Climate Services for Resilient Development (CSRD) Partnership’s work in Latin America

The Climate Services for Resilient Development (CSRD) Partnership is a private-public collaboration led by USAID, which aims to increase resilience to climate change in developing countries through the development and dissemination of climate services. The partnership began with initial projects in three countries: Colombia, Ethiopia, and Bangladesh. The International Center for Tropical Agriculture (CIAT) was the lead organization for the Colombian CSRD efforts – which then expanded to encompass work in the whole Latin American region

Workshop report: Integrated Food Security Modeling in Eastern and Southern Africa

CCAFS organized a workshop on Integrated Food Security Modeling in Eastern and Southern Africa on 10-13 February 2014 in Nairobi, Kenya. The workshop was attended by participants from global, regional, and national institutions, including: the World Food Programme (WFP); the Food and Agriculture Organization (FAO); the UN Office for Disaster Risk Reduction (UNISDR), USAID Famine Early Warning System Network (FEWS NET); the IGAD Climate Prediction and Applications Centre (ICPAC); the Regional Integrated Multi-Hazard Early Warning System for Africa and Asia (RIMES); CGIAR Research Centers (CIMMYT, CIAT, ICRISAT, ICRAF, CIP, ILRI, AfricaRice, IRRI,); and the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS); Workshop presentations and discussions accomplished the following objectives: The concepts and components of Integrated Food Security Modeling were explained along with descriptions, methodologies, and progress of work for current modeling activities in Eastern Africa and globally, including climate models, bio-physical crop models, and econometric models. Data and knowledge gaps, technical challenges, and uncertainties which constrain the accuracy of model outputs were identified, including lack of access to data in formats suitable for model input, data quality issues, errors arising from the aggregation of data collected at points to represent heterogenous areas, and the challenge of quantifying uncertainty when different models are combined. Challenges specific to the region include improving the skill of seasonal climate forecasts for East Africa, adopting the crop models to smallholder farming systems. Institutions participating in in the workshop agreed to prepare a concept note for research on these topics and submit it to CCAFS for funding consideration under Flagship 2: Climate Information Services and Climate-informed Safety Nets

Role of Machine Learning, Deep Learning and WSN in Disaster Management: A Review and Proposed Architecture

Disasters are occurrences that have the potential to adversely affect a community via casualties, ecological damage, or monetary losses. Due to its distinctive geoclimatic characteristics, India has always been susceptible to natural calamities. Disaster Management is the management of disaster prevention, readiness, response, and recovery tasks in a systematic manner. This paper reviews various types of disasters and their management approaches implemented by researchers using Wireless Sensor Networks (WSNs) and machine learning techniques. It also compares and contrasts various prediction algorithms and uses the optimal algorithm on multiple flood prediction datasets. After understanding the drawbacks of existing datasets, authors have developed a new dataset for Mumbai, Maharashtra consisting of various attributes for flood prediction. The performance of the optimal algorithm on the dataset is seen by the training, validation and testing accuracy of 100%, 98.57% and 77.59% respectively

Closing the Loop: the Capacities and Constraints of Information and Communication Technologies for Development (ICT4D)

As a mechanism for collecting and sharing information, information and communications technologies (ICT) hold immense potential for individuals and institutions in low- and middle-income countries. Currently the distribution and adoption of ICTs--particularly mobile devices--has far outpaced the provision of other household services like clean water, sanitation, hygiene, or energy services. At the same time, the development and deployment of Internet of Things (IoT) devices including cellular- and satellite-connected sensors is facilitating more rapid feedback from remote regions where basic services are most limited. When used in conjunction with economic development or public health interventions, these devices and the feedback they provide can inform operation and maintenance activities for field staff and improve the monitoring and evaluation of outcomes for project stakeholders. This dissertation includes three chapters written as journal articles. While each chapter is framed around the work and research efforts being undertaken by the Sustainable Water, Energy, and Environmental Technologies Lab (SweetLab) at Portland State University, the common thread that weaves all three investigations together is the theme of ICT-enabled programmatic feedback. The first chapter introduces the three theoretical lenses that inform these investigations and the ways that ICTs and the data they provide can (1) serve as more appropriate proxies for measuring access to services, (2) reduce information asymmetries between various stakeholders including communities, governments, implementers, and funders, and (3) enable more robust methodologies for measuring outcomes and impacts of interventions within complex adaptive systems. The second chapter presents a critical review of the methodologies and technologies being used to track progress on sanitation and hygiene development goals. Chapter three describes how simple sensors and weight measurements can be combined with complex machine learning algorithms to facilitate more reliable and cost-effective latrine servicing in informal settlements. Chapter four presents the results from an investigation exploring how near-time feedback from sensors installed on motorized boreholes can improve water service delivery and drought resilience in arid regions of Northern Kenya. Finally, chapter five provides a summary of the three manuscripts and discusses the significance of this research for future investigations

Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management

2017 Summer.Includes bibliographical references.The majority of river basins in the world, have undergone a great deal of transformations in terms of infrastructure and water management practices in order to meet increasing water needs due to population growth and socio-economic development. Surface water and groundwater systems are interwoven with environmental and socio-economic ones. The systems' dynamic nature, their complex interlinkages and interdependencies are inducing challenges for integrated water resources management. Informed decision-making process in water resources is deriving from a systematic analysis of the available data with the utilization of tools and models, by examining viable alternatives and their associated tradeoffs under the prism of a set of prudent priorities and expert knowledge. In an era of increasing volume and variety of data about natural and anthropogenic systems, opportunities arise for further enhancing data integration in problem-solving approaches and thus support decision-making for water resources planning and management. Although there is a plethora of variables monitored in various spatial and temporal scales, particularly in the United States, in real life, for water resources applications there are rarely, if ever, perfect data. Developing more systematic procedures to integrate the available data and harness their full potential of generating information, will improve the understanding of water resources systems and assist at the same time integrated water resources management efforts. The overarching objective of this study is to develop tools and approaches to overcome data obstacles in water resources management. This required the development of methodologies that utilize a wide range of water and environmental datasets in order to transform them into reliable and valuable information, which would address unanswered questions about water systems and water management practices, contributing to implementable efforts of integrated water resources management. More specifically, the objectives of this research are targeted in three complementary topics: drought, water demand, and groundwater supply. In this regard, their unified thread is the common quest for integrated river basin management (IRBM) under changing water resources conditions. All proposed methodologies have a common area of application namely the South Platte basin, located within Colorado. The area is characterized by limited water resources with frequent drought intervals. A system's vulnerability to drought due to the different manifestations of the phenomenon (meteorological, agricultural, hydrological, socio-economic and ecological) and the plethora of factors affecting it (precipitation patterns, the supply and demand trends, the socioeconomic background etc.) necessitates an integrated approach for delineating its magnitude and spatiotemporal extent and impacts. Thus, the first objective was to develop an implementable drought management policy tool based on the standardized drought vulnerability index framework and expanding it in order to capture more of drought's multifaceted effects. This study illustrated the advantages of a more transparent data rigorous methodology, which minimizes the need for qualitative information replacing it with a more quantitative one. It is believed that such approach may convey drought information to decision makers in a holistic manner and at the same time avoid the existing practices of broken linkages and fragmentation of reported drought impacts. Secondly, a multi-scale (well, HUC-12, and county level) comparative analysis framework was developed to identify the characteristics of the emergent water demand for unconventional oil and gas development. This effort revealed the importance of local conditions in well development patterns that influence water demand, the magnitude of water consumption in local scales in comparison to other water uses, the strategies of handling flowback water, and the need for additional data, and improved data collection methods for a detailed water life-cycle analysis including the associated tradeoffs. Finally, a novel, easy to implement, and computationally low cost methodology was developed for filling gaps in groundwater level time series. The proposed framework consists of four main components, namely: groundwater level time series; data (groundwater level, recharge and pumping) from a regional physically-based groundwater flow model; autoregressive integrated moving average with external inputs modeling; and the Ensemble Smoother (ES) technique. The methodology's efficacy to predict accurately groundwater levels was tested by conducting three numerical experiments at eighteen alluvial wells. The results suggest that the framework could serve as a valuable tool in gaining further insight of alluvium aquifer dynamics by filling missing groundwater level data in an intermittent or continuous (with relative short span) fashion. Overall, it is believed that this research has important implications in water resources decision making by developing implementable frameworks which advance further the understanding of water systems and may aid in integrated river basin management efforts

Information for Meeting Africa’s Agricultural Transformation and Food Security Goals (IMAAFS)

The organizers of this international Conference on Information for Meeting Africa’s Agricultural Transformation and Food Security Goals (IMAAFS) included the African Union, the UN Economic Commission for Africa, and the European Commission (through the Joint Research Center). The Conference took place at the UN Conference Centre in Addis Ababa from 1 to 3 October 2014, to widen the availability and use of evidence-based information for agricultural growth and improved food and nutrition security. With over 180 international participants, the event brought together scientists and policy makers from a wide range of institutions and research organizations from Africa, Europe and the United States, as well as major UN agencies. The Conference took place over the course of three days and included nine presentation and discussion sessions (each with a chairperson and a rapporteur), executive morning briefs, break-out working groups, and a final decision-grid exercise to summarize the expert opinion of participants regarding the most promising strategies.JRC.H.4-Monitoring Agricultural Resource

An Assessment of the National Water Model’s Ability to Reproduce Drought Series in New York State

Accurately quantifying the spatiotemporal extent and intensity of drought is important for water resources planning and management. The onset of drought is impacted by a multitude of meteorologic, climatologic, and anthropogenic triggers. Currently, the United States Drought Monitor (USDM) is the tool used in the United States (U.S.) to both categorize drought and allocate emergency funding based on drought categories. Two key issues with the USDM are the nonuniform scale of its input variables, and its inability to predict drought into the future. This work proposes employing output from the NOAA’s National Water Model (NWM) 25-year reanalysis to augment the USDM. A numerical comparison is presented between concurrent New York State Mesonet (Mesonet) observed and NWM simulated soil moisture data at three depths in the soil column for 119 locations across NY, and between USGS observed and NWM simulated streamflow data for 28 locations across NY. Drought categories are determined according to USDM percentile ranges based on the percentiles derived from the non- exceedance probabilities of NWM streamflow and soil moisture output and USGS streamflow data. It was determined that while there was mixed (streamflow) to poor (soil moisture) agreement between the NWM reanalysis and observational data, the NWM was generally able to reproduce the spatial extent of the 2016 drought in NY with reasonable skill, especially when using data representing deeper soil moisture. It was generally observed that NWM derived drought categories were typically more extreme than those of the USDM

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