Spatial assessment of maize physical drought vulnerability in sub-Saharan Africa: Linking drought exposure with crop failure

Kamali, Bahareh; Abbaspour, Karim C.; Lehmann, Anthony; Wehrli, Bernhard; Yang, Hong

doi:10.1088/1748-9326/aacb37

Cited by 40 publications

(31 citation statements)

References 51 publications

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“…Sensitivity was the most basic link connecting drought events to agricultural production losses [23]. However, crop drought loss sensitivity has not been defined clearly and quantitatively [24]. Therefore, it is foundational to establish sensitivity curve at each crop growth stages by combining practical crop water deficit experiments with crop growth model.…”

Section: Introductionmentioning

confidence: 99%

Simulated Assessment of Summer Maize Drought Loss Sensitivity in Huaibei Plain, China

et al. 2019

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In an agricultural drought risk system, crop drought loss sensitivity evaluation is a fundamental link for quantitative agricultural drought loss risk assessment. Summer maize growth processes under various drought patterns were simulated using the Cropping System Model (CSM)-CERES-maize, which was calibrated and validated based on pit experiments conducted in the Huaibei Plain during 2016 and 2017 seasons. Then S-shaped maize drought loss sensitivity curve was built for fitting the relationship between drought hazard index intensity at a given stage and the corresponding dry matter accumulation and grain yield loss rate, respectively. Drought stress reduced summer maize evapotranspiration, dry matter, and yield accumulation, and the reductions increased with the drought intensity at each stage. Moreover, the losses caused by drought at different stages were significantly different. When maize plants were exposed to a severe water deficit at the jointing stage, the dry matter and grain yield formation were greatly affected. Therefore, maize growth was more sensitive to drought stress at the jointing stage when the stress was serious. Furthermore, when plants encountered a relatively slight drought during the seedling or jointing stage, which represented as a lower soil water deficit intensity, the grain yield loss rates approached the maximum for the sensitivity curves of these two stages. Therefore, summer maize tolerance to water deficit at the seedling and jointing stages were weak, and yield formation was more sensitive to water deficit during these two stages when the deficit was relatively slight.

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Section: Introductionmentioning

confidence: 99%

Simulated Assessment of Summer Maize Drought Loss Sensitivity in Huaibei Plain, China

et al. 2019

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“…Evaluation of watershed characteristics against drought is one of the indicators to determine the basin typology [1]. It also shows the possible water that can be provided by the watershed and drought vulnerability [2], [3],. The level of water drought the potential of the watershed is affected by several parameters: annual rainfall, annual evapotranspiration, the number of dry months for a year, geological factors and water use index as well as specific minimum water discharge.…”

Section: Introductionmentioning

confidence: 99%

“…Since the influence of climate change is the tremendous unusually dry season, thus it needs to be studied in order to anticipate the adverse impact that can occur later.One of them is a drought that will have an impact on yields and region [3], [12]. Therefore, the engineering in improving the water demand need to be done.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Drought Vulnerability on Watersheds in West Sumatera Province by Using Cropwat-8 and GIS

Daoed

Rusman

Istijono

et al. 2018

Int. J. Adv. Sci. Eng. Inf. Technol.

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Differences in temperature, duration of irradiation, wind speed, watershed shape, slope, and rainfall are the factors that determine the amount of evaporation and discharge flow also characterizing of the watershed. As noted, the difference between the maximum and minimum temperatures is over6 and the dry season happens mostly from May to October in West Sumatra Province each year. It, of course,will affect the magnitude of potential evapotranspiration and the minimum water flow that tend to decrease. Therefore, a particular evaluation of the impact of drought or susceptibility to water potential of the watersheds in the Areas of Akuaman River of West Sumatra should be undertaken. The methods used were the standard of Ministry of Forestry of Indonesiathe Agency for Research and Development of Forestry and the Center for Research and Development of Conservation and Rehabilitation 2012 and Arc-GIS-10.3 software to determine the index of vulnerability to drought and Cropwat-8to calculate evapotranspiration by Penman-Monteith method. The evaluation results show evapotranspiration value was 5.32 mm / day, 161.7 mm / month and the category of susceptibility tended to be medium and somewhat vulnerable. A review of the aspect of service levels of the use of water and minimum specific discharge is seen that in small watersheds is more susceptible to get drought than larger basins. It is therefore suggested to stakeholders to consider the possibilities for watershed integration as a solution to improve water supply for irrigation.

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“…Water deficit is a significant factor in crop production worldwide, but precipitation affects yields non-linearly, implying that good total seasonal rainfall during a crop growing period may not result in good yields (Bannayan et al, 2010;Lobell and Field, 2007). However, quantifying crop vulnerability to water stress is not defined in a standardized and spatially comparable manner (Kamali et al, 2018) and vulnerability differs from one region to another. Linking crop failure to drought in sub-Saharan Africa, Kamali et al (2018) found geographical dependency of vulnerability to climate stresses.…”

Section: Introductionmentioning

confidence: 99%

“…However, quantifying crop vulnerability to water stress is not defined in a standardized and spatially comparable manner (Kamali et al, 2018) and vulnerability differs from one region to another. Linking crop failure to drought in sub-Saharan Africa, Kamali et al (2018) found geographical dependency of vulnerability to climate stresses.…”

Section: Introductionmentioning

confidence: 99%

Towards seasonal forecasting of maize yield in eastern Africa: skill in the forecast model chain as a basis for agricultural climate services

Ogutu¹

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Climate variability is an important driver for regionally anomalous production levels of especially rainfed crops, with implication for food security of subsistence farmers and economic performance for market oriented agriculturalists. In large parts of the tropics, modern seasonal ensemble forecast systems have useful levels of skill, that open up the possibility to develop climate services that assist agriculturalist and others in the food chain (farm suppliers, commodity traders, aid organisations) to anticipate on expected anomalous conditions. In this thesis we explore the forecast skill at various steps in the modelling chain for seasonal maize yield anomalies in East Africa. First, we analyse the skill of ECMWF System-4 (S4) climate forecasts for primary meteorological variables against gridded observations and find both potential and real skill for rainfall and temperature in typical cropping seasons in eastern Africa. However, forecast skill is a function of geographical region, season, climate variable (i.e. higher skill in temperature, rainfall, downwelling shortwave radiation in that order) and forecast lead-time, as such skill assessment should not be generalized over a large geographical area. Next we analyse correlations between reported production and anomalous weather conditions, using a range of climate indicators relevant for arable farming, such as growing and killing degree days, and rainfall amount, evenness, random independent events (unevenness), and timing during consequent maize growth phases in two case study regions. In this case significant levels of correlation and skill are revealed that open up the potential for statistical forecasting by use of climate forecast derived variables. Sensitivity of yields to climate indicators depend on geographical location, for example, higher sensitivity to rainfall is found in northern Ethiopia while in a location in equatorial-western Kenya, there is higher sensitivity to temperature indicators. At the next level of complexity we explore the use of full process based crop models forced by seasonal climate forecasts to forecast anomalous water-limited maize yield in the region, and find again potentially useful levels of skill with at least two months lead before planting, in most agricultural regions. But this again depends on regions, for example yield forecasts in Tanzania, in the season starting October did not have skill. Finally, we try to attribute skill levels to physiographic characteristics (soils, maize cultivars, geographical region etc.) and address some issues of scale of aggregation for two case study regions in Kenya and Ethiopia. The results showed that skill assessment at national boundaries and high resolution crop simulation units may inform both maize production related policy decisions at regional or national levels, and also support maize production decisions at specific cropping locations such as farm management decisions made by farmers. We conclude with a synthesis discussing further on found skill levels in relation to p...

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Spatial assessment of maize physical drought vulnerability in sub-Saharan Africa: Linking drought exposure with crop failure

Cited by 40 publications

References 51 publications

Simulated Assessment of Summer Maize Drought Loss Sensitivity in Huaibei Plain, China

Simulated Assessment of Summer Maize Drought Loss Sensitivity in Huaibei Plain, China

Evaluation of Drought Vulnerability on Watersheds in West Sumatera Province by Using Cropwat-8 and GIS

Towards seasonal forecasting of maize yield in eastern Africa: skill in the forecast model chain as a basis for agricultural climate services

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