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It is known that representing wetland dynamics in land surface modeling improves models’ capacity to reproduce fluxes and land surface boundary conditions for atmospheric modeling in general circulation models. This study presents the development of the full coupling between the Noah‐MP land surface model (LSM) and the HyMAP flood model in the NASA Land Information System and its application over the Inner Niger Delta (IND), a well‐known hot‐spot of strong land surface‐atmosphere interactions in West Africa. Here, we define two experiments at 0.02º spatial resolution over 2002‐2018 to quantify the impacts of the proposed developments on simulating IND dynamics. One represents the one‐way approach for simulating land surface and flooding processes (1‐WAY), i.e., Noah‐MP neglects surface water availability, and the proposed two‐way coupling (2‐WAY), where Noah‐MP takes surface water availability into account in the vertical water and energy balance. Results show that accounting for two‐way interactions between Noah‐MP and HyMAP over IND improves simulations of all selected hydrological variables. Compared to 1‐WAY, evapotranspiration derived from 2‐WAY over flooding zones doubles, increased by 0.8mm/day, resulting in an additional water loss rate of ∼18,900km3/year, ∼40% drop of wetland extent during wet seasons and major improvement in simulated water level variability at multiple locations. Significant soil moisture increase and surface temperature drop were also observed. Wetland outflows decreased by 35%, resulting in a substantial a Nash‐Sutcliffe coefficient improvement, from ‐0.73 to 0.79. It is anticipated that future developments in water monitoring and water‐related disaster warning systems will considerably benefit from these findings.
Augusto Getirana; Sujay V. Kumar; Goutam Konapala; Christopher E. Ndehedehe. Impacts of Fully Coupling Land Surface and Flood Models on the Simulation of Large Wetlands' Water Dynamics: The Case of the Inner Niger Delta. Journal of Advances in Modeling Earth Systems 2021, 13, 1 .
AMA StyleAugusto Getirana, Sujay V. Kumar, Goutam Konapala, Christopher E. Ndehedehe. Impacts of Fully Coupling Land Surface and Flood Models on the Simulation of Large Wetlands' Water Dynamics: The Case of the Inner Niger Delta. Journal of Advances in Modeling Earth Systems. 2021; 13 (5):1.
Chicago/Turabian StyleAugusto Getirana; Sujay V. Kumar; Goutam Konapala; Christopher E. Ndehedehe. 2021. "Impacts of Fully Coupling Land Surface and Flood Models on the Simulation of Large Wetlands' Water Dynamics: The Case of the Inner Niger Delta." Journal of Advances in Modeling Earth Systems 13, no. 5: 1.
In many of the world’s mountainous regions, river discharge is largely influenced by the seasonal melt of snow. Therefore, accurate information on the amount of water stored as snow is essential for water management and flood forecasting. However, there are large uncertainties in model simulations of snow depth, partly due to uncertain precipitation estimates in mountain regions with complex topography. A study by Lievens et al. (2019) showed the potential of Sentinel-1 (S1) satellite observations to provide snow depth estimates at 1 km spatial and ~weekly temporal resolution in mountain regions. In this study, we assimilated these retrievals into the Noah Multiparameterization (Noah-MP) v3.6 land surface model for the western Alps using an ensemble Kalman filter. The land surface model was coupled to the Hydrological Modeling and Analysis Platform (HyMAP) routing scheme to also provide estimates of river discharge. With S1 data assimilation, the snow depth estimates improved, reducing the bias from 0.23 m to 0.05 m compared to in situ measurements. Preliminary results also show improved discharge simulations mainly in mountain catchments at high elevations that are less prone to regulations (e.g., by dams). This study demonstrates the capability of the S1 snow depth retrievals to improve not only snow depth estimates, but also the estimation of snow melt water contributions to river discharge.
Isis Brangers; Hans Lievens; Augusto Getirana; Sujay Kumar; Gabrielle De Lannoy. Sentinel-1 snow depth assimilation improves river discharge simulations in the western Alps. 2021, 1 .
AMA StyleIsis Brangers, Hans Lievens, Augusto Getirana, Sujay Kumar, Gabrielle De Lannoy. Sentinel-1 snow depth assimilation improves river discharge simulations in the western Alps. . 2021; ():1.
Chicago/Turabian StyleIsis Brangers; Hans Lievens; Augusto Getirana; Sujay Kumar; Gabrielle De Lannoy. 2021. "Sentinel-1 snow depth assimilation improves river discharge simulations in the western Alps." , no. : 1.
It is known that representing wetland dynamics in land surface modeling improves models’ capacity to reproduce fluxes and land surface boundary conditions for atmospheric modeling in general circulation models. This study presents the development of the full coupling between the Noah-MP land surface model (LSM) and the HyMAP flood model in the NASA Land Information System and its application over the Inner Niger Delta (IND), a well-known hot-spot of strong land surface-atmosphere interactions in West Africa. Here, we define two experiments at 0.02º spatial resolution over the 2002-2018 period to quantify the impacts of the proposed developments on IND dynamics. One represents the one-way approach for simulating land surface and flooding processes (1-WAY), i.e., Noah-MP neglects surface water availability, and the proposed two-way coupling (2-WAY), where Noah-MP takes surface water availability into account in the vertical water and energy balance. Results show that accounting for two-way interactions between Noah-MP and HyMAP over IND improves all selected hydrological variables. Compared to 1-WAY, evapotranspiration derived from 2-WAY over flooding zones doubles, increased by 0.8mm/day, resulting in an additional water loss rate of ~18,900km3/year, ~40% drop of wetland extent during wet seasons and major improvement in water level variability at multiple locations. Significant soil moisture increase and surface temperature drop were also observed. Wetland outflows decreased by 35%, resulting in a substantial a Nash-Sutcliffe coefficient improvement, from -0.73 to 0.79. It is anticipated that future developments in global water monitoring and water‐related disaster warning systems will considerably benefit from these findings.
Augusto Getirana; Sujay Kumar; Goutam Konapala; Christopher Edet Ndehedehe. Impacts of fully coupling land surface and flood models on large wetland's water dynamics: the case of the Inner Niger Delta. 2021, 1 .
AMA StyleAugusto Getirana, Sujay Kumar, Goutam Konapala, Christopher Edet Ndehedehe. Impacts of fully coupling land surface and flood models on large wetland's water dynamics: the case of the Inner Niger Delta. . 2021; ():1.
Chicago/Turabian StyleAugusto Getirana; Sujay Kumar; Goutam Konapala; Christopher Edet Ndehedehe. 2021. "Impacts of fully coupling land surface and flood models on large wetland's water dynamics: the case of the Inner Niger Delta." , no. : 1.
Though coarse in spatial resolution, the nearly all weather measurements from passive microwave sensors can help in improving the spatio‐temporal coverage of optical and thermal infrared sensors for monitoring vegetation changes on the land surface. This study demonstrates the use of vegetation optical depth retrievals from the Soil Moisture Active Passive mission for capturing the vegetation alterations from the recent 2019‐2020 Australian bushfires and drought. The impact of vegetation disturbances on terrestrial water budget is examined by assimilating the vegetation optical depth retrievals into a dynamic phenology model. The results demonstrate that assimilating vegetation optical depth observations lead to improved simulation of evapotranspiration, runoff, and soil moisture states. The study also demonstrates that the vegetation changes from the 2019‐2020 Australian drought and fires led to significant modifications in the partitioning of evaporative and runoff fluxes, resulting in increased bare soil evaporation, reduced transpiration, and higher runoff.This article is protected by copyright. All rights reserved.
Sujay V. Kumar; Thomas Holmes; Niels Andela; Imtiaz Dharssi; Vinodkumar; Christopher Hain; Christa Peters‐Lidard; Sarith P. Mahanama; Kristi R. Arsenault; Wanshu Nie; Augusto Getirana. The 2019–2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes. Geophysical Research Letters 2021, 48, 1 .
AMA StyleSujay V. Kumar, Thomas Holmes, Niels Andela, Imtiaz Dharssi, Vinodkumar, Christopher Hain, Christa Peters‐Lidard, Sarith P. Mahanama, Kristi R. Arsenault, Wanshu Nie, Augusto Getirana. The 2019–2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes. Geophysical Research Letters. 2021; 48 (1):1.
Chicago/Turabian StyleSujay V. Kumar; Thomas Holmes; Niels Andela; Imtiaz Dharssi; Vinodkumar; Christopher Hain; Christa Peters‐Lidard; Sarith P. Mahanama; Kristi R. Arsenault; Wanshu Nie; Augusto Getirana. 2021. "The 2019–2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes." Geophysical Research Letters 48, no. 1: 1.
Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001–2019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4 mm/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12–35%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.
Augusto Getirana; Dalia Kirschbaum; Felipe Mandarino; Marta Ottoni; Sana Khan; Kristi Arsenault. Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil. Remote Sensing 2020, 12, 4095 .
AMA StyleAugusto Getirana, Dalia Kirschbaum, Felipe Mandarino, Marta Ottoni, Sana Khan, Kristi Arsenault. Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil. Remote Sensing. 2020; 12 (24):4095.
Chicago/Turabian StyleAugusto Getirana; Dalia Kirschbaum; Felipe Mandarino; Marta Ottoni; Sana Khan; Kristi Arsenault. 2020. "Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil." Remote Sensing 12, no. 24: 4095.
River channels store large volumes of water globally, critically impacting ecological and biogeochemical processes. Despite the importance of river channel storage, there is not yet an observational constraint on this quantity. We introduce a 26-year record of entirely remotely sensed volumetric channel water storage anomaly (VCWS) on 26 major world rivers. We find mainstem VCWS climatology amplitude (VCWSCA) represents an appreciable amount of basin-wide terrestrial water storage variability (median 2.2%, range 0.05-13.8% across world rivers), despite the fact that mainstem rivers themselves represent an average of just 0.2% of basin area. We find that two global river routing schemes coupled with land surface models reasonably approximate VCWSCA (within {plus minus}50%) in only 19.2 % and 23.1 % of rivers considered (by model). These findings demonstrate VCWS is a useful measurement for assessing global hydrological model performance, and for advancing understanding of spatial patterns in global hydrology.
Stephen Paul Coss; Michael Durand; C. K. Shum; Yuchan Yi; Xiao Yang; Tamlin M Pavelsky; Augusto Getirana; Dai Yamazaki. Channel water storage anomalies: A new remotely sensed measurement for global river analysis. 2020, 1 .
AMA StyleStephen Paul Coss, Michael Durand, C. K. Shum, Yuchan Yi, Xiao Yang, Tamlin M Pavelsky, Augusto Getirana, Dai Yamazaki. Channel water storage anomalies: A new remotely sensed measurement for global river analysis. . 2020; ():1.
Chicago/Turabian StyleStephen Paul Coss; Michael Durand; C. K. Shum; Yuchan Yi; Xiao Yang; Tamlin M Pavelsky; Augusto Getirana; Dai Yamazaki. 2020. "Channel water storage anomalies: A new remotely sensed measurement for global river analysis." , no. : 1.
The Korea Land Data Assimilation System (KLDAS) has been established for agricultural drought (i.e. soil moisture deficit) monitoring in South Korea, running the Noah-MP land surface model within the NASA Land Information System (LIS) framework with the added value of local precipitation forcing dataset and soil texture maps. KLDAS soil moisture is benchmarked against three global products: the Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and the European Space Agency Climate Change Initiative (ESA CCI) satellite product. The evaluation is performed using in situ measurements for 2013–2015 and one month standardized precipitation index (SPI-1) for 1982–2016, focusing on four major river basins in South Korea. The KLDAS outperforms all benchmark products in capturing soil moisture states and variability at a basin scale. Compared to GLDAS and FLDAS products, the EAS CCI product is not feasible for long term agricultural monitoring due to lower data quality for early periods (1979–1991) of soil moisture estimates. KLDAS shows that the most recent 2015 drought event leads to highest drought areas in the Han and Geum River basins in the past 35 years. This work supports KLDAS as an effective agricultural drought monitoring system to provide continuous regional high-resolution soil moisture estimates in South Korea.
Hahn Chul Jung; Do-Hyuk Kang; Edward Kim; Augusto Getirana; Yeosang Yoon; Sujay Kumar; Christa D. Peters-Lidard; Euiho Hwang. Towards a soil moisture drought monitoring system for South Korea. Journal of Hydrology 2020, 589, 125176 .
AMA StyleHahn Chul Jung, Do-Hyuk Kang, Edward Kim, Augusto Getirana, Yeosang Yoon, Sujay Kumar, Christa D. Peters-Lidard, Euiho Hwang. Towards a soil moisture drought monitoring system for South Korea. Journal of Hydrology. 2020; 589 ():125176.
Chicago/Turabian StyleHahn Chul Jung; Do-Hyuk Kang; Edward Kim; Augusto Getirana; Yeosang Yoon; Sujay Kumar; Christa D. Peters-Lidard; Euiho Hwang. 2020. "Towards a soil moisture drought monitoring system for South Korea." Journal of Hydrology 589, no. : 125176.
The region of southern Africa (SA) has a fragile food economy and is vulnerable to frequent droughts. Interventions to mitigate food insecurity impacts require early warning of droughts – preferably as early as possible before the harvest season (typically starting in April) and lean season (typically starting in November). Hydrologic monitoring and forecasting systems provide a unique opportunity to support early warning efforts, since they can provide regular updates on available root-zone soil moisture (RZSM), a critical variable for crop yield, and provide forecasts of RZSM by combining the estimates of antecedent soil moisture conditions with climate forecasts. For SA, this study documents the predictive capabilities of RZSM products from the recently developed NASA Hydrological Forecasting and Analysis System (NHyFAS). Results show that the NHyFAS products would have identified the regional severe drought event – which peaked during December–February of 2015–2016 – at least as early as 1 November 2015. Next, it is shown that during 1982–2016, February RZSM (Feb-RZSM) forecasts (monitoring product) available in early November (early March) have a correlation of 0.49 (0.79) with the detrended regional crop yield. It is also found that when the February RZSM forecast (monitoring product) available in early November (early March) is indicated to be in the lowest tercile, the detrended regional crop yield is below normal about two-thirds of the time (always), at least over the sample years considered. Additionally, it is shown that the February RZSM forecast (monitoring product) can provide “out-of-sample” crop yield forecasts with comparable (substantially better with 40 % reduction in mean error) skill to December–February ENSO. These results indicate that the NHyFAS products can effectively support food insecurity early warning in the SA region. Finally, since a framework similar to NHyFAS can be used to provide RZSM monitoring and forecasting products over other regions of the globe, this case study also demonstrates potential for supporting food insecurity early warning globally.
Shraddhanand Shukla; Kristi R. Arsenault; Abheera Hazra; Christa Peters-Lidard; Randal D. Koster; Frank Davenport; Tamuka Magadzire; Chris Funk; Sujay Kumar; Amy McNally; Augusto Getirana; Greg Husak; Ben Zaitchik; Jim Verdin; Faka Dieudonne Nsadisa; Inbal Becker-Reshef. Improving early warning of drought-driven food insecurity in southern Africa using operational hydrological monitoring and forecasting products. Natural Hazards and Earth System Sciences 2020, 20, 1187 -1201.
AMA StyleShraddhanand Shukla, Kristi R. Arsenault, Abheera Hazra, Christa Peters-Lidard, Randal D. Koster, Frank Davenport, Tamuka Magadzire, Chris Funk, Sujay Kumar, Amy McNally, Augusto Getirana, Greg Husak, Ben Zaitchik, Jim Verdin, Faka Dieudonne Nsadisa, Inbal Becker-Reshef. Improving early warning of drought-driven food insecurity in southern Africa using operational hydrological monitoring and forecasting products. Natural Hazards and Earth System Sciences. 2020; 20 (4):1187-1201.
Chicago/Turabian StyleShraddhanand Shukla; Kristi R. Arsenault; Abheera Hazra; Christa Peters-Lidard; Randal D. Koster; Frank Davenport; Tamuka Magadzire; Chris Funk; Sujay Kumar; Amy McNally; Augusto Getirana; Greg Husak; Ben Zaitchik; Jim Verdin; Faka Dieudonne Nsadisa; Inbal Becker-Reshef. 2020. "Improving early warning of drought-driven food insecurity in southern Africa using operational hydrological monitoring and forecasting products." Natural Hazards and Earth System Sciences 20, no. 4: 1187-1201.
River impoundments strongly modify the global water cycle and terrestrial water storage (TWS) variability. Given the susceptibility of global water cycle to climate change and anthropogenic influence, the synthesis of science with sustainable reservoir operation strategy is required as part of an integrated approach to water management. Here, we take advantage of new approaches combining state-of-the-art computational models and a novel satellite-based reservoir operation scheme to spatially and temporally decompose Lake Victoria's TWS, which has been dam-controlled since 1954. A ground-based lake bathymetry is merged with a global satellite-based topography to accurately represent absolute water storage, and radar altimetry data is integrated in the hydrodynamic model as a proxy of reservoir operation practices. Compared against an idealized naturalized system (i.e., no anthropogenic impacts) over 2003–2019, reservoir operation shows a significant impact on water elevation, extent, storage and outflow, controlling lake dynamics and TWS. For example, compared to Gravity Recovery and Climate Experiment (GRACE) data, reservoir operation improved correlation and root mean square error of basin-wide TWS simulations by 80% and 54%, respectively. Results also show that lake water storage is 20% higher under dam control and basin-wide surface water storage contributes 64% of TWS variability. As opposed to existing reservoir operation schemes for large-scale models, the proposed model simulates spatially distributed surface water processes and does not require human water demand estimates. Our proposed approaches and findings contribute to the understanding of Lake Victoria's water dynamics and can be further applied to quantify anthropogenic impacts on the global water cycle.
Augusto Getirana; Hahn Chul Jung; Jamon Van Den Hoek; Christopher E. Ndehedehe. Hydropower dam operation strongly controls Lake Victoria's freshwater storage variability. Science of The Total Environment 2020, 726, 138343 .
AMA StyleAugusto Getirana, Hahn Chul Jung, Jamon Van Den Hoek, Christopher E. Ndehedehe. Hydropower dam operation strongly controls Lake Victoria's freshwater storage variability. Science of The Total Environment. 2020; 726 ():138343.
Chicago/Turabian StyleAugusto Getirana; Hahn Chul Jung; Jamon Van Den Hoek; Christopher E. Ndehedehe. 2020. "Hydropower dam operation strongly controls Lake Victoria's freshwater storage variability." Science of The Total Environment 726, no. : 138343.
West Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite‐based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003‐2016 and used to initialize six‐month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE‐DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE‐DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast and water‐related disaster warning systems for Africa.
Augusto Getirana; Hahn Chul Jung; Kristi Arsenault; Shraddhanand Shukla; Sujay Kumar; Christa Peters‐Lidard; Issoufou Maigari; Bako Mamane. Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa. Water Resources Research 2020, 56, 1 .
AMA StyleAugusto Getirana, Hahn Chul Jung, Kristi Arsenault, Shraddhanand Shukla, Sujay Kumar, Christa Peters‐Lidard, Issoufou Maigari, Bako Mamane. Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa. Water Resources Research. 2020; 56 (2):1.
Chicago/Turabian StyleAugusto Getirana; Hahn Chul Jung; Kristi Arsenault; Shraddhanand Shukla; Sujay Kumar; Christa Peters‐Lidard; Issoufou Maigari; Bako Mamane. 2020. "Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa." Water Resources Research 56, no. 2: 1.
This paper presents methods of monitoring river basin development and water variability for the transboundary river in North and South Korea. River basin development, such as dams and water infrastructure in transboundary rivers, can be a potential factor of tensions between upstream and downstream countries since dams constructed upstream can adversely affect downstream riparians. However, because most of the information related to North Korea has been limited to the public, the information about dams constructed and their locations were inaccurate in many previous studies. In addition, water resources in transboundary rivers can be exploited as a political tool. Specifically, due to the unexpected water release from the Hwanggang Dam, upstream of the transboundary Imjin River in North and South Korea, six South Koreans died on 6 September 2009. The Imjin River can be used as a political tool by North Korea, and seven events were reported as water conflicts in the Imjin River from 2001 to 2016. In this paper, firstly, we have updated the information about the dams constructed over the Imjin River in North Korea using multi-temporal images with a high spatial resolution (15–30 cm) obtained from Google Earth. Secondly, we analyzed inter- and intra-water variability over the Hwanggang Reservoir using open-source images obtained from the Global Surface Water Explorer. We found a considerable change in water surface variability before and after 2008, which might result from the construction of the Hwanggang Dam. Thirdly, in order to further investigate intra-annual water variability, we present a method monitoring water storage changes of the Hwanggang Reservoir using the area-elevation curve (AEC), which was derived from multi-sensor Synthetic Aperture Radar (SAR) images (Sentinel-1A and -1B) and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). Since many previous studies for estimating water storage change have depended on satellite altimetry dataset and optical images for deriving AEC, the method adopted in this study is the only application for such inaccessible areas since no altimetry ground track exists for the Hwanggang Reservoir and because clouds can block the study area for wet seasons. Moreover, this study has newly proven that unexpected water release can occur in dry seasons because the water storage in the Hwanggang Reservoir can be high enough to conduct a release that can be used as a geopolitical tool. Using our method, potential risks can be mitigated, not in response to a water release, but based on pre-event water storage changes in the Hwanggang Reservoir.
Donghwan Kim; Hyongki Lee; Hahn Chul Jung; Euiho Hwang; Faisal Hossain; Matthew Bonnema; Do-Hyuk Kang; Augusto Getirana. Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing. Remote Sensing 2020, 12, 195 .
AMA StyleDonghwan Kim, Hyongki Lee, Hahn Chul Jung, Euiho Hwang, Faisal Hossain, Matthew Bonnema, Do-Hyuk Kang, Augusto Getirana. Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing. Remote Sensing. 2020; 12 (1):195.
Chicago/Turabian StyleDonghwan Kim; Hyongki Lee; Hahn Chul Jung; Euiho Hwang; Faisal Hossain; Matthew Bonnema; Do-Hyuk Kang; Augusto Getirana. 2020. "Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing." Remote Sensing 12, no. 1: 195.
We evaluate the impact of Gravity Recovery and Climate Experiment data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the United States, focusing on groundwater storage. GRACE-based terrestrial water storage (TWS) estimates are assimilated into a land surface model for the 2003–16 period. Three-month hindcast (i.e., forecast of past events) simulations are initialized using states from the reference (no data assimilation) and GRACE-DA runs. Differences between the two initial hydrological condition (IHC) sets are evaluated for two forecast techniques at 305 wells where depth to water table measurements are available. Results show that using GRACE-DA-based IHC improves seasonal groundwater forecast performance in terms of both RMSE and correlation. While most regions show improvement, degradation is common in the High Plains, where withdrawals for irrigation practices affect groundwater variability more strongly than the weather variability, which demonstrates the need for simulating such activities. These findings contribute to recent efforts toward an improved U.S. drought monitoring and forecast system.
Augusto Getirana; Matthew Rodell; Sujay Kumar; Hiroko Kato Beaudoing; Kristi Arsenault; Benjamin Zaitchik; Himanshu Save; Srinivas Bettadpur. GRACE Improves Seasonal Groundwater Forecast Initialization over the United States. Journal of Hydrometeorology 2020, 21, 59 -71.
AMA StyleAugusto Getirana, Matthew Rodell, Sujay Kumar, Hiroko Kato Beaudoing, Kristi Arsenault, Benjamin Zaitchik, Himanshu Save, Srinivas Bettadpur. GRACE Improves Seasonal Groundwater Forecast Initialization over the United States. Journal of Hydrometeorology. 2020; 21 (1):59-71.
Chicago/Turabian StyleAugusto Getirana; Matthew Rodell; Sujay Kumar; Hiroko Kato Beaudoing; Kristi Arsenault; Benjamin Zaitchik; Himanshu Save; Srinivas Bettadpur. 2020. "GRACE Improves Seasonal Groundwater Forecast Initialization over the United States." Journal of Hydrometeorology 21, no. 1: 59-71.
Despite the serious threats posed by floods, the driving mechanisms of floods are still not well understood. Here, we apply a physically‐based inundation model coupled with a river routing model (Model for Scale Adaptive River Transport, MOSART) within the Energy Exascale Earth System Model (E3SM) framework to investigate flood inundation dynamics. After calibration using observed streamflow and satellite‐derived flood extent, the model is used to simulate global flood inundation from 1953 to 2004. The mean date and seasonality of annual maximum flood, defined based on flood extent, exhibit significant regional differences across 16 major basins. Generally, soil moisture and monthly maximum daily rainfall (MMR) are the dominant drivers of flood in tropical basins while monthly maximum daily snowmelt (MMS) is the dominant driver in high latitude basins. From 1953‐1982 to 1975‐2004, significant changes in flood generation mechanisms are found in some basins such as Amazon, Lena, Yenisey, and Kolyma. Analysis of the rainfall seasonality and water balance at grid scale reveals a stronger rainfall seasonality in the Amazon during the later period that increases the synchrony between extreme rainfall and wet soil. With high antecedent soil moisture coinciding with rainfall, MMR contributes more to flood in the later period. Fewer extreme rainfall events and increasing soil moisture reduced the contribution of MMR and increased the role of MMS in floods in the Lena and Yenisey basins, respectively. Lastly, increased soil moisture and frequency of large MMS reduced the contribution of the latter to floods in the Kolyma basin.
Yuna Mao; Tian Zhou; L. Ruby Leung; Teklu K. Tesfa; Hong‐Yi Li; Kaicun Wang; Zeli Tan; Augusto Getirana. Flood Inundation Generation Mechanisms and Their Changes in 1953–2004 in Global Major River Basins. Journal of Geophysical Research: Atmospheres 2019, 124, 11672 -11692.
AMA StyleYuna Mao, Tian Zhou, L. Ruby Leung, Teklu K. Tesfa, Hong‐Yi Li, Kaicun Wang, Zeli Tan, Augusto Getirana. Flood Inundation Generation Mechanisms and Their Changes in 1953–2004 in Global Major River Basins. Journal of Geophysical Research: Atmospheres. 2019; 124 (22):11672-11692.
Chicago/Turabian StyleYuna Mao; Tian Zhou; L. Ruby Leung; Teklu K. Tesfa; Hong‐Yi Li; Kaicun Wang; Zeli Tan; Augusto Getirana. 2019. "Flood Inundation Generation Mechanisms and Their Changes in 1953–2004 in Global Major River Basins." Journal of Geophysical Research: Atmospheres 124, no. 22: 11672-11692.
The Gravity Recovery and Climate Experiment (GRACE) mission has provided us with unforeseen information on terrestrial water-storage (TWS) variability, contributing to our understanding of global hydrological processes, including hydrological extreme events and anthropogenic impacts on water storage. Attempts to decompose GRACE-based TWS signals into its different water storage layers, i.e., surface water storage (SWS), soil moisture, groundwater and snow, have shown that SWS is a principal component, particularly in the tropics, where major rivers flow over arid regions at high latitudes. Here, we demonstrate that water levels, measured with radar altimeters at a limited number of locations, can be used to reconstruct gridded GRACE-based TWS signals in the Amazon basin, at spatial resolutions ranging from 0.5 to 3, with mean absolute errors (MAE) as low as 2.5 cm and correlations as high as 0.98. We show that, at 3 spatial resolution, spatially-distributed TWS time series can be precisely reconstructed with as few as 41 water-level time series located within the basin. The proposed approach is competitive when compared to existing TWS estimates derived from physically based and computationally expensive methods. Also, a validation experiment indicates that TWS estimates can be extrapolated to periods beyond that of the model regression with low errors. The approach is robust, based on regression models and interpolation techniques, and offers a new possibility to reproduce spatially and temporally distributed TWS that could be used to fill inter-mission gaps and to extend GRACE-based TWS time series beyond its timespan.
Davi De C. D. Melo; Augusto Getirana. Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins. Remote Sensing 2019, 11, 2487 .
AMA StyleDavi De C. D. Melo, Augusto Getirana. Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins. Remote Sensing. 2019; 11 (21):2487.
Chicago/Turabian StyleDavi De C. D. Melo; Augusto Getirana. 2019. "Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins." Remote Sensing 11, no. 21: 2487.
Acute and chronic water scarcity impacts four billion people, a number likely to climb with population growth and increasing demand for food and energy production. Chronic water insecurity and long-term trends are well studied at the global and regional level; however, there have not been adequate systems in place for routinely monitoring acute water scarcity. To address this gap, we developed a monthly monitoring system that computes annual water availability per capita based on hydrologic data from the Famine Early Warning System Network (FEWS NET) Land Data Assimilation System (FLDAS) and gridded population data from WorldPop. The monitoring system yields maps of acute water scarcity using monthly Falkenmark classifications and departures from the long-term mean classification. These maps are designed to serve FEWS NET monitoring objectives; however, the underlying data are publicly available and can support research on the roles of population and hydrologic change on water scarcity at sub-annual and sub-national scales.
Amy McNally; Kristine Verdin; Laura Harrison; Augusto Getirana; Jossy Jacob; Shraddhanand Shukla; Kristi Arsenault; Christa Peters-Lidard; James P. Verdin. Acute Water-Scarcity Monitoring for Africa. Water 2019, 11, 1968 .
AMA StyleAmy McNally, Kristine Verdin, Laura Harrison, Augusto Getirana, Jossy Jacob, Shraddhanand Shukla, Kristi Arsenault, Christa Peters-Lidard, James P. Verdin. Acute Water-Scarcity Monitoring for Africa. Water. 2019; 11 (10):1968.
Chicago/Turabian StyleAmy McNally; Kristine Verdin; Laura Harrison; Augusto Getirana; Jossy Jacob; Shraddhanand Shukla; Kristi Arsenault; Christa Peters-Lidard; James P. Verdin. 2019. "Acute Water-Scarcity Monitoring for Africa." Water 11, no. 10: 1968.
The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water storage (TWS) product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM simulated groundwater correlates strongly with 12‐month precipitation anomalies in low and mid‐latitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional‐scale drought indicators, with discrepancies mainly in their estimated drought severity.
Bailing Li; Matthew Rodell; Sujay Kumar; Hiroko Kato Beaudoing; Augusto Getirana; Benjamin F. Zaitchik; Luis Gustavo De Goncalves; Camila Cossetin; Soumendra Bhanja; Abhijit Mukherjee; Siyuan Tian; Natthachet Tangdamrongsub; Di Long; Jamiat Nanteza; Jejung Lee; Frederick Policelli; Ibrahim B. Goni; Djoret Daira; Mohammed Bila; Gabriëlle De Lannoy; David Mocko; Susan C. Steele‐Dunne; Himanshu Save; Srinivas Bettadpur. Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges. Water Resources Research 2019, 55, 7564 -7586.
AMA StyleBailing Li, Matthew Rodell, Sujay Kumar, Hiroko Kato Beaudoing, Augusto Getirana, Benjamin F. Zaitchik, Luis Gustavo De Goncalves, Camila Cossetin, Soumendra Bhanja, Abhijit Mukherjee, Siyuan Tian, Natthachet Tangdamrongsub, Di Long, Jamiat Nanteza, Jejung Lee, Frederick Policelli, Ibrahim B. Goni, Djoret Daira, Mohammed Bila, Gabriëlle De Lannoy, David Mocko, Susan C. Steele‐Dunne, Himanshu Save, Srinivas Bettadpur. Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges. Water Resources Research. 2019; 55 (9):7564-7586.
Chicago/Turabian StyleBailing Li; Matthew Rodell; Sujay Kumar; Hiroko Kato Beaudoing; Augusto Getirana; Benjamin F. Zaitchik; Luis Gustavo De Goncalves; Camila Cossetin; Soumendra Bhanja; Abhijit Mukherjee; Siyuan Tian; Natthachet Tangdamrongsub; Di Long; Jamiat Nanteza; Jejung Lee; Frederick Policelli; Ibrahim B. Goni; Djoret Daira; Mohammed Bila; Gabriëlle De Lannoy; David Mocko; Susan C. Steele‐Dunne; Himanshu Save; Srinivas Bettadpur. 2019. "Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges." Water Resources Research 55, no. 9: 7564-7586.
The region of southern Africa (SA) has a fragile food economy and is vulnerable to frequent droughts. In 2015–2016, an El Niño-driven drought resulted in major maize production shortfalls, food price increases, and livelihood disruptions that pushed 29 million people into severe food insecurity. Interventions to mitigate food insecurity impacts require early warning of droughts – preferably as early as possible before the harvest season (typically, starting in April) and lean season (typically, starting in November). Hydrologic monitoring and forecasting systems provide a unique opportunity to support early warning efforts, since they can provide regular updates on available rootzone soil moisture (RZSM), a critical variable for crop yield, and provide forecasts of RZSM by combining the estimates of antecedent soil moisture conditions with climate forecasts. For SA, this study documents the predictive capabilities of a recently developed NASA Hydrological Forecasting and Analysis System (NHyFAS). The NHyFAS system's ability to forecast and monitor the 2015/2016 drought event is evaluated. The system's capacity to explain interannual variations in regional crop yield and identify below-normal crop yield events is also evaluated. Results show that the NHyFAS products would have identified the regional severe drought event, which peaked during December–February of 2015/2016, at least as early as 1 November 2015. Next, it is shown that February RZSM forecasts produced as early as 1 November (4–5 months before the start of harvest and about a year before the start of the next lean season) correlate fairly well with regional crop yields (r = 0.49). The February RZSM monitoring product, available in early March, correlates with the regional crop yield with higher skill (r = 0.79). It is also found that when the February RZSM forecast produced on November 1 is indicated to be in the lowest tercile, the detrended regional crop yield is below normal about two-thirds (significance level ~ 86 %) of the time. Furthermore, when the February RZSM monitoring product (available in early March) indicates a lowest tercile value, the crop yield is always below normal, at least over the sample years considered. These results indicate that the NHyFAS products can effectively support food insecurity early warning in the SA region.
Shraddhanand Shukla; Kristi R. Arsenault; Abheera Hazra; Christa Peters-Lidard; Randal D. Koster; Frank Davenport; Tamuka Magadzire; Chris Funk; Sujay Kumar; Amy McNally; Augusto Getirana; Greg Husak; Ben Zaitchik; Jim Verdin; Faka Dieudonne Nsadisa; Inbal Becker-Reshef. Improving early warning of drought-driven food insecurity in Southern Africa using operational hydrological monitoring and forecasting products. 2019, 2019, 1 -29.
AMA StyleShraddhanand Shukla, Kristi R. Arsenault, Abheera Hazra, Christa Peters-Lidard, Randal D. Koster, Frank Davenport, Tamuka Magadzire, Chris Funk, Sujay Kumar, Amy McNally, Augusto Getirana, Greg Husak, Ben Zaitchik, Jim Verdin, Faka Dieudonne Nsadisa, Inbal Becker-Reshef. Improving early warning of drought-driven food insecurity in Southern Africa using operational hydrological monitoring and forecasting products. . 2019; 2019 ():1-29.
Chicago/Turabian StyleShraddhanand Shukla; Kristi R. Arsenault; Abheera Hazra; Christa Peters-Lidard; Randal D. Koster; Frank Davenport; Tamuka Magadzire; Chris Funk; Sujay Kumar; Amy McNally; Augusto Getirana; Greg Husak; Ben Zaitchik; Jim Verdin; Faka Dieudonne Nsadisa; Inbal Becker-Reshef. 2019. "Improving early warning of drought-driven food insecurity in Southern Africa using operational hydrological monitoring and forecasting products." 2019, no. : 1-29.
Recent annual trends of precipitation and terrestrial water storage (TWS) in West Africa have been increasing over the past decade. Despite a significant impact of soil moisture on the TWS in West Africa, there is little research on the recent spatial and temporal behaviors of surface soil moisture (SSM) along with the hydrological trends and variability in West Africa. In this study, we assimilate TWS estimates from the Gravity Recovery and Climate Experiment (GRACE) mission into the Catchment Land Surface Model (CLSM) and evaluate its impacts on SSM simulations for the years, 2002–2017. The evaluation is performed using reference datasets: the African Monsoon Multidisciplinary Analysis (AMMA) in situ soil moisture observations, three currently available microwave satellite SSM observations from the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS), and the Soil Moisture Active Passive (SMAP) satellites and also the triple collocation analysis (TCA). Overall, modeled SSM shows good agreement with the reference datasets in terms of the anomaly SSM correlations. However, both modeled and ASCAT SSM are limited in their representation of the drying rates, as observed by ground observations, SMOS and SMAP estimates. Further, GRACE data assimilation results in improved SSM simulations in the humid regions with large annual TWS variability. This study demonstrates the utility of land data assimilation to inform hydrological conditions in West Africa, where soil moisture monitoring is necessary for water resource and livestock management.
Hahn Chul Jung; Augusto Getirana; Kristi R. Arsenault; Sujay Kumar; Issoufou Maigary. Improving surface soil moisture estimates in West Africa through GRACE data assimilation. Journal of Hydrology 2019, 575, 192 -201.
AMA StyleHahn Chul Jung, Augusto Getirana, Kristi R. Arsenault, Sujay Kumar, Issoufou Maigary. Improving surface soil moisture estimates in West Africa through GRACE data assimilation. Journal of Hydrology. 2019; 575 ():192-201.
Chicago/Turabian StyleHahn Chul Jung; Augusto Getirana; Kristi R. Arsenault; Sujay Kumar; Issoufou Maigary. 2019. "Improving surface soil moisture estimates in West Africa through GRACE data assimilation." Journal of Hydrology 575, no. : 192-201.
An evapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models.
Hahn Chul Jung; Augusto Getirana; Kristi R. Arsenault; Thomas R.H. Holmes; Amy McNally. Uncertainties in Evapotranspiration Estimates over West Africa. Remote Sensing 2019, 11, 892 .
AMA StyleHahn Chul Jung, Augusto Getirana, Kristi R. Arsenault, Thomas R.H. Holmes, Amy McNally. Uncertainties in Evapotranspiration Estimates over West Africa. Remote Sensing. 2019; 11 (8):892.
Chicago/Turabian StyleHahn Chul Jung; Augusto Getirana; Kristi R. Arsenault; Thomas R.H. Holmes; Amy McNally. 2019. "Uncertainties in Evapotranspiration Estimates over West Africa." Remote Sensing 11, no. 8: 892.
Tropical reservoirs are critical infrastructure for managing drinking and irrigation water and generating hydroelectric power. However, long-term spaceborne monitoring of reservoir storage is challenged by data scarcity from near-persistent cloud cover and drought, which may reduce volumes below those in the observational record. In evaluating our ability to accurately monitor long-term reservoir volume dynamics using spaceborne data and overcome such observational challenges, we integrated optical, lidar, and radar time series to estimate reservoir volume dynamics across 13 reservoirs in eastern Brazil over a 12-year (2003–2014) period affected by historic drought. We (i) used 1560 Landsat images to measure reservoir surface area; (ii) built reservoir-specific regression models relating surface area and elevation from ICESat GLAS and Envisat RA-2 data; (iii) modeled volume changes for each reservoir; and (iv) compared modeled and in situ reservoir volume changes. Regression models had high goodness-of-fit (median RMSE = 0.89 m and r = 0.88) across reservoirs. Even though 88% of an average reservoir’s volume time series was based on modeled area–elevation relationships, we found exceptional agreement (RMSE = 0.31 km3 and r = 0.95) with in situ volume time series, and accurately captured seasonal recharge/depletion dynamics and the drought’s prolonged drawdown. Disagreements in volume dynamics were neither driven by wet/dry season conditions nor reservoir capacity, indicating analytical efficacy across a range of monitoring scenarios.
Jamon Van Den Hoek; Augusto Getirana; Hahn Chul Jung; Modurodoluwa A. Okeowo; Hyongki Lee. Monitoring Reservoir Drought Dynamics with Landsat and Radar/Lidar Altimetry Time Series in Persistently Cloudy Eastern Brazil. Remote Sensing 2019, 11, 827 .
AMA StyleJamon Van Den Hoek, Augusto Getirana, Hahn Chul Jung, Modurodoluwa A. Okeowo, Hyongki Lee. Monitoring Reservoir Drought Dynamics with Landsat and Radar/Lidar Altimetry Time Series in Persistently Cloudy Eastern Brazil. Remote Sensing. 2019; 11 (7):827.
Chicago/Turabian StyleJamon Van Den Hoek; Augusto Getirana; Hahn Chul Jung; Modurodoluwa A. Okeowo; Hyongki Lee. 2019. "Monitoring Reservoir Drought Dynamics with Landsat and Radar/Lidar Altimetry Time Series in Persistently Cloudy Eastern Brazil." Remote Sensing 11, no. 7: 827.