Hydrologic modeling by means of a hybrid downscaling approach: an application to the Sai Gon–Dong Nai Rivers Basin

The spatial and temporal availability and reliability of hydrological data are substantial contribution to the accuracy of watershed modeling; unfortunately, such data requirements are challenging and perhaps impossible in many regions of the world. In this study, hydrological conditions are simulated using the hydrologic model-WEHY, whose data input are obtained from a hybrid downscaling technique to provide reliable and high temporal and spatial resolution hydrological data. The hybrid downscaling technique is coupled a hydroclimate and a machine learning models; wherein the global atmospheric reanalysis data, including ERA-Interim, ERA-20C, and CFSR are used for initial and boundary conditions of dynamical downscaling utilizing the Weather Research and Forecasting model (WRF). The machine learning model (ANN) then follows to further downscale the WRF outputs to a finer resolution over the studied watershed. An application of the combination of mentioned techniques is applied to the third-largest river basin in Vietnam, the Sai Gon–Dong Nai Rivers Basin. The validation of hybrid model is in the ‘satisfactory’ range. After the estimation of geomorphology and land cover within the watershed, WEHY's calibration and validation are performed based on observed rainfall data. The simulation results matched well with flow observation data with respect to magnitude for both the rising and recession time segments. In comparison among the three selected reanalysis data sets, the best calibration and validation results were obtained from the CFSR data set. These results are closer to the observation data than those using only the dynamic downscaling technique in combination with the WEHY model.

Watershed subdivision and weather input effect on streamflow simulation using SWAT model

In watershed modeling research, it is practical to subdivide a watershed into smaller units or sub-watersheds for modeling purposes. The ability of a model to simulate the watershed system depends on how well watershed processes are represented by the model and how well the watershed system is described by model input. This study is conducted to evaluate the impact of watershed subdivision and different weather input datasets on streamflow simulations using the soil and water assessment tool model. For this purpose, Cuhai-Bakonyér watershed was chosen as a study area. Two climate databases and four subdivision variations levels were evaluated. The model streamflow predictions slightly effected by subdivision impact. The climate datasets showed significant differences in streamflow predictions.

Define–Investigate–Estimate–Map (DIEM) Framework for Modeling Habitat Threats

As the human population increases, the landscape is altered to provide housing, food, and industry. Human activity poses a risk to the health of natural habitats that, in turn, affect biodiversity. Biodiversity is necessary for a functioning ecosystem, as species work synergistically to create a livable environment. It is, therefore, important to know how human practices and natural events threaten these habitats and the species living in them. A universal method of modeling habitat threats does not exist. This paper details the use of a literature review to formulate a new framework called Define–Investigate–Estimate–Map (DIEM). This framework is a process of defining threats, investigating an area to discover what threats are present, estimating the severity of those threats, and mapping the threats. Analysis of 62 studies was conducted to determine how different authors define and characterize threats in various contexts. The results of this analysis were then applied to a case study to evaluate the Choctawhatchee River and Bay Watershed. Results suggest that the most abundant threat in the watershed is agricultural development, and the most destructive threat is urban development. These two threats have the greatest impact on the total threat level of the watershed. Applying the DIEM framework demonstrates its helpfulness in regional analysis, watershed modeling, and land development planning.

Integrative Assessment of Stormwater Infiltration Practices in Rapidly Urbanizing Cities: A Case of Lucknow City, India

The lack of strategic planning in stormwater management has made rapidly urbanizing cities more vulnerable to urban water issues than in the past. Low infiltration rates, increase in peak river discharge, and recurrence of urban floods and waterlogging are clear signs of unplanned rapid urbanization. As with many other low to middle-income countries, India depends on its conventional and centralized stormwater drains for managing stormwater runoff. However, in the absence of a robust stormwater management policy governed by the state, its impact trickles down to a municipal level and the negative outcome can be clearly observed through a failure of the drainage systems. This study examines the role of onsite and decentralized stormwater infiltration facilities, as successfully adopted by some higher income countries, under physical and social variability in the context of the metropolitan city of Lucknow, India. Considering the 2030 Master Plan of Lucknow city, this study investigated the physical viability of the infiltration facilities. Gridded ModClark rainfall-runoff modeling was carried out in Kukrail river basin, an important drainage basin of Lucknow city. The HEC-HMS model, inside the watershed modeling system (WMS), was used to simulate stormwater runoff for multiple scenarios of land use and rainfall intensities. With onsite infiltration facilities as part of land use measures, the peak discharge reduced in the range of 48% to 59%. Correlation analysis and multiple regression were applied to understand the rainfall-runoff relationship. Furthermore, the stormwater runoff drastically reduced with decentralized infiltration systems.

Assessing interannual variability in nitrogen sourcing and retention through hybrid Bayesian watershed modeling

Excessive nutrient loading is a major cause of water quality problems worldwide, often leading to harmful algal blooms and hypoxia in lakes and coastal systems. Efficient nutrient management requires that loading sources are accurately quantified. However, loading rates from various urban and rural non-point sources remain highly uncertain especially with respect to climatological variation. Furthermore, loading models calibrated using statistical techniques (i.e., hybrid models) often have limited capacity to differentiate export rates among various source types, given the noisiness and paucity of observational data common to many locations. To address these issues, we leverage data for two North Carolina Piedmont river basins collected over three decades (1982–2017) using a mechanistically parsimonious watershed loading and transport model calibrated within a Bayesian hierarchical framework. We explore temporal drivers of loading by incorporating annual changes in precipitation, land use, livestock, and point sources within the model formulation. Also, different representations of urban development are compared based on how they constrain model uncertainties. Results show that urban lands built before 1980 are the largest source of nutrients, exporting over twice as much nitrogen per hectare than agricultural and post-1980 urban lands. In addition, pre-1980 urban lands are the most hydrologically constant source of nutrients, while agricultural lands show the most variation among high- and low-flow years. Finally, undeveloped lands export an order of magnitude (∼7–13×) less nitrogen than built environments.

The demonstration and validation of a linked watershed-riverine modeling system for DoD installations : user guidance report version 2.0

A linked watershed model was evaluated on three watersheds within the U.S.: (1) House Creek Watershed, Fort Hood, TX; (2) Calleguas Creek Watershed, Ventura County, CA; and (3) Patuxent River Watershed, MD. The goal of this demonstration study was to show the utility of such a model in addressing water quality issues facing DoD installations across a variety of climate zones. In performing the demonstration study, evaluations of model output with regards to accuracy, predictability and meeting regulatory drivers were completed. Data availability, level of modeling expertise, and costs for model setup, validation, scenario analysis, and maintenance were evaluated in order to inform installation managers on the time and cost investment needed to use a linked watershed modeling system. Final conclusions were that the system evaluated in this study would be useful for answering a variety of questions posed by installation managers and could be useful in developing management scenarios to better control pollutant runoff from installations.

Modelling Watershed and River Basin Processes in Cold Climate Regions: A Review

Watersheds in cold regions provide water, food, biodiversity and ecosystem service. However, the increasing demand for water resources and climate change challenge our ability to provide clean freshwater. Particularly, watersheds in cold regions are more sensitive to changing climate due to their glaciers’ retreat and permafrost. This review revisits watershed system and processes. We analyze principles of watershed modelling and characteristics of watersheds in cold regions. Then, we show observed evidence of their impacts of cold processes on hydrological and biogeochemical processes and ecosystems, and review the watershed modeling and their applications in cold regions. Finally, we identify the knowledge gaps in modeling river basins according to model structures and representations of processes and point out research priorities in future model development.