scholarly journals A novel soil moisture‐based drought severity index (DSI) combining water deficit magnitude and frequency

2015 ◽  
Vol 30 (2) ◽  
pp. 289-301 ◽  
Author(s):  
Carmelo Cammalleri ◽  
Fabio Micale ◽  
Jürgen Vogt
Keyword(s):  
Soil Moisture ◽  
Water Deficit ◽  
Severity Index ◽  
Drought Severity ◽  
Drought Severity Index

scholarly journals Drought Analysis in the Yellow River Basin Based on a Short-Scalar Palmer Drought Severity Index

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1526 ◽  
Author(s):  
Ye Zhu ◽  
Yi Liu ◽  
Xieyao Ma ◽  
Liliang Ren ◽  
Vijay Singh
Keyword(s):  
Soil Moisture ◽  
Time Scale ◽  
Palmer Drought Severity Index ◽  
Yellow River ◽  
Severity Index ◽  
Yellow River Basin ◽  
Drought Severity ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Drought Severity Index

Focusing on the shortages of moisture estimation and time scale in the self-calibrating Palmer drought severity index (scPDSI), this study proposed a new Palmer variant by introducing the Variable Infiltration Capacity (VIC) model in hydrologic accounting module, and modifying the standardization process to make the index capable for monitoring droughts at short time scales. The performance of the newly generated index was evaluated over the Yellow River Basin (YRB) during 1961–2012. For time scale verification, the standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) at a 3-month time scale were employed. Results show that the new Palmer variant is highly correlated with SPI and SPEI, combined with a more stable behavior in drought frequency than original scPDSI. For drought trend detection, this new index is more inclined to reflect comprehensive moisture conditions and reveals a different spatial pattern from SPI and SPEI in winter. Besides, two remote sensing products of soil moisture and vegetation were also employed for comparison. Given their general consistent behaviors in monitoring the spatiotemporal evolution of the 2000 drought, it is suggested that the new Palmer variant is a good indicator for monitoring soil moisture variation and the dynamics of vegetation growth.

scholarly journals Evaluating the Performance of Palmer Drought Severity Index (PDSI) In Various Vegetation Regions of the Ethiopian Highlands

2021 ◽  
Vol 4 (2) ◽  
pp. 14-31
Author(s):  
Polina Lemenkova
Keyword(s):  
Soil Moisture ◽  
Wind Speed ◽  
Palmer Drought Severity Index ◽  
Environmental Parameters ◽  
Severity Index ◽  
Drought Severity ◽  
Topographic Effects ◽  
Vegetation Monitoring ◽  
Ethiopian Highlands ◽  
Drought Severity Index

Abstract This paper focuses on the environment of Ethiopia, a country highly sensitive to droughts severely affecting vegetation. Vegetation monitoring of Ethiopian Highlands requires visualization of environmental parameters to assess droughts negatively influencing agricultural sustainable management of crops. Therefore, this study presented mapping of several climate and environmental variables including Palmer Drought Severity Index (PDSI). The data were visualized and interpreted alongside the topographic data to evaluate the environmental conditions for vegetation. The datasets included WorldClim and GEBCO and Digital Chart of the World (DCW). Research has threefold objectives: i) environmental mapping; ii) technical cartographic scripting; iii) data processing. Following variables were visualized on seven new maps: 1) topography; 2) soil moisture; 3) T °C minimum; 4) T °C maximum; 5) Wind speed; 6) Precipitation; 7) Palmer Drought Severity Index (PDSI). New high-resolution thematic environmental maps are presented and the utility of GMT for mapping multi-source datasets is described. With varying degrees of soil moisture (mean value of 15.0), min T°C (−1.8°C to 24°C), max T°C (14.4°C to 40.2°C) and wind speed (0.1 to 6.1 m/s), the maps demonstrate the variability of the PDSI fields over the country area (from −11.7 to 2.3) induced by the complex sum of these variables and intensified by the topographic effects notable over the Ethiopian Highlands which can be used for vegetation analysis. The paper presents seven new maps and contributes to the environmental studies of Ethiopia.

scholarly journals Application of Improved Remotely Sensed Drought Severity Index Based on Soil Moisture Product in Inner Mongolia

SOLA ◽  
2020 ◽  
Vol 16 (0) ◽  
pp. 259-264
Author(s):  
Lusha Wang ◽  
Ayumi Kotani ◽  
Takafumi Tanaka ◽  
Takeshi Ohta
Keyword(s):  
Soil Moisture ◽  
Inner Mongolia ◽  
Severity Index ◽  
Remotely Sensed ◽  
Drought Severity ◽  
Drought Severity Index

scholarly journals The Modified Palmer Drought Severity Index Based on the NCEP North American Regional Reanalysis

2006 ◽  
Vol 45 (10) ◽  
pp. 1362-1375 ◽  
Author(s):  
Kingtse C. Mo ◽  
Muthuvel Chelliah
Keyword(s):  
Soil Moisture ◽  
North American ◽  
Palmer Drought Severity Index ◽  
Grid Point ◽  
Severity Index ◽  
Drought Severity ◽  
Total Soil ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis ◽  
Drought Severity Index

Abstract A 32-km high-resolution modified Palmer drought severity index (MPDSI) based on the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (RR) from 1979 to 2004 is presented. The assumptions of Palmer, such as the water balance equation, the difference between observed precipitation and the climatologically expected precipitation over the maximum conditions, and the changes of the index as a function of the current index, are preserved. Many deficiencies of the original PDSI are eliminated by taking fields directly from the RR or by making better estimates. For example, fields such as potential evapotranspiration, evaporation, runoff, total soil moisture, and soil moisture change in a given month are obtained directly from the RR. The potential recharge is defined as the total soil moisture needed to reach the maximum total soil moisture at each grid point for each calendar month. The potential precipitation is defined as the maximum precipitation at each grid point for a given calendar month. The underground volumetric soil moisture includes both frozen and liquid form. Therefore, the contribution of snowmelt is taken into account inexplicitly. The questionable assumptions of two-layer soil model and the available soil moisture capacity are no longer needed. Overall, the MPDSI, when averaged over a large area and long time, often resembles the traditional PDSI based on the Palmer formula and the climate-division data. The MPDSI obeys Gaussian distribution, and so it can also be used to assess the potential for floods. Together with a consistent suite of soil moisture, surface energy, and atmospheric terms from the RR, the MPDSI can be used to monitor and diagnose drought and floods.

scholarly journals A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship with Soil Moisture and Effects of Surface Warming

2004 ◽  
Vol 5 (6) ◽  
pp. 1117-1130 ◽  
Author(s):  
Aiguo Dai ◽  
Kevin E. Trenberth ◽  
Taotao Qian
Keyword(s):  
Soil Moisture ◽  
Palmer Drought Severity Index ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Severity Index ◽  
Drought Severity ◽  
Surface Warming ◽  
Precipitation Decrease ◽  
Global Land ◽  
Drought Severity Index

Abstract A monthly dataset of Palmer Drought Severity Index (PDSI) from 1870 to 2002 is derived using historical precipitation and temperature data for global land areas on a 2.5° grid. Over Illinois, Mongolia, and parts of China and the former Soviet Union, where soil moisture data are available, the PDSI is significantly correlated (r = 0.5 to 0.7) with observed soil moisture content within the top 1-m depth during warm-season months. The strongest correlation is in late summer and autumn, and the weakest correlation is in spring, when snowmelt plays an important role. Basin-averaged annual PDSI covary closely (r = 0.6 to 0.8) with streamflow for seven of world's largest rivers and several smaller rivers examined. The results suggest that the PDSI is a good proxy of both surface moisture conditions and streamflow. An empirical orthogonal function (EOF) analysis of the PDSI reveals a fairly linear trend resulting from trends in precipitation and surface temperature and an El Niño– Southern Oscillation (ENSO)-induced mode of mostly interannual variations as the two leading patterns. The global very dry areas, defined as PDSI < −3.0, have more than doubled since the 1970s, with a large jump in the early 1980s due to an ENSO-induced precipitation decrease and a subsequent expansion primarily due to surface warming, while global very wet areas (PDSI > +3.0) declined slightly during the 1980s. Together, the global land areas in either very dry or very wet conditions have increased from ∼20% to 38% since 1972, with surface warming as the primary cause after the mid-1980s. These results provide observational evidence for the increasing risk of droughts as anthropogenic global warming progresses and produces both increased temperatures and increased drying.

scholarly journals Analyzing Trend and Pattern of Agricultural Drought: A Case Study of Karnali and Sudurpashchim Provinces

2021 ◽  
Vol 20 (1) ◽  
pp. 1-8
Author(s):  
Naresh Bista ◽  
Dikpal Mahat ◽  
Sachin Manandhar ◽  
Binayak Regmi ◽  
Uma Shankar Panday ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Severity Index ◽  
Agricultural Drought ◽  
Drought Severity ◽  
Modis Ndvi ◽  
Ecological Zones ◽  
Evapotranspiration Rate ◽  
Drought Severity Index

A drought is a period of time when an area or region experiences below-normal precipitation, with characteristics and impacts that can vary from region to region. Agricultural Drought analyzes and reflects the extent of the soil moisture and morphology of crop. Deficient rainfall in the winter of 2008 resulted in a severe drop in crop production right across the country. So, there is a necessity of assessment of drought events to make informed and timely decisions. The main focus of our study is to monitor the agricultural drought in Karnali and Sudurpashchim provinces of Nepal. The condition of drought in Karnali and Sudurpashchim provinces from 2001- 2020 were analysed with the help of Drought Severity Index. MODIS NDVI (MOD13) and MODIS ET-PET (MOD16) datasets were used to monitor and analyze the trend and pattern of agricultural drought scenario. Both datasets were then normalized for DSI calculation and the DSI result was used to monitor and to analyze the trend and pattern in the agricultural drought scenario. Further, trend and pattern analyses were performed in terms of landcover, ecological zones, and the variation of DSI. After completion of this project, we can conclude that the Maximum dryness was found in March, it might be due to less NDVI and increase in evapotranspiration rate and maximum wetness in November. Agricultural area experienced more drought variation than other landcover zones

scholarly journals Analysis of wet and dry season by using the Palmer Drought Severity Index (PDSI) over Java Island

2021 ◽  
Author(s):  
Sinta Berliana S. ◽  
Indah Susanti ◽  
Bambang Siswanto ◽  
Amalia Nurlatifah ◽  
Hidayatul Latifah ◽  
...  
Keyword(s):  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Dry Season ◽  
Drought Severity ◽  
Drought Severity Index
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