productivity of several enterprises on income and food security.AgMI

Assessing the impacts of climate variability and change on agricultural systems in Eastern Africa while enhancing the region’s capacity to undertake integrated assessment of vulnerabilities to future changes in climate

One of the key messages emerging out of the recent IPCC reports is that the climate change is real, happening and will continue to happen for the foreseeable future , irrespective of what happens to future greenhouse gas emissions . The report also estimates wi th high confidence that the negative impacts on agriculture outweigh the positives which makes adaptation an urgent and pressing challenge. However, adaptation planning requires accurate information about where, when and how the impacts are going to be fel t and who will be more vulnerable. Among the regions, Africa is considered as more vulnerable due to its high dependence on agriculture for subsistence, employment and income. In Eastern Africa, agriculture accounts for 43% of GDP and contributes to more than 80% employment (Omano et al. 20 06). Within Africa, Eastern Africa is one of the most vulnerable regions due to its high dependence on rain - fed agriculture for subsistence, employment and income. The region experiences high variability in rainfall (Webster et al., 1999, Hastenrath et al. , 2007) which has a direct bearing on the performance of agriculture. Generally the region experiences prolonged and highly destructive droughts covering large areas at least once every decade and more localized events even more frequently. The region reco rded severe droughts and/or famines in 1973 - 74, 1984 - 85, 1987, 1992 - 94, 1999 - 2000, 2005 - 2006 and more recently in 2010 - 11. According to UNDP (2006), a single drought event in a 12 - year period will lower GDP by 7% – 10% and increase poverty by 12% – 14%. Extrem e events, including floods and droughts, are becoming increasingly frequent and severe (IPCC 2007). Based on the analysis of data from the international Disaster Database (EM - DAT), Shongwe et al. (2009) concluded that there has been an increase in the numb er of reported disasters in the region, from an average of less than 3 events per year in the 1980s to over 7 events per year in the 1990s and 10 events per year from 2000 to 2006. The negative impacts of climate are not limited to the years with extreme c limatic conditions. Even with normal rainfall, the countries in the region do not produce enough food to meet their people’s needs. Left unmanaged, these impacts can have far - reaching consequences on the local food security, economy, and poverty. Over the past few years, climate research has contributed significantly to increased understanding of how the climate in the region is var ying on inter - annual and decadal time scales and on how the climate is changing in response to global warming and other factors . The impacts of this variability and changes in climate on various sectors including agriculture have also received considerable attention . These studies indicate that a griculture, especially the one practiced under rainfed conditions in moisture limiting environments such as semi - arid tropics , is one of the most vulnerable sectors since these are relatively warmer places and rainfall is the only source of water. There is a rapidly growing literature on vulnerability and adaptation to climatic variability and change , but most of these studies are based on assessments made using statistical and empirical models that fail to account for the full range of complex interactions and their effects on agricultural systems (Parry et al., 2004; Cline, 2007; Lobell e t al., 2008). Evidence available to date indicate s that w ith 1°C of warming, roughly 65% of current maize growing areas in Africa will experience yield losses (Lobell et al., 2011) and the average predicted production loss es by 2050 for most crops are in t he ra n ge of 10 - 25% (Schlenker and Lobell, 2010) . For developing and implementing adaptation programs, more detailed information about the impacts of climate change on various components of the smallholder farming systems such as which crops and varieties are more vulnerable and which management practices are unviable is required . This requires a comprehensive assessment using site and location specific climate and crop management information. However, s everal problems constrain such an assessment. Firstly, downscaled local level climate change projections that are required to make such assessments are not readily available . While climate models provide various scenarios with high levels of confidence at global and sub - regional level, there are challenges in downscaling them to local level (IPCC, 2007) . Secondly, lack of information on the sensitivity of smallholder agricultural systems to changes in climate . Though process based crop simulation models can serve as important tools to make a more realistic assessment of impacts of climate variability and change on agricultural systems, application of the same is limited to few location specific studies mainly because of the intensive data requirements and practical limitations including capaci ty to calibrate, validate and perform detailed analyses. Thirdly, there is scarcity of information on how the impacts of climate change on the production and productivity of agriculture translate into economic impacts including food security at household a nd national levels. This assessment is aimed at developing more accurate information on how the projected changes in climate impact the productivity and profitability of agricultural systems that are widely adopted by smallholder farmers in Eastern Africa using the protocols and methods developed by Agricultural Model Intercomparision and Improvement Project (AgMIP) (Rosenzweig et al., 2013) . One key aspect of this assessment is the attention paid to captur e the complexity and diversity that exists in the s mallholder farm ing systems including the different ways in which th e system is managed. The study is an attempt to make a comprehensive assessment of climate change on crop growth and performance under conditions that interactions as well as related economic impacts by integrat ing state of the art downscal ed climate scenarios with crop and economic models. Th e assessment was carried out in contrasting agro - ecological zones spread over the four major countries in eastern Africa – Ethiopia, Keny a, Tanzania and Uganda. This report summarizes the findings that include trends and changes in the observed and downscaled climate scenarios, quantified information on impacts of these trends and changes on performance of maize under a range of environment al and management conditions, implication of these changes in crop performance on in come, poverty and food security of smallholder farmers and potential adaptation strategies that can assist smallholder farmers in minimizing negative impacts .AgMI

Assessing the impacts of climate variability and change on agricultural systems in Eastern Africa while enhancing the region’s capacity to undertake integrated assessment of vulnerabilities to future changes in climate

One of the key messages emerging out of the recent IPCC reports is that the climate change is real, happening and will continue to happen for the foreseeable future , irrespective of what happens to future greenhouse gas emissions . The report also estimates wi th high confidence that the negative impacts on agriculture outweigh the positives which makes adaptation an urgent and pressing challenge. However, adaptation planning requires accurate information about where, when and how the impacts are going to be fel t and who will be more vulnerable. Among the regions, Africa is considered as more vulnerable due to its high dependence on agriculture for subsistence, employment and income. In Eastern Africa, agriculture accounts for 43% of GDP and contributes to more than 80% employment (Omano et al. 20 06). Within Africa, Eastern Africa is one of the most vulnerable regions due to its high dependence on rain - fed agriculture for subsistence, employment and income. The region experiences high variability in rainfall (Webster et al., 1999, Hastenrath et al. , 2007) which has a direct bearing on the performance of agriculture. Generally the region experiences prolonged and highly destructive droughts covering large areas at least once every decade and more localized events even more frequently. The region reco rded severe droughts and/or famines in 1973 - 74, 1984 - 85, 1987, 1992 - 94, 1999 - 2000, 2005 - 2006 and more recently in 2010 - 11. According to UNDP (2006), a single drought event in a 12 - year period will lower GDP by 7% – 10% and increase poverty by 12% – 14%. Extrem e events, including floods and droughts, are becoming increasingly frequent and severe (IPCC 2007). Based on the analysis of data from the international Disaster Database (EM - DAT), Shongwe et al. (2009) concluded that there has been an increase in the numb er of reported disasters in the region, from an average of less than 3 events per year in the 1980s to over 7 events per year in the 1990s and 10 events per year from 2000 to 2006. The negative impacts of climate are not limited to the years with extreme c limatic conditions. Even with normal rainfall, the countries in the region do not produce enough food to meet their people’s needs. Left unmanaged, these impacts can have far - reaching consequences on the local food security, economy, and poverty. Over the past few years, climate research has contributed significantly to increased understanding of how the climate in the region is var ying on inter - annual and decadal time scales and on how the climate is changing in response to global warming and other factors . The impacts of this variability and changes in climate on various sectors including agriculture have also received considerable attention . These studies indicate that a griculture, especially the one practiced under rainfed conditions in moisture limiting environments such as semi - arid tropics , is one of the most vulnerable sectors since these are relatively warmer places and rainfall is the only source of water. There is a rapidly growing literature on vulnerability and adaptation to climatic variability and change , but most of these studies are based on assessments made using statistical and empirical models that fail to account for the full range of complex interactions and their effects on agricultural systems (Parry et al., 2004; Cline, 2007; Lobell e t al., 2008). Evidence available to date indicate s that w ith 1°C of warming, roughly 65% of current maize growing areas in Africa will experience yield losses (Lobell et al., 2011) and the average predicted production loss es by 2050 for most crops are in t he ra n ge of 10 - 25% (Schlenker and Lobell, 2010) . For developing and implementing adaptation programs, more detailed information about the impacts of climate change on various components of the smallholder farming systems such as which crops and varieties are more vulnerable and which management practices are unviable is required . This requires a comprehensive assessment using site and location specific climate and crop management information. However, s everal problems constrain such an assessment. Firstly, downscaled local level climate change projections that are required to make such assessments are not readily available . While climate models provide various scenarios with high levels of confidence at global and sub - regional level, there are challenges in downscaling them to local level (IPCC, 2007) . Secondly, lack of information on the sensitivity of smallholder agricultural systems to changes in climate . Though process based crop simulation models can serve as important tools to make a more realistic assessment of impacts of climate variability and change on agricultural systems, application of the same is limited to few location specific studies mainly because of the intensive data requirements and practical limitations including capaci ty to calibrate, validate and perform detailed analyses. Thirdly, there is scarcity of information on how the impacts of climate change on the production and productivity of agriculture translate into economic impacts including food security at household a nd national levels. This assessment is aimed at developing more accurate information on how the projected changes in climate impact the productivity and profitability of agricultural systems that are widely adopted by smallholder farmers in Eastern Africa using the protocols and methods developed by Agricultural Model Intercomparision and Improvement Project (AgMIP) (Rosenzweig et al., 2013) . One key aspect of this assessment is the attention paid to captur e the complexity and diversity that exists in the s mallholder farm ing systems including the different ways in which th e system is managed. The study is an attempt to make a comprehensive assessment of climate change on crop growth and performance under conditions that interactions as well as related economic impacts by integrat ing state of the art downscal ed climate scenarios with crop and economic models. Th e assessment was carried out in contrasting agro - ecological zones spread over the four major countries in eastern Africa – Ethiopia, Keny a, Tanzania and Uganda. This report summarizes the findings that include trends and changes in the observed and downscaled climate scenarios, quantified information on impacts of these trends and changes on performance of maize under a range of environment al and management conditions, implication of these changes in crop performance on in come, poverty and food security of smallholder farmers and potential adaptation strategies that can assist smallholder farmers in minimizing negative impacts .AgMI

Agronomic management strategies for adaptation to the current climate variability : the case of North-Eastern Tanzania

Meeting: Second International Conference on Climate, Sustainability and Development in Semi-Arid Regions (ICID+18, 2010), 16-20 Aug. 2010, Fortaleza, BRResearch was conducted to quantify both the risk and the profitability of agronomic management strategies for maize using long-term climatic data and a crop simulation model. Based on the results of this study, it is recommended that farmers employ innovative agronomic management practices only when the seasonal forecast indicates above normal rainfall. The early availability of seasonal rainfall forecast is thus vital for improved agricultural strategies. Alternatively, farmers are safer if they use conventional approaches, as these have lower associated risks. Increasingly high variability and unreliability of rainfall makes rainfed agriculture in semi-arid areas of sub-Saharan Africa a great challenge