Soil moisture-based drought monitoring at different time scales: a case study for the U.S. Great Plains

2015 ◽  
Vol 52 (1) ◽  
pp. 77-88 ◽  
Author(s):  
T.A. Engda ◽  
T.J. Kelleners
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Great Plains ◽  
Drought Monitoring ◽  
The U.S ◽  
Different Time Scales

scholarly journals Quantifying the Land–Atmosphere Coupling Behavior in Modern Reanalysis Products over the U.S. Southern Great Plains

2015 ◽  
Vol 28 (14) ◽  
pp. 5813-5829 ◽  
Author(s):  
Joseph A. Santanello ◽  
Joshua Roundy ◽  
Paul A. Dirmeyer
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Southern Great Plains ◽  
Diurnal Cycles ◽  
The North ◽  
Energy Cycle ◽  
Coupling Behavior ◽  
Regional Reanalysis ◽  
Modern Era ◽  
The U.S

Abstract The coupling of the land with the planetary boundary layer (PBL) on diurnal time scales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve understanding of land–atmosphere (L–A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land–PBL coupling at the process level. In this paper, the authors apply a suite of local land–atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-yr period over the U.S. southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation is applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface–PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land–PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. Each RA has a unique land–PBL coupling that has implications for downstream impacts on the diurnal cycle of PBL evolution, clouds, convection, and precipitation as well as representation of extremes and drought. As a result, caution should be used when treating RAs as truth in terms of their water and energy cycle processes.

A novel index for ecological drought monitoring based on ecological water deficit: a case study of Northwestern China

2021 ◽  
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su
Keyword(s):  
Water Deficit ◽  
Time Scales ◽  
Drought Index ◽  
Vegetation Index ◽  
Standardized Precipitation Index ◽  
Northwestern China ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Different Time Scales

<p>Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982–2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI<sub></sub>= 0.34, SSI<sub></sub>= 0.24, scPDSI<sub></sub>= 0.23, SPI<sub></sub>= 0.20, SPEI<sub></sub>= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982–1986, 1990–1996, and 2005–2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.</p>

scholarly journals Drought Monitoring in Chaharmahl-Bakhtiyari Province in Iran

2017 ◽  
Vol 32 (4) ◽  
pp. 615-621 ◽  
Author(s):  
Hamid Mohammadi ◽  
Mojgan Abasi ◽  
Javad Bazrafshan
Keyword(s):  
Time Scales ◽  
Normal Level ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Maximum Frequency ◽  
Drought Duration ◽  
Resources Management ◽  
Drought Occurrence ◽  
Different Time Scales ◽  
Selection Of

Abstract The monitoring of drought is the most important factor in water resources management. This study focuses on evaluation of the drought characteristics such as intensity, frequency and duration drought using Standardized Precipitation Index (SPI) in different time scales such as: SPI1, SPI3 months, during 1980-2012. The results show that selection of different time scales can be based on management goals and kind of drought. The results of the drought occurrence frequency showed that, with increase of length of time scales, drought duration will increase and maximum frequency was at the normal level and there is no particular procedure in different time scales. Furthermore, Drought patterns maps showed that the northern and central parts of study area had experienced these recent droughts more than other places, and these place have potential to destroy the lands. So, by identification of sensitivity regions can be take appropriate management to prevent damage resulting of drought.

scholarly journals Predicting U.S. Drought Monitor States Using Precipitation, Soil Moisture, and Evapotranspiration Anomalies. Part I: Development of a Nondiscrete USDM Index

2017 ◽  
Vol 18 (7) ◽  
pp. 1943-1962 ◽  
Author(s):  
David J. Lorenz ◽  
Jason A. Otkin ◽  
Mark Svoboda ◽  
Christopher R. Hain ◽  
Martha C. Anderson ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Goodness Of Fit ◽  
Forecasting Methods ◽  
Different Seasons ◽  
Numerous Data ◽  
Empirical Methodology ◽  
Probability Density Function Pdf ◽  
Drought Classes ◽  
The U.S

Abstract The U.S. Drought Monitor (USDM) classifies drought into five discrete dryness/drought categories based on expert synthesis of numerous data sources. In this study, an empirical methodology is presented for creating a nondiscrete USDM index that simultaneously 1) represents the dryness/wetness value on a continuum and 2) is most consistent with the time scales and processes of the actual USDM. A continuous USDM representation will facilitate USDM forecasting methods, which will benefit from knowledge of where, within a discrete drought class, the current drought state most probably lies. The continuous USDM is developed such that the actual discrete USDM can be reconstructed by discretizing the continuous USDM based on the 30th, 20th, 10th, 5th, and 2nd percentiles—corresponding with USDM definitions for the D4–D0 drought classes. Anomalies in precipitation, soil moisture, and evapotranspiration over a range of different time scales are used as predictors to estimate the continuous USDM. The methodology is fundamentally probabilistic, meaning that the probability density function (PDF) of the continuous USDM is estimated and therefore the degree of uncertainty in the fit is properly characterized. Goodness-of-fit metrics and direct comparisons between the actual and predicted USDM analyses during different seasons and years indicate that this objective drought classification method is well correlated with the current USDM analyses. In Part II, this continuous USDM index will be used to improve intraseasonal USDM intensification forecasts because it is capable of distinguishing between USDM states that are either far from or near to the next-higher drought category.

Soil Moisture Influence on the Incidence of Summer Mesoscale Convective Systems in the U.S. Great Plains

2021 ◽  
Author(s):  
Rachel Gaal ◽  
James L. Kinter
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Large Scale ◽  
Mesoscale Convective Systems ◽  
Antecedent Soil Moisture ◽  
Initiation Point ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
The U.S

AbstractMesoscale convective systems (MCS) are known to develop under ideal conditions of temperature and humidity profiles and large-scale dynamic forcing. Recent work, however, has shown that summer MCS events can occur under weak synoptic forcing or even unfavorable large-scale environments. When baroclinic forcing is weak, convection may be triggered by anomalous conditions at the land surface. This work evaluates land surface conditions for summer MCS events forming in the U.S. Great Plains using an MCS database covering the contiguous United States east of the Rocky Mountains, in boreal summers 2004-2016. After isolating MCS cases where synoptic-scale influences are not the main driver of development (i.e. only non-squall line storms), antecedent soil moisture conditions are evaluated over two domain sizes (1.25° and 5° squares) centered on the mean position of the storm initiation. A negative correlation between soil moisture and MCS initiation is identified for the smaller domain, indicating that MCS events tend to be initiated over patches of anomalously dry soils of ~100-km scale, but not significantly so. For the larger domain, soil moisture heterogeneity, with anomalously dry soils (anomalously wet soils) located northeast (southwest) of the initiation point, is associated with MCS initiation. This finding is similar to previous results in the Sahel and Europe that suggest that induced meso-β circulations from surface heterogeneity can drive convection initiation.

Trend analysis of streamflow with different time scales: a case study of the upper Senegal River

2017 ◽  
Vol 24 (1) ◽  
pp. 105-114 ◽  
Author(s):  
Lamine Diop ◽  
Zaher Mundher Yaseen ◽  
Ansoumana Bodian ◽  
Koffi Djaman ◽  
Larry Brown
Keyword(s):  
Trend Analysis ◽  
Time Scales ◽  
Senegal River ◽  
Different Time Scales

scholarly journals Evaluating the impacts of environmental factors on soil moisture temporal dynamics at different time scales

2020 ◽  
Author(s):  
Qi Chai ◽  
Tiejun Wang ◽  
Chongli Di
Keyword(s):  
Soil Moisture ◽  
Environmental Factors ◽  
Time Scales ◽  
Temporal Dynamics ◽  
Soil Moisture Dynamics ◽  
Temporal Variance ◽  
The Impact ◽  
Moisture Dynamics ◽  
Different Time Scales

Abstract Soil moisture displays complex spatiotemporal patterns across scales, making it important to disentangle the impacts of environmental factors on soil moisture temporal dynamics at different time scales. This study evaluated the factors affecting soil moisture dynamics at different time scales using long-term soil moisture data obtained from Nebraska and Utah. The empirical mode decomposition method was employed to decompose soil moisture time series into different temporal components with several intrinsic mode functions (IMFs) and one residual component. Results showed that the percent variance contribution (PVC) of IMFs to the total soil moisture temporal variance tended to increase for the IMFs with longer time periods. It indicated that the long-term soil moisture variations in study regions were mainly determined by low-temporal frequency signals related to seasonal climate and vegetation variations. Besides, the PVCs at short- and medium-temporal ranges were positively correlated with climate dryness, while negatively at longer temporal ranges. Moreover, the results suggested that the impact of climate on soil moisture dynamics at different time scales might vary across different climate zones, while soil effect was comparatively less in both regions. It provides additional insights into understanding soil moisture temporal dynamics in regions with contrasting climatic conditions.

scholarly journals The Physics of Drought in the U.S. Central Great Plains

2016 ◽  
Vol 29 (18) ◽  
pp. 6783-6804 ◽  
Author(s):  
Ben Livneh ◽  
Martin P. Hoerling
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Growing Season ◽  
Surface Model ◽  
Moisture Conditions ◽  
Soil Moisture Variability ◽  
The U.S ◽  
Rainfall Deficits ◽  
Moisture Variability

Abstract The semiarid U.S. Great Plains is prone to severe droughts having major consequences for agricultural production, livestock health, and river navigation. The recent 2012 event was accompanied by record deficits in precipitation and high temperatures during the May–August growing season. Here the physics of Great Plains drought are explored by addressing how meteorological drivers induce soil moisture deficits during the growing season. Land surface model (LSM) simulations driven by daily observed meteorological forcing from 1950 to 2013 compare favorably with satellite-derived terrestrial water anomalies and reproduce key features found in the U.S. Drought Monitor. Results from simulations by two LSMs reveal that precipitation was directly responsible for between 72% and 80% of the soil moisture depletion during 2012, and likewise has accounted for the majority of Great Plains soil moisture variability since 1950. Energy balance considerations indicate that a large fraction of the growing season temperature variability is itself driven by precipitation, pointing toward an even larger net contribution of precipitation to soil moisture variability. To assess robustness across a larger sample of drought events, daily meteorological output from 1050 years of climate simulations, representative of conditions in 1979–2013, are used to drive two LSMs. Growing season droughts, and low soil moisture conditions especially, are confirmed to result principally from rainfall deficits. Antecedent meteorological and soil moisture conditions are shown to affect growing season soil moisture, but their effects are secondary to forcing by contemporaneous rainfall deficits. This understanding of the physics of growing season droughts is used to comment on plausible Great Plains soil moisture changes in a warmer world.

Sign in / Sign up

Export Citation Format

Share Document