scholarly journals Evaluation and Comparison of Satellite-Derived Estimates of Rainfall in the Diverse Climate and Terrain of Central and Northeastern Ethiopia

2021 ◽  
Vol 13 (7) ◽  
pp. 1275
Author(s):  
Girma Berhe Adane ◽  
Birtukan Abebe Hirpa ◽  
Chul-Hee Lim ◽  
Woo-Kyun Lee
Keyword(s):  
River Basin ◽  
Hydrological Cycle ◽  
Rainfall Data ◽  
Data Availability ◽  
Trend Test ◽  
Climate Data ◽  
Significance Level ◽  
Monotonic Trend ◽  
Mk Test ◽  
Satellite Rainfall

Understanding rainfall processes as the main driver of the hydrological cycle is important for formulating future water management strategies; however, rainfall data availability is challenging for countries such as Ethiopia. This study aims to evaluate and compare the satellite rainfall estimates (SREs) derived from tropical rainfall measuring mission (TRMM 3B43v7), rainfall estimation from remotely sensed information using artificial neural networks—climate data record (PERSIANN-CDR), merged satellite-gauge rainfall estimate (IMERG), and the Global Satellite Mapping of Precipitation (GSMaP) with ground-observed data over the varied terrain of hydrologically diverse central and northeastern parts of Ethiopia—Awash River Basin (ARB). Areal comparisons were made between SREs and observed rainfall using various categorical indices and statistical evaluation criteria, and a non-parametric Mann–Kendall (MK) trend test was analyzed. The monthly weighted observed rainfall exhibited relatively comparable results with SREs, except for the annual peak rainfall shifts noted in all SREs. The PERSIANN-CDR products showed a decreasing trend in rainfall at elevations greater than 2250 m above sea level in a river basin. This demonstrates that elevation and rainfall regimes may affect satellite rainfall data. On the basis of modified Kling–Gupta Efficiency, the SREs from IMERG v06, TRMM 3B43v7, and PERSIANN-CDR performed well in descending order over the ARB. However, GSMaP showed poor performance except in the upland sub-basin. A high frequency of bias, which led to an overestimation of SREs, was exhibited in TRMM 3B43v7 and PERSIANN-CDR products in the eastern and lower basins. Furthermore, the MK test results of SREs showed that none of the sub-basins exhibited a monotonic trend at 5% significance level except the GSMap rainfall in the upland sub-basin. In ARB, except for the GSMaP, all SREs can be used as alternative options for rainfall frequency-, flood-, and drought-monitoring studies. However, some may require bias corrections to improve the data quality.

scholarly journals Inhomogeneity detection in the rainfall series for the Mae Klong River Basin, Thailand

2021 ◽  
Vol 11 (9) ◽  
Author(s):  
Alamgir Khalil
Keyword(s):  
River Basin ◽  
Curve Analysis ◽  
Rainfall Series ◽  
Rainfall Data ◽  
Homogeneity Test ◽  
Significance Level ◽  
Von Neumann ◽  
Standard Normal Homogeneity Test ◽  
Double Mass ◽  
Climate Studies

AbstractAn accurate and complete rainfall record is prerequisite for climate studies. The purpose of this research study was to evaluate the homogeneity of the rainfall series for the Mae Klong River Basin in Thailand. Monthly rainfall data of eight stations in the Mae Klong River Basin for the period 1971–2015 were used. The double mass curve analysis was used to check the consistency of rainfall data, whereas the absolute homogeneity was assessed using the Pettitt test, standard normal homogeneity test, Buishand test, and von Neumann test at a 5% significance level. The results of these tests were qualitatively classified as ‘useful’, ‘doubtful’, and ‘suspect’ according to the null hypothesis. Results of the monthly time series indicated the rainfall data as ‘useful’ for 75% of the stations, while two stations’ data were classified as ‘doubtful’ (Stn130221) and ‘suspect’ (Stn376401). On an annual scale, seven out of eight stations data were classified as ‘useful,’ while one station (Stn376401) data were classified as ‘suspect’. Double mass curve analysis technique was used for the adjustment of inhomogeneous data. The results of this study can help provide reliable rainfall data for climate studies in the basin.

scholarly journals Assessment of the impact of climate change on the freshwater availability of Kaduna River basin, Nigeria

2018 ◽  
Vol 38 (1) ◽  
pp. 105-114 ◽  
Author(s):  
Gloria C. Okafor ◽  
Kingsley N. Ogbu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Water Availability ◽  
Hydrological Cycle ◽  
Temporal Trends ◽  
Kendall Test ◽  
Well Being ◽  
Trend Test ◽  
Climate Indices ◽  
The Impact

AbstractChanges in runoff trends have caused severe water shortages and ecological problems in agriculture and human well-being in Nigeria. Understanding the long-term (inter-annual to decadal) variations of water availability in river basins is paramount for water resources management and climate change adaptation. Climate change in Northern Nigeria could lead to change of the hydrological cycle and water availability. Moreover, the linkage between climatic changes and streamflow fluctuations is poorly documented in this area. Therefore, this study examined temporal trends in rainfall, temperature and runoff records of Kaduna River basin. Using appropriate statistical tools and participatory survey, trends in streamflow and their linkages with the climate indices were explored to determine their amplifying impacts on water availability and impacts on livelihoods downstream the basin. Analysis indicate variable rainfall trend with significant wet and dry periods. Unlike rainfall, temperature showed annual and seasonal scale statistically increasing trend. Runoff exhibit increasing tendency but only statistically significant on annual scale as investigated with Mann–Kendall trend test. Sen’s estimator values stood in agreement with Mann–Kendall test for all variables. Kendall tau and partial correlation results revealed the influence of climatic variables on runoff. Based on the survey, some of the hydrological implications and current water stress conditions of these fluctuations for the downstream inhabitants were itemized. With increasing risk of climate change and demand for water, we therefore recommend developing adaptive measures in seasonal regime of water availability and future work on modelling of the diverse hydrological characteristics of the entire basin.

scholarly journals Application of Remotely Sensed Rainfall Data in Rainfall-Runoff Modelling. A Case of Pangani River Basin, Tanzania

2014 ◽  
Vol 35 (1) ◽  
pp. 1-14
Author(s):  
Joel Nobert ◽  
Patric Kibasa
Keyword(s):  
River Basin ◽  
Average Method ◽  
River Flow ◽  
Tropical Rainfall Measuring Mission ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Data Set ◽  
Satellite Rainfall ◽  
Areal Rainfall

Rainfall runoff modelling in a river basin is vital for number of hydrologic applicationincluding water resources assessment. However, rainfall data from sparse gauging stationsare usually inadequate for modelling which is a major concern in Tanzania. This studypresents the results of comparison of Tropical Rainfall Measuring Mission (TRMM)satellite rainfall products at daily and monthly time-steps with ground stations rainfalldata; and explores the possibility of using satellite rainfall data for rainfall runoffmodelling in Pangani River Basin, Tanzania. Statistical analysis was carried out to find thecorrelation between the ground stations data and TRMM estimates. It was found thatTRMM estimates at monthly scale compare reasonably well with ground stations data.Time series comparison was also done at daily and annual time scales. Monthly and annualtime series compared well with coefficient of determination of 0.68 and 0.70, respectively.It was also found that areal rainfall comparison in the northern parts of the study area hadpoor results compared to the rest of areas. On the other hand, rainfall runoff modellingwith ground stations data alone and TRMM data set alone was carried out using five Real-Time River Flow Forecasting System models and then outputs combined by Models OutputsCombination Techniques. The results showed that ground stations data performed betterduring calibration period with coefficient of efficiency of 76.7%, 81.7% and 89.1% forSimple Average Method, Weight Average Method and Neural Network Method respectively.Simulation results using TRMM data were 59.8%, 73.5% and 76.8%. It can therefore beconcluded that TRMM data are adequate and promising in hydrological modelling.

scholarly journals Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data

2017 ◽  
Vol 21 (1) ◽  
pp. 323-343 ◽  
Author(s):  
Oliver López ◽  
Rasmus Houborg ◽  
Matthew Francis McCabe
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Colorado River ◽  
Hydrological Cycle ◽  
Water Storage ◽  
Rainfall Data ◽  
Colorado River Basin ◽  
Degree Correlation ◽  
Degree Correlations ◽  
Niger River

Abstract. Advances in space-based observations have provided the capacity to develop regional- to global-scale estimates of evaporation, offering insights into this key component of the hydrological cycle. However, the evaluation of large-scale evaporation retrievals is not a straightforward task. While a number of studies have intercompared a range of these evaporation products by examining the variance amongst them, or by comparison of pixel-scale retrievals against ground-based observations, there is a need to explore more appropriate techniques to comprehensively evaluate remote-sensing-based estimates. One possible approach is to establish the level of product agreement between related hydrological components: for instance, how well do evaporation patterns and response match with precipitation or water storage changes? To assess the suitability of this consistency-based approach for evaluating evaporation products, we focused our investigation on four globally distributed basins in arid and semi-arid environments, comprising the Colorado River basin, Niger River basin, Aral Sea basin, and Lake Eyre basin. In an effort to assess retrieval quality, three satellite-based global evaporation products based on different methodologies and input data, including CSIRO-PML, the MODIS Global Evapotranspiration product (MOD16), and Global Land Evaporation: the Amsterdam Methodology (GLEAM), were evaluated against rainfall data from the Global Precipitation Climatology Project (GPCP) along with Gravity Recovery and Climate Experiment (GRACE) water storage anomalies. To ensure a fair comparison, we evaluated consistency using a degree correlation approach after transforming both evaporation and precipitation data into spherical harmonics. Overall we found no persistent hydrological consistency in these dryland environments. Indeed, the degree correlation showed oscillating values between periods of low and high water storage changes, with a phase difference of about 2–3 months. Interestingly, after imposing a simple lag in GRACE data to account for delayed surface runoff or baseflow components, an improved match in terms of degree correlation was observed in the Niger River basin. Significant improvements to the degree correlations (from  ∼  0 to about 0.6) were also found in the Colorado River basin for both the CSIRO-PML and GLEAM products, while MOD16 showed only half of that improvement. In other basins, the variability in the temporal pattern of degree correlations remained considerable and hindered any clear differentiation between the evaporation products. Even so, it was found that a constant lag of 2 months provided a better fit compared to other alternatives, including a zero lag. From a product assessment perspective, no significant or persistent advantage could be discerned across any of the three evaporation products in terms of a sustained hydrological consistency with precipitation and water storage anomaly data. As a result, our analysis has implications in terms of the confidence that can be placed in independent retrievals of the hydrological cycle, raises questions on inter-product quality, and highlights the need for additional techniques to evaluate large-scale products.

scholarly journals Integrating Satellite Rainfall Estimates with Hydrological Water Balance Model: Rainfall-Runoff Modeling in Awash River Basin, Ethiopia

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 800 ◽  
Author(s):  
Girma Berhe Adane ◽  
Birtukan Abebe Hirpa ◽  
Belay Manjur Gebru ◽  
Cholho Song ◽  
Woo-Kyun Lee
Keyword(s):  
Water Resources ◽  
Water Balance ◽  
River Basin ◽  
Pearson Correlation ◽  
Hydrologic Model ◽  
Water Balance Model ◽  
Rainfall Data ◽  
Balance Model ◽  
Awash River Basin ◽  
Satellite Rainfall

Hydrologic models play an indispensable role in managing the scarce water resources of a region, and in developing countries, the availability and distribution of data are challenging. This research aimed to integrate and compare the satellite rainfall products, namely, Tropical Rainfall Measuring Mission (TRMM 3B43v7) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), with a GR2M hydrological water balance model over a diversified terrain of the Awash River Basin in Ethiopia. Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and root mean square error (RMSE) and Pearson correlation coefficient (PCC) were used to evaluate the satellite rainfall products and hydrologic model performances of the basin. The satellite rainfall estimations of both products showed a higher PCC (above 0.86) with areal observed rainfall in the Uplands, the Western highlands, and the Lower sub-basins. However, it was weakly associated in the Upper valley and the Eastern catchments of the basin ranging from 0.45 to 0.65. The findings of the assimilated satellite rainfall products with the GR2M model exhibited that 80% of the calibrated and 60% of the validated watersheds in a basin had lower magnitude of PBIAS (<±10), which resulted in better accuracy in flow simulation. The poor performance with higher PBIAS (≥±25) of the GR2M model was observed only in the Melka Kuntire (TRMM 3B43v7 and PERSIANN-CDR), Mojo (PERSIANN-CDR), Metehara (in all rainfall data sets), and Kessem (TRMM 3B43v7) watersheds. Therefore, integrating these satellite rainfall data, particularly in the data-scarce basin, with hydrological data, generally appeared to be useful. However, validation with the ground observed data is required for effective water resources planning and management in a basin. Furthermore, it is recommended to make bias corrections for watersheds with poorlyww performing satellite rainfall products of higher PBIAS before assimilating with the hydrologic model.

scholarly journals Statistical and spatial variability of climate data in the Mareb-Gash river basin in Eritrea

Vestnik MGSU ◽  
2020 ◽  
pp. 85-99
Author(s):  
Anghesom A. Ghebrehiwot ◽  
Dmitriy V. Kozlov
Keyword(s):  
River Basin ◽  
Potential Evapotranspiration ◽  
Statistical Analyses ◽  
Estimation Methods ◽  
Drought Indices ◽  
Climate Data ◽  
Hydrologic Modelling ◽  
Monotonic Trend ◽  
Dry Conditions ◽  
Global Reanalysis

Introduction. Global reanalysis products are extensively used for hydrologic applications in sparse data regions. The establishment of inputs for hydrologic modelling from such global reanalysis requires prior checking and analyses. Materials and methods. The present study attempts to utilize Climate Forecast System Reanalysis (CFSR) datasets for the Mereb-Gash river basin in Eritrea, to prepare the input data for forthcoming hydrological modelling studies. The activities include statistical analyses, computation of PET, and drought indices using different methods so as to understand basin characteristics through the use of geospatial and geostatistical tools. Results. The results of statistical analyses indicated that there was predominantly a significant monotonic trend in the majority of the data. Precipitation (P) and relative humidity tend to decrease, whereas temperature (T) and potential evapotranspiration (PET) tend to increase. Among the PET estimation methods, the Thornthwaite method gave inconsistent results as compared to Hargreaves and Penman-Monteith methods, the former being highly dependent on the elevation of the station. In most cases, it was found that Penman-Monteith produced the highest PET values. Conclusions. Besides, Standardized Precipitation and Evapotranspiration Index (SPEI) analyses in the basin indicate persistent dry conditions over the period 2000–2013 and predominantly humid conditions over the period 1979–2000. The study concluded that the presence of a significant trend in most of the climatic variables and persistent drought conditions in recent years were found to be congruent with global and regional climatic studies that are highly likely linked to human and climate influence on the environment.

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.

scholarly journals The modified Mann-Kendall test: on the performance of three variance correction approaches

Bragantia ◽  
2013 ◽  
Vol 72 (4) ◽  
pp. 416-425 ◽  
Author(s):  
Gabriel Constantino Blain
Keyword(s):  
Serial Correlation ◽  
Kendall Test ◽  
Trend Test ◽  
Climate Trends ◽  
Nominal Significance Level ◽  
Trade Off ◽  
Significance Level ◽  
Mk Test ◽  
Nominal Significance ◽  
Mann Kendall Test

The Mann-Kendall test has been used to detect climate trends in several parts of the Globe. Three variance correction approaches (MKD, MKDD and MKRD) have been proposed to remove the influence of serial correlation on this trend test. Thus, the main goal of this study was to evaluate the probability of occurrence of types I and II errors associated with these three approaches. The results obtained by means of Monte Carlo simulations and from a case of study allowed us to drawn the following conclusions: All approaches are capable of meeting the adopted significant level when they are applied to trend-free uncorrelated series. The approaches are as powerful as the original MK test when they are applied to uncorrelated series. Regarding serially correlated series it was verified that: (i) the performance of the MKDD and MKRD are comparable; (ii) both approaches may not be able to preserve the adopted significance level and (iii) although the MKD is capable of preserving the adopted significance level, it is less powerful than the MKDD and MKRD. Thus, there is a trade-off between the power of the three approaches and their capability of meeting the nominal significance level. Accordingly, we recommend the use of at least two approaches -MKD and MKDD(MKRD)- to evaluate the presence of trends in a given dataset.

scholarly journals Trend Analysis of Rainfall Data in Magelang District Using Mann-Kendall Test and Modification Mann-Kendall Variation

AGRIFOR ◽  
2018 ◽  
Vol 17 (2) ◽  
pp. 293 ◽  
Author(s):  
Joko Suryanto ◽  
Joko Krisbiyantoro
Keyword(s):  
Kendall Test ◽  
Significant Trend ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Partial Sums ◽  
Trend Test ◽  
Positive Trend ◽  
Mk Test ◽  
Rainfall Trends ◽  
Negative Significant Trend

The objective of the research was to analyzed rainfall trends from 6 rainfall stations Kajoran, Mendut, Muntilan, Ngablak, Salaman and Tempuran rainfall station in different time scales (monthly, 3-months periodicityand annual). Identification homogenity of the rainfall data period 1986-2016 for Magelang district using Rescaled Adjusted Partial Sums (RAPS) methode. The three non-parametric tests, Mann-Kendall (MK), modified Mann-Kendall (MMK), trend free prewhitening Mann-Kendall (TFPW-MK) and Sen’s slope wereemployed to assess significance of trends and detecting magnitude of trends.The results shows that monthly rainfall have no significant trend using MK, MMK, and TFPW-MK test at 0.05 level significance. Rainfall 3-month based January-February-March (JFM) period Kajoran station have negative significant trend with magnitude 19.4 mm/3-month. Mendut station have positive trend for April-May-June (AMJ) period with magnitude 6.75 mm/3-month. No significant trends at 0.05 level significance using MK trend test were detected in annual rainfall for 6 rainfall stations.

scholarly journals Hydro-Meteorological Trends in the Upper Omo-Ghibe River Basin, Ethiopia

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1951 ◽  
Author(s):  
Jaweso ◽  
Abate ◽  
Bauwe ◽  
Lennartz
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Data Availability ◽  
Change Points ◽  
Annual Rainfall ◽  
Significance Level ◽  
Annual Time Scale ◽  
Planning Decisions ◽  
Increasing Trends ◽  
Annual Time

This study aimed to assess trends of hydro-meteorological variables in the Upper Omo-Ghibe river basin, Ethiopia. Data records from eleven rainfall, eight air temperature, and five streamflow stations between 1981 to 2008 were investigated. The trends and change points were evaluated for different periods of time depending on data availability. Mann-Kendall and Pettit tests were used to identify trends and change points at a 5% significance level. The tests were applied to mean annual, monthly and seasonal time scales. Rainfall exhibited statistically decreasing trends at a mean annual time scale, while seasonal rainfall depicted heterogeneous results in both directions. For the majority of the stations, air temperature showed statistically significant increasing trends. The magnitude of change in temperature for mean annual, wet and dry season has increased about 0.48, 0.46, and 0.61 °C per decade for Jimma station. The Pettit test revealed that the late 1980s and 1990s were the change points. There is generally a decreasing trend in streamflow. The decline in annual rainfall and rise in temperature affected the streamflow negatively. Overall, the results indicate that trend sand change point times varied considerably across the stations and catchments. The identified significant trends can help to support planning decisions for water management.

Sign in / Sign up

Export Citation Format

Share Document