scholarly journals Analysing the Relationship between Multiple-Timescale SPI and GRACE Terrestrial Water Storage in the Framework of Drought Monitoring

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1672 ◽  
Author(s):  
Carmelo Cammalleri ◽  
Paulo Barbosa ◽  
Jürgen V. Vogt
Keyword(s):  
Real Time ◽  
Extreme Values ◽  
Water Storage ◽  
Global Scale ◽  
Drought Monitoring ◽  
Limited Area ◽  
Standardised Precipitation Index ◽  
Wide Range ◽  
Multiple Timescale

The operational monitoring of long-term hydrological droughts is often based on the standardised precipitation index (SPI) for long accumulation periods (i.e., 12 months or longer) as a proxy indicator. This is mainly due to the current lack of near-real-time observations of relevant hydrological quantities, such as groundwater levels or total water storage (TWS). In this study, the correlation between multiple-timescale SPIs (between 1 and 48 months) and GRACE-derived TWS is investigated, with the goals of: (i) evaluating the benefit of including TWS data in a drought monitoring system, and (ii) testing the potential use of SPI as a robust proxy for TWS in the absence of near-real-time measurements of the latter. The main outcomes of this study highlight the good correlation between TWS anomalies (TWSA) and long-term SPI (12, 24 and 48 months), with SPI-12 representing a global-average optimal solution (R = 0.350 ± 0.250). Unfortunately, the spatial variability of the local-optimal SPI underlines the difficulty in reliably capturing the dynamics of TWSA using a single meteorological drought index, at least at the global scale. On the contrary, over a limited area, such as Europe, the SPI-12 is able to capture most of the key traits of TWSA that are relevant for drought studies, including the occurrence of dry extreme values. In the absence of actual TWS observations, the SPI-12 seems to represent a good proxy of long-term hydrological drought over Europe, whereas the wide range of meteorological conditions and complex hydrological processes involved in the transformation of precipitation into TWS seems to limit the possibility of extending this result to the global scale.

scholarly journals Global meteorological drought – Part 1: Probabilistic monitoring

2014 ◽  
Vol 18 (7) ◽  
pp. 2657-2667 ◽  
Author(s):  
E. Dutra ◽  
F. Wetterhall ◽  
F. Di Giuseppe ◽  
G. Naumann ◽  
P. Barbosa ◽  
...  
Keyword(s):  
Real Time ◽  
Tropical Rainfall Measuring Mission ◽  
Meteorological Drought ◽  
Global Scale ◽  
Added Value ◽  
Drought Monitoring ◽  
Data Set ◽  
Probabilistic Forecasts ◽  
Standardised Precipitation Index ◽  
Mean Square Errors

Abstract. Near-real-time drought monitoring can provide decision-makers with valuable information for use in several areas, such as water resources management, or international aid. One of the main constrains of assessing the current drought situation is associated with the lack of reliable sources of observed precipitation on a global scale available in near-real time. Furthermore, monitoring systems also need a long record of past observations to provide mean climatological conditions. To address these problems, a novel probabilistic drought monitoring methodology based on ECMWF probabilistic forecasts is presented, where probabilistic monthly means of precipitation were derived from short-range forecasts and merged with the long-term climatology of the Global Precipitation Climatology Centre (GPCC) data set. From the merged data set, the standardised precipitation index (SPI) was estimated. This methodology was compared with the GPCC first guess precipitation product as well as SPI calculations using the ECMWF ERA-Interim reanalysis and Tropical Rainfall Measuring Mission (TRMM) precipitation data sets. ECMWF probabilistic forecasts for near-real-time monitoring are similar to GPCC and TRMM in terms of correlation and root mean square errors, with the added value of including an estimate of the uncertainty given by the ensemble spread. The real-time availability of this product and its stability (i.e. that it does not directly depend on local rain gauges or single satellite products) are also beneficial in the light of an operational implementation.

Long Term Experience of the Real Time Fouling Deposits Thickness Measurements for On-Line Sootblowing Optimization

2015 ◽  
Author(s):  
B. Chudnovsky ◽  
N. Menn
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Real Time ◽  
Operation Conditions ◽  
Wide Range ◽  
On Line ◽  
Cycle Efficiency ◽  
The Impact ◽  
Long Term Experience

Over the past years there has been a dramatic increase in the regulatory requirements for low emissions. Renewable energy targets and CO2 emissions markets drive the transition to a cleaner and renewable energy production system. In addition to increasing the overall plant cycle efficiency, there two principal means of the reduction of the CO2 from coal fired power plants: by coal and biomass co-firing and by the capture and long term storage of the CO2 emitted from power plant. Carbon dioxide capture and storage will involve substantial capital investment, accompanied by a significant power plant cycle efficiency penalty, and is not currently available on a fully commercial basis. Co-firing biomass, in comparison with other renewable sources, is the main contributor to technologies meeting the world’s renewable energy target. However, the impact of biomass co-firing on boilers performance and integrity has been modest. Operational problems associated with the deposition and retention of ash materials can and do occur on all the major gas-side components of combustion and boilers. The process occurs over a wide range of flue gas and surface temperatures, and dependent both on the characteristics of the ash and on the design and operation conditions of the furnace and boiler. Development and validation of the predictive models have been hindered significantly by the practical difficulties in the obtaining reliable data from the boilers operated with coal and biomass. Although specialized on–line deposition monitoring and sootblowing control systems are commercially available, but they are based on a very simple estimates of the fouling factors, which results in crude and not reliable approach to optimization of sootblowers operation. In the present paper an alternative approach and a new technique based on electro-optical sensor are demonstrated. The long term experience with the system attached to the furnace wall and capable to move the compact sensor in and out of the furnace, allowing to measure simultaneously deposits thickness and reflectivity, is described in details. Results of our study show that dynamics of both parameters on the operated power unit can be registered simultaneously in real time and then interpreted separately. Experiments have been carried out with different coal types at 575MW unit equipped with CE tangential boiler and 550 Mw equipped with B&W boiler with opposite fired burners. The measurements were performed in different locations of the furnace. It was shown that dynamics of thickness and reflectivity variation just after the wall cleaning activation are quite different. Situations have been registered where changes of reflectivity have a significant impact on heat transfer, comparable and sometimes even greater than that of growing fouling thickness. Technique and device exploited in this study appears to be a very useful tool for sootblowing optimization and, as a result, for improvement of boiler efficiency and reduction of water wall erosion and corrosion in both pulverized coal and co-firing boilers.

scholarly journals Inferring Nighttime Satellite Imagery from Human Mobility

2020 ◽  
Vol 34 (01) ◽  
pp. 394-402
Author(s):  
Brian Dickinson ◽  
Gourab Ghoshal ◽  
Xerxes Dotiwalla ◽  
Adam Sadilek ◽  
Henry Kautz
Keyword(s):  
Real Time ◽  
Satellite Imagery ◽  
Differential Privacy ◽  
Human Mobility ◽  
Smart Phone ◽  
Global Scale ◽  
User Privacy ◽  
Socioeconomic Variables ◽  
Mobility Data ◽  
Wide Range

Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for studying a wide range of socioeconomic factors. Recently, another more terrestrial source is producing data with similarly uniform global coverage: anonymous and aggregated smart phone location. This data, which measures the movement patterns of people and populations rather than the light they produce, could prove just as valuable in decades to come. In fact, since human mobility is far more directly related to the socioeconomic variables being predicted, it has an even greater potential. Additionally, since cell phone locations can be aggregated in real time while preserving individual user privacy, it will be possible to conduct studies that would previously have been impossible because they require data from the present. Of course, it will take quite some time to establish the new techniques necessary to apply human mobility data to problems traditionally studied with satellite imagery and to conceptualize and develop new real time applications. In this study we demonstrate that it is possible to accelerate this process by inferring artificial nighttime satellite imagery from human mobility data, while maintaining a strong differential privacy guarantee. We also show that these artificial maps can be used to infer socioeconomic variables, often with greater accuracy than using actual satellite imagery. Along the way, we find that the relationship between mobility and light emissions is both nonlinear and varies considerably around the globe. Finally, we show that models based on human mobility can significantly improve our understanding of society at a global scale.

scholarly journals Evaluating the Drought-Monitoring Utility of GPM and TRMM Precipitation Products over Mainland China

2021 ◽  
Vol 13 (20) ◽  
pp. 4153
Author(s):  
Shuai Cheng ◽  
Weiguang Wang ◽  
Zhongbo Yu
Keyword(s):  
Real Time ◽  
Spatial Scales ◽  
Eastern China ◽  
Mainland China ◽  
Western China ◽  
Drought Monitoring ◽  
Ground Observation ◽  
Trmm Precipitation ◽  
Temporal And Spatial

The purpose of this study was to evaluate the applicability of medium and long-term satellite rainfall estimation (SRE) precipitation products for drought monitoring over mainland China. Four medium and long-term (19 a) SREs, i.e., the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42V7, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement V06 post-real time Final Run precipitation products (IMF6), Global Rainfall Map in Near-real-time Gauge-calibrated Rainfall Product (GSMaP_Gauge_NRT) for product version 6 (GNRT6) and gauge-adjusted Global Satellite Mapping of Precipitation V6 (GGA6) were considered. The accuracy of the four SREs was first evaluated against ground observation precipitation data. The Standardized Precipitation Evapotranspiration Index (SPEI) based on four SREs was then compared at multiple temporal and spatial scales. Finally, four typical drought-influenced regions, i.e., the Northeast China Plain (NEC), Huang-Huai-Hai Plain (3HP), Yunnan–Guizhou Plateau (YGP) and South China (SC) were chosen as examples to analyze the ability of four SREs to capture the temporal and spatial changes of typical drought events. The results show that compared with GNRT6, the precipitation estimated by GGA6, IMF6 and 3B42V7 are in better agreement with the ground observation results. In the evaluation using SPEI, the four SREs performed well in eastern China but have large uncertainty in western China. GGA6 and IMF6 perform superior to GNRT6 and 3B42V7 in estimating SPEI and identifying typical drought events and behave almost the same. In general, GPM precipitation products have great potential to substitute TRMM precipitation products for drought monitoring. Both GGA6 and IMF6 are suitable for historical drought analysis. Due to the shorter time latency of data release and good performance in the eastern part of mainland China, GNRT6 and GGA6 might play a role for near real-time drought monitoring in the area. The results of this research will provide reference for the application of the SREs for drought monitoring in the GPM era.

Operational Near-real Time Drought Monitoring Using Global Satellite Precipitation Estimates

2020 ◽  
Author(s):  
Olivier Prat ◽  
Alec Courtright ◽  
Ronald Leeper ◽  
Brian Nelson ◽  
Rocky Bilotta ◽  
...  
Keyword(s):  
United States ◽  
Real Time ◽  
The United States ◽  
Global Scale ◽  
Drought Monitoring ◽  
Drought Indices ◽  
In Situ Data ◽  
Drought Conditions ◽  
Precipitation Estimates ◽  
Monitoring Information

<p>We present an operational near-real time drought monitoring framework on a global scale that uses satellite quantitative precipitation estimates from the NOAA/CDR program (CMORPH-CDR, PERSIANN-CDR). Monthly and daily Standardized Precipitation Indexes (SPI) are computed for various time scales over the entire period of record of the respective datasets. The near-real time availability of CMORPH-CDR permits for a daily update of the global drought conditions starting in 1998, while the longer period of record of PERSIANN-CDR allows to compute global drought conditions since 1983. The SPI sensitivity to different precipitation datasets and to various lengths of record is quantified. Results indicated that both monthly and daily SPIs computed with both CDRs presented the same timing and area for the major droughts episodes over the continental United States as well as for selected drought events around the globe. Furthermore, the difference resulting from the use of the two-parameter Gamma distribution (McKee et al. 1993) and the three-parameter Pearson III distribution (Guttman 1999) is evaluated. The global mapping of the different distribution parameters (2 and 3 parameters respectively for the Gamma and Pearson III distributions) informs us on how to optimally compute the SPI in areas experiencing too much or too little rainfall. Both CMORPH-CDR and PERSIANN-CDR SPIs are evaluated primarily over CONUS where long-term drought monitoring products based on in-situ data exists such as the United States Drought Monitor (USDM) and the nClimGrid derived SPI. A publicly available interactive visualization tool that provides access to global drought information is also presented. The tools is intended to fill some of the drought monitoring information gaps around the globe. A variety of visualization techniques are used to aid in the interpretation of global drought indices while interactive functionality allows users to focus on a specific region and time-scale of interest. Additional information for region specific drought monitoring resources is also provided to help users access regional drought monitoring information.</p>

scholarly journals A Comprehensive Review on Types, Methods and Different Regions Related to Water–Energy–Food Nexus

2021 ◽  
Vol 18 (16) ◽  
pp. 8276
Author(s):  
Zeyang Bian ◽  
Dan Liu
Keyword(s):  
Food Systems ◽  
Water Security ◽  
Global Scale ◽  
Scientometric Analysis ◽  
Term Survival ◽  
Current State ◽  
Wide Range ◽  
Survival And Development ◽  
Nexus Analysis

Water, food, and energy are three of the most important resources for long-term survival and development. The term “nexus” is used to underline the need of controlling these primary components collectively rather than separately because they are interconnected and linked. With the purpose of better understanding nexus thinking and showcasing nexus analysis approaches and tools, this study explores the current state of the approach to the water–energy–food relationship, which has gotten a lot of attention in recent years. Water–energy, water–food, water–energy–food, water–energy, and climate are the four forms of nexus. This paper examines a variety of methodologies based on their principal objectives and provides a basic overview of a wide range of currently available methods and instruments for analyzing the water–energy–food (WEF) nexus. According to this study, the quantity of studies on the water–energy–food nexus has increased significantly, as the scientific community’s ability to analyze water, food, and energy interlinkages at a greater resolution. The integration and optimization of this multi-centric nexus is explored, with focus on four regions—Asia, Europe, America, and Africa—as a case study. The WEF nexus should be used in case studies to help illustrate its intricacies. Furthermore, this study builds a methodology and frameworks to find study linkages between water, energy, food, and other components, for a nexus analysis and discuss the major challenges and its solutions. This study also includes a scientometric analysis that looks at the countries and keyword mapping. Furthermore, the study is being planned, with an emphasis on quantitative analysis of the water–energy–food nexus which is helpful for the water security at local and global scale. This study aids in the coordination of research efforts to solve the difficult issues in nexus research and create sustainable and adaptable water, energy, and food systems.

Near real time plasma irregularity monitoring by FORMOSAT-7/COSMIC-2

2020 ◽  
Author(s):  
ShihPing Chen ◽  
Charles C. Lin ◽  
Rajesh Panthalingal Krishnanunni ◽  
Richard Eastes ◽  
Jong-Min Choi
Keyword(s):  
Real Time ◽  
Global Scale ◽  
Plasma Bubble ◽  
Low Latitude ◽  
Plasma Irregularities ◽  
Ion Drift ◽  
F Region ◽  
Low Latitudes ◽  
Bottom Side

<p>The near real-time global plasma bubble map is constructed by utilizing the FORMOSAT-7/COSMIC-2(F7/C2) radio occultation(RO) scintillation observations in low latitudes. Several tools investigating plasma bubbles like the rate of TEC index(ROTI), Range-Time-Intensity(RTI) diagrams of the Jicamarca Unattended Long-term Investigations of the Ionosphere and Atmosphere(JULIA), and the Global-scale Observations of the Limb and Disk(GOLD) 135.6nm airglow observations are provided validating the RO scintillations. Result shows that the F7/C2 scintillation is sensitive detecting plasma irregularities, especially for the bottom side of these bubbles, which can be used to investigating nighttime vertical plasma drifts in low latitudinal F-region. The hourly quick look of the low latitude plasma bubble occurrence and vertical ion drift around the globe is significant to the space weather monitoring.</p>

Multi-Sensor Multi-Satellite Remote Sensing of Drought Analysis with Multi-Sectoral Impacts and Multi-Scale Vulnerability in Thailand

2020 ◽  
Author(s):  
Sasin Jirasirirak ◽  
Aksara Putthividhya
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Groundwater Resources ◽  
Standardized Precipitation Index ◽  
Water Storage ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Groundwater Storage ◽  
Multi Scale

<p>Drought monitoring and assessment is critical considering the immense costs and impacts Thailand has been experiencing these days.  Deficit in precipitation is typically referred to as meteorological drought.  While deficit in soil moisture (i.e., below average moisture in the soil) is known as agricultural drought.  Hydrological drought corresponds to a deficit in runoff or groundwater resources. Socio-economic drought (also known as anthropogenic drought) refers to water stress intensified by human activities and increase water demands.  Our long-term research in ground observation drought monitoring and assessment has been integrated with remotely sensed precipitation and soil moisture information necessary for the computation of extensively used drought indicators, such as Standardized Precipitation Index (SPI) using widely available satellite-based precipitation products including PERSIANN, TRMM, GSMaP, and IMERG to demonstrate the multidimensional and multi-sectoral impacts of change in rainfall patterns which is directly linked to drought assessment.  Long-term satellite-based soil moisture time series obtained from NASA’s Soil Moisture Active Passive (SMAP) mission have been employed for drought detection from provided near real-time top soil moisture estimates in accordance with The Gravity Recover and Climate Experiment (GRACE) mission.  Preliminary results indicate that multi-sensor multi-satellite remotely sensing data can enhance soil moisture mapping and its long-term spatial and temporal trends match well with change in terrestrial water storage and groundwater storage of the country.   This approach can provide more robust and integrated measure of drought based on wider range of satellite observations such as precipitation, soil moisture, total water storage anomalies, groundwater storage change, offering the opportunities to investigate droughts from different viewpoints. Drought monitoring scheme developed in this work can serve as a supporting tool for water resources and climate change policy making.  It can contribute to improve understanding on potential impacts of climate change, multi-sectoral linkages, multi-scale vulnerability, and adaptation programs.   </p>

Development of a drought monitor for South-Asia

2020 ◽  
Author(s):  
Toma Rani Saha ◽  
Luis Samaniego ◽  
Pallav K Shrestha ◽  
Stephan Thober ◽  
Oldrich Rakovec
Keyword(s):  
Soil Moisture ◽  
South Asia ◽  
Real Time ◽  
Monitoring System ◽  
Hydrologic Model ◽  
Agricultural Drought ◽  
Cumulative Distribution ◽  
Food Storage ◽  
Drought Monitoring ◽  
Wide Range

<p>South Asia (SA) is highly vulnerable to extreme climatic events and experiences a wide range of natural hazards such as floods, drought, storms, and sea-level rise.  Droughts are recurrent in SA and its impact on regional agriculture, food storage, and livelihood is enormous. Agricultural droughts have severe consequences on the economy, society, health and water resources sectors. In this work, a state-of-the-art monitoring system of soil moisture drought in SA is developed. This study aims at improving the agricultural drought monitoring system for SA and contributing towards better adaptation solutions in the region. The SA drought monitoring system is inspired by the German Drought Monitor (www.ufz.de/duerremonitor)[1]. First, we implement the mesoscale hydrologic model (mHM, https://git.ufz.de/mhm) to reconstruct daily soil moisture from 1981 to 2019 using a near-real-time precipitation product (CHIRPS version 2, 0.25-degree resolution). Second, the SMI is estimated with a non-parametric kernel-based cumulative distribution function [2] based on mHM’s historic soil moisture reconstruction. The generated SMI maps are classified into five classes based on severity: abnormally dry, moderate drought, severe drought, extreme drought and exceptional drought. Third, we develop the South Asia Drought Monitor (SADM) which is an interactive web-portal (http://southasiadroughtmonitor.pythonanywhere.com/) for the dissemination of the simulated near-real-time drought classes. To achieve maximum dissemination, the daily and monthly SMI fields will be uploaded and published on the SADM portal. The SADM will help to inform decision-makers, the general public, researchers, and stakeholders in the SA. The drought monitoring system will allow the scientific community to conduct micro-level in-depth research and to enable policymakers to formulate proper planning and to take mitigation measures in sectors encompassing energy, health, forestry, and agriculture at local to regional scales.</p><p> </p><p>[1] Zink, M., Samaniego, L., Kumar, R., Thober, S., Mai, J., Schäfer, D., Marx, A., 2016: The German drought monitor, Environ. Res. Lett. 11 (7), art. 074002, DOI:10.1088/1748-9326/11/7/074002.</p><p>[2] Samaniego, L., Kumar, R. and Zink, M.,2013: Implications of Parameter Uncertainty on Soil Moisture Drought Analysis in Germany, Journal of Hydrometeorology, DOI: 10.1175/JHM-D-12-075.1.</p><p> </p>

scholarly journals Global meteorological drought – Part 1: Probabilistic monitoring

2014 ◽  
Vol 11 (1) ◽  
pp. 889-917 ◽  
Author(s):  
E. Dutra ◽  
F. Wetterhall ◽  
F. Di Giuseppe ◽  
G. Naumann ◽  
P. Barbosa ◽  
...  
Keyword(s):  
Real Time ◽  
Standardized Precipitation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Meteorological Drought ◽  
Global Scale ◽  
Added Value ◽  
Drought Monitoring ◽  
Global Precipitation Climatology Centre ◽  
Probabilistic Forecasts ◽  
Mean Square Errors

Abstract. Near-real time drought monitoring can provide decision makers valuable information for use in several areas, such as water resources management, or international aid. One of the main constrains of assessing the current drought situation is associated with the lack of reliable sources of observed precipitation on a global scale available in near-real time. Furthermore, monitoring systems also need a long record of past observations to provide mean climatological conditions. To address these problems a novel probabilistic drought monitoring methodology based on ECMWF probabilistic forecasts is presented where probabilistic monthly means of precipitation were derived from short-range forecasts and merged with the long term climatology of the Global Precipitation Climatology Centre (GPCC) dataset. From the merged dataset, the Standardized Precipitation Index (SPI) was estimated. This methodology was compared with the GPCC first guess precipitation product and also SPI calculations using the ECMWF ERA-Interim reanalysis and Tropical Rainfall Measuring Mission (TRMM) precipitation datasets. ECMWF probabilistic forecasts for near-real time monitoring are similar to GPCC and TRMM in terms of correlation and root mean square errors, with the added value of including an estimate of the uncertainty given by the ensemble spread. The real time availability of this product and its stability, i.e. that it does not depend directly on local rain-gauges or single satellite products, are also beneficial in light of an operational implementation.

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