Analysis of Rainfall Variability and Farmers’ Perception towards it in Agrarian Community of Southern Ethiopia

Rainfall variability has historically been a major cause of food insecurity and famines in Ethiopia. Obtaining scientific evidence regarding the annual and seasonal rainfall variability through statistical rainfall analysis and farmers’ perceptions about rainfall variability in the region provides a credible information to decision makers and end users. The present study focuses on five selected agriculture dominant areas (Hadiya, Alaba, Kambate Tambaro, Gurage and Silte zones) of the Southern Ethiopia. Seasonal and annual rainfall data extending from 1983-2012 has been analyzed using two rainfall indices (Precipitation concentration Index (PCI), Rainfall Anomaly Index (AI)) and Mann-Kendall trend test method. A total of 80 household respondents are accounted to assess rainfall variability with respect to farmers’ perspective. The years of occurrence of the maximum and minimum AI values in any particular season are not uniform for all the stations during the analysis window which is characteristic feature of high rainfall variability. The frequency of the minimum AI values is more in Kiremt and Belg season, whereas, maximum AI values are more palpable in Bega  The annual PCI for all the stations is highly variable which entails year to year non-uniform rainfall concentration over the stations. The PCI variability is more pronounced during the Bega season. Annual rainfall series at Alaba, Angacha, Fonko, Hossana and Wulberag stations show an increasing trend over the study period, however, for all other seven station there is no statistically significant trend observed. In view of farmers’ perception towards rainfall variability, on average 80 % of the respondents opined that there were rainfall variability in magnitude and frequency, while 11 % perceived as no change in rainfall pattern and 4 % responded that they do not know  whether it exists or not over the past 20 years. Majority of the respondents (80%) agree that the rainfall variability is due to combined effect of natural and man-induced impacts. Keywords: Rainfall variability, concentration index, anomaly index, Farmers’ Perception, Trend analysis

Impacts of land use and land cover change on surface runoff, discharge and low flows: evidence from East Africa

Region: East Africa. Focus: A review of catchment studies (n=37) conducted in East Africa evaluating the impacts of Land Use and Land Cover Changes (LULCC) on discharge, surface runoff, and low flows. New hydrological insights: Forest cover loss is accompanied by increased stream discharges and surface runoff. No significant difference in stream discharge is observed between bamboo and pine plantation catchments, and between cultivated and tea plantation catchments. Trend analyses show that despite forest cover loss, 63% of the watersheds show non-significant changes in annual discharges while 31% show increasing trends. Half of the watersheds show non-significant trends in wet season flows and low flows while 35% reveal decreasing trends in low flows. Modeling studies estimate that forest cover loss increases annual discharges and surface runoff by 16 ± 5.5% and 45 ± 14%, respectively. Peak flows increased by a mean of 10 ± 2.8% while low flows decreased by a mean of 7 ± 5.3%. Increased forest cover decreases annual discharges and surface runoff by 13 ± 1.9% and 25 ± 5%, respectively. Weak correlations between forest cover and runoff (r=0.42, p < 0.05), mean discharge (r=0.63, p < 0.05) and peak discharge (r=0.67, p < 0.05) indicate that forest cover alone is not an accurate predictor of hydrological fluxes in East African catchments. The variability in these results supports the need for long-term field monitoring to better understand catchment responses and to improve the calibration of currently used simulation models

Loss and damage from flooding in the Gambela region, Ethiopia

In this article, we explore the ways in which people in the Ethiopian Gambela region dealt with the extreme flood that occurred in 2007, with specific attention to the associated loss and damage, i.e., the impacts that people were not able to avoid through preventive and coping measures. We found that all of the 431 surveyed households took preventive measures such as the construction of boundary walls, harvesting premature crops and digging drainage ditches to divert the flood away from croplands. However, these could not prevent widespread negative effects such as damage to houses and crops, the outbreak of diseases, and loss of livestock. To deal with the adverse effects, 50% of the respondents relied on the help of relatives, neighbours or friends for food and money. Such assistance appeared crucial. People were, however, worried about over-using their social networks, especially with floods occurring more regularly. Widening people's agricultural and non-agricultural options, for example through investments in micro-finance services and irrigation systems, will help to increase their coping capacity

Characterisation of hydroclimatological trends and variability in the Lake Naivasha basin, Kenya

Recent hydro-climatological trends and variability characteristics were investigated for the Lake Naivasha basin with the aim of understanding the changes in water balance components and their evolution over the past 50¿years. Using a Bayesian change point analysis and modified Mann–Kendall tests, time series of annual mean, maximum, minimum, and seasonal precipitation and flow, as well as annual mean lake volumes, were analysed for the period 1960–2010 to uncover possible abrupt shifts and gradual trends. Double cumulative curve analysis was used to investigate the changes in hydrological response attributable to either human influence or climatic variability. The results indicate a significant decline in lake volumes at a mean rate of 9.35¿×¿106¿m3¿year-1. Most of the river gauging stations showed no evidence of trends in the annual mean and maximum flows as well as seasonal flows. Annual minimum flows, however, showed abrupt shifts and significant (upward/downward) trends at the main outlet stations. Precipitation in the basin showed no evidence of abrupt shifts, but a few stations showed gradual decline. The observed changes in precipitation could not explain the decline in both minimum flows and lake volumes. The findings show no evidence of any impact of climate change for the Lake Naivasha basin over the past 50¿years. This implies that other factors, such as changes in land cover and infrastructure development, have been responsible for the observed changes in streamflow and lake volumes