Spatio-temporal trend and homogeneity analysis of gridded and gauge precipitation in Indravati River basin, India

2018 ◽  
Vol 11 (1) ◽  
pp. 178-199 ◽  
Author(s):  
Ch. Praveenkumar ◽  
V. Jothiprakash
Keyword(s):  
River Basin ◽  
Time Scales ◽  
Time Scale ◽  
India Meteorological Department ◽  
Rainfall Data ◽  
Trend Test ◽  
Poor Correlation ◽  
Homogeneity Analysis ◽  
Grid Data ◽  
Spatio Temporal

Abstract The study aims to analyze spatio-temporal variations in rainfall data over Indravati River basin, India. Three rainfall data sets, Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), India Meteorological Department (IMD) grid, and IMD gauge were used. Data from 2001 to 2013 were analyzed for three time scales, namely, daily, monthly, and annual. Analysis showed good correlation between IMD gauge and TMPA grid rainfall at monthly time scale, poor correlation is observed at daily and annual time scales. Mann–Kendall (MK) trend test reveals a significant increasing trend of IMD gauge and IMD grid data, whereas TMPA rainfall is free from trends at the majority of stations for daily time scale. Nevertheless, both IMD grid as well as TMPA grid rainfall can be considered as a better representative of rainfall, since it is attained from observed rainfall data over the country. The Pettitt and standard normal homogeneity tests show that TMPA rainfall has a more non-homogeneous nature, whereas IMD grid rainfall and IMD gauge rainfall data are homogeneous. Overall, the trend and homogeneity analysis indicate that TMPA grid and IMD grid rainfall is in line with IMD gauge data, however IMD grid rainfall has the edge over TMPA grid data.

Time-scale dependent mechanism of atmospheric CO2 concentration drivers of watershed water-energy balance

2021 ◽  
Author(s):  
Jing Zhao
Keyword(s):  
Energy Balance ◽  
River Basin ◽  
Time Scales ◽  
Time Scale ◽  
Hydrological Processes ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
The Wei River Basin ◽  
Balance Dynamics ◽  
The Impact

<p>The elevated atmospheric carbon dioxide concentration (CO<sub>2</sub>), as a key variable linking human activities and climate change, seriously affects the watershed hydrological processes. However, whether and how atmospheric CO<sub>2</sub> influences the watershed water-energy balance dynamics at multiple time scales have not been revealed. Based on long-term hydrometeorological data, the variation of non-stationary parameter n series in the Choudhury's equation in the mainstream of the Wei River Basin (WRB), the Jing River Basin (JRB) and Beiluo River Basin (BLRB), three typical Loess Plateau regions in China, was examined. Subsequently, the Empirical Mode Decomposition method was applied to explore the impact of CO<sub>2</sub> on watershed water-energy balance dynamics at multiple time scales. Results indicate that (1) in the context of warming and drying condition, annual n series in the WRB displays a significantly increasing trend, while that in the JRB and BLRB presents non-significantly decreasing trends; (2) the non-stationary n series was divided into 3-, 7-, 18-, exceeding 18-year time scale oscillations and a trend residual. In the WRB and BLRB, the overall variation of n was dominated by the residual, whereas in the JRB it was dominated by the 7-year time scale oscillation; (3) the relationship between CO<sub>2 </sub>concentration and n series was significant in the WRB except for 3-year time scale. In the JRB, CO<sub>2 </sub>concentration and n series were significantly correlated on the 7- and exceeding 7-year time scales, while in the BLRB, such a significant relationship existed only on the 18- and exceeding 18-year time scales. (4) CO<sub>2</sub>-driven temperature rise and vegetation greening elevated the aridity index and evaporation ratio, thus impacting watershed water-energy balance dynamics. This study provided a deeper explanation for the possible impact of CO<sub>2</sub> concentration on the watershed hydrological processes.</p>

Watershed water-energy balance dynamics and their association with diverse influencing factors at multiple time scales

2020 ◽  
Author(s):  
Shengzhi Huang ◽  
Jing Zhao ◽  
Kang Ren
Keyword(s):  
Energy Balance ◽  
Influencing Factors ◽  
River Basin ◽  
Time Scales ◽  
Time Scale ◽  
Dynamic Change ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Plateau Region ◽  
Balance Dynamics

<p>The Budyko curve is an effective tool for estimating how precipitation (P) partition into evapotranspiration (E) and streamflow (Q). Controlling the shape of the Budyko curve, the Budyko parameter represents the superimposed impact of various periodic factors (including climatic factors, catchment characteristics, teleconnection factors and anthropogenic activities) on the watershed water-energy balance dynamics, and such superimposed impact is not conducive to identifying the driving factors of the dynamic change of Budyko parameter at different time scales, and thus affect the parameter estimation. Here we obtain the dynamic change of Budyko parameter for the Wei River Basin (WRB)-a typical Loess Plateau region in China based on a 11-years moving window, and then adopt the Empirical Mode Decomposition (EMD) method to reveal the relationships between influencing factors and Budyko parameter series at multiple time scales by considering the interplay among different influencing factors. Results indicate that (1) Budyko parameter series are decomposed into 4-, 12-, 20-, exceeding 20-year time scale oscillations and a residual component with an significantly increasing trend in the upstream of the WRB (UWR) and the middle and lower reaches of the WRB (MDWR), a non-significantly decreasing trend in the Jing River Basin (JRB) and Beiluo River Basin (BLRB); (2) by analyzing the residual trend component, evaporation ratio (E/P), soil moisture (SM) and effective irrigated area (EIA) are found to induce the significant increase of parameter in the UWR, whereas that in the MDWR is dominated by baseflow (BF) and Niño 3.4; (3) parameter dynamics at the 4-year time scale is dominated by E/P, aridity index (E<sub>P</sub>/P), BF and SM; BF, PDO and sunspots attribute to the dynamics at 12-year time scale; all the factors except BF and SM contribute to the dynamics at 20- or exceeding 20-year time scales. The results of this study will help identify the connection between watershed water-energy balance dynamics and changing environment at multiple time scales, and also be beneficial for guiding water resources management and ecological development planning on the Loess Plateau region.</p>

Exploring Temporal Rainfall Variability and Trends Over a Tropical Region Using Tropical Rainfall Measurement Mission (TRMM) and Observatory Data

2021 ◽  
Vol 5 (2) ◽  
pp. 56-71
Author(s):  
Anu David Raj ◽  
K. R. Sooryamol ◽  
Aju David Raj
Keyword(s):  
Time Scales ◽  
Water Resource Management ◽  
Rainfall Variability ◽  
Winter Season ◽  
India Meteorological Department ◽  
Southwest Monsoon ◽  
Rainfall Data ◽  
Tropical Rainfall Measurement Mission ◽  
Tropical Rainfall ◽  
Observatory Data

Kerala is the gateway of the Indian southwest monsoon. The Tropical Rainfall Measurement Mission (TRMM) rainfall data is an efficient approach to rainfall measurement. This study explores the temporal variability in rainfall and trends over Kerala from 1998-2019 using TRMM data and observatory data procured from India Meteorological Department (IMD). Direct comparison with observatory data at various time scales proved the reliability of the TRMM data (monthly, seasonal and annual). The temporal rainfall converted by averaging the data on an annual, monthly and seasonal time scale, and the results have confirmed that the rainfall estimated based on satellite data is dependable. The station wise comparison of rainfall in monsoon season provides satisfactory results. However, estimation of rainfall in mountainous areas is challenging task using the TRMM. In the basins of humid tropical regions, TRMM data can be a valuable source of rainfall data for water resource management and monitoring with some vigilance. In Kerala, the study found an insignificant increase in the southwest monsoon and winter season rainfall during last two decades. The rainfall over Kerala showed uncertainty in the distribution of monthly, seasonal and yearly time scales. This study provides a preview of recent weather patterns that would enable us to make better decisions and improve public policy against climate change.

scholarly journals Multi-scale event synchronization analysis for unravelling climate processes: A wavelet-based approach

2017 ◽  
Author(s):  
Ankit Agarwal ◽  
Norbert Marwan ◽  
Maheswaran Rathinasamy ◽  
Bruno Merz ◽  
Jürgen Kurths
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Time Scale ◽  
Temporal Dynamics ◽  
Multiple Scales ◽  
Nonlinear Interactions ◽  
Reference Time ◽  
Multi Scale ◽  
Spatio Temporal ◽  
Different Time Scales

Abstract. The temporal dynamics of climate processes are spread across different time scales and, as such, the study of these processes only at one selected time scale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. For capturing the nonlinear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analyse the time series at one reference time scale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, wavelet based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various time scales. The proposed method allows the study of spatio-temporal patterns across different time scales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different time scales.

Spatio-temporal variability in Ebro river basin (NE Spain): Global SST as potential source of predictability on decadal time scales

2011 ◽  
Vol 409 (3-4) ◽  
pp. 759-775 ◽  
Author(s):  
S.R. Gámiz-Fortis ◽  
J.M. Hidalgo-Muñoz ◽  
D. Argüeso ◽  
M.J. Esteban-Parra ◽  
Y. Castro-Díez
Keyword(s):  
River Basin ◽  
Time Scales ◽  
Temporal Variability ◽  
Ebro River ◽  
Potential Source ◽  
Spatio Temporal ◽  
Ne Spain

HOMOGENEITY ANALYSIS OF RAINFALL IN KELANTAN, MALAYSIA

2015 ◽  
Vol 76 (15) ◽  
Author(s):  
Ng Jing Lin ◽  
Samsuzana Abd Aziz ◽  
Huang Yuk Feng ◽  
Aimrun Wayayok ◽  
Md Rowshon Kamal
Keyword(s):  
River Basin ◽  
Monthly Rainfall ◽  
Rainfall Series ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Homogeneity Test ◽  
Ratio Test ◽  
Homogeneity Analysis ◽  
Standard Normal Homogeneity Test ◽  
Kelantan River Basin

Good quality of rainfall data is required for the hydrological studies, water resources planning and sustainable environmental management. Consequently, the assessment of the homogeneity of rainfall data at different region is becoming increasing popular in the past few decades. In this study, the homogeneity analysis of rainfall data was carried out in Kelantan River Basin, Malaysia. The methods, namely standard normal homogeneity test (SHNT), Buishand range test, Pettitt test and von Neumann ratio test were applied to the monthly, yearly and seasonal data. The historical rainfall data from 10 rainfall stations covering the study period from 28 to 60 years were selected. The four tests were applied to 120 monthly series, 10 yearly series and 40 seasonal series. ‘Useful’, ‘doubtful’ and ‘suspect’ were used to classify the results of the four tests. The results showed that 94.17% of the monthly rainfall series, 70% of yearly rainfall series and 97.5% of seasonal rainfall series are labelled ‘useful’. There is 5% of monthly rainfall series, 30% of yearly rainfall series and 1% of seasonal rainfall series are classified as ‘doubtful’. Meanwhile, there is only 0.83% of monthly rainfall series and no yearly rainfall series and seasonal rainfall series detected in the class ‘suspect’. Overall, the percentage of inhomogeneity detected in the monthly, yearly and seasonal rainfall data series of Kelantan River Basin is very small, thus most of the data is suitable to be used for further hydrological and variability analysis.

scholarly journals Linking climate change to soil loss estimation in the Kosi river basin, India

2021 ◽  
Author(s):  
Aadil Towheed ◽  
Thendiyath Roshni
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Soil Loss ◽  
General Circulation ◽  
General Circulation Models ◽  
Rainfall Data ◽  
Rainfall Runoff ◽  
Rainfall Analysis ◽  
Time Period ◽  
Spatio Temporal

Abstract This study assessed the spatio-temporal variability of soil loss based on rainfall–runoff erosivity in the context of climate change in the Kosi river basin. The observed rainfall data (1985–2017) were used for past and present analyses, and the projected rainfall data (2020–2100) interpolated for various general circulation models (GCMs) were used for future analysis. The results of rainfall analysis for the projected period show a maximum percentage variation of 26.2% for a particular GCM and an average of 9.4% increase in the rainfall data from all selected GCMs considering three representative concentration pathways (RCPs). We also evaluated the implications of change in the soil loss due to changes in the rainfall pattern and crop management factor for three time slices. The results for the projected time period showed a concomitant increase in the average soil loss of −13.03–10.39% with respect to the baseline. The average soil loss results for the time period of 2020–2100 are also compared with the average soil loss for each RCP scenario and found very meager changes in the area of soil erosion. The results due to climate change aid in prioritizing the areas with suitable conservation support practices.

scholarly journals Development of IDF-curves for tropical india by random cascade modeling

2013 ◽  
Vol 10 (4) ◽  
pp. 4709-4738 ◽  
Author(s):  
A. Rana ◽  
L. Bengtsson ◽  
J. Olsson ◽  
V. Jothiprakash
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Efficient Design ◽  
Daily Data ◽  
Current Design ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Fine Time

Abstract. Efficient design of urban drainage systems is based on statistical analysis of past rainfall events at fine time scales. However, fine time scale rainfall data are usually lacking in many parts of the world. A possible way forward is to develop methods to derive fine time scale rain intensities from daily observations. This paper applied cascade-based disaggregation modeling for generation of fine time scale rainfall data for Mumbai, India from daily rainfall data. These data were disaggregated to 10-min values. The model was used to disaggregate daily data for the period 1951–2004 and develop intensity-duration-frequency (IDF) relationships. This disaggregation technique is commonly used assuming scale-invariance using constant parameters. For the Mumbai rains it was found better to use parameters dependent on time scale and rain volume. Very good agreement between modeled and observed disaggregation series was found for the time scales larger than 1/2 h for the 1/2-yr period when short term data were available. Although the parameters were allowed to change with time scale, the rain intensities of duration shorter than 1/2 h were overestimated. When IDF-curves had been established, they showed that the current design standard for Mumbai city, 25 mm h−1, has a return period of less than one year. Thus, annual recurring flooding problems in Mumbai appear evident.

scholarly journals Standardized Water Budget Index and Validation in Drought Estimation of Haihe River Basin, North China

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Shaohua Liu ◽  
Denghua Yan ◽  
Hao Wang ◽  
Chuanzhe Li ◽  
Baisha Weng ◽  
...  
Keyword(s):  
River Basin ◽  
Time Scales ◽  
Time Scale ◽  
Water Budget ◽  
Drought Index ◽  
Multiple Time Scales ◽  
Haihe River Basin ◽  
Drought Indices ◽  
Multiple Time ◽  
Haihe River

The physical-based drought indices such as the self-calibrated Palmer Drought Severity Index (sc-PDSI) with the fixed time scale is inadequate for the multiscalar drought assessment, and the multiscalar drought indices including Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), and Standardized Precipitation Evapotranspiration Index (SPEI) based on the meteorological factors are lack of physical mechanism and cannot depict the actual water budget. To fill this gap, the Standardized Water Budget Index (SWBI) is constructed based on the difference between areal precipitation and actual evapotranspiration (AET), which can describe the actual water budget but also assess the drought at multiple time scales. Then, sc-PDSI was taken as the reference drought index to compare with multiscalar drought indices at different time scale in Haihe River basin. The result shows that SWBI correlates better with sc-PDSI and the RMSE of SWBI is less than other multiscalar drought indices. In addition, all of drought indices show a decreasing trend in Haihe River Basin, possibly due to the decreasing precipitation from 1961 to 2010. The decreasing trends of SWBI were significant and consistent at all the time scales, while the decreasing trends of other multiscalar drought indices are insignificant at time scale less than 3 months.

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