20th Century District-level Spatio-Temporal Annual Rainfall Changes Over West Bengal

2018 ◽  
Vol 4 (2) ◽  
pp. 31-39 ◽  
Author(s):  
Lalu Das ◽  
Hanuman Prasad ◽  
Jitendra Kumar Meher
Keyword(s):  
20Th Century ◽  
West Bengal ◽  
District Level ◽  
Annual Rainfall ◽  
Spatio Temporal

How to assess the vulnerability and the risk of flooding of the most important catchment in the Republic of Djibouti?

2021 ◽  
Author(s):  
Golab Moussa Omar ◽  
Jean-Emmanuel Paturel ◽  
Christian Salles ◽  
Gil Mahe ◽  
Mohamed Jalludin
Keyword(s):  
Temporal Variability ◽  
Groundwater Resources ◽  
Annual Rainfall ◽  
Series Data ◽  
Boreal Summer ◽  
Precipitation Regime ◽  
Daily Data ◽  
Spatio Temporal ◽  
The Republic ◽  
Rainy Days

<p><span>This study focus on the catchment of Ambouli wadi which is one of the country’s largest watersheds covering 794 km² (3.5 % of the total area of the Republic of Djibouti). Because of its groundwater resources, this exoreic watershed is of major importance. Indeed, the aquifer is the main source of drinking water supply for the city of Djibouti-city. In addition, this wadi is also responsible for floods causing human suffering and severe economic damages. Despite the importance of the catchment for the development of Djibouti-city, Ambouli wadi has been the subject of few scientific studies. This partly explains the scarcity of rainfall stations and therefore data in this area. Analysis of the spatio-temporal variability of rainfall is required to assess the risk of flooding. </span></p><p><span>In an arid country like the Republic of Djibouti flash floods are an important concern for the management of water resources systems and risk prevention and protection. The desertic climate of the country is characterized by high levels of temperature and evaporation, and also by very weak and irregular annual rainfall, distributed in two major seasons : a cooler season (from October to March) with high relative humidity and low temperatures comprised between 22°C and 30°C, and a hot and dry season (from June to September). </span></p><p><span>Rain data were collected from a network of 9 raingauge stations at different time scales, from monthly to hourly. These data are provided by the national meteorological agency (4 stations) and the early warning system of CERD National Research Center (5 stations).</span></p><p><span> </span><span>The spatio-temporal variability of rainfall, is characterized using the Standardized Precipitation Index (SPI) and the analysis of rainfall normals over 30 years (1951-1980 and 1961-1990). Long time series data were available from 4 of the 9 stations: (Djibouti-serpent, Djibouti-aeorodrome, Oueah and Arta). At annual scale, the variability is clearly described by a succession of dry and humid years. Also, the monthly rainfall clearly demonstrates the well-known bimodal precipitation regime of east Africa. It shows, two peaks corresponding to the « long rain » and the « short rain » rainy seasons, which correspond to the period of March-April-May and of October-November-December, respectively. On the other hand, we also observe a dry period which is characterized by a rainfall deficit (negative rainfall index for almost all the stations) corresponding to the boreal summer (June to September). </span><span>Daily data is currently collecting from the Djibouti-aerodrome station (1981-2017) for a better understanding of the precipitation regime. Rainy days are computed from daily data (rainfall > 1 mm) and we find an annual average of 11 wet days with a minimum in 1988 (1 rainy day) and a maximum in 1993 (23 rainy days). </span></p>

scholarly journals Spatio-temporal modeling of surface runoff in ungauged sub-catchments of Subarnarekha river basin using SWAT

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 597-606
Author(s):  
CHINMAYA PANDA ◽  
DWARIKA MOHAN DAS ◽  
B. C. SAHOO ◽  
B. PANIGRAHI ◽  
K. K. SINGH
Keyword(s):  
Surface Runoff ◽  
Assessment Tool ◽  
Nutrient Loss ◽  
Coefficient Of Determination ◽  
Annual Rainfall ◽  
Model Parameters ◽  
Runoff Generation ◽  
Temporal Modeling ◽  
Spatio Temporal ◽  
R Factors

In this present study, Soil and Water Assessment Tool (SWAT) embedded with ArcGIS interface has been used to simulate the surface runoff from the un-gauged sub-catchments in the upper catchment of Subarnarekha basin. Model calibration and validation were performed with the help of Sequential Uncertainty Fitting (SUFI-2) in-built in the SWAT-CUP package (SWAT Calibration Uncertainty Programs). The model was calibrated for a period from 1996 to 2008 with 3 years warm up period (1996-1998) and validated for a period of 5 years from 2009 to 2013. The model evaluation was performed by Nash - Sutcliffe coefficient (NSE), Coefficient of determination (R2) and Percentage Bias (PBIAS). The degree of uncertainty was evaluated by P and R factors. Basing upon the R2, NSE and PBIAS values respectively, of the order of 0.90, 0.90 and -12%, during calibration and 0.85, 0.83 and -15% during validation, substantiate performance of the model. All uncertainties of model parameters have been well taken by the P and R factors respectively, of the order of 0.95 and 0.77 during calibration and 0.82 and 0.87 during validation. The runoff generation from 19 sub-catchments of Adityapur catchment varies from 29.2-44.1% of the annual rainfall and average surface runoff simulated for the entire catchment is 545 mm. As the surface runoff generated in most of the sub-catchments amounts to above 30% of rainfall, it is recommended for adequate number of structural interventions at appropriate locations in the catchment to store the rainfall excess for providing irrigation, recharging groundwater and restricting the sediment and nutrient loss.

scholarly journals Spatio-Temporal Variability and Trend of Rainfall and Its Association with Pacific Ocean Sea Surface Temperature in West Harerge Zone, Eastern Ethiopia

2020 ◽  
Author(s):  
Getachew Bayable Tiruneh ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw
Keyword(s):  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Variability ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Annual Rainfall ◽  
Eastern Ethiopia ◽  
Spatio Temporal ◽  
Annual Time

Abstract Background: Rainfall variability is a common characteristic in Ethiopia and it exceedingly affects agriculture particularly in the eastern parts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatio-temporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.Method: The coefficient of variation (CV) and standardized anomaly index (SAI) was employed to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by the Pearson correlation coefficient (r).Results: The annual rainfall CV ranges from 12-19.36% while the seasonal rainfall CV extends from 15-28.49%, 24-35.58%, and 38-75.9% for average Kiremt (June-September), Belg (February-May), and Bega (October-January) seasons, respectively (1983-2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends of rainfall were not statistically significant (α = 0.05), unlike November. The annual rainfall trends showed a non-significant decreasing trend. On a seasonal basis, the trend of mean Kiremt and Belg seasons rainfall was decreased. But, it increased in Bega season although it was not statistically significant. Moreover, the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, the correlation between rainfall and Pacific Ocean SST was negative at annual time scales.Conclusions: High spatial and temporal rainfall variability on monthly, seasonal, and annual time scales was observed in the study area. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall was increased annually and in the Bega season rather than other seasons. Generally, the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

“Fatally Tied Together”: The Intertwined History of Kurds and Armenians in the 20th Century

2019 ◽  
Vol 23 (4) ◽  
pp. 390-406
Author(s):  
David Leupold
Keyword(s):  
National Identity ◽  
20Th Century ◽  
Armenian Genocide ◽  
Binary Coding ◽  
History Of ◽  
Spatio Temporal ◽  
Perpetrators And Victims ◽  
Kurdish Question ◽  
Kurdish Issue ◽  
Geographical Space

More than a century years ago Talât Pasha declared famously that in the Eastern Provinces “The Armenian question does not exist anymore”. Today, far from being resolved, the former binary coding (Armenian/Turkish) is even further complicated by a third element— the ongoing Kurdish question (doza Kurdistanê). While most research and journalistic works frame the Armenian issue and the Kurdish issue as two separate events that merely coincide(d) in the same geographical space, this work explores their interdependence and the historical trajectories of two peoples fatally “tied together” across a spatio-temporal scale. In my paper I identify two opposing lines of continuity through which both peoples are tied together: friendly and fatal ties. With regard to the first (friendly ties), I turn to the SSR Armenia and her role in fostering Kurdish culture and advancing Kurdish nationalism. Hereby, I argue that a marginalized community of Kurmanji-speakers—the Yezidis, previously othered as “devil-worshippers” (şeytanperest)— emerged as the vanguard in forging a novel, secularized Kurdish national identity. With regard to the latter (fatal ties), I link the irrevocable erasure of Ottoman Armenians to the emergence of an imagined “Northern Kurdistan” stretching over large parts of historic Armenia. This, finally, raises the question of Kurdish complicity in the Armenian Genocide—as state-mobilized regiments, tribal members and ordinary residents—in a geography where, as Recep Maraşlı put it, the descendants “are the children of both perpetrators and victims alike”.

scholarly journals An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine

2020 ◽  
Vol 12 (4) ◽  
pp. 709 ◽  
Author(s):  
Abhishek Banerjee ◽  
Ruishan Chen ◽  
Michael E. Meadows ◽  
R.B. Singh ◽  
Suraj Mal ◽  
...  
Keyword(s):  
River Basin ◽  
Temporal Trends ◽  
Google Earth ◽  
Monthly Rainfall ◽  
Annual Rainfall ◽  
Google Earth Engine ◽  
Spatio Temporal ◽  
Uttarakhand Himalaya ◽  
Rainy Days

This paper analyses the spatio-temporal trends and variability in annual, seasonal, and monthly rainfall with corresponding rainy days in Bhilangana river basin, Uttarakhand Himalaya, based on stations and two gridded products. Station-based monthly rainfall and rainy days data were obtained from the India Meteorological Department (IMD) for the period from 1983 to 2008 and applied, along with two daily rainfall gridded products to establish temporal changes and spatial associations in the study area. Due to the lack of more recent ground station rainfall measurements for the basin, gridded data were then used to establish monthly rainfall spatio-temporal trends for the period 2009 to 2018. The study shows all surface observatories in the catchment experienced an annual decreasing trend in rainfall over the 1983 to 2008 period, averaging 15.75 mm per decade. Analysis of at the monthly and seasonal trend showed reduced rainfall for August and during monsoon season as a whole (10.13 and 11.38 mm per decade, respectively); maximum changes were observed in both monsoon and winter months. Gridded rainfall data were obtained from the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). By combining the big data analytical potential of Google Earth Engine (GEE), we compare spatial patterns and temporal trends in observational and modelled precipitation and demonstrate that remote sensing products can reliably be used in inaccessible areas where observational data are scarce and/or temporally incomplete. CHIRPS reanalysis data indicate that there are in fact three significantly distinct annual rainfall periods in the basin, viz. phase 1: 1983 to 1997 (relatively high annual rainfall); phase 2: 1998 to 2008 (drought); phase 3: 2009 to 2018 (return to relatively high annual rainfall again). By comparison, PERSIANN-CDR data show reduced annual and winter precipitation, but no significant changes during the monsoon and pre-monsoon seasons from 1983 to 2008. The major conclusions of this study are that rainfall modelled using CHIRPS corresponds well with the observational record in confirming the decreased annual and seasonal rainfall, averaging 10.9 and 7.9 mm per decade respectively between 1983 and 2008, although there is a trend (albeit not statistically significant) to higher rainfall after the marked dry period between 1998 and 2008. Long-term variability in rainfall in the Bhilangana river basin has had critical impacts on the environment arising from water scarcity in this mountainous region.

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