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Mushore Terence Manatsa Desmond Pedzisai Ezra Muzenda-Mudavanhu Chipo Mushore Washington Kudzotsa Innocent 《Theoretical and Applied Climatology》2017,129(3-4):1167-1173
The study focuses on the impacts of climate variability and change on maize yield in Mt. Darwin District. The rainfall and temperature data for the period under study that is from 1992 to 2012 were obtained from Meteorological Services Department of Zimbabwe at daily resolution while crop yield data were obtained from Department of Agricultural, Technical and Extension Services (AGRITEX) and Zimbabwe Statistics Agency (ZIMSTAT) at seasonal/yearly resolution. In order to capture full rainfall seasons, a year was set to begin on 1 June and end on 31 July the next year. Yearly yield, temperature and rainfall data were used to compute time series analysis of rainfall, temperature and yield. The relationship between temperature, rainfall, quality of season (start, cessation, dry days, wet days and length) and yield was also investigated. The study also investigated the link between meteorological normal and maize yield. The study revealed that temperature is rising while rainfall is decreasing with time hence increasing risk of low maize yield in Mt. Darwin. Correlation between maize yield was higher using a non-linear (R 2 = 0.630) than a linear regression model (R 2 = 0.173). There was a very high correlation between maize yield and number of dry days (R = −0.905) as well as between maize yield and length of season (R = 0.777). We also observed a strong correlation between percentage normal rainfall and percentage normal maize yield (R 2 = 0.753). This was also agreed between rainfall tessiles and maize yield tessiles as 50 % of the seasons had normal and above normal rainfall coinciding with normal and above normal maize yield. Of the 21 seasons considered, only one season had above normal rainfall while maize yield was below normal. The study concluded that there is a strong association between meteorological normal and maize yield in a rain-fed agricultural system. Climate information remains crucial to agricultural productivity hence the need to train farmers to access the information and use it for the benefit of their activities.
相似文献2.
The assessment of the policy framework governing Invasive Alien Species (IAS) control is of critical importance in conservation. The undertaking of a SWOT analysis of such a framework is necessary because it enhances the efficacy of IAS control. The aim of this study is to carry out a SWOT analysis of the policy framework guiding the control of the spreading of Acacia mearnsii and other IAS in the Golden Gate Highlands National Park in South Africa, as well as the implementation of restorative measures in the park and adjacent communities in line with the recommendations of the Convention on Biodiversity. A comparative analysis of this framework and the hierarchical framework that was developed during the European Union Conference on Freshwater Invasives - Networking for Strategy in 2013 is undertaken. The results indicate the need to strengthen park-community relations, upgrade existing legislation, and boost the technical capacity of South African national parks to identify, detect, monitor and predict IAS invasions, both within the parks and their surroundings. This knowledge is important for developing future policies on IAS control in South Africa. 相似文献
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Desmond Manatsa Leonard Unganai Christopher Gadzirai Swadhin K. Behera 《Natural Hazards》2012,64(2):1187-1207
Farmers?? adaptation to climate change over southern Africa may become an elusive concept if adequate attention is not rendered to the most important adaptive tool, the regional seasonal forecasting system. Uptake of the convectional seasonal rainfall forecasts issued through the southern African regional climate outlook forum process in Zimbabwe is very low, most probably due to an inherent poor forecast skill and inadequate lead time. Zimbabwe??s recurrent droughts are never in forecast, and the bias towards near normal conditions is almost perpetual. Consequently, the forecasts are poorly valued by the farmers as benefits accrued from these forecasts are minimal. The dissemination process is also very complicated, resulting in the late and distorted reception. The probabilistic nature of the forecast renders it difficult to interpret by the farmers, hence the need to review the whole system. An innovative approach to a regional seasonal forecasting system developed through a participatory process so as to offer a practically possible remedial option is described in this paper. The main added advantage over the convectional forecast is that the new forecast system carries with it, predominantly binary forecast information desperately needed by local farmers??whether a drought will occur in a given season. Hence, the tailored forecast is easier for farmers to understand and act on compared to the conventional method of using tercile probabilities. It does not only provide a better forecasting skill, but gives additional indications of the intra-seasonal distribution of the rainfall including onsets, cessations, wet spell and dry spell locations for specific terciles. The lead time is more than 3?months, which is adequate for the farmers to prepare their land well before the onset of the rains. Its simplicity renders it relatively easy to use, with model inputs only requiring the states of El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) climate modes. The developed forecast system could be one way to enhance management of risks and opportunities in rain-fed agriculture among small-holder farmers not only in Zimbabwe but also throughout the SADC region where the impact of ENSO and/or IOD on a desired station rainfall is significant. 相似文献
4.
Maize yield forecasting for Zimbabwe farming sectors using satellite rainfall estimates 总被引：1，自引：1，他引：0
Manatsa Desmond Nyakudya Innocent W. Mukwada Geoffry Matsikwa Herbet 《Natural Hazards》2011,59(1):447-463
Southern Africa rainfall station network is suffering from an unfortunate serious decline while climate-related food insecurity
is worsening. In the current work, we demonstrate the possibility of exploiting the complementary roles that remote sensing,
modeling, and geospatial data analysis can play in forecasting maize yield using data for the growing seasons from 1996/1997
to 2003/2004. Satellite-derived point-specific rainfall estimates were input into a crop water balance model to calculate
the Water Requirement Satisfaction Index (WRSI). When these WRSI values were regressed with historical yield data, the results
showed that relatively high skill yield forecasts can be made even when the crops are at their early stages of growth and
in areas with sparse or without any ground rainfall measurements. Inferences about the yield at national level and small-scale
commercial farming sector (SSCF) sector can be made at confidence levels above 99% from the second dekad of February. However,
the most unstable models are those for the communal farming sectors whose inferences for yield forecast can only be made above
the 95% confidence level from the end of February, after having recovered from a state of complete breakdown two dekads earlier.
The large-scale commercial farming (LSCF) sector has generally the weakest fitting, but it is usable from the first dekad
of February to the end of the rainy season. Validation of the national yield models using independent data set shows that
an early estimation of maize yield is quite feasible by the use of the WRSI. 相似文献
5.
Desmond Manatsa Yushi Morioka Swadhin K. Behera Caxston H. Matarira Toshio Yamagata 《Climate Dynamics》2014,42(5-6):1259-1274
The interannual variability of East African ‘short rains’ (EASR) and its link with the Mascarene High (MH) variation are explored, using observations and reanalysis data. Correlation and composite analyses for flood and drought events reveal that the EASR variability is strongly linked to the MH zonal displacement, in particular, the zonal movement of the MH eastern ridge. When the MH eastern ridge is anomalously displaced to the west (east) of its normal position, the south east (SE) trade winds over the South Indian Ocean (SIO) anomalously strengthen (weaken). This enhances (reduces) the relatively cool and dry SE trade winds and induces cold (warm) sea surface temperature anomaly in the SIO. As a result, convection over the western equatorial SIO is suppressed (enhanced) and leads to rainfall deficits (excess) over East Africa. Droughts in East Africa are associated with a westward migration of the MH eastern ridge, while the relationship is less clear for flood events and their link to an eastward migration of the MH. Therefore, the zonal migration of the MH eastern ridge provides a novel indicator for the EASR extremes especially droughts. This revelation has immense social application for rainfall forecast over East Africa where rainfall deficits have become more prevalent against the background of deteriorating conventional forecasts for EASR droughts. 相似文献
6.
D. Manatsa W. Chingombe H. Matsikwa C. H. Matarira 《Theoretical and Applied Climatology》2008,92(1-2):1-14
Summary The dominant climatic mode responsible for seasonal rainfall variability across central southern Africa has been well-established
as ENSO. Hence, the El Ni?o signal of the equatorial Pacific has been used extensively to predict droughts in this sub-region.
Although this paper acknowledges that El Ni?o influences rainfall deficits over eastern southern Africa, an earlier signal
of extreme positive sea level pressure (SLP) anomalies at Darwin for the averaged March to June period (MAMJ Darwin) has proved
to have a superior remote connection to droughts in the sub-region. Simple linear statistical tools including composite techniques
and correlation methods have been employed on century long data sets (1901–2000) to identify the emerging paramount connection
between MAMJ Darwin SLP anomalies and southern African rainfall.
Both MAMJ Darwin SLP anomalies and the Zimbabwe seasonal rainfall time series are significantly correlated (above the 95%
significant level) with sea surface temperature anomalies. These represent the Indian Ocean Dipole mode in the tropical Indian
Ocean and ENSO in the tropical Pacific for the averaged September to December period. ‘Pure’ MAMJ Darwin (that occur in the
absence of El Ni?o in the Pacific) coincide with droughts more significantly (83% hit rate) than ‘pure’ El Ni?o events (not
preceded by a high MAMJ Darwin) (38% hit rate). Co-occurrences (MAMJ Darwin preceded by El Ni?o) do not only have the highest
hit rate of 93% but subsequent droughts are noticeably more severe. The ‘pure’ El Ni?os however, are not only poorly related
to Zimbabwe seasonal rainfall deficits, but are apparently not connected to extreme droughts of the 20th century. Thus, MAMJ Darwin is a good simple predictor of droughts associated with or without ENSO in the Pacific. The high
prediction skill of these results, especially the inherent longer lead-time than ENSO, makes MAMJ Darwin SLP anomalies an
ideal additional input candidate for sub-regional drought monitoring and forecasting schemes. In this way, drought early warning
and disaster preparedness activities can be enhanced over the sub-region.
Authors’ addresses: D. Manatsa, W. Chingombe, H. Matsikwa, Faculty of Science, Bindura University of Science Education, P.
Bag 1020, Bindura, Zimbabwe; C. H. Matarira, Department of Geography and Environmental Science, National University of Lesotho,
Roma 180, Lesotho. 相似文献
7.
Desmond Manatsa Barnabas Chipindu Swadhin K. Behera 《Theoretical and Applied Climatology》2012,110(1-2):115-128
The decadal shift in the relationship between the Indian Ocean Dipole (IOD) and the East African rainfall is investigated using historical observational data. The climate system for equatorial East Africa (EEA) during the October to December (OND) ‘short rains’ season is characterised by spatiotemporal variations of the equatorial East African rainfall (EEAR). Therefore, the EEAR index is derived from the first principal component of the empirical orthogonal function analysis (EOF) of the EEA’s rainfall domain. The IOD, which has been linked with the EEAR in the previous studies, is the main climate mode controlling the tropical Indian Ocean during the OND period. It is usually represented by a dipole mode index based on the zonal gradient of SST anomalies in the tropical Indian Ocean. Therefore the climate modes, IOD and EEAR, are assumed to form a two-node network of subsystems which primarily control the climate of equatorial East Africa during the OND period. The collective behaviour of these climate modes is investigated through the examination of their representative indices for the period 1901 to 2009 using simple statistical techniques. The results suggest that the interaction between these two climate modes, which comprise the network, is not predominantly linear as previously assumed, but is characterised by shifts which are determined by the coupling and synchronisation processes of the tropical systems. In cases where synchronisation is preceded by an abrupt increase in coupling strength between the two subsystems, the established synchronous state is destroyed and a new climate state emerges such as in the years 1961 and 1997. This alteration in the regional climate is accompanied by notable changes in the regional rainfall and IOD variations. But in those events where synchronisation is followed by a sudden loss in coupling strength, the climate state is not disturbed and no shift in the climate of equatorial East Africa is noticed as in 1918. This climate shift mechanism appears to be consistent with the theory of synchronised chaos and is useful for long range predictions of the East African short rains. 相似文献
8.
Analysis of multidimensional aspects of agricultural droughts in Zimbabwe using the Standardized Precipitation Index (SPI) 总被引：2，自引：0，他引：2
Desmond Manatsa Geoffrey Mukwada Emmanuel Siziba Tafadzwa Chinyanganya 《Theoretical and Applied Climatology》2010,102(3-4):287-305
This study focuses on a framework of methodologies used for analyzing the frequency and spatiotemporal characteristics of agricultural droughts in Zimbabwe from a vulnerability context. By employing an empirical orthogonal analysis method, the study revealed that relatively strong spatial and temporal station drought relationships prevail, making the drought spatiotemporal characteristics of the country to be considered highly homogeneous. Thus, agricultural droughts were characterized temporarily using the Standardized Precipitation Index derived from rainfall data for the longer but sparse data period from 1901 to 2004. At the same time, higher spatial density analysis was achieved from shorter but denser database for the period 1941 to 1999. The results indicated that drought is a natural climatic feature of the region and occurs from time to time in defined periods. However, severe and extreme droughts tend to concentrate near the end of the time series, suggesting that during the earlier period of the twentieth century, droughts have been smaller or less pervasive. The extreme droughts appear to inherit the coincidence of both very high values of spatial extent and intensity in a single event. This offers a possible explanation to why extreme droughts in Zimbabwe usually have dire consequences on agriculture and the national economy. By showing that the related national drought impacts on staple maize food production can be estimated, this study has demonstrated that it is possible to anticipate future drought hazard impacts and predict periods of food insecurity. As far as the forecasting of agricultural droughts is concerned, the recently discovered Indian Ocean dipole/zonal mode seems to perform better than the traditional El Niño–Southern Oscillation as a potential drought predictor during the twentieth century. 相似文献
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