Numerical Models for Predicting the Fate of Ammonia Nitrogen for Biological Treatment Processes in Urbanized Rivers in China

Volume 1 • Issue 6 • 2012 found to remove over 70% of nutrients during restoration exercises. The growing technology, Biological Treatment Method (BTM) is not new to history but it is beginning to receive attention in river and wastewater treatment nowadays. The BTM has been successfully used in many countries worldwide including China for domestic and industrial wastewater treatment. For instance, the method has been used in urban streams in Shenzen, Rui'an and Wuxi of China. This method has been known to rapidly reduce the concentrations of effluent BOD and COD There is however lack of requisite mathematical algorithms to support the forecasting and monitoring of water quality variables under the BTM. Nutrient flux in urban rivers is very important for monitoring water quality. Nitrogen is one of these nutrients that promote cellular growth and thus eutrophication in water bodies. In wastewater, nitrogen has the capability to exist in different forms -ammonia, organic, nitrate and nitrite. In this particular case, the ammonia-nitrogen widely known to contribute towards eutrophication is considered. Mathematical algorithms are developed and tested to determine their predicative Keywords: Fate; Ammonia-nitrogen; Numerical models; Biological treatment method Introduction Developing economies face the challenge of poor surface water quality of water bodies. Environmental degradation coupled with industrial growth and infrastructural development further adds more challenge to water planners and managers in urban communities. China for instance, is undergoing water related challenges due to urban expansion and the rapid growing industrial activity. It is also partly because the transport of household and industrial wastewater from both point and non-point sources into rivers have increased their vulnerability and support for aquatic life Abstract One of the sustainable approaches towards polluted urbanized rivers restoration is the use of biological treatment method. The method has been successfully used in China since the past decade and has received growing recognition among university and government authorities. Field campaigns during biological treatment methods to measure water quality variables are expensive as in most water quality measurements. Therefore, the availability of mathematical models helps to provide a basis for forecasting and planning for such campaigns. Ammonia-nitrogen is a key variable supporting eutrophication of rivers. In this research, mathematical models were developed to describe the fate of ammonia-nitrogen given a set of water quality variables (i.e. transparency, water temperature, COD, DO, total nitrogen and total phosphorus). Selected six models were chosen based on adjusted R2, Akaike Information Criterion (AICc) and Bayesian Information Criterion (BIC). The selected models were tested with independent dataset. The results show that the prediction errors range from ±20% to ±36%. The errors found in this research are comparable to previous studies and are considered to be largely due to the large sampling and measurement errors usually encountered in water quality testing and measurements. The results in this research support on-going numerical modelling in wastewater treatment, water quality modelling and water resources planning and management

Households’ Livelihood Vulnerability to Climate Change and Climate Variability: A Case Study of the Coastal Zone, The Gambia

Climate change and its variability are negatively influencing climate-dependent activities such as agriculture and fishing in Africa, of which The Gambia is no exception. Households are vulnerable to its impacts. With the impacts of climate change and its variability in The Gambia, livelihoods of people will be negatively affected. There is the need to know which regions are more vulnerable than others are so livelihood improvement actions can be taken in areas they are needed the most in the wake of present and future climate change impacts, thus, the objective of this study. This will aid in eluding maladaptation and waste of limited developmental resources for climate change adaptation. The results of the study will also assist the Government and other development partners in making decisions that are more informed as to areas where and the kind of assistance needed between the districts in the coastal zone of The Gambia. The study employed the Livelihood Vulnerability Index (LVI) in the estimation of household vulnerability to Climate Change (CC) and its variability based on their: Socio-Demographic Profile; Livelihood strategies; Social Networks; Health; Water; Natural disasters and Climate Variability and; Knowledge and Skills. This approach is divided into the Intergovernmental Panel on Climate Change (IPCC) three main components of vulnerability, namely: Exposure; Sensitivity and; Adaptive Capacity. The primary data used is based on a survey of 355 household heads in agriculture or fishing activities in the coastal zone of The Gambia, while the secondary data used was on rainfall and temperature. Microsoft Office Excel 2016 was the software employed in estimating the livelihood vulnerability index, developing the vulnerability spider (radar) chart and the vulnerability triangle in this study. The findings of the study reveal households in Kombo South may be more vulnerable to climate change and its variability than Lower Niumi districts in the study area. The LVI revealed Kombo South district may be more vulnerable to: Health; Food and; Knowledge and Skills while Lower Niumi district is more vulnerable to: Socio-Demographic Profile; Livelihood Strategies; Social Networks; Water and; Natural Disasters and Climate Variability. The overall LVI-IPCC main components of vulnerability reveals households in Kombo South may be more vulnerable than households in Lower Niumi district in the coastal zone of The Gambia. Keywords: Vulnerability, Climate Change, Climate Variability, Livelihood Vulnerability Index, Coastal Zone, Households, Farmers, The Gambi

Water resources data, models and decisions: International expert opinion on knowledge management for an uncertain but resilient future

© 2019 The Authors. Assessing the resilience of water resources systems requires knowledge of properties and performance, which depends on data availability and use within models and decision making. Connections between data, models and decision making are crucial to plan for uncertainty and invest in interventions. To explore international perceptions of these connections, we conducted a threeround Delphi survey with an expert panel (see Supplementary material, available with the online version of this paper). Consensus and divergence existed within and between countries on ability to manage data, modelling and decision making, with the most consensus seen on use of hydrometric databases. There was a wide range of models and tools utilised by participants and a shift occurred between first and second rounds to a preference for trying new modelling. There was consensus between and within all countries that every data type was important. River flow data consistently scored highest. Access to data and models primarily impacted evaluating future capacity, planning under uncertainty, policy implementation and conflict resolution. The panel called for reviewing existing and developing new policy, collaborative research and available funding all focusing on water resources data-model-decision integration. Findings offer a strategic view on knowledge management regarding connections between data, models and decision making through identification of consensus areas for future focus and dissensus areas for reprioritisation

Editorial: Oceanobs'19: An ocean of opportunity

The OceanObs conferences are held once every 10 years for the scientific, technical, and operational communities involved in the planning, implementation, and use of ocean observing systems. They serve to communicate progress, promote plans, and to define advances in ocean observing in response to societies' needs. Each conference provides a forum for the community to review the state of the ocean observing science and operations, and to define goals and plans to achieve over the next decade

Multiyear Rainfall and Temperature Trends in the Volta River Basin and their Potential Impact on Hydropower Generation in Ghana

The effects of temperature and rainfall changes on hydropower generation in Ghana from 1960–2011 were examined to understand country-wide trends of climate variability. Moreover, the discharge and the water level trends for the Akosombo reservoir from 1965–2014 were examined using the Mann-Kendall test statistic to assess localised changes. The annual temperature trend was positive while rainfall showed both negative and positive trends in different parts of the country. However, these trends were not statistically significant in the study regions in 1960 to 2011. Rainfall was not evenly distributed throughout the years, with the highest rainfall recorded between 1960 and 1970 and the lowest rainfalls between 2000 and 2011. The Mann-Kendall test shows an upward trend for the discharge of the Akosombo reservoir and a downward trend for the water level. However, the discharge irregularities of the reservoir do not necessarily affect the energy generated from the Akosombo plant, but rather the regular low flow of water into the reservoir affected power generation. This is the major concern for the operations of the Akosombo hydropower plant for energy generation in Ghana

Impacts of Rainfall Variability, Land Use and Land Cover Change on Stream Flow of the Black Volta Basin, West Africa

Potential implications of rainfall variability along with Land Use and Land Cover Change (LULC) on stream flow have been assessed in the Black Volta basin using the SWAT model. The spatio-temporal variability of rainfall over the Black Volta was assessed using the Mann-Kendall monotonic trend test and the Sen’s slope for the period 1976–2011. The statistics of the trend test showed that 61.4% of the rain gauges presented an increased precipitation trend whereas the rest of the stations showed a decreased trend. However, the test performed at the 95% confidence interval level showed that the detected trends in the rainfall data were not statistically significant. Land use trends between the year 2000 and 2013 show that within thirteen years, land use classes like bare land, urban areas, water bodies, agricultural lands, deciduous forests and evergreen forests have increased respectively by 67.06%, 33.22%, 7.62%, 29.66%, 60.18%, and 38.38%. Only grass land has decreased by 44.54% within this period. Changes in seasonal stream flow due to LULC were assessed by defining dry and wet seasons. The results showed that from year 2000 to year 2013, the dry season discharge has increased by 6% whereas the discharge of wet season has increased by 1%. The changes in stream flows components such us surface run-off (SURF_Q), lateral flow (LAT_Q) and ground water contribution to stream flow (GW_Q) and also on evapotranspiration (ET) changes due to LULC was evaluated. The results showed that between the year 2000 and 2013, SURF_Q and LAT_Q have respectively increased by 27% and 19% while GW_Q has decreased by 6% while ET has increased by 4.59%. The resultant effects are that the water yield to stream flow has increased by 4%

Land Use and Land Cover Changes under Climate Uncertainty: Modelling the Impacts on Hydropower Production in Western Africa

The Bui hydropower plant plays a vital role in the socio-economic development of Ghana. This paper attempt to explore the combined effects of climate-land use land cover change on power production using the (WEAP) model: Water Evaluation and Planning system. The historical analysis of rainfall and stream flow variability showed that the annual coefficient of variation of rainfall and stream flow are, respectively, 8.6% and 60.85%. The stream flow varied greatly than the rainfall, due to land use land cover changes (LULC). In fact, the LULC analysis revealed important changes in vegetative areas and water bodies. The WEAP model evaluation showed that combined effects of LULC and climate change reduce water availability for all of demand sectors, including hydropower generation at the Bui hydropower plant. However, it was projected that Bui power production will increase by 40.7% and 24.93%, respectively, under wet and adaptation conditions, and decrease by 46% and 2.5%, respectively, under dry and current conditions. The wet condition is defined as an increase in rainfall by 14%, the dry condition as the decrease in rainfall by 15%; current account is business as usual, and the adaptation is as the efficient use of water for the period 2012–2040

The Climate Change Vulnerability and Risk Management Matrix for the Coastal Zone of The Gambia

Global Climate Change is one of the dire challenges facing the international community today. Coastal zones are vulnerable to its impacts. An effective approach with long-term prospects in addressing climate change impacts is it’s mainstreaming into development agenda of sectoral policies. A comprehensive risk and vulnerability assessment is a pre-requisite to ensure that the right adaptive response is taken for effective integration into developmental plans. The objective of this study is to evaluate and prioritize risks, vulnerability and adaptation issues of current and anticipated impacts of climate change on the coastal zone of The Gambia. The study will also give a methodological contribution for assessing risks, vulnerability and adaptation from the sub-national to local levels. The relevance of this study will be to create a link between the sub-national and local levels in order to facilitate the integration and mainstreaming of climate change into sectoral and local policies for more climate-resilient communities. This will aid in the promotion of strategic investment of constrained developmental resources to actualize successfully dynamic coping strategies, elude ‘maladaptation’ and less compelling responsive measures. A purposive expert sampling technique was used in selecting respondents for the study. The findings of the study reveal that by the end of the 21st century, the climatic variables likely to have the highest impact on the coastal zone of The Gambia are ‘increased flood severity’ and ‘increased temperature’. The coastal zone of The Gambia showed a high vulnerability to these climate change variables. The suggested adaptive response in addressing the impacts of increased flood intensity in the study area includes; improving regulations for restricting agriculture and livestock grazing activities to improve land cover; strengthening of early-warning systems, among others. The suggested adaptive response in addressing the increase in temperature includes: increase crop diversification and rotation to reduce total crop failure; switching to drought-tolerant crop and animal species, among others

Analysis of drought patterns in the Tano river basin of Ghana

The objective of this study is to analyze drought patterns in the Tano River Basin (TRB) of Ghana using Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Precipitation data from 1981 to 2019 for the TRB was accessed from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), extracted into time Series using Python to four locations within the basin and used for the analysis together with the National Aeronautics and Space Administration (NASA) POWER (Prediction Of Worldwide Energy Resource) Temperature data. Anderson-Darling test was performed to check for the normality of the precipitation. Two separate station data sets from TAHMO and Earth Observation Research Innovation Centre (EORIC) were used to validate the CHIRPS data. The Scaler Index (SI) from the two data sets are respectively 0.383 and 0.016. This indicates the CHIRPS data extracted is sufficiently accurate. The SPI and RDI on the time scales of 1, 3, 6 and 12 months were calculated using the Drought Indices Calculator (DrinC) software and characterized into the magnitude, duration, and severity of the drought. Regression analysis was performed to compare RDI and SPI values. The results show that the coefficient of regression R2 is 0.9789, 0.9689 and 0.8799 for 1, 6 and 12 months respectively. This indicates a stronger correlation between SPI and RDI values. However, R2 is observed to decreases with increasing time scale, which means for shorter time scales, SPI and RDI are more similar than for longer time scales. To further examine the possible impacts of climate change on the drought profile of the basin, the Mann-Kendall trend test was conducted to compare the trends in SPI and RDI for 1, 6 and 12 timescales. Apart from RDI 6 for Tanoso which recorded a decrease in trend of – 0.17 as against 0.14 of SPI 6, all other timescales recorded an increase in trend for RDI as compared to SPI. Although most of these increases in trend is not significant at 10% significance level, a trend of 1.95 and 1.71 of RDI 1 for Buako and Sepremboi respectively were significant compared to that of SPI 1 for same stations. These increases in trend of RDI as compared to SPI suggests the possible impact of climate change since RDI estimation takes into consideration potential evapotranspiration (PET), which is a factor of temperature. This could have negative implications on agricultural production and drinking water supply within the basin considering that the basin solely relies on surface water for crop production and drinking water supply