Spatial Multi-Criterion Decision Making (SMDM) Drought Assessment and Sustainability over East Africa from 1982 to 2015

Abstract

Droughts are ranked among the most devastating agricultural disasters that occur naturally in the world. East Africa is the most vulnerable and drought-prone region worldwide. In this study, four drought indices were used as input variables for drought assessment from 1982 to 2015. This work applied the SMDM algorithm to the integrated approach of OLR and Hurst exponent. The Detrended Fluctuation Analysis (DFA) and Ordinary Least Square (OLR) were merged to compute the trend and persistence (Hurst exponent) of the drought indices. Result indicates that the OLR at time scale 1, 6, and 12 shows a similar distribution with positive (negative) trends scattered in the Northwest (Northeast and Southern) parts of the study area which differs with the OLR aggregated at a 3-month time scale. The percentage pixel distribution for OLR-1, OLR-3, OLR-6, and OLR-12 is 18.2 (81.8), 72.5 (27.5), 32.9 (67.1), and 36.9 (63.1) for increasing (decreasing) trends respectively. Additionally, results indicate that DFA-1 is highly persistent with few random pixels scattered around Ethiopia, South Sudan and Tanzania, with percentage pixels as 88.7, 11.3 and 0.1 representing h > 0.5, h = 0.5, and h < 0.5, respectively. DFA-6 shows high (low) pixels representing h > 0.5 (h > 1), respectively. Meanwhile, for DFA-3 and DFA-12, the distribution shows persistence and a random walk, respectively. Drought conditions may eventually persist, reverse or vary drastically in an unpredictable manner depending on the driving forces. Overall, the drought risk map at 1-, 3-, and 6-month aggregates has shown severe degradation in Southern Kenya and Tanzania while noticeable improvements are seen in western Ethiopia and South Sudan.

Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects

“…The findings confirmed that drought fluctuations over Eastern Africa regions maintain the "dryness becoming more drier, wetness becoming more wetter" model. Kalisa et al [92] applied the Spatial Multi-Criterion Decision Making (SMDM) algorithm to an integrated approach of Ordinary Least Square (OLR) and the Hurst exponent to drought assessment over East Africa at various time scales from 1982 to 2015. Their report combined four drought indicators to create a spatial drought risk mapping; SPEI, SPI, Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) were among the indicators.…”

Assessment of Two Drought Indices to Quantify and Characterize Drought Incidents: A Case Study of the Northern Part of Burundi

“…Drought harms humanity directly or unintentionally through food insecurity, conflicts among individuals or communities, economic losses, and diseases [2,3]. Since drought can develop gradually and softly [4,5], it can be difficult to identify its exact onset and end, unlike many natural disasters that hit the region and have immediate and noticeable consequences, such as floods, landslides, earthquakes, and windstorms. It is indispensable to capture the onset of drought within a week for better extension forecasts that describe changes in drought situations over a sub-seasonal timescale [6] because duration and severity are the characteristics of drought that significantly influence adaptability and preparation for drought [7].…”

Vegetation dynamic patterns of arid rangelands : a multifractal approach

“…Different studies have been conducted to predict vegetation dynamics (Miao et al, 2015;Tong et al, 2018), while others have developed tools to evaluate current management practices (Igbawua et al, 2019;Kalisa et al, 2021;Wang et al, 2020;Zhou et al, 2020). The NDVI values were then checked for quality.…”

“…The vegetation and meteorological time series have been demonstrated to have fractal properties as part of this complexity. The mathematical properties of their fractal nature can be used for research and management, as has been suggested byIgbawua et al (2019) andKalisa et al (2021).The main goal of this thesis is to further understand the relationships among different variables (vegetation indices, temperature, precipitation and water soil content index) in arid rangelands as a complex agricultural dynamical system, and the fractal nature of vegetation indices time series.The main goal was divided into four main questions as written below:1. Which is the temporal response of NDVI to temperature and precipitation in arid areas and how does it change through the year?…”