Enhancement of coupled surface / subsurface flow models in watersheds: analysis, model development, optimization, and user accessibility

2018 Fall.Includes bibliographical references.To view the abstract, please see the full text of the document

Water Resources in Lake Tana Basin: Analysis of hydrological time series data and impact of climate change with emphasis on groundwater, Upper Blue Nile Basin, Ethiopia

Ethiopia is a source region of the Nile River and famous for its water resources potential. The available annual average water per person per year is estimated to be 1575 m3. The Lake Tana accounts for 50% of the national fresh water. It has a total catchment area of about 15,321 km2 and hosts more than three million people. The climate is characterized by a high seasonality of rainfall with a rainy season between June and September. However, the scientific understanding of the hydrologic response to intensive agriculture, the interconnection of groundwater and surface water, and future perspectives of the water availability under global climate change is limited. Therefore, the main aim of this study is to improve our understanding of past, present, and future hydrologic conditions in the Lake Tana basin. To this end, long-term time series analysis and hydrological modeling using SWAT (Soil and Water Assessment Tools) and a coupled surface water and groundwater model (SWAT-MODFLOW) were applied. Time series analysis and modelling results revealed that the hydrology of the basin was changed significantly during the last half century and is expected to change during the 21st century mainly due to land use change and climate change. Although projections of annual rainfall did not show a significant change, surface runoff increased, whereas base flow decreased during the past and for mid- and long-term periods in the 21st century. Results from the coupled model revealed a high connectivity of groundwater and surface water systems. Agricultural crops influence the hydrologic components differently. Groundwater recharge was relatively high on agricultural land covered by cereal crops, whereas surface runoff was significantly enhanced on cultivated land covered by leguminous crops like peas. Overall, the results of this dissertation reveal that hydrology of the Lake Tana Basin has changed considerably during the last half century and more changes are to be expected in the future. Consequently, the results of this dissertation can contribute to develop future water management plans in the region and beyond

Review of saturated groundwater model codes for Hydro-JULES

This report reviews saturated groundwater model codes, one to be implemented into the Hydro-JULES modelling framework. First, the criteria for the code evaluation is described, and then commercial groundwater modelling codes, codes for thermo-hydro-chemical modelling and finally open source groundwater modelling codes are evaluated using the aforementioned criteria. Considering a groundwater code for the simulation of groundwater flooding or drought, we recommend either MODFLOW-2005, or the newly developed MODFLOW 6, the latter will need to be tested. Alternatively, BGS could develop a custom code that can solve the groundwater flow equation using moving grids, allowing a dynamic representation of the model grid for a moving water table. If also thermo and chemical processes are of interest, then codes such as OpenGeoSys, Dumux, and PFLOTRAN could be good choices, however they will need benchmarking to evaluate their ease of use

Spatial Data Management and Numerical Modelling: Demonstrating the Application of the QGIS-Integrated FREEWAT Platform at 13 Case Studies for Tackling Groundwater Resource Management

Because of the spatial nature of groundwater-related data and their time component, effective groundwater management requires the application of methods pertaining to the Information and Communication Technologies sector, such as spatial data management and distributed numerical modelling. The objective of this paper is to demonstrate the effectiveness of the QGIS-integrated FREEWAT platform and an approach combining spatial data management and numerical models to target groundwater management issues. FREEWAT is a free and open source platform integrated in a Geographic Information System environment and embedding tools for pre- and post-processing of spatial data and integrating numerical codes for the simulation of the hydrological cycle, with a main focus on groundwater. To this aim, this paper briefly presents the FREEWAT platform, introduces the FREEWAT approach, and showcases 13 case studies in European and non-European countries where the FREEWAT platform was applied. Application of the FREEWAT platform to real-world case studies is presented for targeting management of coastal aquifers, ground- and surface-water interaction, climate change impacts, management of transboundary aquifers, rural water management and protection of groundwater-dependent ecosystems. In this sense, compared to other existing software suites, FREEWAT allows data analysis and visualization to accomplish each step of the modelling workflow, i.e., from data analytics, to conceptual model definition, to numerical modelling and reporting of results. The presented experiences demonstrate that improved access to data and the portability of models and models’ results can help to promote water sustainability from the local- to the basin-scale. Furthermore, FREEWAT may represent a valuable tool to target the objective of increasing the capabilities of public authorities and private companies to manage groundwater resources by means of up-to-date, robust, well-documented and reliable software, without entailing the need of costly licensing, nowadays seldom affordable by public water authorities. Based on the strengths highlighted, the FREEWAT platform is a powerful tool for groundwater resources management, and for data collection, sharing, implementation and comparison of scenarios, for supporting planning and decision-making

Numerical groundwater flow modeling under future climate change in the Central Rift Valley Lakes Basin; Ethiopia

\ua9 2024 The AuthorsStudy area: Katar and Meki subbasins, Rift Valley Lakes Basin, Ethiopia.Study focus: This research was carried out to characterized the recharge mechanism and quantify the steady-state groundwater balance and its sensitivity to future climate change. A groundwater simulation model was constructed and calibrated using a hydro-geo spatial dataset. Three regional climate models were used to assess the potential impact of changes in future precipitation on the recharge rate and groundwater balance components.New Hydrogeological Insight: Groundwater potential assessment depends on accurate estimation of the recharge rate. Precipitation contributed 11.95% and 11.96% to groundwater recharge in the Katar and Meki subbasins, respectively. The steady-state numerical groundwater model was calibrated and the model performed in the ranges of R2: 0.95–0.99; RMSE: 16.17–25.18; and MAE: 12.69–24.55, demonstrating \u27excellent\u27 model performance. In particular, the model exhibited high sensitivity to changes in the recharge rate and horizontal hydraulic conductivity. Future change in precipitation caused a reduction in groundwater potential in the range of 6.24–40.32% by the 2040 s and 2070 s, respectively, in the Katar subbasin. Likewise, the Meki Subbasin will experience a reduction in groundwater potential in the range of 0.29–37.17% by the 2040 s and 2070 s, respectively. These results emphasize how crucial it is for future water resource development initiatives to take into account climate variability for sustainable groundwater development

Assessing the Impacts of Salinity and Nitrate Leaching on Sustainability of Groundwater and Irrigated Agriculture in the Central Valley

Salinity and nitrate leaching in California's Central Valley significantly impair agricultural productivity and groundwater sustainability. Through extensive biophysical and agrohydrological modeling and empirical field data, the research quantifies the impacts of these environmental stressors and offers evidence-based strategies for mitigating their effects. A biophysical model that incorporates soil, weather, crop data, water cost, and production costs predicted that salinity levels exceeding 5 dS/m can reduce crop yields by up to 45% for highly sensitive crops like almonds and table grapes. On the other hand, these crops could profit growers more because of their market values. The economic analysis shows that the profitability of agricultural production under different salinity scenarios varies significantly, with potential annual economic losses amounting to hundreds of millions of dollars, underscoring the critical need for tailored salinity management strategies. A salinity decision-support web tool was developed. This tool enables users to input data and predict crop yields and economic outcomes. The tool's application in real-world scenarios has shown that it can effectively assist farmers and policymakers in making informed decisions that optimize economic returns and environmental sustainability.Concurrently, the dissertation evaluates the effectiveness of various conservation practices, such as cover crops, irrigation nitrogen credits, and high-frequency low fertigation, in reducing nitrate leaching. Utilizing the APEX model, the results demonstrate that these practices can reduce nitrate leaching of the root zone by up to 90%, thereby substantially decreasing the risk of groundwater contamination. This study also evaluated an integrated AMRS model to assess and manage nitrate nitrogen (NO3-N) leaching into groundwater at a field scale. The model was evaluated at the deep vadose zone and shallow groundwater and showed that conservation practices such as HFLC can mitigate groundwater NO3-N contamination. This part of the research highlights the practical benefits of integrating agronomic and environmental conservation practices into farming operations to enhance the sustainability of water resources. Overall, this dissertation provides a comprehensive framework for understanding and addressing the dual challenges of salinity and nitrate leaching in irrigated agriculture. By offering detailed insights into the mechanisms underlying these challenges and developing practical tools for stakeholders, the research contributes to the sustainable management of natural resources in agricultural regions facing similar environmental pressures

Runoff simulation of ungauged catchments : importance in the Nepalese context

Nepal is a landlocked country in the foothills of the Himalayan region in South Asia and a country endowed with rich water resources. However, the country is unable to utilize and manage the full potential of available water resources. One of the reasons for this is the lack of an adequate network of river gauging stations necessary to collect hydrologic data. Installation of hydrological stations is an expensive proposition and not financially viable for small water resources projects (water supply, irrigation, mini and micro-hydro projects). This research aims to address the challenges via an alternative strategy - i.e. the use of a hydrological model which can reliably simulate runoff in ungauged catchments even in the absence of adequate hydrologic data. SWAT (Soil & Water Assessment Tool), a popular simulation model with ArcGIS and QGIS interface, was chosen to simulate flow in an ungauged catchment in the mid-western region of Nepal. The model was applied to the West Rapti River basin using five years (1981-1985) of data from the Global Runoff Data Centre (GRDC). The GRDC was the only source, and the dataset was incomplete, limiting the model calibration and validation process. This limitation was addressed by using another simulation model, HEC-HMS (Hydrologic Engineering Centre’s Hydrologic Modeling System), for comparison. The results of the SWAT model were compared with those from HEC-HMS, one of the most widely used rainfall-runoff simulation models. Comparative analysis showed that both models generated comparable results. Historical rainfall data (1979-2009) were extracted from the Global Weather Data for SWAT to predict the rainfall trend in the West Rapti Watershed. This trend in rainfall pattern was used to extract rainfall and simulate runoff for 2023 to 2026, considering rainfall data of 2013 as a baseline. The simulated results showed a minor shift in time to peak and increased peak discharge. Similarly, the simulated runoff trends matched perfectly with the observed rainfall trend in SWAT. Thus, the results proved the reliability of SWAT to simulate runoff in the West Rapti Basin. The conclusion was drawn that the SWAT model can be used reliably to predict runoff in ungauged catchments that assist with managing water resources and contribute to the development of Nepal’s economy

Modelling climate change impacts on the water regimes of the river-wetland systems in the data-scarce transboundary Upper Meghna River Basin (Bangladesh and India)

Many regions are likely to be increasingly exposed to water related problems due to climate change-driven modifications to the hydrological cycle. Flooding is the major long-term problem in the haor wetlands of the transboundary (Bangladesh and India) Upper Meghna River Basin (UMRB). Past studies of haor wetlands and changes due to climate change have provided conflicting results. Many studies either ignore the role of haors on local hydrology or do not correctly represent haor hydraulics. In order to address the above issues, this study first develops a modified version of the Soil and Water Assessment Tool (SWAT) for riparian wetlands (SWATrw). This model better represents bidirectional hydraulic interactions between wetlands, rivers and aquifers. A case study for the comparatively data rich Hakaluki haor shows that SWATrw outperforms the original SWAT in the simulation of haor hydrology including flash flooding from adjacent rivers and the persistence of water through the dry season haor which is sustained by aquifers. A SWATrw model for the entire UMRB is developed and manually calibrated and validated against 21 years (1990–2010) of observed streamflow and river stage at 18 gauging stations. The model is forced with projections from four CMIP5 GCMs for the RCP4.5 scenario. An improved Quantile Mapping (QM) based approach is developed to remove biases from raw GCM data as well as adjusting dry day (coldest day for temperature) frequency. Compared to the baseline (1981–2000), monsoonal streamflows are projected to increase by up to 12% for 2021–2040 and 42% for 2061–2080. Dry season low flows decrease by as much as 58%. The average flooding risk in haors in April is likely to decrease which will likely benefit Boro rice cultivation. However, flooding risk in May is considerably higher compared to the baseline

3D indoor modeling and game theory based navigation for pre and post COVID-19 situation

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural facilities. There aren’t any maps available for most installations, and there are no proven techniques to categorize features within indoor areas to provide location-based services. During a pandemic like COVID-19, the direct connection between the masses is one of the significant preventive steps. Hospitals are the main stakeholders in managing such situations. This study presents a novel method to create an adaptive 3D model of an indoor space to be used for localization and routing purposes. The proposed method infuses LiDAR-based data-driven methodology with a Quantum Geographic Information System (QGIS) model-driven process using game theory. The game theory determines the object localization and optimal path for COVID-19 patients in a real-time scenario using Nash equilibrium. Using the proposed method, comprehensive simulations and model experiments were done using QGIS to identify an optimized route. Dijkstra algorithm is used to determine the path assessment score after obtaining several path plans using dynamic programming. Additionally, Game theory generates path ordering based on the custom scenarios and user preference in the input path. In comparison to other approaches, the suggested way can minimize time and avoid congestion. It is demonstrated that the suggested technique satisfies the actual technical requirements in real-time. As we look forward to the post-COVID era, the tactics and insights gained during the pandemic hold significant value. The techniques used to improve indoor navigation and reduce interpersonal contact within healthcare facilities can be applied to maintain a continued emphasis on safety, hygiene, and effective space management in the long term. The use of three-dimensional (3D) modeling and optimization methodologies in the long-term planning and design of indoor spaces promotes resilience and flexibility, encouraging the adoption of sustainable and safe practices that extend beyond the current pandemic