No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Integration of farmers’ knowledge and science-based assessment of soil quality for peri-urban vegetable production in Ghana
Abstract
This study, based on vegetable production fields, combined soil quality assessed by three approaches (qualitatively by farmers, semi-quantitatively by a researcher and quantitatively by laboratory analyses) with the aim of improving the integration of the different approaches. We interviewed 79 peri-urban vegetable growers in two communities within the Sunyani Municipality, Ghana. Eight of the farmers were selected to participate in the farmer-based assessment of soil quality. Further, visual evaluation of soil quality was conducted by the researcher, followed by laboratory analyses of soil properties to corroborate the farmers’ assessment of good and poor soils in their fields. Results showed that the farmers used locally-defined characteristics to describe the physical, biological and crop performance indicators of soil quality. There was, in general, limited use and understanding of soil chemical properties as indicators of soil quality. The farmers’ perception on soil quality of their fields largely influenced their decision on the type of crops they cultivate, and application regimes of mineral fertilizers. Results from the visual evaluation by the researcher agreed in some respects with the farmers’ assessment of soil quality of the good and poor soils in their respective farms. Laboratory analyses did not show specific trends for the content of chemical properties for neither good nor poor soils. The study highlighted that none of the approaches of soil quality assessment is necessarily superior in and of itself. We emphasized the need for integration to capitalize on the strengths of each approach, enhance mutual learning between farmers and soil scientists, build the capacity of farmers, and improve their decision on soil use for agricultural production.
... Popularisation of the use of visual soil evaluation techniques has spread to several countries, in areas of a temperate, subtropical and tropical climate. Worldwide studies applying visual examinations have been conducted on agricultural fields, and plot experiments (Munkholm and Holden, 2015), but also the application of these methods has extended to remote areas in the Amazon (Guimarães et al., 2017a;Cherubin et al., 2019) and rural areas in Africa (Cornelis et al., 2019a;Obour et al., 2020). Franco et al. (2019) suggest that this is a reflection of a global need for reliable and low-cost methods that can provide an evaluation of soil structure status complementary to direct evaluation for research and extension service purposes. ...
... This can help the transition away from intensive farming by participation in groups on farming focussed on soil conditions and regeneration of soil fertility such as organic farming or no-till (Ball et al., 2018). A study in Ghana showed how the VESS method could help integrate farmers' knowledge with a science-based assessment of soil qualities (Obour et al., 2020). One of the properties of soil evaluation during visual soil evaluation that is most appreciated by farmers and general users is smell; this provides a useful, intuitive indicator of the function of living organisms within the soil (Ball et al., 2017). ...
... When evaluating the impact of soil management on soil physical quality, most studies in resource-poor countries rely on measuring bulk density. Despite their particular potential for evaluating soil structural quality, visual soil evaluation methods are at present rarely applied in Africa (Franco et al., 2019) or at least very few uses are reported in the scientific literature (Obour et al., 2020). In one of such studies, Cornelis et al. (2019a) explored the potential of the VSA method (Shepherd, 2009), the VESS method (Guimarães et al., 2011), VESS variants like CoreVESS (Johannes et al., 2017) or with alternative scoring (i.e. ...
Soil structure is a complex and dynamic soil property that constitutes a key aspect of soil health. Soil structure assessment can be evaluated in the field by visual soil evaluation techniques. Development and improvement of these techniques/methods have been the focus of numerous soil scientists worldwide since the mid-20th century. Divided into topsoil and soil profile methods, they differ in principle and level of detail of the assessment. The development and protocols of selected methods are presented in this chapter in chronological order of development, to show differences in methodological approaches. The description given for each of the methods includes guidance for the appropriate selection of the method to be used by stakeholders. Two case studies are given as examples of i) how visual techniques can contribute to achieving the challenges for developing sustainable agricultural management focused on nurturing soil fertility, and ii) the use of visual techniques as tools to assess and monitor soil health in developing countries.
... These results corroborate with previous studies which show that VESS is a useful method to assess soil structure on smallholder farms. Furthermore, it enables a rapid, uncomplicated, and inexpensive assessment, and is a useful method (albeit that users may require prior training) to analyze changes in agricultural land use (Ball et al. 2017;Pulido Moncada et al. 2017;Obour et al. 2020). By monitoring such changes using VESS, regional smallholder farmers may gather useful information that will facilitate decision making, especially when setting up an optimized soil management system that promotes the maintenance of soil structure. ...
... Smallholder farmers perceptions of soil quality may influence their management decisions, including their choice of cultivated crops and soil management strategies (Six et al. 1998). This study demonstrated that VESS is a useful tool for smallholder farmers to assess soil quality, as previously demonstrated in other studies across the world (Pheap et al. 2019;Obour et al. 2020). ...
Different soil management strategies may either promote or degrade soil structure. This study aimed to test the Visual Evaluation of Soil Structure (VESS) method in a smallholder agroforestry system in the eastern Amazon. Three plots (P1, papaya field; P2, banana intercropped with cassava; P3, banana, cassava, and açaí), as well as an adjoining area under native vegetation (NV), were evaluated using VESS. Quantitative assessments of soil physical quality were also performed, including soil water retention curve (SWRC), bulk density (Bd), particle density (Pd), microporosity (Mi), macroporosity (Ma), total porosity (Tp), available water capacity (AWC), field capacity (FC), and permanent wilting point (PWP). The VESS scores in P2 (2.6) and P3 (1.8) were similar to NV (1.4), while P1 (2.8) had a poorer structure. P1 differed from the other plots, with lower Ma (0.05 m3 m−3) and Tp (0.39 m3 m−3), and higher Bd (1.57 Mg m−3), AWC (0.32 m3 m−3), and water retention at FC (θFC: 0.33 m3 m−3). VESS scores were significantly correlated with most quantitative measurements. These results indicate that VESS is effective to assess soil structure, providing a convenient strategy for soil structural quality assessment in smallholders from Amazon.
... In addition to the FGDs, questionnaires were administered to approximately half of the farmers who participated in the FGDs. A similar approach to that described by Obour, et al. [9] was used in selecting the respondents of the questionnaire. Thus, the respondents targeted in each study community were those who were more experienced and knowledgeable about the 2020 minor season maize failure than the average farmer and were willing to participate. ...
This paper examines the causes of widespread maize production failure in Ghana during the 2020 minor growing season. A mixed-methods approach was used to study smallholder maize farmers in the Ejura-Sekyedumase Municipality to provide a holistic understanding of the factors behind the maize production failure and to inform policy interventions. The results show that the decline in maize grain yield was caused by the failure of the minor season rains and, more importantly, the destruction of maize plants by fall armyworms. Other factors including poor soils and inadequate farm inputs contributed minimally to the observed maize failures. The agronomic practices adopted by the farmers to mitigate crop failures were undermined by their inability to master the onset and cessation of rainfall, the ineffectiveness of pesticides to control the fall armyworms and financial challenges. It is recommended that the government promotes and supports rainwater harvesting to address the impacts of drought and pests on food crop production. Furthermore, to ensure sustainable food production, a combination of indigenous knowledge and scientific farm practices are crucial to accurately forecast the weather and to control the fall armyworms.
... Hybrid approaches to soil health assessment where farmers' observational techniques are integrated with conventional soil testing (Barrios et al., 2006) are more appropriate. For example, conventional soil testing on areas identified by farmers can provide quantitative data to verify farmers' assertions (Obour et al., 2020). It can also provide information on specific nutrient deficiencies and toxicities that can inform targeted fertilizer application or other nutrient management practices (Belachew and Abera, 2010). ...
Improving soil health is necessary for increasing agricultural productivity and providing multiple ecosystem services. In the African Highlands (AH) where conversion of forests to cultivation on steep slopes is leading to soil degradation, sustainable land management practices are vital. Farmers’ awareness of soil health indicators (SHI) influences their choice of land management and needs to be better understood to improve communication between land managers and other stakeholders in agricultural systems. This study aims to collate and evaluate case study analyses of farmers’ awareness and use of soil health indicators in African Highlands. This is achieved by using a multi-method approach that combines a meta-summary analysis of AH’s SHI data from 24 published studies together with farmer interviews in the East Usambara Mountain region of Tanzania (EUM). Our findings show that farmers across the AH use observable attributes of the landscape as SHI. Out of 16 SHI reported by the farmers, vegetation performance/crop yield and soil colour were most frequently used across the AH. These were also the only two SHI that influenced farmers’ land management decisions in the EUM, where organic manure addition was the only land management option resulting from observed changes in SHI. Farmers’ use of only one or two SHI in land management decisions, as is the case in the EUM, seems to limit their choice and/or adoption of sustainable land management options, highlighting the need to increase awareness and use of more relevant SHI. This could be achieved by sharing SHI knowledge through learning alliances and agricultural extension service. Integration of farmers’ observation techniques and conventional soil testing in a hybrid approach is recommended for a more targeted assessment of soil health to inform appropriate and sustainable land management practices.
African agriculture is underperforming and this is due to institutional, climatic factors and low adoption rate of innovations. Among these factors, the major source of yield variability which is not under the control of farmers and policymakers is climate. Climate is changing and its effects on agriculture are uncertain, but globally scientists agree that actions to lowering damages or improving benefits depending on what the prevailing situation presents is. One means to mitigate climate change is the use of meteorological information in agriculture. This approach has been used for about three decades in Africa. The question therefore is, how harmful or useful has this technological option been? This study builds a meta‐database and using descriptive statistics revealed that the optimal date of delivery in advance of Agrometeorological information to farmers is between 1 and 2 month. Farmers in most cases have as main response to agrometeorological forecasts non‐intensified options. The mean yield gain is around 20%. The results of the analysis showed that a 60‐70% accuracy of agrometeorological information is necessary for the agrometeorological information to be worthwhile. If the accuracy of information is less than 60% then the use of meteorological information will be harmful.
Conventional wisdom holds that Sub-Saharan African farmers use few modern inputs despite the fact that most poverty-reducing agricultural growth in the region is expected to come largely from expanded use of inputs that embody improved technologies, particularly improved seed, fertilizers and other agro-chemicals, machinery, and irrigation. Yet following several years of high food prices, concerted policy efforts to intensify fertilizer and hybrid seed use, and increased public and private investment in agriculture, how low is modern input use in Africa really? This article revisits Africa’s agricultural input landscape, exploiting the unique, recently collected, nationally representative, agriculturally intensive, and cross-country comparable Living Standard Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) covering six countries in the region (Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda). Using data from over 22,000 households and 62,000 agricultural plots, we offer ten potentially surprising facts about modern input use in Africa today.
Biodiversity is responsible for the provision of many ecosystem services; human well-being is based on these services, and consequently on biodiversity. In soil, earthworms represent the largest component of the animal biomass and are commonly termed ‘ecosystem engineers’. This review considers the contribution of earthworms to ecosystem services through pedogenesis, development of soil structure, water regulation, nutrient cycling, primary production, climate regulation, pollution remediation and cultural services. Although there has been much research into the role of earthworms in soil ecology, this review demonstrates substantial gaps in our knowledge related in particular to difficulties in identifying the effects of species, land use and climate. The review aims to assist people involved in all aspects of land management, including conservation, agriculture, mining or other industries, to obtain a broad knowledge of earthworms and ecosystem services.
Erratic rainfall and increasing temperature is rapidly emerging as one of the most serious global problems affecting many sectors in the world. It is considered to be one of the most serious threats to sustainable development with adverse impact on environment, human health, food security, economic activities, natural resources and physical infrastructure. Southern Africa is one of the most vulnerable regions to climate change in the world, particularly because of widespread poverty, recurrent droughts, inequitable land distribution, over-dependence on rain-fed agriculture and low adaptive capacity. Yet rural farmers in southern Africa have managed to survive the vagaries of climate change over the years. This review reveals that these rural farmers can use indigenous knowledge to cope and adapt to climate change. Availability and access to scientific weather information to make cropping and other decisions at the local level remain key issues to usage of climatic data by rural farmers. On the other hand, indigenous knowledge is what rural farmers have been using but is also becoming unreliable due to climate change and variability. Integration of indigenous knowledge and scientific seasonal forecast seems to be a key possible thrust to reduce vulnerability, enhance resilience of rural farmers and increase their adaptive capacity.
Climate change tends to have negative effects on crop yield through its influence on crop production. Understanding the relationship between climatic variables and crop area on the mean and variance of crop yield will facilitate development of appropriate policies to cope with climate change. This paper examines the effects of climatic variables and crop area on the mean and variance of maize yield in Ghana. The Just and Pope stochastic production function using the Cobb-Douglas functional form was employed. The results show that average maize yield is positively related to crop area and negatively related to rainfall and temperature. Furthermore, increase in crop area and temperature will enlarge maize yield variability while rainfall increase will decrease the variability in maize yield.
Most General Circulation Models predict more infrequent but larger precipitation events in the eastern United States combined with a warmer climate. This could have a negative effect on maize production. To understand the sensitivity of maize production to future changes in precipitation, we analyzed growing season precipitation and average state maize yields in the eastern United States for the period 1963-2011. Growing season precipitation did not show a strong trend during this period. However, crop yields increased at 3.90% in the southern, 2.62% in the central, and 2.31% in the northern part of the eastern United States, which we attributed to technology and management. To separate technology and management effects from precipitation variability, we corrected maize yields for these yield trends. We then correlated maize yield corrected for advances in technology and management with total growing season precipitation and precipitation in the critical month of pollination, from the regional to state scale. Maize yield - precipitation relationships showed that moisture shortage rather than excess determined maize yield in the Eastern United States. The relationship between total growing season precipitation-maize yield was stronger in the southeastern than in the northeastern U.S., but the critical month precipitation-maize yield relationship was stronger in the northeastern than in the southeastern U.S. If climate model predictions are accurate and total growing season precipitation will not decrease in this region but variability will, it is likely that maize yields in the northeastern U.S. will be more significantly affected.
Environmentally induced farmer migration is an important livelihood strategy, yet little is known of the effects on the destination region agroecosystem information networks and management practices. In the forest-savanna transition zone (Brong Ahafo Region) of Ghana, where migration from northern regions (migrant) and from neighboring regions (settler) is active, we chart the role of migrant famers and the type of agroecosystem management practices embedded in information networks using a social networks approach. Based on empirical network data from 44 respondents across three communities, we illustrate a diffuse information network, with variable tie frequency between settlement categories (local, settler, or migrant) of farmers. The cohesion of this network is dependent on a few strategic bridging ties initiated by migrant farmers, who are thus centrally positioned to exchange agroecosystem management practices between geographically and socially distant groups. At the individual level, migrant and settler farmers are more likely: (1) to have larger networks with more ties between members of their networks, (2) to be brokers positioned between non-migrant farmers, and (3) to tend (although not statistically significantly) to use pro-environmental management regimes, including agroforestry practices, new planting methods, and plot-scale weeding. We conceptualize this phenomenon as extended social and environmental experience and the deployment of social-ecological memory, with migrant farmers as potential agents of innovation and adaptive management.
The El Niño Southern Oscillation (ENSO) is one of the main factors influencing global climate variability and consequently has a major effect on crop yield variability. However, most studies have been based on statistical approaches, which make it difficult to discover the underlying impact mechanisms. Here, using process-based crop model Model to Capture the Crop-Weather relationship over a Large Area (MCWLA)-Maize, we found a consistent spatial pattern of maize yield variability in association with ENSO between MCWLA-Maize model outputs and observations. During El Niño years, most areas of China, especially in the north, experience a yield increase, whereas some areas in the south have a decrease in yields. During La Niña years, there is an obvious decline in yields, mainly in the north and northeast, and a general increase in the south. In-depth analyses suggest that precipitation P rather than temperature T and solar radiation S during the maize growing season is the main cause of ENSO-induced maize yield variability in northern and northeastern China. Although a 2 °C change of T can affect maize yields more than a 20% change of P, greater changes of P contribute more to maize yield variability during ENSO years. In general, maize yields in drier regions are much more sensitive to P variability than those in wetter areas. All changes in meteorological variables, including T, P, S, and vapour pressure deficit (VPD) during ENSO years, affect yield variability mainly through their effects on water stress. Our results suggest that more effective agricultural information can be provided to government decision makers and farmers by developing a food security warning system based on the MCWLA-Maize model and ENSO forecast information.
The right to food is one of those most consistently mentioned in international human rights documents, but it is the one most frequently violated in recent times. Targets set by the World Food Summit in 1996 for the reduction of hunger have largely failed, despite food production having grown faster than world population. Global, national and human security issues are increasingly converging, and in some regions overlapping. Some 840 million people worldwide are malnourished, the highest percentage of these being in Africa. The magnitude of the problem in Africa has now reached unprecedented crisis levels—some 38 million people face “an urgent and imminent threat to their peace, security and stability”.
In 2012, food insecurity is still a major global concern as 1 billion people are suffering from starvation, under-, and malnutrition, and the Food and Agriculture Organization of the United Nations (FAO) has concluded that we are still far from reaching millennium development goal (MDG) number 1: to halve extreme poverty and hunger by 2015. In sub-Saharan Africa, the number of people suffering from hunger is estimated at 239 million, and this figure could increase in the near future.
There are many examples of food insecurity in sub-Saharan Africa, some of them having reached catastrophic dimensions, for example, in the Horn of Africa or southern Madagascar. Food insecurity is not just about insufficient food production, availability, and intake, it is also about the poor quality or nutritional value of the food. The detrimental situation of women and children is particularly serious, as well as the situation among female teenagers, who receive less food than their male counterparts in the same households.
Soaring food prices and food riots are among the many symptoms of the prevailing food crisis and insecurity. Climate change and weather vagaries, present and forecast, are generally compounding food insecurity and drastically changing farming activities, as diagnosed by the Consultative Group on International Agricultural Research (CGIAR) in June 2011.
The key cause of food insecurity is inadequate food production. Since the global food crisis of 2007–2008, there has been an increasing awareness throughout the world that we must produce more and better food; and we should not be derailed from this goal, despite some relief brought by the good cereal harvests in 2011–2012. This is particularly true in sub-Saharan Africa, which needs and wants to make its own green revolution.
The African challenge indeed is key to mitigating food insecurity in the world. Commitments were made by the heads of states and governments of the African Union to double the part of their domestic budgets devoted to agriculture in 2010–2011, so as to reach 10%. Technical solutions exist and there are indeed, throughout Africa, good examples of higher-yielding and sustainable agriculture. But good practices have to spread throughout the continent, while at the same time social and economic measures, as well as political will, are indispensable ingredients of Africa’s green revolution. It is also necessary that international donors fulfil their commitment to help African farmers and rural communities and protect them against unfair trade, competition, and dumping of cheap agrifood products from overseas.
Soil quality (SQ) assessment from farmers' point of view can be used as a primary indicator for planning sustainable agriculture. Despite this fact, limited information is documented with regard to SQ indicators, for example weed species, crop types and management practices from farmers' knowledge perspectives. The aims of this study are to analyse factors that determine farmers' knowledge of SQ, identify SQ indicators of weed species and crop types across different SQ status and assess soil-and-crop management practices that maintain SQ in the Mai-Negus catchment, northern Ethiopia. Fifty-two farmer household heads were chosen randomly for questionnaire interview. The results showed significant (p ≤ 0·05) differences in the proportion of respondents who used different crop-and-soil management practices. The success of overall prediction by the logistic regression model (model χ2 = 0·84, p < 0·01) and level of model correct predictions (86%) indicated that the explanatory variables have sufficiently explained farmers' knowledge of SQ indicators. Provided that other conditions remained constant, the odds ratio of variables such as farmer experience, access to information, farm location, education, field slope and land tenure have significantly increased the likelihood of farmers for being knowledgeable of SQ indicators. This study also demonstrated that most farmers are knowledgeable in identifying weed species, crop types and management practices across various SQ status, which suggests that such SQ indicators should be used to assess SQ status (degradation severity) while locating fields to be intervened using appropriate management strategies. © 2013 The Authors. Land Degradation & Development published by John Wiley & Sons, Ltd.
This paper builds on national- and regional-level vulnerability assessments by developing and applying a livelihood vulnerability index at the community and household scales to explore the nature of climate vulnerability. It provides innovative methodological steps in relation to livelihood assessment to identify the vulnerability of households and communities to drought. This will help to improve drought vulnerability assessments in Ghana and more widely as it shows extra information can be obtained from local-level vulnerability assessment that may be lacking in national- and regional-level analysis. The research employs quantitative and qualitative data collected through participatory methods, key informant interviews and a questionnaire survey with 270 households across 6 communities in two regions in Ghana. Results show that within the same agroecological zone, households and communities experience different degrees of climate vulnerability. These differences can be largely explained by socioeconomic characteristics such as wealth and gender, as well as access to capital assets. Results identify vulnerable households within resilient communities as well as more resilient households within vulnerable communities. These outliers are studied in detail. It is found that outlier households in vulnerable communities have an array of alternative livelihood options and tend to be socially well connected, enabling them to take advantage of opportunities associated with environmental and economic changes. To sustain and enhance the livelihoods of vulnerable households and communities, policymakers need to identify and facilitate appropriate interventions that foster asset building, improve institutional capacity as well as build social capital.
Climate change is projected to have serious environmental, economic, and social impacts on Ghana, particularly on rural farmers whose livelihoods depend largely on rainfall. The extent of these impacts depends largely on awareness and the level of adaptation in response to climate change. This study examines the perception of farmers in Sekyedumase district of Ashanti region of Ghana on climate change and analyzes farmers’ adaptation responses to climate change. A hundred and eighty farming households were interviewed in February and October 2009. Results showed that about 92% of the respondents perceived increases in temperature, while 87% perceived decrease in precipitation over the years. The major adaptation strategies identified included crop diversification, planting of short season varieties, change in crops species, and a shift in planting date, among others. Results of logit regression analysis indicated that the access to extension services, credit, soil fertility, and land tenure are the four most important factors that influence farmers’ perception and adaptation. The main barriers included lack of information on adaptation strategies, poverty, and lack of information about weather. Even though the communities are highly aware of climate issues, only 44.4% of farmers have adjusted their farming practices to reduce the impacts of increasing temperature and 40.6% to decreasing precipitation, giving lack of funds as the main barrier to implementing adaptation measure. Implications for policymaking will be to make credit facilities more flexible, to invest in training more extension officers and more education on climate change and adaptation strategies.
The characteristics of rainfall regime and its variability in the sub-humid region of mid-Ghana is analyzed using daily rainfall data from the Wenchi, 1950–2000. Prior research in the area, suggests that climatic variability occurs at lower frequencies than the typical ENSO signal and may be more closely related to noted shifts in global climatic patterns. Fifty-six possible starting dates encompassing the traditional growing season, extending from late January to early November, at 5 day increments, are used to define temporal units of varying lengths, variable temporal units (VTUs). Rainfall characteristics in each unit are described by two variables: total rainfall and number of rainy days. Given the widely noted global climatic shift in the 1970s and the results of regional analyses, the 50 year record is sub-divided into two 20 year periods, 1950–1969 (period 1) and 1980–2000 (period 2). The means and variances of the two variables in each VTU are compared to identify any times when the changes in rainfall characteristics are most noticeable within the rainfall regime between periods. Both variables yield results consistent with the main rainy season and the long dry season being relatively unchanged, however the short dry spell is becoming wetter and the minor rainy season (September/October) has become significantly drier and shorter. The observations are consistent with the general north–south erosion of the bi-modal regime in West African which is associated with the southward shift of the ITCZ and the monsoonal system. This phenomenon is believed to be ongoing for the last 10,000 years in step with the hypothesized shift of the perihelion into the boreal winter. The use of independent arbitrary starting dates and durations (VTU) advances the understanding of temporal variability of rainfall, at a scale appropriate to agricultural practices in the study area.
Farmers’ local knowledge of soil fertility and management strategies plays a significant role in fertility maintenance of farmlands and also contributes to the participatory development of interventions to sustain farm productivity. A field study was conducted in the Ashanti Region of Ghana to assess farmers’ local knowledge of soil fertility and fertility processes, and to analyze how this knowledge influences soil fertility management strategies. Farmer's local knowledge of soil was not significantly related to age, location, or gender in this study. However, knowledge and perceptions of soil fertility were based on observable plant and soil related characteristics namely; soil colour, crop yield, soil water holding/retention capacity, stoniness, difficulty to work soil, type and abundance of indicator weeds, colour of leaves and deficiency symptoms observed on crops, crop growth rate and presence and abundance of soil macro-fauna. Though farmers’ indicators were purely qualitative, it nevertheless was congruent to scientific assessment of fertile or infertile soils in many respects. Reported fertile sites were confirmed to exhibit higher levels of soil N, P, K and organic matter compared to reported infertile sites. It is argued that there is the need to utilize the complementary nature of local and scientific knowledge. To facilitate integration and inclusion of farmer perspectives in the national agricultural development planning and policy formulation processes, the use of truly participatory, gender sensitive, collaborative and capacity-building approaches is required particularly the established rich knowledge base on soils.
The study examines the impact of variability in rainfall characteristics on maize yield in a tropical setting. The study design involves the collection and analyses of data on rainfall characteristics and maize yield at Gboko LGA in Benue State, Nigeria. The methodology adopted is the use of archival data on rainfall and maize yield for 30 years, collected from the Agro-Meteorological Unit and Farm Department of Akperan Orshi College of Agriculture, Yandev (AOCAY). The data was analyzed using mean, correlation and regression analysis to establish cause and effect relationship be- tween rainfall characteristics and maize yield at the study area. The result of the correlation analysis showed that rain days and rainfall amount had strong positive relationship (r = 0.747 and r = 0.599, respectively) with maize yield. It was also observed that the rainfall characteristics jointly contributed 67.4% in explaining the variations in the yield of maize per hectare. The study concludes with the development of a model for predicting maize yield in Gboko LGA. The study also recommended the application of irrigation technology, use of appropriate management practices that ensured mois- ture conservation and improved crop species with shorter growing periods/less moisture consumption as adaptive measures to the changing rainfall pattern within the study area.
The El Niño–Southern Oscillation (ENSO) is a naturally occurring fluctuation that originates in the tropical Pacific region and affects ecosystems, agriculture, freshwater supplies, hurricanes and other severe weather events worldwide. Under the influence of global warming, the mean climate of the Pacific region will probably undergo significant changes. The tropical easterly trade winds are expected to weaken; surface ocean temperatures are expected to warm fastest near the equator and more slowly farther away; the equatorial thermocline that marks the transition between the wind-mixed upper ocean and deeper layers is expected to shoal; and the temperature gradients across the thermocline are expected to become steeper. Year-to-year ENSO variability is controlled by a delicate balance of amplifying and damping feedbacks, and one or more of the physical processes that are responsible for determining the characteristics of ENSO will probably be modified by climate change. Therefore, despite considerable progress in our understanding of the impact of climate change on many of the processes that contribute to El Niño variability, it is not yet possible to say whether ENSO activity will be enhanced or damped, or if the frequency of events will change.
In the recent past there has been increasing recognition that local knowledge of farmers can yield insight into soil quality. With regard to constraints and possibilities for the production of irrigated rice in the south of Brazil there is no documentation on local soil knowledge. The goals of this study were to answer the following questions: (1) Which soil quality perceptions do rice farmers have? (2) Which soil quality indicators are most important to them? (3) Do rice farmers use their knowledge about soil quality indicators when making soil management decisions and developing sustainable management? The study was carried out in the municipality of Camaquã-Rio Grande do Sul, Brazil. The research methods used included semi-structured interviews alternated with group discussions. Farmers named eleven characteristics as good indicators for soil quality: earthworms, soil colour, yield, spontaneous vegetation, soil organic matter, root development, soil friability, rice plant development, colour of the rice plant, number of rice tillers and cattle health. Out of these, three indicators were found to be useful in farmers’ decision-making: spontaneous vegetation, rice plant development and soil colour. The potential use of local knowledge for maintaining soil quality and developing sustainable land management is discussed.
The objective of this paper is to compare soil fertility evaluation based on experience and knowledge of smallholder farmer communities with the evaluation by scientists based on soil analysis and model calculations. The role of the smallholder farmer community in soil fertility evaluation and management was examined from two ‘research for development’ projects in northern Tanzania. These are the African Highlands Initiative (AHI) and the Soil Water Management Research Group (SWMRG). Participatory approaches were applied by both projects. Farmers’ experience and knowledge of local indicators of soil quality were used in identifying soil fertility constraints and in generating resource flow maps. The farmers’ evaluation of soil fertility was compared with soil analytical data and with calculations of maize yields by the model QUEFTS. Farmers’ indigenous knowledge in soil fertility evaluation mostly agreed with laboratory analysis and model calculations by QUEFTS. Model calculations identified potassium as the most limiting nutrient in the highlands in northeastern Tanzania for yields less than 3 t ha−1 and phosphorus for yields higher than 4 t ha−1. In Maswa (Lake Victoria Basin) nitrogen was most limiting. Given that farmers’ evaluation of soil fertility is relative to what they see around them, there is a need to verify their observations, but also the interpretation of laboratory data by models like QUEFTS requires continuous and critical validation. Both projects have shown that there is scope to reverse the trends of declining soil fertility in smallholder farms in northern Tanzania. Essential was that the interaction with scientists has built confidence in the farmers because their knowledge in addressing soil fertility constraints was recognized.
To design more appropriate research and to facilitate communication with farmers, researchers need to understand farmers’ knowledge, perceptions and assessments of soil fertility. To address this issue for the mid-hills of western Nepal, semi-structured interviews were conducted in 68 households to gain insight into soil fertility management practices, local methods used to assess the fertility status of a field, and perceived trends in soil fertility. Thirty-three farmers were then asked to identify fertile and infertile fields. Characteristics of these fields in terms of the indicators mentioned in the interviews were recorded, and soil samples were taken for chemical analysis in a laboratory. Data were stratified according to altitude and type of field, khet (irrigated) and bari (rainfed).A total of 62 indicators was found to be used by farmers to evaluate and monitor soil fertility, which were classified into five categories: those relating to soil characteristics, crop performance, agricultural management, environmental factors, and biology. There was good agreement between farmers’ assessment of the soil fertility status of a field and a number of these indicators, particularly soil colour and weed abundance, which were examined in more detail. The soil chemical analysis also corresponded well with farmers assessment of soil fertility.Farmers’ perceptions of soil fertility were found to be more ‘holistic’ than those of researchers, as they included factors they felt influenced the soils and crop growth in their fields. The term ‘field fitness’ is proposed as it conveys farmers’ perceptions more accurately than ‘soil fertility’ alone.
Concerns over environmental and human health impacts of conventional weed management practices, herbicide resistance in weeds, and rising costs of crop production and protection have led agricultural producers and scientists in many countries to seek strategies that take greater advantage of ecological processes and thereby allow a reduction in herbicide use. This book provides principles and practices for ecologically based weed management in a wide range of temperate and tropical farming systems. After examining weed life histories and processes determining the assembly of weed communities, the authors describe how tillage and cultivation practices, manipulations of soil conditions, competitive cultivars, crop diversification, grazing livestock, arthropod and microbial biocontrol agents, and other factors can be used to reduce weed germination, growth, competitive ability, reproduction and dispersal. Special attention is given to the evolutionary challenges that weeds pose and the roles that farmers can play in the development of new weed-management strategies.
Ghana continues to rely heavily on hydropower for her electricity needs. This hydropower reliance cannot ensure sustainable development since there is a strong association between hydropower production and climate variability and change including ENSO-related lake water levels reduction. Using regression analysis this study found that rainfall variability accounted for 21% of the inter-annual fluctuations in power generation from the Akosombo Hydroelectric power station between 1970 and 1990 while ENSO and lake water level accounted for 72.4% of the inter-annual fluctuations between 1991 and 2010. There is therefore the need to diversify power production to attain energy security in Ghana.
Soil structure forms a key component of soil quality, and its assessment by semi-quantitative visual soil evaluation (VSE) techniques can help scientists, advisors and farmers make decisions regarding sampling and soil management. VSE techniques require inexpensive equipment and generate immediate results that correlate well with quantitative measurements of physical and biochemical properties, highlighting their potential utility. We reviewed published VSE techniques and found that soils of certain textures present problems and a lack of research into the influence of soil moisture content on VSE criteria. Generally, profile methods evaluate process interactions at specific locations within a field, exploring both intrinsic aspects and anthropogenic impacts. Spade methods focus on anthropogenic characteristics, providing rapid synopses of soil structure over wider areas. Despite a focus on structural form, some methods include criteria related to stability and resiliency. Further work is needed to improve existing methods regarding texture influences, on-farm sampling procedures and more holistic assessments of soil structure.
A sample group of 119 farmers from a semi-arid district of Madrid was interviewed to determine the knowledge of individuals about soil conservation and management. Farmers commonly identify physical factors in the landscape that are visually recognizable and those chemical factors that clearly affect productivity. Often, factors, such as salinity or pH that require laboratory analysis, are less readily identified. Farmer knowledge of soils is influenced by their main source of income, gender, education and age. Although there is a high degree of correspondence between scientific and traditional knowledge of soil, some gaps have been identified, notably those related to erosion. Key steps identified for promoting the adoption of sustainable soil management practices to farmers were as follows: involvement of public institutions, the need for increased agricultural prices and an improvement in training and public awareness. Farmers were aware of their own limitations and demanded capacity building, technical and policy support.
Rainfall variability has become a major agricultural issue in sub-Saharan Africa, especially since crop production is mainly rainfed. Irrigation technologies are expensive and their implementation is slow. Many researchers now believe that some understanding of the causes of rainfall variability would lead to measures that could be used to investigate reduction in total rainfall and/or drought effects.
El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) climatology (1980–2010) is developed and analyzed across the U.S. Corn Belt using state climate division weather and historic corn yield data using analysis of variance (ANOVA) and correlation analysis. Findings provide insight to agroclimatic conditions under different ENSO and AO episodes and are analyzed with a perspective for potential impacts to agricultural production and planning, with findings being developed into a web-based tool for the U.S. Corn Belt.
This study is unique in that it utilizes the oceanic Niño index and explores two teleconnection patterns that influence weather across different spatiotemporal scales. It is found that the AO has a more frequent weak to moderate correlation to historic yields than ENSO when correlated by average subgrowing season index values. Yield anomaly and ENSO and AO episode analysis affirms the overall positive impact of El Niño events on yields compared to La Niña events, with neutral ENSO events in between as found in previous studies. Yields when binned by the AO episode present more uncertainty. While significant temperature and precipitation impacts from ENSO and AO are felt outside of the primary growing season, correlation between threshold variables of episode-specific temperature and precipitation and historic yields suggests that relationships between ENSO and AO and yield are present during specific months of the growing season, particularly August. Overall, spatial climatic variability resulting from ENSO and AO episodes contributes to yield potential at regional to subregional scales, making generalization of impacts difficult and highlighting a continued need for finescale resolution analysis of ENSO and AO signal impacts on corn production.
The monitoring and prediction of climate-induced variations in crop yields, production and export prices in major food-producing regions have become important to enable national governments in import-dependent countries to ensure supplies of affordable food for consumers. Although the El Niño/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Niño likely improves the global-mean soybean yield by 2.1-5.4% but appears to change the yields of maize, rice and wheat by -4.3 to +0.8%. The global-mean yields of all four crops during La Niña years tend to be below normal (-4.5 to 0.0%). Our findings highlight the importance of ENSO to global crop production.
Several drought indices are available to compute the degree of drought to which crops are exposed. They vary in complexity, generality, and the adequacy with which they represent processes in the soil, plant, and atmosphere. Agricultural Reference Index for Drought (ARID) was developed as a reference index to approximate the water stress factor that is used to affect growth and other physiological processes in crop simulation models. Using RMSE, Willmott d index, and modeling efficiency (ME) as performance measures, ARID was evaluated using soil water contents in the root zone measured daily in two grass fields in Florida. The ability of ARID was assessed through comparison with the water deficit index (WSPD) of the Decision Support System for Agrotechnology Transfer (DSSAT) CERES-Maize model. Seven other drought indices were compared with WSPD to identify the most appropriate agricultural drought index. Values of each index were computed for full canopy cover periods of maize (Zea mays L.) crops for 16 locations in the U.S. Southeast. Using periodic values, the performance of each index was assessed in terms of its correlation (r) with and departure from WSPD. The ARID reasonably predicted soil water contents (RMSE = 0.01-0.019, d index = 0.92-0.94, ME = 0.66-0.73) and adequately approximated WSPD (r = 0.90, RMSE = 0.15). Among the indices compared, ARID mimicked WSPD the most closely (RMSE smaller by 1-83%, r larger by 1-630%) and captured weather fluctuation effects the most accurately. Results indicated that ARID may be used as a simple index for quantifying drought and its effects on crop yields.
Though soil quality (SQ) degradation is a serious challenge to national food security, little information is available that evaluate farmer SQ knowledge vis-à-vis scientific knowledge at catchment scale in Ethiopia. Scientific soil analysis is not an effective approach for SQ assessment in developing regions. An alternative option to evaluate using farmer knowledge is thus necessary but this can be sound after verified scientifically in the context of each region. The present study aims to evaluate SQ status (categories) identified by local farmers using scientific soil measurements, and assess their potential as indicators of soil degradation for decision making in the Mai-Negus catchment, northern Ethiopia. In this study, the scientifically measured soil attributes significantly differed (P≤0.05) among the SQ categories identified by the local farmers. Using variables retained in the four identified component factors, discriminant analysis identified soil porosity to be the most powerful variable that can help discriminate the SQ status. The study shows that farmer derived SQ status (low, medium, high) could be crucial in providing basis for management and policy decision making as validated by analytical components. Therefore, attention should be given toward integrating farmer knowledge in SQ management to increase chance of technology adoption by farmers.
This essay summarizes deliberation by the Soil Science Society of America (SSSA) Ad Hoc Committee on Soil Quality (S-581) and was written to spur discussion among SSSA members. Varying perceptions of soil quality have emerged since the concept was suggested in the early 1990s, and dialogue among members is important because, unlike air and water quality, legislative standards for soil quality have not been and perhaps should not be defined. In simplest terms, soil quality is "the capacity (of soil) to function". This definition, based on function, reflects the living and dynamic nature of soil. Soil quality can be conceptualized as a three-legged stool, the function and balance of which requires an integration of three major components - sustained biological productivity, environmental quality, and plant and animal health. The concept attempts to balance multiple soil uses (e.g., for agricultural production, remediation of wastes, urban development, forest, range, or recreation) with goals for environmental quality. Assessing soil quality will require collaboration among all disciplines of science to examine and interpret their results in the context of land management strategies, interactions, and trade-offs. Society is demanding solutions from science. Simply measuring and reporting the response of an individual soil parameter to a given perturbation or management practice is no longer sufficient. The soil resource must be recognized as a dynamic living system that emerges through a unique balance and interaction of its biological, chemical, and physical components. We encourage SSSA members to consider the concept of soil quality (perhaps as a marketing tool) and to debate how it might enable us to more effectively meet the diverse natural resource needs and concerns of our rural, urban, and suburban clientele of today and tomorrow.
Abstract Increased awareness of the role of soil structure in defining the physical fertility or quality of soil has led to the need for a simple assessment relevant to the environmental and economic sustainability of soil productivity. A test is required that is usable by farmer, consultant and researcher alike. Here an assessment of soil structure quality (Sq) is described which is based on a visual key linked to criteria chosen to be as objective as possible. The influences of operator, tillage and crop type on Sq value were tested. The test takes 5–15 min per location and enough replicates were obtained for statistical comparison of data sets. The assessments of individual operators were influenced to an extent by differences between fields, making the use of multiple operators desirable. Differences in soil management were revealed by the test and related to differences in soil physical properties (bulk density, penetration resistance and porosity) and crop growth. Indicative thresholds of soil management are suggested. The assessment should be viewed as complementary to conventional laboratory assessments of soil structure. Visual soil structure assessment can indicate to the soil scientist where to sample and what soil measurements are likely to be worthwhile.
A review is given of the meaning of the term El Niño and how it
has changed in time, so there is no universal single definition. This
needs to be recognized for scientific uses, and precision can only be
achieved if the particular definition is identified in each use to
reduce the possibility of misunderstanding. For quantitative purposes,
possible definitions are explored that match the El Niños
identified historically after 1950, and it is suggested that an El
Niño can be said to occur if 5-month running means of sea surface
temperature (SST) anomalies in the Niño 3.4 region
(5°N-5°S, 120°-170°W) exceed 0.4°C for 6 months or
more. With this definition, El Niños occur 31% of the time and La
Niñas (with an equivalent definition) occur 23% of the time. The
histogram of Niño 3.4 SST anomalies reveals a bimodal character.
An advantage of such a definition is that it allows the beginning, end,
duration, and magnitude of each event to be quantified. Most El
Niños begin in the northern spring or perhaps summer and peak
from November to January in sea surface temperatures.
Spade methods to visually evaluate soil structural quality (Sq) are simple, quick, cheap and can be used by farmers, gardeners, consultants and the scientific community. However, European and Brazilian users of one such method, viz. visual evaluation of soil structure (VESS) which is a development of the Peerlkamp test, have been concerned about its subjectivity. The method of soil slice break-up and operator influence on scores have been questioned. Thus, our aim was to make soil scoring by the VESS technique more objective and thus to revise the scoring guide. We compared scoring with normal breaking up of the soil slice by hand with scoring after breaking up the slice by dropping (drop shatter) to make the soil break-up more operator independent. After slice break-up, aggregates were split by hand and their internal porosity was evaluated to develop the use of visible porosity as an aid to scoring. This proved inconclusive on its own, so a method of reducing larger aggregates to 1.5–2.0 cm core fragments and describing their shape and porosity was developed to score soil Sq. Breaking up a spadeful of soil by hand or by dropping resulted in the same Sq score. The method of reducing aggregates and evaluation of their shape improved VESS, particularly in the middle range of soil quality and the revised chart is shown. VESS was sensitive to changes in Sq in layers within the profile and its use for diagnosing Sq in different layers allows targeted soil improvement by tillage.
The impact of El Niño–southern oscillation (ENSO) on Indian foodgrain production was analysed for the period 1950–99. The inverse relationship between sea-surface temperature (SST) anomalies from June to August (JJA) over the NINO3 sector of the tropical Pacific Ocean and Indian foodgrain production anomalies (r = −0.50) was significant at the 1% level. During the warm ENSO phase, the total foodgrain production frequently decreased (12 out of 13 years) by 1 to 15%. In 10 out of 13 cold ENSO-phase years, the total foodgrain production increased from normal. The relationship between the SST-based NINO3 ENSO index and the Kharif season (June–September) foodgrain production anomalies (r = −0.52) was greater than for the Rabi season (October–February) foodgrain production (r = −0.27). The ENSO impact on rice production was greatest among the individual crops. The average drop in rice (Kharif season crop) production during a warm ENSO-phase year was 3.4 million tonnes (7%). In a cold ENSO-phase year the average production increase was 1.3 million tones (3%). Wheat (Rabi season crop) production was also influenced by ENSO, as it depends on the carryover soil water storage from the Kharif season. Sorghum and chickpea production are not significantly influenced by ENSO extremes.
The ability to predict rainfall variability a season in advance could have a major impact on the fragile Kenyan economy. The ability to benefit from climate prediction arises from the intersection of human vulnerability, climate predictability, and decision capacity. Africa may be a prime potential benefactor of seasonal climate forecasting. With this in mind, the link between El Niño-related variability in rainfall at annual and seasonal scales and national-level maize yield in Kenya was explored. The spatial and seasonal variations in El Niño influence on rainfall are highly inconclusive in Kenya except for some highland high rainfall sites and seasons. Significant event-to-event variability was observed, however, during the October–January (OJ) crop growing season during El Niño events. Increases in the OJ seasonal rainfall during El Niño events were reflected in the annual rainfall. While the mean change in rainfall between El Niño and neutral was positive during OJ season and annually, however, the change was negative during the March–June (MJ) season. El Niño effects were greater on rainfall in the second growing season (OJ) for the 1982–83 and 1997–98 El Niño compared with the 1986–87, 1987–88, 1991–92 events. Sites on the highland ecoregion recorded a significant increase in rainfall during El Niño events compared with neutral years. However, the 1987–88 El Niño had a significant effect on the MJ growing season rainfall with consequent positive influence on national maize yield. Furthermore, ‘super El Niños’ may give rise to larger rainfall responses than normal El Niños at some sites; the magnitude varies from site to site and the effect is not obvious at some sites. The results lead to the conclusion that all El Niños are not equal in terms of their regional manifestation. All this clearly indicates the need to address critical user needs of climate information in order to produce information that is useful. Copyright © 2002 Royal Meteorological Society.
Food security is a crucial issue in sub-Saharan Africa as a consequence of unreliable rainfall, marginal soil fertility and a low level of inputs leading to declining crop yields. As a case study, we investigated the most important variables affecting maize yield in northern Ghana. We combined a soil quality index on a continuous scale with a social data set to model maize yield using linear multiple regression. Five significant variables have been identified (P < 0.05): soil quality index, fertilizer use, household size, distance from main market, and the interaction between fallow length and soil quality index. The effect of the interaction between soil quality and fallow on maize yield is negative, suggesting the influence of litter quality and N immobilization in the soils. Research and policy should focus on the development of site-specific, legume-based cropping, and the integration of crop and livestock farming in Northern Ghana and similar areas in sub-Saharan Africa.
Rainfall over West Africa shows strong interannual variability related to changes in Sea Surface Temperature (SST). Nevertheless,
this relationship seem to be non-stationary. A particular turning point is the decade of the 1970s, which witnessed a number
of changes in the climatic system, including the climate shift of the late 1970s. The first aim of this study is to explore
the change in the interannual variability of West African rainfall after this shift. The analysis indicates that the dipolar
features of the rainfall variability over this region, related to changes in the Atlantic SST, disappear after this period.
Also, the Pacific SST variability has a higher correlation with Guinean rainfall in the recent period. The results suggest
that the current relationship between the Atlantic and Pacific El Niño phenomena is the principal responsible for these changes.
A fundamental goal of climate research is the development of models simulating a realistic current climate. For this reason,
the second aim of this work is to test the performance of Atmospheric General Circulation models in simulating rainfall variability
over West Africa. The models have been run with observed SSTs for the common period 1957–1998 as part of an intercomparison
exercise. The results show that the models are able to reproduce Guinean interannual variability, which is strongly related
to SST variability in the Equatorial Atlantic. Nevertheless, problems in the simulation of the Sahelian interannual variability
appear: not all models are able to reproduce the observed negative link between rainfall over the Sahel and El Niño-like anomalies
in the Pacific, neither the positive correlation between Mediterranean SSTs and Sahelian rainfall.
KeywordsInterannual climate variability–West African Monsoon–Atmospheric general circulation models
A study was conducted to determine farmers' perceptions of soil quality and common soil management practices that influenced soil fertility within farmers' fields in Chuka and Gachoka divisions, Kenya. Soils were characterised by smallholders after which they were geo-referenced and sampled at surface depth (0–20 cm) for subsequent physical and chemical analyses, to determine differences within farmers' soil quality categories. Indicators for distinguishing productive and non-productive fields included crop yield and performance, soil colour and soil texture. There were significant differences among soil fertility categories, using parametric techniques (ANOVA) for key soil properties (p < 0.005), implying that there was a qualitative difference in the soils that were characterised as different by farmers. Fertile soils had significantly higher pH, total organic carbon, exchangeable cations and available-N. Factor analysis on 15 soil properties identified 4 main factors that explained 68% of the total variance in soil quality. The four Varimax-rotated factors were designated as contrasts that described soil quality status on farmers' fields. The first factor grouped calcium, magnesium and soil pH, while the second component comprised available nitrogen, organic carbon and total nitrogen. The third factor included plant nutrients mainly extractable phosphorus and available nitrogen, while the fourth factor comprised soil physical properties (macroaggregates, microaggregates, silt, and clay). Soil fertility and crop management practices that were investigated indicated that farmers understood and consequently utilised spatial heterogeneity and temporal variability in soil quality status within their farms as a resource to maintain or enhance agricultural productivity.
The use of the Southern Oscillation Index (Sol) for rainfall prediction and subsequent management of water for rainfed crop production in Ghana was explored. Five sites were selected to represent the major vegetation zones in Ghana, three of which were located in the south and two in the north. For most sites, the occurrence of severe drought coincided with negative SOI (SOI below zero). It was also apparent that when the SOI was very low (below - 10) for long periods all five sites experienced severe drought. Generally, recovery from drought was very slow. In terms of agricultural productivity, some two seasons's crops would be adversely affected once a drought phase commenced before rainfall became normal again.Correlation between total seasonal rainfall and the average seasonal SOI was generally low at all sites and weakened from the south (r=0.3) to the north (r= −0.09). The use of these observations in water management was limited owing to the low correlations. However, lagged relationships between the SOI in March and the rainfall onset date in the south showed a fairly high inverse correlation (r= −0.61). The onset was delayed with negative SOI in March and was brought forward with positive Sol in March. It was also shown that, for two sites in the south, rainfall at the peak crop water demand month (June) was significantly affected by the SOI in March/April SOI (P <0.05). Positive Sol in March/April resulted in above average rainfall in June and vice versa. Hence appropriate water management strategies (e.g. supplementary irrigation or drainage) could be planed ahead of time depending on the Sol in March/April.The SOI-phase system showed high promise of rainfall prediction and water management in southern Ghana. In both simultaneous and lagged situations, positive or rising pre-seasonal SOI phases correlated well with above-average rainfall and while negative or falling SOI patterns resulted in below-average rainfall (P < 0.05). The use of SOI-phase system for water management is discussed in the text.However, the application of SOI generally to sites in northern sites did not provide any clear cut results and requires some further research. Some recommendations have been made in the text.
The challenge of producing food for a rapidly increasing population in semi-arid agro-ecosystems in Southern Africa is daunting. More food necessarily means more consumptive use of so-called green water flow (vapour flow sustaining crop growth). Every increase in food production upstream in a watershed will impact on water user and using systems downstream. Intensifying agriculture has in the past often been carried out with negative side effects in terms of land and water degradation. Water legislation is increasingly incorporating the requirement to safeguard a water reserve to sustain instream ecology.To address the challenges of increasing food production, improving rural livelihoods, while safeguarding critical ecological functions, a research programme has recently been launched on “Smallholder System Innovations in Integrated Watershed Management” (SSI). The programme takes an integrated approach to agricultural water management, analysing the interactions between the adoption and participatory adaptation of water system innovations (such as water harvesting, drip irrigation, conservation farming, etc.), increased water use in agriculture and water flows to sustain ecological functions that deliver critical ecosystem services to humans. The research is carried out in the Pangani Basin in Tanzania and the Thukela Basin in South Africa. A nested scale approach is adopted, which will enable the analysis of scale interactions between water management at the farm level, and cascading hydrological impacts at watershed and basin scale.This paper describes the integrated research approach of the SSI programme, and indicates areas of potential to upgrade rainfed agriculture in water scarcity-prone agro-ecosystems while securing water for downstream use.
We estimate the potential value of general circulation model (GCM)-based seasonal precipitation forecasts for maize planting and fertilizer management decisions at two semi-arid locations (Katumani and Makindu) in Southern Kenya. Analyses combine downscaled rainfall forecasts, crop yield simulation, stochastic enterprise budgeting and identification of profit-maximizing fertilizer N rates and stand densities. October–February rainfall predictions were downscaled from a GCM, run with both observed and forecast sea surface temperature boundary conditions – representing upper and lower bounds of predictability – and stochastically disaggregated into daily crop model inputs. Simulated interactive effects of rainfall, N supply and stand density on yield and profit are consistent with literature. Perfect foreknowledge of daily weather for the growing season would be worth an estimated 15–30% of the average gross value of production and 24–69% of average gross margin, depending on location and on whether household labor is included in cost calculations. GCM predictions based on observed sea surface temperatures increased average gross margins 24% at Katumani and 9% at Makindu when labor cost was included. At the lead time used, forecasts using forecast sea surface temperatures are not skillful and showed near-zero value. Forecast value was much more sensitive to grain price than to input costs. Stochastic dominance analysis shows that farmers at any level of risk aversion would prefer the forecast-based management strategy over management optimized for climatology under the study’s assumptions, despite high probability (25% at Katumani, 34% at Makindu) of lower returns in individual years. Results contribute to knowledge of seasonal forecast value in a relatively high-risk, high-predictability context; utility and value of forecasts derived from a GCM; and risk implications of smallholder farmers responding to forecasts.