https://archive.conscientiabeam.com/index.php/108 Conscientia Beam en-US International Journal of Hydrology Research 2771-5590 https://archive.conscientiabeam.com/index.php/108/article/view/3297 <p>Availability of hydrological data and various soft wares for developing models make easy way to answer frequently asked questions to hydrologists. A great deal of concentration has given to the development of models in the last decades. But the thorough study regarding uncertainty of simulations has not carried out in comparison with the development of models. Uncertainty in models emanates from input data, calibrated data, parameters and from the structure of models. The sources of uncertainty, cause of generation and how these can be dealt with are reviewed here. This also comprises a review about five different methods viz. Monte Carlo sampling, Bayesian approach, Generalized Likelihood Uncertainty Estimation, Bootstrap Approach and Machine learning methods which were applied in the estimation of the model and parameter uncertainty. This will indicate the comparison between the methods which were applied to measure the uncertainty of hydrological models and highlight the strengths and weaknesses of the methods in identifying the usefulness of the models. By the comparison of the methods the improvement of the model reliability, slackening of the prediction error of the hydrological models can be suggested. By a proper quantification of uncertainty of data applied for the building up and evaluation of models, model performance can be improved, cost can be reduced and unambiguous results can lead the proper water resources management.</p> Syeda Zehan Farzana Copyright (c) 2023 2023-02-17 2023-02-17 8 1 1 13 10.18488/ijhr.v8i1.3297 https://archive.conscientiabeam.com/index.php/108/article/view/3485 <p>Assessment of hydrological drought indices in drought prone areas provides useful information for accurate and sustainable water resources management. However, meteorological drought estimation in ungauged basin remains less studied. The main objective of this study was to compare the ability of Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to reproduce historiological drought within Massili basin. To this end, monthly historical rainfall and temperature time series spanning from 1960 to 2021 have been collected from the national agency of meteorology. R programming language has been applied to display Boxplots in order to identified the temporal dispersion of the rainfall indices.&nbsp; Then the Spearman correlation was applied to illustrate the relationships between the SPEI and the SPI. The results shows that both SPEI and SPI exhibit consistent behavior in observed drought within the Massili watershed. Dry conditions prevailed during the period 1980–1990, 1990–2000 and 2000-2010. Severe wet conditions prevailed in years 1984, 1985,1998 and 2002.&nbsp; In all time scale the SPEI and SPI are characterized by high correlation. The Spearman correlation coefficients value is above 0.7 with the highest correlation value detected between SPEI-24 and SPI-24 (0.97).&nbsp; This study may contribute to better understand the drought patterns within the basin for water resources planning perspectives.</p> Tog-Noma Patricia Emma Bontogho Michelline Marie Regina Kansole Mamounata Kabore Moussa Guira Copyright (c) 2023 2023-09-21 2023-09-21 8 1 14 22 10.18488/ijhr.v8i1.3485