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. 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. 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). This study may contribute to better understand the drought patterns within the basin for water resources planning perspectives.

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.

It is the need of the hour to study the changes occurring in the future rainfall trends for the Pune metropolitan region. General Circulation Models (GCMs) are used to study the variations in the climatic conditions occurring in the near and far future. GCMs yield the values of the required parameters over specific grid points which are not location specific and need to be downscaled. The current study suggests Artificial Neural Networks (ANN) as a tool for statistical downscaling. 5 precipitation causative parameters were mined from 5 GCMs each and then used as input to the neural networks, with the observed historical monthly cumulative precipitation as output. The best model was then used estimate the rainfall that would occur in the near future for Pune. The future rainfall analysis showed that the intensity of rainfall seems to be increasing for the non-monsoon months and decreasing for the monsoon months.

Hydro-meteorological trend and recurring seasonal flood are fundamental obstacles in the country’s task towards the attainment of food security, diversification of economy, sustainability of the physical environment and socio-economic livelihood. This study utilized rainfall records (1980-2015) and hydrological record (1990-2015). A simple flood monitoring and early warning methodology hinged on an Intra-seasonal Rainfall Monitoring Index (IRMI) to identify and monitor flood condition adopted. The computed Hydro-meteorological variables (IRMI, Gauge Height, Inflow and Discharge) were summarized and classified at pentad level to determine peak flow, its variability and flood risk from low to extremely high. The result revealed spatio-temporal variability in IRMI peak values and consistency peak values across the study area. This triggered high, very high and extremely high inflow values that led to sustained moderate and high discharge in recent times; thus, leading to loss of floodplain wetland that aggravated downstream flood as evident in the study area in the years 2010, 2011, 2012, 2013 and 2014 due to steady increase and consistency in IRMI, inflow and discharge peak values. Consequently, there is need to adequately understand the hydro-climatic parameters that trigger flood risk and its impact on sustainability of wetland ecosystems to enhance the knowledge base for effective disaster risk reduction.

Groundwater is the dynamic local water source for agriculture, industry, wildlife and human development activity. Hence, in order to sustain long-term groundwater use, make intelligent groundwater allocation decisions and water budget planning, develop on-farm water management strategies, the estimation of the net groundwater recharge from agricultural areas like Kanzenze swamp is paramount important. The study findings therefore showed that Ground Water Recharge estimation for the study area ranges from 33.85mm to 52.96mm while the average mean of ground water recharge is about 45.06mm per year. The coefficient of ground water recharge is ranging from 3.41% to 5.27% while average mean recharge coefficient is 4.06% recharged to ground water level yearly. However, monthly basis planning have advantages for farmers’ water budgeting. It revealed that highest recharge coefficient is recorded in months of March, April and November representing 17.22% and 17% of the mean monthly rainfall while the lowest recharge coefficient is recorded during the period of June, July and February representing 16.17%, 15.73% and 16.71% of the average monthly rainfall. Thus, it is recommended that utmost farmers around the Kanzenze swamp should plan the irrigation activities and minimizes unnecessary water use consumption in such way that in June and July there is water enough water even taught there is shortage of rainfall. It meant that priori irrigation systems should be applied to obtain optimum moisture content and water table levels for effective crop production mainly horticultural crops in season C rather than season A and season B of cultivation in Rwanda.

Agricultural swamps are among the major fruitful and exposed to heavy metals deposition and contributes to ecological concerns. Heavy metals are mainly pollutants to deteriorate water quality and affect plant health through leaching and seepage process from industrial services, anthropogenic activities, erosion and mining activities. The study aimed to assess heavy metals, water quality and their effect on plant growth along Kanzenze Swamp of the Akagera Upper Catchment. The total of Sixteen chemical parameters of water including Calcium, Magnesium, Sodium, Potassium, Copper, Zinc, Manganese, Lead, Cadmium, Chromium, pH, Electrical Conductivity, Sodium Adsorption Ratio, Magnesium hazards, Kelly Index and Soluble Sodium Percent were analyzed and observed values were thereafter compared with international standards values recommended by Food and Agriculture Organization. Photometric methods and Atomic Adsorption Spectrometer machines were used to detect the heavy metals while analytical. Descriptive analysis and Principal Components Analysis techniques were used to correlate water quality parameters for similarities and dissimilarities through cluster analysis. All statistical analysis were performed by using Statistical Package for Social Science version 22.0. The study findings shows that most water use for irrigation is polluted by heavy metals with maximum values compared to Rwanda national and international permissible standards for irrigation. The heavy metals with highest content included Calcium, Magnesium, Potassium, Copper, Manganese, Cadmium and Chromium. Hence farmers relaying on this water may be disposed to health hazards issues and other environmental concerns. Therefore some effective measures like water treatments are compulsory vital needed to boost the quality of water for irrigation purpose.

The experiences of the last 30 years developed an understanding in the Addis Ababa Water Utility that groundwater sources are not fully dependable for such a big city. Notwithstanding this, additional wells and well-fields are being developed especially in the last 10 years to meet the ever increasing demand. The Akaki well-field was initially designed for an abstraction rate of up to 35,000 m3/day for 20 years until 2020 though the current abstraction rate is nearly ten-fold. The current developments are only demand driven irrespective of safe and sustainable utilization. What is making things worse is the rise of other water competing demands for irrigation projects in adjacent well-fields. The present water supply coverage of the Addis Ababa city is not more than 50%. The situation in other urban centers in the Upper Awash basin is not different. Conceptual modelling, time series well water level measurements and operational assessments showed that the aquifer systems are not uniform and dotted with many volcanic flow barriers; there is sharp decline of water table (up to 70 meters since 2000) in some well-fields and the decline is propagating upstream of the Akaki well-field. Moreover, the excessive and uncontrolled pumping is impacting regional groundwater table. Topographic and technical issues are hampering upstream water distribution, and the once exemplary hundreds of wells are now abandoned. The frequent tapping of thermal and high fluoride water is another complication. Unless proper intervention is devised, grave environmental problems are likely to come in the near future.

Climate change and population growth are seen to be the major factors that will shape the pattern of per capita water up to the end of 21st century. The study aimed to project water stress condition in Guinea and Sudano-Sahelian ecological zones of Nigeria under the impacts of climate change and population growth. Firstly, annual water yield was generated using KNMI climate explorer for (2019-2048), (2049-2078) and (2079-2100) under three CO2 emission trajectories. Secondly, population was projected using the Nigeria’s average growth rate of 2.6%. Thirdly, the per capita water was analysed based on water stress index. Mann-Kendal statistical test was used to analyses trends in water stress at 0.05 significant levels. Result demonstrated that the Guinea and Sudano-Sahelian ecological zones of Nigeria will experience significant positive trend in water stress with respect to climate change impact for mid and long-term periods whereas no significant trend under the short-term projection. However, regional trend analysis under the influence of population growth at constant climate observed that there were significant positive trends in water stress for the three projected periods. More so, the same positive trends were obtained under the combined impacts of climate change and population growth in Guinea and Sudano-Sahelian ecological zones of Nigeria. This implies that future water scarcity is imminent and will primarily cause by population growth and secondarily by climate change in the area. The results can act as guidelines for strategic planning for adaptive and mitigation measures to water stress as envisaged by the projection.

Coral reefs are extensively studied around the world with regard to their taxonomy, distribution, diversity, bleaching events, diseases, conservation, and restoration aspects. However, exhibition of blue pigmentation by corals under certain stressed condition such as high temperature and bleaching events has not been widely investigated. In the present study, during a massive bleaching event of coral reefs in 21 islands of Gulf of Mannar Marine Biosphere Reserve, corals such as Acropora sp. and Turbinaria sp. and some other encrusting corals have displayed purple blue pigmentation in response to high temperature and to avoid complete bleaching of their food supplying symbiotic zooxanthellae. This documentation from this environment is being reported for the first time and thus further immunological and genomic studies are required to study the variation in the zooxanthellae in bleached and non-bleached corals as well as blue pigment showing and non-pigmented corals. The compound responsible for blue pigmentation is needed to be analyzed further which could be employed for other industrial and biomedical applications.

Sediment load and its response to the variations of the hydrological elements are important to understand the phenomena of erosion. This study was fulfilled with the aim of developing a model to predict sediment load using sediment rating curve for the Ain Berda gauging station. The model was developed based on the available streamflow discharge and suspended sediment concentration data during sampled storm events over 39 year-period in the Ressoul watershed. Relationships between sediment concentration and water discharge were used according to single and rising-falling stage ratings to determine the best model for sediment load prediction. Additionally, a technique was devised to correct for log-transform bias on the sediment rating curves. The mean annual sediment yield during high and medium high flood events was 302 T km-2 yr-1. The high sediment loads in the study basin could be explained by the intensity of rain, the aggressiveness of the flows, the topography and the availability of sediments from hillslopes. The sediment load was dominated by winter and spring seasons accounting for 89% of the annual load. A high sediment supply in winter might confirm the intense geomorphic action caused by high intensity rainfall, low vegetation cover, and heavy machine activity in the agricultural fields. Following watershed management for local communities may bring multiple benefits. The adoption of suitable measures for soil conservation should reduce soil erosion and improve the livelihoods of the inhabitants. This study can serve as a reference for policymakers and planners.