scholarly journals Bangladesh; GIS; Meteorological drought; Rainfall data; Spatial analysis; SPI

2018 ◽  
Vol 09 (03) ◽  
Author(s):  
Abdullah Al Mamun ◽  
Md Niaz Farhat Rahman ◽  
Md Abdullah Aziz ◽  
Md Abdul Qayum ◽  
Md Ismail Hossain ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Meteorological Drought ◽  
Rainfall Data

scholarly journals Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

2011 ◽  
Vol 24 (8) ◽  
pp. 2025-2044 ◽  
Author(s):  
Martha C. Anderson ◽  
Christopher Hain ◽  
Brian Wardlow ◽  
Agustin Pimstein ◽  
John R. Mecikalski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Drought Index ◽  
Temporal Correlation ◽  
Meteorological Drought ◽  
Rainfall Data ◽  
Added Value ◽  
Stress Index ◽  
Drought Indices ◽  
Shallow Water Table

Abstract The reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–09 growing seasons. Spatial and temporal correlation analyses suggest that the ESI performs similarly to short-term (up to 6 months) precipitation-based indices but can be produced at higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall: for example, in areas of intense irrigation or shallow water table. Normalization by PET serves to isolate the ET signal component responding to soil moisture variability from variations due to the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.

scholarly journals Spatial Interpolation on Rainfall Data over Peninsular Malaysia Using Ordinary Kriging

2013 ◽  
Vol 63 (2) ◽  
Author(s):  
Suhaila Jamaludin ◽  
Hanisah Suhaimi
Keyword(s):  
Spatial Analysis ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Rainfall Intensity ◽  
Peninsular Malaysia ◽  
Rainfall Data ◽  
Kriging Method ◽  
Intensity Index ◽  
Dry Conditions ◽  
Two Indices

This study presents the spatial analysis of the rainfall data over Peninsular Malaysia. 70 rainfall stations were utilized in this study. Due to the limited number of rainfall stations, the Ordinary Kriging method which is one of the techniques in Spatial Interpolation was used to estimate the values of the rainfall data and to map their spatial distribution. This spatial analysis was analysed according to the two indices that describe the wet events and another two indices that characterize dry conditions. Large areas at the east experienced high rainfall intensity compared to the areas in the west, northwest and southwest. The small value that has been obtained in Aridity Intensity Index (AII) reflects that the high amount of rainfall in the eastern areas is not contributed by low-intensity events (less than 25th percentile). In terms of number of consecutive dry days, Northwestern areas in Peninsular Malaysia recorded the highest value. This finding explains the occurrence of a large number of floods and soil erosions in the eastern areas.

Modelling Catchment Rainfall Using Sum of Correlated Gamma Variables

2013 ◽  
Vol 63 (2) ◽  
Author(s):  
Zakaria, R. ◽  
Howlett, P. G. ◽  
Piantadosi, J. ◽  
Boland, J. W. ◽  
Moslim, N. H.
Keyword(s):  
Spatial Analysis ◽  
Random Variables ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Weighted Sum ◽  
Statistical Parameters ◽  
Dependent Random Variables ◽  
Rainfall Model

One of the major difficulties in simulating rainfall is the need to accurately represent rainfall accumulations. An accurate simulation of monthly rainfall should also provide an accurate simulation of yearly rainfall by summing the monthly totals. A major problem in this regard is that rainfall distributions for successive months may not be independent. Thus the rainfall accumulation problem must be represented as the summation of dependent random variables. This study is aimed to show if the statistical parameters for several stations within a particular catchment is known, then a weighted sum is used to determine a rainfall model for the entire local catchment. A spatial analysis for the sum of rainfall volumes from four selected meteorological stations within the same region using the monthly rainfall data is conducted. The sum of n correlated gamma variables is used to model the sum of monthly rainfall totals from four stations when there is significant correlation between the stations.

Spatial analysis of meteorological drought in Chhattisgarh State

2017 ◽  
Vol 32 (2) ◽  
pp. 94
Author(s):  
Hemant Kumar Sinha ◽  
J.L. Chaudhary ◽  
N. Manikandan ◽  
Shiv Kumar Bhuarya
Keyword(s):  
Spatial Analysis ◽  
Meteorological Drought

Application of FY-2 precipitation data in meteorological drought monitoring of the Weihe river basin

2014 ◽  
Vol 11 (5) ◽  
pp. 487-494
Author(s):  
Yujuan Wang ◽  
Shudong Wang ◽  
Shengtian Yang ◽  
Yuling Zhao ◽  
Mingcheng Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Meteorological Drought ◽  
Precipitation Anomaly ◽  
Rainfall Data ◽  
Drought Monitoring ◽  
Precipitation Data ◽  
Spatial Continuity ◽  
Macro Scale ◽  
Weihe River ◽  
Weihe River Basin

The remote sensing data have become the irreplaceable source of data for the regions with little or without rainfall data, but these data also require scientific analysis, correction and application. This paper uses FY-2 rainfall data and the case studies of the droughts occurred in the Weihe River Basin from 2006 to 2009 to monitor the spatial and temporal evolution of climatic droughts. The monitoring results indicate that: (1) Except for 2008 which was a dry year, the other years in the Weihe River Basin had normal dry/wet conditions; (2) From October 2008 to January 2009, the rainfall was significantly reduced across the Weihe River Basin, and the continual rainfall was even less than 1 mm for December and January with a precipitation anomaly percentage lower than -80%, a sign of severe climatic drought. But the rainfall has improved since February 2009, when the precipitation reached 17.8 mm and Pa exceeded 100%, which helped to relieve the stress from drought resistance. A heavy precipitation continued for four months from June to September 2008, with the Pa exceeding 50%; (3) Due to the better temporal and spatial continuity than the ground-based meteorological observation, FY-2 precipitation data have good application prospects in the meteorological drought monitoring at a national or regional macro-scale.

scholarly journals A TIME-SERIES AND SPATIAL ANALYSIS OF 56 YEARS (1961–2017) OF RAINFALL HISTORICAL DATA FROM MALAYBALAY, BUKIDNON

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 71-76
Author(s):  
B. J. Buenaobra ◽  
M. K. L. Alleto ◽  
J. M. V. Manhuyod
Keyword(s):  
Time Series ◽  
Spatial Analysis ◽  
Null Hypothesis ◽  
Historical Data ◽  
Rainfall Data ◽  
Computational Method ◽  
P Value ◽  
Time Domain Signal ◽  
Augmented Dickey Fuller ◽  
Stationarity Test

Abstract. This paper focuses on using time series and spatial analysis methods to detect climate change indicators in Malaybalay, Bukidnon. We look at 56 years of historical rainfall data between the years 1961 to 2017 and perform a computational method for data processing to arrive at spatial statistics and provide data visualization. We demonstrate the use of the Augmented Dickey-Fuller test (ADF), where a p-value is tested versus a threshold to reject or accept the null hypothesis for a stationarity test. For the seasonality test, we perform a time-domain signal processing by an autocorrelation function. The time-series analysis shows that for Malaybalay, Bukidnon rainfall data shows ADF statistic of −16.348964, a p-value = 0.000000 with critical values 1%:−3.431, 5%:−2.862, 10%:−2.567. Hence, the significant negative values indicate more likely to reject the null hypothesis. We showed that rainfall does not demonstrate periodicity, is not seasonal, and is non-stationary. This work does not cover those that can be detected and attributed to anthropogenic causes.

scholarly journals Fluctuating Rainfall, Persistent Food Crisis—Use of Rainfall Data in the Kenyan Drought Early Warning System

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1328
Author(s):  
Sofie Sandström ◽  
Sirkku Juhola ◽  
Aleksi Räsänen
Keyword(s):  
Early Warning ◽  
Food Systems ◽  
Qualitative Content Analysis ◽  
Warning System ◽  
Meteorological Drought ◽  
Early Warning Systems ◽  
Rainfall Data ◽  
Humanitarian Crises ◽  
Drought Early Warning ◽  
Systems Framework

Early warning systems (EWSs) have been developed to trigger timely action to disasters, yet persistent humanitarian crises resulting from hazards such as drought indicate that these systems need improvements. We focus our research on the county of Turkana in Kenya, where drought repeatedly results in humanitarian crises, especially with regard to food insecurity. Focusing on the key elements of the Kenyan EWS, we ask two questions: firstly, what indicators, especially meteorological drought indicators, are used in the national biannual assessments conducted by the Kenyan National Drought Management Authority and monthly drought bulletins for Turkana? Secondly, are there differences in the methodology used for analysis of meteorological indicators in the different documents? Firstly, by utilizing a food systems framework, we conduct qualitative content analysis of the use of indicators in the documents; secondly, we analyze rainfall data and its use. The EWS relies primarily on food availability indicators, with less focus for food access and utilization. The biannual assessments and the country bulletins use different sets of rainfall data and different methodologies for establishing the climate normal, leading to discrepancies in the output of the EWS. We recommend further steps to be taken towards standardization of methodologies and cooperation between various institutions to ensure streamlining of approaches.

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