Automated estimation and analyses of meteorological drought characteristics from monthly rainfall data

The paper describes a new software package for automated estimation, display and analyses of various drought indices – continuous functions of precipitation that allow quantitative assessment of meteorological drought events to be made. The software at present allows up to five different drought indices to be estimated. They include the Decile Index (DI), the Effective Drought Index (EDI), the Standardized Precipitation Index (SPI) and deviations from the long-term mean and median value. Each index can be estimated from point and spatially averaged rainfall data and a number of options are provided for months' selection and the type of the analysis, including a running mean, single value or multiple annual values. The software also allows spell/run analysis to be performed and maps of a specific index to be constructed. The software forms part of the comprehensive computer package, developed earlier and designed to perform the multitude of water resources analyses and hydro-meteorological data processing. The 7-step procedure of setting up and running a typical drought assessment application is described in detail. The examples of applications are given primarily in the specific context of South Asia where the software has been used

Meteorological and hydrological drought hazard, frequency and propagation analysis : a case study in southeast Australia

Study region: Southeast Australia.Study focus: We investigated meteorological and hydrological drought characteristics using Standardized Precipitation Index (SPI), Standardized Streamflow Index (SSFI) and Effective Drought Index (EDI). Drought Hazard Index (DHI) was derived based on the probability of drought occurrence and Thiessen polygons using SPI/EDI, whereas Drought Frequency Index (DFI) was derived based on number of drought events, and data length using SPI, EDI, and SSFI. The modified Mann-Kendall test was applied to detect trends in streamflow data and hydrological droughts. Furthermore, correlation between meteorological and hydrological drought indices for different timesteps was assessed through Pearson's and Spearman's rank correlation analysis. Finally, the drought propagation time (DPT) from meteorological to hydrological drought was estimated by 'theory of run.'New hydrological insights for the region: Our major findings include: (i) The spatial coverage of DHI and DFI, based on SPI/EDI, illustrate that mainly south and coastal regions of the study area are the most 'drought-prone' (ii) A considerable proportion of streamflow stations shows a significant trend of decrease in annual streamflow, with the most dominant year of abrupt change is 1996; (iii) Hydrological droughts are increasing in the study area; (iv) Performance of EDI with SSFI is found to be better than SPI at 3-month timestep; and (v) DPT can be found using 'theory of run' however, defined DPT cannot be directly applied to other regions

An Assessment of the Relationship between Air Mass Frequency and Extreme Drought in the Midwest United States

The Midwest of the United States is a region extensively utilized for agriculture and livestock production despite great susceptibility to widespread and persistent drought. While the location and duration of droughts are related to dynamic meteorological factors, pinpointing when and where a drought will commence, how long it will persist, and when the drought will end, remains a challenge. This investigation examines significant Midwest drought events from a synoptic meteorological perspective through an assessment of air mass frequency over the past decade. A synoptic approach is useful since air masses characteristically describe multiple weather and climate parameters at the same time across wide areas. The daily air mass conditions in the Spatial Synoptic Classification that are dominant during extreme droughts are examined across the region and compared to “normal” periods without substantial or extensive drought. Extreme episodes are established with new criteria expanded from United States Drought Monitor information, normal average decadal and seasonal baselines are calculated, and the air mass frequency departures from these periods are examined for statistical and practical significance. Results indicate that the Dry Polar, Dry Tropical and Moist Tropical air masses exhibit important and statistically significant changes in frequency during drought. Tendencies for substantial increases in warm and dry types, regardless of season, and moist air mass declines are detected. The exact air masses with significant changes are unique for different sub-regions, particularly in the northwest and south. These patterns are consistent with changing upper-air flows such as southerly, meridional flow to more southwesterly, zonal flow

Drought and drought mitigation in Yobe State, Nigeria

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy (PhD).Drought is regarded as a natural phenomenon and its impacts accumulate slowly over a long period. It is considered to be insufficient precipitation that leads to water scarcity, as triggered by meteorological parameters, such as temperature, precipitation and humidity. However, drought mitigation has mostly been reactive, but this has been challenged by extreme events globally. Many countries and regions around the world have made efforts in mitigating drought impacts, including Nigeria. This research produced frameworks for drought amelioration and management as a planning tool for Yobe State, Nigeria. Mixed methods were employed to investigate the effects of drought; 1,040 questionnaires were administered to farmers in three regions of Yobe State (South, North and East). Some 721 were returned, representing a 69.3% return rate. Drought is pronounced in the State and has been recent over the years; it has also affected many people, with losses of ~70-80% of their harvests and livestock. Drought coping strategies have also caused environmental degradation in Yobe State. Farmers over-harvest their farms, practise deforestation and over-exploit wild animals. Several efforts to mitigate the impacts of drought by the Nigerian Government have failed, thus this research adopts a bottom-top approach to mitigate drought impacts in Yobe State. Focus Group Discussions (FGD) were also conducted at government and community levels to gather farmers’ and government officials’ opinions on their drought experience and suggestions for mitigation measures. Farmers believed that rainfall is their main problem and officials pointed that there are no proper drought mitigation plans in Yobe State. Four validated drought mitigation and management frameworks were developed for Yobe State. The frameworks were evaluated pre-use through respondent validation. State officials and farmers believed that these frameworks will reduce the impacts of drought in Yobe State. The frameworks include social, economic, environmental impact mitigation and an Integrated Drought Mitigation and Management Framework. The proposed frameworks were designed and have advocates a paradigm shift, using both proactive and reactive measures. A new drought definition was proposed based on the findings of the study. The definition states that drought is the shortage of rainfall or water that affects people’s livelihood and the environment both directly and indirectly

Ajuste del índice de precipitación estandarizado (SPI), bajo condiciones de precipitación mensual cero

La evaluación de la magnitud de la sequía es fundamental para la prevención de las problemáticas climatológicas, uno de los métodos más utilizados debido a su practicidad en la utilización de variables como la precipitación es el Índice De Precipitación Estandarizado (SPI). Al evaluar el SPI bajo condiciones de precipitación cero (0 mm) en más de la mitad de los datos, se encontró que se producen desviaciones en las magnitudes del índice, obteniendo magnitudes de humedad en lugar de sequía, según la tabla de clasificación del SPI propuesta por McKee et al., 1993. Esta investigación tiene como objeto la construcción de un nuevo modelo de SPI, el cual ajusta las magnitudes al calcular el índice bajo condiciones de escasa precipitación, mejorando así, la identificación de la sequía al utilizar el SPI. Para esto se caracterizaron las zonas en Colombia que presentan precipitación mensual cero en más de la mitad de los datos, utilizando la cuenca del Arroyo Pechelín como zona de evaluación para el cálculo del índice y la presentación del ajuste, denominado SPI-C. Se estableció un ajuste por medio de la tipificación del SPI, corrigiendo los valores de humedad presentes en los meses de escasa precipitación. Posteriormente, se realizó la evaluación del SPI-C en Colombia, el cual ajustó las magnitudes del SPI en algunos municipios de la región caribe. Finalmente, esta investigación demostró que el SPI-C mejora la identificación de la sequía en zonas que cuenten con precipitación cero en más de la mitad de los datos disponibles.DoctoradoDoctor en Ingeniería Civi

Deployment, Maintenance And Further Development Of Spatsim-HDSF Volume

The National Water Act (NWA, 1998) of South Africa (Act 36 of 1998) aims to ensure that South Africa’s water resources are managed and used in an equitable and sus-tainable manner for the benefit of all. The National Water Act (NWA) requires a dif-ferent approach to managing the nation’s water resources and the concept of inte-grated water resources management (IWRM) is central to this approach (Pollard and Du Toit, 2008). IWRM requires water managers to consider hydrological, ecological, economic, political, social and institutional aspects of water resources. To imple-ment IWRM, water managers require integrated modelling tools to provide infor-mation that can assist in making managements decisions. There are two aspects of integrated modelling that have received increasing attention in recent years: (i) the coupling of models representing different water resource domains, and (ii) the de-velopment of integrated modelling frameworks or decision support systems. These integrated modelling frameworks typically include a common data repository, common data editing tools, common spatial and temporal data visualisation and analysis tools, and a collection of framework compatible models that make use of these common tools

ITIKI: Bridge between African indigenous knowledge and modern science on drought prediction

The now more rampant and severe droughts have become synonymous with Sub-Saharan Africa; they are a major contributor to the acute food insecurity in the Region. Though this scenario may be replicated in other regions in the globe, the uniqueness of the problem in Sub-Saharan Africa is to be found in the ineffectiveness of the drought monitoring and predicting tools in use in these countries. Here, resource-challenged National Meteorological Services are tasked with drought monitoring responsibility. The main form of forecasts is the Seasonal Climate Forecasts whose utilisation by small-scale farmers is below par; they instead consult their Indigenous Knowledge Forecasts. This is partly because the earlier are too supply-driven, too ""coarse"" to have meaning at the local level and their dissemination channels are ineffective. Indigenous Knowledge Forecasts are under serious threat from events such as climate variations and ""modernisation""; blending it with the scientific forecasts can mitigate some of this. Conversely, incorporating Indigenous Knowledge Forecasts into the Seasonal Climate Forecasts will improve its relevance (cultural and local) and acceptability, hence boosting its utilisation among small-scale farmers. The advantages of such a mutual symbiosis relationship between these two forecasting systems can be accelerated using ICTs. This is the thrust of this research: a novel drought-monitoring and predicting solution that is designed to work within the unique context of small-scale farmers in Sub-Saharan Africa. The research started off by designing a novel integration framework that creates the much-needed bridge (itiki) between Indigenous Knowledge Forecasts and Seasonal Climate Forecasts. The Framework was then converted into a sustainable, relevant and acceptable Drought Early Warning System prototype that uses mobile phones as input/output devices and wireless sensor-based weather meters to complement the weather stations. This was then deployed in Mbeere and Bunyore regions in Kenya. The complexity of the resulting system was enormous and to ensure that these myriad parts worked together, artificial intelligence technologies were employed: artificial neural networks to develop forecast models with accuracies of 70% to 98% for lead-times of 1 day to 4 years; fuzzy logic to store and manipulate the holistic indigenous knowledge; and intelligent agents for linking the prototype modules