Rainfall distribution and trends of the daily precipitation concentration index in northern Morocco: a need for an adaptive environmental policy

A national priority at the Moroccan level is to understand the spatiotemporal rainfall irregularity to anticipate suitable strategies for water and agriculture management. The most northern mountainous region shows intense sensitivity to extreme hydroclimatic hazards which may compromise the future of socioeconomic acceleration and further weaken environmental balances. However, planning and decision making require accurate data, on a detailed scale and with good spatial distribution which is not the case in several south-Mediterranean countries where rainfall data and/or well- established hydro-meteorological network is lacking. In this paper, abundant rain gauge measurements combined with time-series open data (1958-2015) were used to study the rainfall variability. Results show an annual rainfall increase trend since 1996 with frequent, intense and abundant rains causing violent torrents and floods. This humid trend alter- nates with short but severe dry periods. Spatial distribution shows a rainfall increase from eastern to western area and from the coastal plains to high mountains. Based on a continuous daily rainfall dataset (from 1988 to 2012) from six scat- tered stations, it appears that the pattern of heavy and extreme wet days takes the form of an irregular interannual cycle. Trends of the annual precipitation daily concentration indicate a significant positive trend in the center than in the East of the study area. Considering these observations, a review of water needs/obligations priorities seems crucial so that a new conscious and adaptative environmental policy would approve new procedures for a sustainable management

A New Soil Moisture Agricultural Drought Index (SMADI) Integrating MODIS and SMOS Products: A Case of Study over the Iberian Peninsula

25 pages, 9 figures, 4 tablesA new index for agricultural drought monitoring is presented based on the integration of different soil/vegetation remote sensing observations. The synergistic fusion of the surface soil moisture (SSM) from the Soil Moisture and Ocean Salinity (SMOS) mission, with the Moderate Resolution Imaging Spectroradiometer (MODIS) derived land surface temperature (LST), and water/vegetation indices for agricultural drought monitoring was tested. The rationale of the approach is based on the inverse relationship between LST, vegetation condition and soil moisture content. Thus, the proposed Soil Moisture Agricultural Drought Index (SMADI) combines the soil and temperature conditions while including the lagged response of vegetation. SMADI was retrieved every eight days at 500 m spatial resolution for the whole Iberian Peninsula (IP) from 2010 to 2014, and a time lag of eight days was used to account for the plant response to the varying soil/climatic conditions. The results of SMADI compared well with other agricultural indices in a semiarid area in the Duero basin, in Spain, and also with a climatic index in areas of the Iberian Peninsula under contrasted climatic conditions. Based on a standard classification of drought severity, the proposed index allowed for a coherent description of the drought conditions of the IP during the study periodThis study was supported by the Spanish Ministry of Economy and Competitiveness, MINECO (Projects AYA2012-39356-C05 and ESP2015-67549-C3-3) and the European Regional Development Fund, FEDER. Partial funding was also received from the BBVA FoundationPeer Reviewe

Evaluation of the similarity between drought indices by correlation analysis and Cohen's Kappa test in a Mediterranean area

AbstractIn the literature, numerous papers report comparative analyses of drought indices. In these types of studies, the similarity between drought indices is usually evaluated using the Pearson correlation coefficient, r, calculated between corresponding severity time series. However, it is well known that the correlation does not describe the strength of agreement between two variables. Two drought indices can exhibit a high degree of correlation but can, at the same time, disagree substantially, for example, if one index is consistently higher than the other. From an operational point of view, two indices can be considered in agreement when they indicate the same severity category for a given period (e.g. moderate drought). In this work, we compared six meteorological drought indices based on both correlation analysis and Cohen's Kappa test. This test is typically used in medical or social sciences to obtain a quantitative assessment of the degree of agreement between different methods or analysts. The indices considered are five timescale-dependent indices, i.e. the Percent of Normal Index, the Deciles Index, the Percentile Index, the Rainfall Anomaly Index, and the Standardised Precipitation Index, computed at the 1-, 3-, and 6-month timescales, and the Effective Drought Index, a relatively new index, which has a self-defined timescale. The indices were calculated for 15 stations in the Abruzzo region (central Italy) during 1951–2018. We found that the strength of agreement depends on both the criteria of drought severity classification and the different indices' calculation method. The Cohen's Kappa test indicates a prevailing moderate or fair agreement among the indices considered, despite the generally very high correlation between the corresponding severity times series. The results demonstrate that the Cohen's Kappa test is more effective than the correlation analysis in discriminating the actual strength of agreement/disagreement between drought indices

Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño−Southern Oscillation (ENSO)

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982−2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1−12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI−12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1−12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008−2010, 2000−2003, and 1984−1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997−1998, 1993−1994, and 1991−1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria

Technical Report Series on Global Modeling and Data Assimilation, Volume 41 : GDIS Workshop Report

The workshop "An International Global Drought Information System Workshop: Next Steps" was held on 10-13 December 2014 in Pasadena, California. The more than 60 participants from 15 countries spanned the drought research community and included select representatives from applications communities as well as providers of regional and global drought information products. The workshop was sponsored and supported by the US National Integrated Drought Information System (NIDIS) program, the World Climate Research Program (WCRP: GEWEX, CLIVAR), the World Meteorological Organization (WMO), the Group on Earth Observations (GEO), the European Commission Joint Research Centre (JRC), the US Climate Variability and Predictability (CLIVAR) program, and the US National Oceanic and Atmospheric Administration (NOAA) programs on Modeling, Analysis, Predictions and Projections (MAPP) and Climate Variability & Predictability (CVP). NASA/JPL hosted the workshop with logistical support provided by the GEWEX program office. The goal of the workshop was to build on past Global Drought Information System (GDIS) progress toward developing an experimental global drought information system. Specific goals were threefold: (i) to review recent research results focused on understanding drought mechanisms and their predictability on a wide range of time scales and to identify gaps in understanding that could be addressed by coordinated research; (ii) to help ensure that WRCP research priorities mesh with efforts to build capacity to address drought at the regional level; and (iii) to produce an implementation plan for a short duration pilot project to demonstrate current GDIS capabilities. See http://www.wcrp-climate.org/gdis-wkshp-2014-objectives for more information

Agrometeorological forecasting

Agrometeorological forecasting covers all aspects of forecasting in agrometeorology. Therefore, the scope of agrometeorological forecasting very largely coincides with the scope of agrometeorology itself. All on-farm and regional agrometeorological planning implies some form of impact forecasting, at least implicitly, so that decision-support tools and forecasting tools largely overlap. In the current chapter, the focus is on crops, but attention is also be paid to sectors that are often neglected by the agrometeorologist, such as those occurring in plant and animal protection. In addition, the borders between meteorological forecasts for agriculture and agrometeorological forecasts are not always clear. Examples include the use of weather forecasts for farm operations such as spraying pesticides or deciding on trafficability in relation to adverse weather. Many forecast issues by various national institutions (weather, but also commodity prices or flood warnings) are vital to the farming community, but they do not constitute agrometeorological forecasts. (Modified From the introduction of the chapter: Scope of agrometeorological forecasting)JRC.H.4-Monitoring Agricultural Resource

Modelling agricultural drought: a review of latest advances in big data technologies

Open Access Journal; Published online: 12 Oct 2022This article reviews the main recent applications of multi-sensor remote sensing and Artificial Intelligence techniques in multivariate modelling of agricultural drought. The study focused mainly on three fundamental aspects, namely descriptive modelling, predictive modelling, and spatial modelling of expected risks and vulnerability to drought. Thus, out of 417 articles across all studies on drought, 226 articles published from 2010 to 2022 were analyzed to provide a global overview of the current state of knowledge on multivariate drought modelling using the inclusion criteria. The main objective is to review the recent available scientific evidence regarding multivariate drought modelling based on the joint use of geospatial technologies and artificial intelligence. The analysis focused on the different methods used, the choice of algorithms and the most relevant variables depending on whether they are descriptive or predictive models. Criteria such as the skill score, the given game complexity used, and the nature of validation data were considered to draw the main conclusions. The results highlight the very heterogeneous nature of studies on multivariate modelling of agricultural drought, and the very original nature of studies on multivariate modelling of agricultural drought in the recent literature. For future studies, in addition to scientific advances in prospects, case studies and comparative studies appear necessary for an in-depth analysis of the reproducibility and operational applicability of the different approaches proposed for spatial and temporal modelling of agricultural drought

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

The Near East Drought Planning Manual: Guidelines for Drought Mitigation and Preparedness Planning

Table of Contents 1. Introduction to Drought Planning.............................................1 1.1 Effects of Drought in the Near East Region........................................................1 1.2 New Emphasis on Proactive Drought Planning .................................................. 3 1.3 Integration of Drought Planning and Sustainable Development ......................... 3 2. Explanation of Drought Concepts..............................................................5 2.1 Definitions ........................................................................................................ 5 2.2 The Nature of Drought ...................................................................................... 7 2.3 The Effects of Drought ...................................................................................... 7 3. HowtoDevelopaDroughtPlan.....................................................................................9 Step 1: Creating Political Momentum and Authority................................................9 Step 2: Coordinating Strategic Drought Planning .................................................. 12 Step 3: Fostering Involvement and Developing Common Understandings .............. 15 Step 4: Investigating Drought Monitoring, Risk, and Management Options............ 16 Step 5: Writing a Drought Plan ............................................................................. 33 Step 6: Implementing a Drought Plan ................................................................... 33 4. Example of National Drought Planning: The Islamic Republic of Iran....................35 4.1 Overview of the Iran National Strategy and Action Plan on Drought Preparedness, Management, and Mitigation in the Agricultural Sector ........... 36 4.2 Steps in the Development of the Iran National Strategy and Action Plan on Drought Management and Mitigation .............................................. 36 5. Drought Planning and Risk Management Resources......................................... 41 5.1 United Nations System.................................................................................... 41 5.2 International Networks and Centers................................................................45 5.3 Regional Networks and Organizations ............................................................. 46 5.4 Country-Based Organizations ......................................................................... 47 6. References................................................................................5