scholarly journals Drought Events over the Amazon River Basin (1993–2019) as Detected by the Climate-Driven Total Water Storage Change

2021 ◽  
Vol 13 (6) ◽  
pp. 1124
Author(s):  
Kunjun Tian ◽  
Zhengtao Wang ◽  
Fupeng Li ◽  
Yu Gao ◽  
Yang Xiao ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Water Storage ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Severity Index ◽  
Least Square ◽  
Drought Severity ◽  
Total Water ◽  
New Perspective ◽  
Storage Change

The Gravity Recovery and Climate Experiment (GRACE) mission has measured total water storage change (TWSC) and interpreted drought patterns in an unparalleled way since 2002. Nevertheless, there are few sources that can be used to understand drought patterns prior to the GRACE era. In this study, we extended the gridded GRACE TWSC to 1993 by combining principal component analysis (PCA), least square (LS) fitting, and multiple linear regression (MLR) methods using climate variables as input drivers. We used the extended (climate-driven) TWSC to interpret drought patterns (1993–2019) over the Amazon basin. Results showed that, in the Amazon area with the resolution of 0.5°, GRACE, GRACE follow on, and Swarm had correlation coefficients of 0.95, 0.92, and 0.77 compared with climate-driven TWSCS, respectively. The drought patterns assessed by the climate-driven TWSC were consistent with those interpreted by the Palmer Drought Severity Index and GRACE TWSC. We also found that the 1998 and 2016 drought events in the Amazon, both induced by strong El Niño events, showed similar drought patterns. This study provides a new perspective for interpreting long-term drought patterns prior to the GRACE period.

Drought Patterns over the Amazon River Basin (1993-2019) as Interpreted by the Climate-driven Total Water Storage Change Fields

2020 ◽  
Author(s):  
Fupeng Li ◽  
Zhengtao Wang ◽  
Nengfang Chao ◽  
Wei Liang ◽  
Kunjun Tian ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Water Storage ◽  
Severity Index ◽  
Drought Severity ◽  
Total Water ◽  
Decadal Climate ◽  
New Perspective ◽  
Gravity Recovery ◽  
Grace Mission ◽  
Storage Change

<p><span>The Gravity Recovery and Climate Experiment (GRACE) mission, since 2002, has measured total water storage change (TWSC) and interpreted drought patterns in an unparalleled way. Nevertheless, there are still few sources could be used to understand drought patterns prior to the GRACE era. Here we derived multi-decadal climate-driven TWSC grids and used them to interpret drought patterns (1993-2019) over the Amazon basin. The correlations of climate-driven TWSC as compared to GRACE, GRACE Follow-on, and Swarm TWSC are 0.95, 0.92, and 0.77 in Amazon at grid scale (0.5° resolution). The drought patterns assessed by the climate-driven TWSC are consistent to those interpreted by the Palmer Drought Severity Index and GRACE TWSC. We also found that the 1998 and 2016 drought events in Amazon, both induced by the strong El Niño events, show similar drought patterns. This study provides a new perspective for interpreting long-term drought patterns prior to the GRACE period.</span></p>

Estimating the water balance and uncertainty bounds in a highly groundwater-dependent and data-scarce areas: An example for the upper Citarum basin

2021 ◽  
Author(s):  
Steven Reinaldo Rusli ◽  
Albrecht Weerts ◽  
Victor Bense
Keyword(s):  
Water Balance ◽  
Water Storage ◽  
Total Water ◽  
Groundwater Abstraction ◽  
Water Balance Components ◽  
Groundwater Storage ◽  
Actual Evaporation ◽  
Basin Scale ◽  
Basin Water ◽  
Storage Change

<p>In this study, we estimate the water balance components of a highly groundwater-dependent and hydrological data-scarce basin of the upper reaches of the Citarum river in West Java, Indonesia. Firstly, we estimate the groundwater abstraction volumes based on population size and a review of literature (0.57mm/day). Estimates of other components like rainfall, actual evaporation, discharge, and total water storage changes are derived from global datasets and are simulated using a distributed hydrological wflow_sbm model which yields additional estimates of discharge, actual evaporation, and total water storage change. We compare each basin water balance estimate as well as quantify the uncertainty of some of the components using the Extended Triple Collocation (ETC) method.</p><p>The ETC application on four different rainfall estimates suggests a preference of using the CHIRPS product as the input to the water balance components estimates as it delivers the highest r<sup>2</sup>  and the lowest RMSE compared to three other sources. From the different data sources and results of the distributed hydrological modeling using CHIRPS as rainfall forcing, we estimate a positive groundwater storage change between 0.12 mm/day - 0.60 mm/day. These results are in agreement with groundwater storage change estimates based upon GRACE gravimetric satellite data, averaged at 0.25 mm/day. The positive groundwater storage change suggests sufficient groundwater recharge occurs compensating for groundwater abstraction. This conclusion seems in agreement with the observation since 2005, although measured in different magnitudes. To validate and narrow the estimated ranges of the basin water storage changes, a devoted groundwater model is necessary to be developed. The result shall also aid in assessing the current and future basin-scale groundwater level changes to support operational water management and policy in the Upper Citarum basin.</p>

scholarly journals Global trends in visibility: implications for dust sources

2007 ◽  
Vol 7 (12) ◽  
pp. 3309-3339 ◽  
Author(s):  
N. M. Mahowald ◽  
J. A. Ballantine ◽  
J. Feddema ◽  
N. Ramankutty
Keyword(s):  
Land Use ◽  
Human Impacts ◽  
Dominant Role ◽  
Surface Wind ◽  
Correlation Coefficients ◽  
Severity Index ◽  
Drought Severity ◽  
Climate Indices ◽  
Desert Dust ◽  
Dust Sources

Abstract. There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. We did this by looking at time series of visibility derived variables and their correlations with precipitation, drought, winds, land use and grazing. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 357 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility-derived variables and AERONET optical depths indicate a moderate correlation (0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility-derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the Palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility-derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with VIS5 or EXT, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974–2003.

A Multi-decadal Analysis of Reservoir Storage Change in Developing Regions

2021 ◽  
Keyword(s):  
Reservoir Operation ◽  
Storage Capacity ◽  
Assessment Tool ◽  
Severity Index ◽  
Drought Severity ◽  
Developing Regions ◽  
Reservoir Storage ◽  
Historical Observation ◽  
Reservoir Assessment ◽  
Storage Change

Abstract The limited amount of shared reservoir monitoring data around the world is insufficient to quantify the dynamic nature of reservoir operation with conventional ground-based methods. With the emergence of the Reservoir Assessment Tool (RAT) driven by a multitude of earth observing satellites and models, historical observation of reservoir operation spanning 35 years was made using open-source techniques. Trends in reservoir storage change were compared with trends of four critical hydrologic variables (precipitation, runoff, evaporation, and Palmer Drought Severity Index) to understand the potential role of natural drivers in altering reservoir operating pattern. It was found that the reservoirs in Africa were losing active storage at a rate of more than 1% per year of total storage capacity. Smaller reservoirs (with a capacity of less than 0.5 km3) in South-East Asia were found to experience a sharp gain in storage of 0.5% to 1% per year of total storage capacity. Storage change trends of large reservoirs with multiple years of residence time that are designed for strategic water supply needs and drought control were found to be less affected by precipitation trends and influenced more by drought and evaporation trends. Over Africa, most reservoir storage change trends were dictated by evaporation trends, while South Asian reservoirs appear to have their storage change influenced by drought and evaporation trends. Finally, findings suggest that operation of newer reservoirs are more sensitive to long-term hydrological trends and the regulated surface water variability that is controlled by older dams in the upstream.

scholarly journals Long-term Total Water Storage Change from a SAtellite Water Cycle (SAWC) reconstruction over large south Asian basins

2019 ◽  
Author(s):  
Victor Pellet ◽  
Filipe Aires ◽  
Fabrice Papa ◽  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
Water Resources ◽  
Climate Variability ◽  
Water Cycle ◽  
Water Storage ◽  
Anthropogenic Pressure ◽  
Total Water ◽  
Storage Change ◽  
Discharge Measurements

Abstract. The Total Water Storage Change (TWSC) over land is a major component of the global water cycle, with a large influence on climate variability, sea level budget and water resources availability for human life. Its first estimates at large-scale were made available with GRACE observations for the 2002–2016 period, followed since 2018 by the launch of GRACE-FO mission. In this paper, using an approach based on the water mass conservation rule, we proposed to merge satellite-based observations of precipitation and evapotranspiration along with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources, and for which long term record of in situ discharge measurements are available. Our SAtellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP model simulations (1980–2015), and (3) multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived data sets along with in situ data to perform hydrologically coherent reconstruction of missing water component estimate. It provides a new critical source of information for long term monitoring of TWSC and to better understand their critical role in the global and terrestrial water cycle.

scholarly journals Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins

2020 ◽  
Vol 24 (6) ◽  
pp. 3033-3055
Author(s):  
Victor Pellet ◽  
Filipe Aires ◽  
Fabrice Papa ◽  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
Climate Variability ◽  
Water Cycle ◽  
Critical Role ◽  
Water Storage ◽  
Anthropogenic Pressure ◽  
Total Water ◽  
Storage Change ◽  
Discharge Measurements

Abstract. The total water storage change (TWSC) over land is a major component of the global water cycle, with a large influence on the climate variability, sea level budget and water resource availability for human life. Its first estimates at a large scale were made available with GRACE (Gravity Recovery and Climate Experiment) observations for the 2002–2016 period, followed since 2018 by the launch of the GRACE-FO (Follow-On) mission. In this paper, using an approach based on the water mass conservation rule, we propose to merge satellite-based observations of precipitation and evapotranspiration with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources and for which long-term records of in situ discharge measurements are available. Our Satellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP (Interactions between Soil, Biosphere and Atmosphere CNRM – Centre National de Recherches Météorologiques – Total Runoff Integrating Pathways) model simulations (1980–2015) and (3) the multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived datasets along with in situ data to perform a hydrologically coherent reconstruction of a missing water component estimate. It provides a new critical source of information for the long-term monitoring of TWSC and to better understand its critical role in the global and terrestrial water cycle.

Data-driven and physically informed modelling of the Terrestrial Water Storage dynamics 

2021 ◽  
Author(s):  
Karim Douch ◽  
Peyman Saemian ◽  
Nico Sneeuw
Keyword(s):  
Transition Matrix ◽  
Amazon Basin ◽  
Stochastic Matrix ◽  
Water Storage ◽  
Water Volume ◽  
Terrestrial Water Storage ◽  
Total Water ◽  
Monthly Basis ◽  
Terrestrial Water ◽  
Volume Anomaly

<p>The Gravity Recovery and Climate Experiment (GRACE) mission, and its successor GRACE Follow-On, have enabled to map on a monthly basis the Terrestrial Water Storage Anomaly (TWSA) since 2002. This unprecedented capability has provided hydrologists with new observations of the spatiotemporal evolution of TWSA, which have been used, among others, to better constrain numerical runoff models, to characterize empirically the relations between runoff and TWSA, or to simply monitor and quantify groundwater depletions. In this study, we explore the possibility to infer from GRACE observations a physically informed and linear dynamical system that models the intrinsic dynamics of TWSA at sub-basin scales.</p><p>First, we apply a hexagonal binning over the study area and aggregate the total water volume anomaly derived from GRACE data for each bin. Assuming that each bin exchanges water with the others in proportion to its water content, we then reformulate the mass balance equation of the whole basin as a first order matrix differential equation. All the proportionality coefficients encoding the bin exchanges are gathered in an unknown transition matrix to be determined.  Such a transition matrix must satisfy different algebraic properties to be physically consistent and interpretable. In particular, we show that this matrix is necessarily a left stochastic matrix. Finally, we used the time series of total water volume anomaly to estimate this transition matrix by solving an optimization problem on the manifold defined by the aforementioned matrix constraint. This method is applied to the Amazon basin and to mainland Australia respectively, and the predictive performances of the derived dynamical systems are quantified and discussed.</p>

scholarly journals Assessing vegetation response to drought in the Laohahe catchment, North China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 91-101 ◽  
Author(s):  
Xiaofan Liu ◽  
Liliang Ren ◽  
Fei Yuan ◽  
Jing Xu ◽  
Wei Liu
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Correlation Coefficients ◽  
Meteorological Drought ◽  
Growing Season ◽  
Severity Index ◽  
Drought Severity ◽  
Seasonal Effect ◽  
Vegetation Types ◽  
The Relationship

In order to better understand the relationship between vegetation vigour and moisture availability, a correlation analysis based on different vegetation types was conducted between time series of monthly Normalized Difference Vegetation Index (NDVI) and Palmer Drought Severity Index (PDSI) during the growing season from April to October within the Laohahe catchment. It was found that NDVI had good correlation with PDSI, especially for shrub and grass. The correlation between NDVI and PDSI varies significantly from one month to another. The highest value of correlation coefficients appears in June when the vegetation is growing; lower correlations are noted at the end of growing season for all vegetation types. The influence of meteorological drought on vegetation vigour is stronger in the first half of the growing season, before the vegetation reaches the peak greenness. In order to take the seasonal effect into consideration, a regression model with seasonal dummy variables was used to simulate the relationship between NDVI and PDSI. The results showed that the NDVI–PDSI relationship is significant (α = 0.05) within the growing season, and that NDVI is an effective indicator to monitor and detect droughts if seasonal timing is taken into account.

scholarly journals Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins

2019 ◽  
Vol 11 (21) ◽  
pp. 2487 ◽  
Author(s):  
Melo ◽  
Getirana
Keyword(s):  
Time Series ◽  
Amazon Basin ◽  
Anthropogenic Impacts ◽  
Water Storage ◽  
Principal Component ◽  
Water Levels ◽  
Terrestrial Water Storage ◽  
Validation Experiment ◽  
Physically Based ◽  
Terrestrial Water

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.

scholarly journals Growth response of Abies spectabilis to climate along an elevation gradient of the Manang valley in the central Himalayas

2019 ◽  
Vol 31 (6) ◽  
pp. 2245-2254 ◽  
Author(s):  
Samresh Rai ◽  
Binod Dawadi ◽  
Yafeng Wang ◽  
Xiaoming Lu ◽  
Huang Ru ◽  
...  
Keyword(s):  
Tree Ring ◽  
Elevation Gradient ◽  
Ring Width ◽  
Principal Component ◽  
Moisture Stress ◽  
Severity Index ◽  
Forest Growth ◽  
Drought Severity ◽  
Tree Ring Width ◽  
Standard Tree

Abstract The Himalayas are characterized by a broad gradient of bioclimatic zones along their elevation. However, less is known how forest growth responds to climatic change along elevation. In this study, four standard tree-ring width chronologies of Himalayan fir (Abiesspectabilis) were developed, spanning 142–649 years along an elevation gradient of 3076–3900 m a.s.l. Principal component analysis classified the four chronologies into two groups; the ones at lower elevations (M1 and M2) and higher elevations (M3 and M4) show two distinct growth trends. Radial growth is limited by summer (June–August) precipitation at M3, and by precipitation during spring (March–May) and summer at M4. It is limited by spring temperatures and winter precipitation (December–February) at M1. Tree-ring width chronologies also significantly correlate with winter and spring Palmer Drought Severity Index (PDSI) at M1, and with summer PDSI at M3 and M4. Thus, Himalayan fir growth at high elevations is mainly limited by moisture stress rather than by low temperatures. Furthermore, the occurrence of missing rings coincides with dry periods, providing additional evidence for moisture limitation of Himalayan fir growth.

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