Vulnerability of crop production to heavy precipitation in north-eastern Ghana

Abstract

Purpose -The purpose of this paper is to analyze vulnerability of food crop production to heavy precipitation in north-eastern Ghana, specifically, the upper east region (UER) and the policy implications for adaptation. Heavy precipitation events are a common part of climatic variability; but little attention is given to its impact on livelihoods as compared to droughts in research and policy domains. Design/methodology/approach -This paper draws on both quantitative and qualitative research methods and data. Rainfall data are analyzed using the Standardized Precipitation Index (SPI). This is compared with quantitative analysis of crop yields and complemented by narratives of farmers from in-depth interviews and focus group discussions. Findings -The results show that heavy precipitation events often lead to low food crop productivity and this suggests that the latter is vulnerable to the former. Originality/value -Although some adaptation is occurring through a wide range of local measures, these are inadequate for eliminating vulnerability. Thus, additional policy measures are recommended for enhancing farmer adaptation, including: incorporating climate change adaptation policies, including adaptation to heavy precipitation into District Development Planning; building human resource capacity for effective implementation of climate change adaptation policies at district levels; improving market access to seed through improved market infrastructure and rural transportation; establishing Community Seed Banks (CSBs) as back up sources of seed; promoting "nursing and transplant" as an alternative planting method for millet and guinea corn; promoting low costs solar drying technologies for drying food crops; and supporting livelihood diversification through credit and business development services.

A high-resolution unified observational data product of mesoscale convective systems and isolated deep convection in the United States for 2004–2017

“…In the atmosphere, deep convection refers to thermally driven turbulent mixing that displaces air parcels from the lower atmosphere to the troposphere above 500 hPa (Davison, 1999), leading to the development of convective storms. The heavy rain rates associated with deep convection can significantly affect the water cycle (Hu et al, 2020) and other aspects such as soil erosion (Nearing et al, 2004), surface water quality Motew et al, 2018), and managed and unmanaged ecosystems (Angel et al, 2005;Derbile and Kasei, 2012;Rosenzweig et al, 2002) that are essential elements of the biogeochemical cycle. By redistribut-ing heat, mass, and momentum within the atmosphere, deep convection also has important effects on atmospheric chemistry (Anderson et al, 2017;Andreae et al, 2001;Choi et al, 2014;Grewe, 2007;Thompson et al, 1997;Twohy et al, 2002), large-scale environments (Houze Jr, 2004;Piani et al, 2000;Stensrud, 1996Stensrud, , 2013Wang, 2003), and radiation balance (Feng et al, 2011;Zhang et al, 2017).…”

Regional Frequency Analysis of Precipitation Extremes and Its Spatio-Temporal Patterns in the Hanjiang River Basin, China

“…The average intensity and extreme precipitation values tend to increase, so does the extreme precipitation occurrence [5]. Heavy precipitation events present a challenge to public safety, life, and lead to huge economic loss and low food crop productivity [6]. Additionally, precipitation is a key component of the hydrological cycle and a primary input for hydrometeorological models [7].…”

A Probabilistic Model for Maximum Rainfall Frequency Analysis

“…The least of the maximum distances between values of the theoretical and empirical cumulative probability distributions, particularly in the tail part, was situated decidedly below the critical value of the DA−D test defined at a significance level of α = 0.05, which signifies rejection of the hypothesis of the goodness of fit of the theoretical and empirical distributions. The results obtained from the PMAXTP model for the values of maximum precipitation with a specified probability of exceedance were compared with the results from the Bogdanowicz-Stachý model [1,2]. In the latter model, the procedure for computing the values of maximum precipitation with a specified probability of exceedance p consisted of:…”

“…A frequency analysis of values of maximum precipitation of a specified duration and probability of exceedance is an essential part of engineering [1]. Given the significant impact of maximum precipitation on various spheres of human activity (e.g., the economy, agriculture, industry, and the environment), such an analysis is widely applied, particularly in the context of observed climate change [2,3].…”