A Multifaceted Exploration of Hydrologic Drought Using GRACE Satellite Observations and Computer Modeling PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A Multifaceted Exploration of Hydrologic Drought Using GRACE Satellite Observations and Computer Modeling PDF full book. Access full book title A Multifaceted Exploration of Hydrologic Drought Using GRACE Satellite Observations and Computer Modeling by Alys Caitlyn Thomas. Download full books in PDF and EPUB format.
Author: Alys Caitlyn Thomas
Publisher:
ISBN: 9781321301311
Category :
Languages : en
Pages : 107
Get Book Here
Book Description
Prolonged hydrologic drought disturbs the natural state of ecosystems, stresses regional water supplies, and can adversely affect agricultural production. Determining the severity of hydrologic drought traditionally depended on evaluations of historical rainfall, stream flow, and soil moisture; yet, a comprehensive measure of the magnitude of a drought's impact on all components of the terrestrial hydrologic system, including surface, soil, and groundwater storage, remains lacking in standard drought analyses. NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission fills a gap by providing monthly measures of terrestrial water storage anomalies (TWSA) based on time-variable gravitational fields. This dissertation details an investigation of regional hydrological extremes (e.g., drought and flood) using both satellite remote sensing data and outputs from NASA's Catchment Land Surface Model (CLSM). The first project presented in this thesis involves discussion of a novel quantitative, GRACE-based framework for measuring the severity of hydrologic drought. GRACE observations are used to quantify drought by calculating the deviation of monthly-average terrestrial water storage anomalies from the regional climatological reference, where negative deviations represent storage deficits. Each deficit conveys the volume of water that would be required to recover from a drought. Moreover, this finite deficit observation allows for the calculation of a likely time for recovery based on statistical percentiles of storage change distributions, for every month through the end of the event. The second portion of work evaluates and compares the characteristics of subsurface terrestrial water storage variables from the CLSM, assimilated with GRACE satellite observations (CLSM-DA), for the purposes of: acquiring near-real time analysis, downscaling GRACE's spatial resolution, and vertically disaggregating GRACE column-integrated water storage anomalies. Several zones throughout the United States were selected to quantify differences between hydrologic extremes identified by CLSM-DA and those measured by GRACE. Results establish that CLSM-DA TWSA outputs improved those from CLSM Open-loop runs in all regions with R2 increases from 5-14%. We also compared CLSM surface soil moisture content with independent surface moisture observations from the AMSR-E satellite to assess improvements after data assimilation. Results established that assimilation produced modest improvements in correlations between CLSM and AMSR-E in all regions. CLSM-DA hydrologic extremes are comparable to GRACE, however the data-assimilated model continues to struggle with matching the some of the amplitudes of extreme events, in part due to model structure and parameters that do not possess enough information about the hydrologic system to accurately depict changes in TWSA as observed by GRACE. Since CLSM continues to run through the near-present month (April 2014), beyond the current, publically available GRACE month (January 2014), an assessment of the CLSM's performance between assimilation updates is also provided. The final project details the development of a linear multivariate, multi-frequency regression model to estimate monthly water storage change and extremes before and beyond the currently available GRACE observation period (April 2002-April 2014). The regression model provides coefficients that can then be used with any precipitation and evapotranspiration dataset, to calculate the associated amount of water storage change for our study region, California's Central Valley (e.g., Sacramento, San Joaquin, and Tulare river basins). Model results show that 82% of GRACE's TWSA signal can be explained with a combination of precipitation and evapotranspiration. The June 2014 storage estimate from the regression model revealed that water storage deficits persisted in the Central Valley with a monthly value of -28.8 km3 (±1.22 km3). This work concludes that GRACE satellite data can successfully be utilized for regional scale drought analysis and has implications for improving drought early warning lead times together with drought preparation and management efforts. The storage deficit method demonstrates the added benefits of explicitly recognizing the beginning and end of storage deficit periods and of providing additional information about the effects of meteorological drought on regional water storage. Data assimilation increases the usability of GRACE for near-present monitoring, while implementation of the linear multi-frequency regression model allows for the extension of water storage anomalies.
Author: Alys Caitlyn Thomas
Publisher:
ISBN: 9781321301311
Category :
Languages : en
Pages : 107
Get Book Here
Book Description
Prolonged hydrologic drought disturbs the natural state of ecosystems, stresses regional water supplies, and can adversely affect agricultural production. Determining the severity of hydrologic drought traditionally depended on evaluations of historical rainfall, stream flow, and soil moisture; yet, a comprehensive measure of the magnitude of a drought's impact on all components of the terrestrial hydrologic system, including surface, soil, and groundwater storage, remains lacking in standard drought analyses. NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission fills a gap by providing monthly measures of terrestrial water storage anomalies (TWSA) based on time-variable gravitational fields. This dissertation details an investigation of regional hydrological extremes (e.g., drought and flood) using both satellite remote sensing data and outputs from NASA's Catchment Land Surface Model (CLSM). The first project presented in this thesis involves discussion of a novel quantitative, GRACE-based framework for measuring the severity of hydrologic drought. GRACE observations are used to quantify drought by calculating the deviation of monthly-average terrestrial water storage anomalies from the regional climatological reference, where negative deviations represent storage deficits. Each deficit conveys the volume of water that would be required to recover from a drought. Moreover, this finite deficit observation allows for the calculation of a likely time for recovery based on statistical percentiles of storage change distributions, for every month through the end of the event. The second portion of work evaluates and compares the characteristics of subsurface terrestrial water storage variables from the CLSM, assimilated with GRACE satellite observations (CLSM-DA), for the purposes of: acquiring near-real time analysis, downscaling GRACE's spatial resolution, and vertically disaggregating GRACE column-integrated water storage anomalies. Several zones throughout the United States were selected to quantify differences between hydrologic extremes identified by CLSM-DA and those measured by GRACE. Results establish that CLSM-DA TWSA outputs improved those from CLSM Open-loop runs in all regions with R2 increases from 5-14%. We also compared CLSM surface soil moisture content with independent surface moisture observations from the AMSR-E satellite to assess improvements after data assimilation. Results established that assimilation produced modest improvements in correlations between CLSM and AMSR-E in all regions. CLSM-DA hydrologic extremes are comparable to GRACE, however the data-assimilated model continues to struggle with matching the some of the amplitudes of extreme events, in part due to model structure and parameters that do not possess enough information about the hydrologic system to accurately depict changes in TWSA as observed by GRACE. Since CLSM continues to run through the near-present month (April 2014), beyond the current, publically available GRACE month (January 2014), an assessment of the CLSM's performance between assimilation updates is also provided. The final project details the development of a linear multivariate, multi-frequency regression model to estimate monthly water storage change and extremes before and beyond the currently available GRACE observation period (April 2002-April 2014). The regression model provides coefficients that can then be used with any precipitation and evapotranspiration dataset, to calculate the associated amount of water storage change for our study region, California's Central Valley (e.g., Sacramento, San Joaquin, and Tulare river basins). Model results show that 82% of GRACE's TWSA signal can be explained with a combination of precipitation and evapotranspiration. The June 2014 storage estimate from the regression model revealed that water storage deficits persisted in the Central Valley with a monthly value of -28.8 km3 (±1.22 km3). This work concludes that GRACE satellite data can successfully be utilized for regional scale drought analysis and has implications for improving drought early warning lead times together with drought preparation and management efforts. The storage deficit method demonstrates the added benefits of explicitly recognizing the beginning and end of storage deficit periods and of providing additional information about the effects of meteorological drought on regional water storage. Data assimilation increases the usability of GRACE for near-present monitoring, while implementation of the linear multi-frequency regression model allows for the extension of water storage anomalies.
Author: Brian D. Wardlow
Publisher: CRC Press
ISBN: 1439835608
Category : Science
Languages : en
Pages : 484
Get Book Here
Book Description
Remote Sensing of Drought: Innovative Monitoring Approaches presents emerging remote sensing-based tools and techniques that can be applied to operational drought monitoring and early warning around the world. The first book to focus on remote sensing and drought monitoring, it brings together a wealth of information that has been scattered through
Author: Alireza Farahmand
Publisher:
ISBN: 9781339563824
Category :
Languages : en
Pages : 131
Get Book Here
Book Description
The overarching goal of this dissertation is to improve current capabilities in drought monitoring using space-based observations, with a focus on integrating remotely sensed data products that are not commonly being used for drought monitoring. The first chapter of this dissertation, surveys current and emerging drought monitoring approaches using remotely-sensed observations from climatological and ecosystem perspectives. Current and future satellite missions offer opportunities to develop composite and multi-sensor (or multi-index) drought assessment models. While there are immense opportunities, there are major challenges including data continuity, unquantified uncertainty, sensor changes, and community acceptability. One of the major limitations of many of the currently available satellite observations is their short length of record. However, they still provide valuable information about relevant hydrologic and ecological processes linked to this natural hazard. Therefore, there is a need for models and algorithms that combine multiple data sets and/or assimilate satellite observations into model simulations to generate long-term climate data records. To address this gap, Chapter 2 introduces Standardized Drought Analysis Toolbox (SDAT), which includes a generalized framework for deriving nonparametric univariate and multivariate standardized drought indices. Current indicators suffer from deficiencies including some prior distributional assumption, temporal inconsistency, and statistical incomparability. Most drought indicators rely on a representative parametric probability distribution function that fits the data. However, a parametric distribution function may not fit the data, especially in continental/global scale studies. Particularly, when the sample size is relatively small as in the case of many satellite precipitation products. SDAT is based on a nonparametric framework that can be applied to different climatic variables including precipitation, soil moisture and relative humidity, without having to assume representative parametric distributions. The most attractive feature of the framework is that it leads to statistically consistent drought indicators based on different variables. We show that using SDAT with satellite observation leads to more reliable drought information, compared to the commonly used parametric methods.We argue that satellite observations not currently used for operational drought monitoring, such as near-surface air relative humidity data from the Atmospheric Infrared Sounder (AIRS) mission, provide opportunities to improve early drought warning. In the third chapter of this dissertation, we outline a new drought monitoring framework for early drought onset detection using AIRS relative humidity data. The early warning and onset detection of drought is of particular importance for effective agriculture and water resource management. Previous studies show that the Standard Precipitation Index (SPI), a measure of precipitation deficit, detects drought onset earlier than other indicators. Here satellite-based near surface air relative humidity data can further improve drought onset detection and early warning. This chapter introduces the Standardized Relative Humidity Index (SRHI) based on the NASA's AIRS observations. SRHI relies on SDAT's nonparametric framework, introduced in Chapter 2. The results indicate that the SRHI typically detects the drought onset earlier than SPI. While the AIRS mission was not originally designed for drought monitoring, its relative humidity data offers a new and unique avenue for drought monitoring and early warning. Early warning aspects of SRHI may have merit for integration into current drought monitoring systems.One of the research opportunities identified in Chapter 1 is using current (and future) satellite missions to develop composite and multi-indicator drought models. In Chapter 4, we outline a framework for assessing impacts of droughts on forest health using a multi-sensor approach. This framework relies on the relationship between climate conditions (e.g., temperature, precipitation, relative humidity, Vapor Pressure Deficit) and forest health based on greenness of vegetation. Wildfires, tree mortality and forest productivity increase during drought periods. Using the proposed multi-index approach, Chapter 4 aims to investigate the effects of recent summer, dry-season and winter droughts on the forest health in western United States. We use Vapor Pressure Deficit (VPD) as an indicator that combines temperature and relative humidity for forest stress assessment. Normalized Difference Vegetation Index (NDVI) is commonly used for assessing vegetation health. During summer and growing season, VPD values are generally high. The results show that the VPD and NDVI provide consistent information on forest health. In addition to VPD, we use conditional probability of NDVI in high temperature and low relative humidity percentiles over the summer and the growing season. We show that combining temperature and relative humidity using a conditional probability approach offers multi-sensor information on forest condition. During winter, on the other hand, VPD and temperature is relatively lower. NDVI distributions in winter were found to be more associated with precipitation as opposed to relative humidity and temperature. We believe the a joint indicator based on temperature and relative humidity can be considered as a link between climate condition and actual impact on the ecosystem. (Abstract shortened by UMI.)
Author: Chris Funk
Publisher: Elsevier
ISBN: 0128140127
Category : Science
Languages : en
Pages : 242
Get Book Here
Book Description
Drought risk management involves three pillars: drought early warning, drought vulnerability and risk assessment, and drought preparedness, mitigation, and response. This book collects in one place a description of all the key components of the first pillar, and describes strategies for fitting these pieces together. The best modern drought early warning systems incorporate and integrate a broad array of environmental information sources: weather station observations, satellite imagery, land surface and crop model simulations, and weather and climate model forecasts, and analyze this information in context-relevant ways that take into account exposure and vulnerability. Drought Early Warning and Forecasting: Theory and Practice assembles a comprehensive overview of these components, providing examples drawn from the Famine Early Warning Systems Network and the United States Drought Monitor. This book simultaneously addresses the physical, social, and information management aspects of drought early warning, and informs readers about the tools, techniques, and conceptual models required to effectively identify, predict, and communicate potential drought-related disasters. This book is a key text for postgraduate scientists and graduate and advanced undergraduate students in hydrology, geography, earth sciences, meteorology, climatology, and environmental sciences programs. Professionals dealing with disaster management and drought forecasting will also find this book beneficial to their work. Describes and discusses the strategies and components used in effective and integrated 21st century drought early warning systems Provides a one-stop-shop that describes in one book the observations, models, forecasts, indices, social context, and theory used in drought early warning Identifies the latest tools and approaches used to monitor and forecast drought, sources of predictive skill, and discusses the technical and theoretical details required to use these tools and approaches in a real-world setting
Author: Anthony James Mucia
Publisher:
ISBN:
Category : Drought forecasting
Languages : en
Pages : 119
Get Book Here
Book Description
This research compares Gravity Recovery and Climate Experiment (GRACE) groundwater storage (GWS) and root zone soil moisture (RZSM) percentiles to measured data, other drought indicators (DIs) and indices, and stakeholder observations for the purpose of assessing the feasibility and usefulness of these products to detect drought conditions. GRACE percentiles were directly compared to historic groundwater percentiles at 89 Nebraska well locations. Spatial time-series correlations over CONUS were performed between GRACE GWS and RZSM and the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), and soil moisture parameters from several North American Land Data Assimilation System (NLDAS) models. A survey of stakeholder observations during a 2016 flash drought event centered on Montana, Wyoming, South Dakota, and Nebraska was also compared to GRACE percentile data to analyze drought onset timing, geographic coverage, and severity. Overall the results show GRACE GWS has similar spatial and temporal agreement over the well period of record, and generally has the expected negative correlation relationship with observed groundwater, but it does not accurately reflect historic percentiles in Nebraska. GRACE GWS and RZSM have moderate correlation with USDM, and high correlation with SPI, and NLDAS models over the entire U.S. with notable regional and seasonal patterns. SPI accumulation period also plays an important role in correlation strength for both RZSM and GWS with the best agreement seen at 3-month and 12-month accumulation periods, respectively. GRACE RZSM time-series data closely matches stakeholder observations of decreasing soil moisture availability, while observations of decreasing water levels were not as closely matched by GWS. When analyzed as an average over all responding zip codes, RZSM showed an early warning trend up to six weeks prior to observed reports. These results indicate GRACE percentiles are promising drought indicators that can be used as a monitoring and early warning system by decision makers.
Author: Patricia M. Trambauer Arechavaleta
Publisher: CRC Press
ISBN: 9781138028654
Category : Technology & Engineering
Languages : en
Pages : 0
Get Book Here
Book Description
Africa has been severely affected by droughts in the past, contributing to food insecure conditions in several African countries. In view of the (even more) severe drought conditions and water shortage that may be expected in sub-Saharan Africa in the coming years, efforts should focus on improving drought management by ameliorating resilience and preparedness to drought. This study contributes to the development of a modelling framework for hydrological drought forecasting in sub-Saharan Africa as a step towards an effective early warning system. The proposed hydrological drought forecasting system makes use of a hydrological model that was found to be suitable for drought forecasting in Africa and could represent the most severe past droughts in the Limpopo Basin. The modelling results showed that there is an added value in computing indicators based on the hydrological model for the identification of droughts and their severity. The proposed seasonal forecasting system for the Limpopo Basin was found to be skilful in predicting hydrological droughts during the summer rainy season. The findings showed that the persistence of the initial hydrological conditions contribute to the predictability up to 2 to 4 months, while for longer lead times the predictability of the system is dominated by the meteorological forcing. An effective drought forecasting and warning system will hopefully contribute to important aspects in the region such as water security, food security, hazard management, and risk reduction.
Author: Lena M. Tallaksen
Publisher: Gulf Professional Publishing
ISBN: 9780444516886
Category : Mathematics
Languages : en
Pages : 634
Get Book Here
Book Description
The majority of the examples are taken from regions where the rivers run most of the year.
Author: R. Nagarajan
Publisher: Springer Science & Business Media
ISBN: 9048125006
Category : Nature
Languages : en
Pages : 439
Get Book Here
Book Description
Information-based decision-making during drought, often brings out some of the excellent practices that are prevalent in society / individuals. This book is designed to provide information on the drought process, meteorological, hydrological, agriculture, socio-economic aspects and available technologies such as satellite remote sensing data analysis and Geographical Information system for assessment. Assessment procedures utilising the various parameters of importance from various sources for micro level management that would enhance the effectiveness of management practice are dealt in detail. Resource availability and affected group determine the relief assistance for the present event and information that would help them in their realisation and preparedness for the forthcoming years by select countries is highlighted. This would help in the formulation of schemes for event mitigation and area development plans. The readers would gain complete knowledge on drought. This book is expected to act as a guide in preparing people as effective natural resource utilizationist under drought situations.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309388805
Category : Science
Languages : en
Pages : 351
Get Book Here
Book Description
As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.
Author: Joseph P. Bassi
Publisher:
ISBN: 9781935704850
Category : Atmospheric physics
Languages : en
Pages : 0
Get Book Here
Book Description
Despite having little to suggest its future as an international site for science, Boulder, Colorado, rose to prominence as a center of scientific learning in less than two decades. A shifting combination of scientists and sponsors emerged in the post-WWII and Cold War era, giving rise to a landscape littered with interdisciplinary environmental science labs that would become the National Center for Atmospheric Research (NCAR) and NOAA s Space Weather prediction Center, major players among the many agencies that make up Boulder s science community today. This book chronicles the town s meteoric rise from Scientific Siberia to the smartest town in America, including the characters (such as Walter Orr Roberts) the science, and the policies that shaped the AstroBoulder, home of big science, that we know today. "
