A comparative assessment of HEC-HMS and VIC hydrological models for simulating hydrological processes in Cauvery River Basin, India

2021 ◽  
Author(s):  
Gowri Reghunath ◽  
Pradeep Mujumdar
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Geographical Information ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Hydrological Models ◽  
Water Balance Components ◽  
Cauvery River ◽  
Cauvery River Basin ◽  
The Impact

<p>The hydrological cycle is governed by a number of complex processes which occur at different spatial and temporal scales. Hydrological modelling plays an integral role in enhancing the understanding of hydrological behaviour and process complexities at a range of scales. Different hydrological models have various strengths in the representation of hydrological processes. The performance and applicability of each hydrological model can differ between catchments due to several catchment characteristics and dominant hydrological processes. With a wide variety of model structures, it is important to evaluate how different hydrological models capture the process dynamics in various catchments. This study aims at a comprehensive evaluation of the performance of two widely used hydrological models, namely, the HEC-Hydrologic Modeling System (HEC-HMS) and the Variable Infiltration Capacity (VIC) model, in simulating various water balance components in the sub-catchments of the Cauvery River Basin which is a major river basin in Peninsular India. The basin is characterized by extensive regional variability in land use patterns, water availability, and water demands. The chosen models differ in their model structure complexities, methods adopted for simulation of water balance components, and the representation of geographical information, meteorological and physiographical inputs. The models are calibrated with respect to the observed streamflow at various gauge locations, and the simulated water balance components such as evapotranspiration and baseflow are assessed at annual and seasonal time scales. Also, the impact of the representation of the spatial distribution of input variables and model parameters (lumped versus distributed) are evaluated among the models. This work provides valuable insights into the applicability of various hydrological models in simulating hydrological processes in catchments with high regional complexities. Also, this work aids in the identification of effective models and model parameters which can be useful for hydrological data transfers between catchments as well as predictions in ungauged basins.</p>

scholarly journals The Impact of Para Rubber Expansion on Streamflow and Other Water Balance Components of the Nam Loei River Basin, Thailand

Water ◽  
2016 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Winai Wangpimool ◽  
Kobkiat Pongput ◽  
Nipon Tangtham ◽  
Saowanee Prachansri ◽  
Philip Gassman
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Water Balance Components ◽  
The Impact

Evaluating hydrological signatures and catchment similarities to estimate model parameters in Cauvery river basin, India

2020 ◽  
Author(s):  
Gowri Reghunath ◽  
Pradeep Mujumdar
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Meteorological Data ◽  
Model Parameters ◽  
Catchment Scale ◽  
Infiltration Capacity ◽  
Cauvery River ◽  
Groundwater Availability ◽  
Cauvery River Basin ◽  
Hydrological Signatures

<p>Catchments are complex self-organizing environmental systems for which the form, drainage network, channel geometries, soil and vegetation, are all an outcome of co-evolution and adaptation to the ecological, geomorphologic and land-forming processes. Quantification of hydrological signatures provides vital information about the complex system properties and the functional behaviour of catchments. This work aims at evaluating catchment similarity with respect to geomorphology and hydrological signatures such as runoff ratio, flow duration curves and peak flows for calibrating and upscaling model parameters. The study is carried out on the sub-catchments of Cauvery river basin which is a major river basin in Peninsular India. The basin is characterized by extensive regional variability in surface and groundwater availability and large-scale shift in land use patterns in recent decades. With a significant number of anthropogenic interventions such as check dams and reservoirs, the basin faces water management challenges at the local, regional and basin scales. Hydrological signatures derived from elevation, streamflow and meteorological data are used to evaluate geomorphologic and hydrological similarity between the sub-catchments. We employ the physically based macroscale Variable Infiltration Capacity (VIC) model coupled with a routing model to simulate the streamflow. Streamflow simulations are carried out for various sub-catchments delineated based on discharge gauging stations. Model parameters are estimated and hydrological signatures are assessed for effective model calibration. Impact of interventions on flow signatures at the catchment scale is also assessed. This work can significantly improve the scientific understanding of variability of hydrological processes at various scales and provide useful insights for development of scaling relationships. It can also aid in examining the model parameter transferability across scales.</p>

scholarly journals Modelling Hydrological Processes and Identifying Soil Erosion Sources in a Tropical Catchment of the Great Barrier Reef Using SWAT

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2179
Author(s):  
Vahid Rafiei ◽  
Afshin Ghahramani ◽  
Duc-Anh An-Vo ◽  
Shahbaz Mushtaq
Keyword(s):  
Sediment Transport ◽  
Soil Erosion ◽  
Water Balance ◽  
Great Barrier Reef ◽  
Hydrological Processes ◽  
Barrier Reef ◽  
Water Balance Components ◽  
Study Region ◽  
Erosion Hotspots ◽  
The Impact

Study region: North Johnstone catchment, located in the north east of Australia. The catchment has wet tropical climate conditions and is one of the major sediment contributors to the Great Barrier Reef. Study focus: The purpose of this paper was to identify soil erosion hotspots through simulating hydrological processes, soil erosion and sediment transport using the Soil and Water Assessment Tool (SWAT). In particular, we focused on predictive uncertainty in the model evaluations and presentations—a major knowledge gap for hydrology and soil erosion modelling in the context of Great Barrier Reef catchments. We carried out calibration and validation along with uncertainty analysis for streamflow and sediment at catchment and sub-catchment scales and investigated details of water balance components, the impact of slope steepness and spatio-temporal variations on soil erosion. The model performance in simulating actual evapotranspiration was compared with those of the Australian Landscape Water Balance (AWRA-L) model to increase our confidence in simulating water balance components. New hydrological insights for the region: The spatial locations of soil erosion hotspots were identified and their responses to different climatic conditions were quantified. Furthermore, a set of land use scenarios were designed to evaluate the effect of reforestation on sediment transport. We anticipate that protecting high steep slopes areas, which cover a relatively small proportion of the catchment (4–9%), can annually reduce 15–26% sediment loads to the Great Barrier Reef.

scholarly journals Calibration of a Distributed Hydrological Model in a Data-Scarce Basin Based on GLEAM Datasets

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 897 ◽  
Author(s):  
Xin Jin ◽  
Yanxiang Jin
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Great Effort ◽  
Observation Data ◽  
Hydrological Models

The calibration of hydrological models is often complex in regions with scarce data, and generally only uses site-based streamflow data. However, this approach will yield highly generalised values for all model parameters and hydrological processes. It is therefore necessary to obtain more spatially heterogeneous observation data (e.g., satellite-based evapotranspiration (ET)) to calibrate such hydrological models. Here, soil and water assessment tool (SWAT) models were built to evaluate the advantages of using ET data derived from the Global Land surface Evaporation Amsterdam Methodology (GLEAM) to calibrate the models for the Bayinhe River basin in northwest China, which is a typical data-scarce basin. The result revealed the following: (1) A great effort was required to calibrate the SWAT models for the study area to obtain an improved model performance. (2) The SWAT model performance for simulating the streamflow and water balance was reliable when calibrated with streamflow only, but this method of calibration grouped the hydrological processes together and caused an equifinality issue. (3) The combination of the streamflow and GLEAM-based ET data for calibrating the SWAT model improved the model performance for simulating the streamflow and water balance. However, the equifinality issue remained at the hydrologic response unit (HRU) level.

Integrating reservoirs in a landscape-based hydrological model to understand the impact of the reservoir on flow regime in the Cauvery river basin, India

2020 ◽  
Author(s):  
Anjana Ekka ◽  
Saket Kesav ◽  
Saket Pande ◽  
Pieter van der Zaag ◽  
Yong Jiang
Keyword(s):  
Flow Regime ◽  
River Basin ◽  
River Flow ◽  
Calibration Method ◽  
Reservoir Model ◽  
Cauvery River ◽  
River Landscape ◽  
Cauvery River Basin ◽  
The Impact ◽  
Gauging Station

<p>As economic development continues to expand, rivers resources are exploited for power generation, flood control, and irrigation, which substantially impacts the river hydrology and surrounding ecosystem.  Reservoir construction is one of the major contributors to such changes.  Around the world, the long free-flowing rivers are impaired due to reservoirs and their downstream propagation of fragmentation and flow regulation, which impacts the structural and functional connectivities of the entire basin. The extent of interdependence and interactions of biophysical, social, and economic characteristics determine hydrological behaviour and thus define the sustainability of the river ecosystem. In this regard, the topography driven rainfall-runoff modeling (Flex-Topo model) approximates the river landscape hydrological behaviour by delineating the catchment into three functional hydrological units (HRUs).  However, these HRUs are natural and do not take anthropogenic factors into account. Therefore, the present study aims to understand the effects of the integration of reservoirs into a Flex-Topo model to assess model transferability in predicting the river flow regime in ungauged basins.</p><p>The Cauvery river basin in India is chosen as a case study. The construction of reservoirs in the Cauvery basin helped to expand irrigated areas, securing water availability during water stress conditions. Nevertheless, it aggravates the water allocation between upstream and downstream states leading to conflict among states sharing the river basin. Based on size and storage capacity, four large reservoirs are selected for the study. At first, the watershed area is delineated based on the gauge location. For adding reservoirs, two different flex-models are created for the watershed’s areas upstream and downstream of the reservoirs. A separate reservoir model is created for each reservoir. The reservoir model is integrated into the flex-model following operation rule curves to simulate the reservoir based on different reservoir yield. It is assumed that the response of the upstream catchment will serve as an input to the reservoir, and the outflow of the reservoir will be an input to the downstream catchment. These three subunits are connected, and river flow is simulated at the gauge station located at the downstream of the reservoir. Three different procedures are adopted to calibrate the model. First, the integrated flex reservoir model is calibrated using the downstream gauging station. In the second calibration method the reservoir is calibrated first, then keeping the parameters of the reservoir fixed the integrated model is calibrated using downstream gauging station. Third, both the reservoir model and flex model are calibrated separately. The modelled runoff from each parameter sets are compared using Nash-Sutcliffe Model Efficiency and Mean Absolute Error with the observed.</p><p>Results indicate that the second calibration method performed the best and improved the overall performance of the Flex-Topo model. Further, results are compared across the four reservoirs in order to develop a generalized understanding of transferring a integrated flex model to basins where data on reservoirs is unavailable. The proposed method therefore provides a way to simulate both biophysical constraint and anthropogenic modifications simultaneously in river landscape and enhance understanding of impact of reservoirs on river flow regime.</p>

scholarly journals Estimation of Water Balance Components of Watersheds in the Manjira River Basin using SWAT Model and GIS

2020 ◽  
Vol 9 (3) ◽  
pp. 3898-3907
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Assessment Tool ◽  
Potential Evapotranspiration ◽  
Swat Model ◽  
Geographical Information ◽  
Weather Data ◽  
Water Yield ◽  
Water Balance Components ◽  
Rain Data

This study mainly focus on hydrological behavior of watersheds in The Manjira River basin using soil and water assessment tool (SWAT) and Geographical information system (GIS). The water balance components for watersheds in the Manjira River were determined by using SWAT model and GIS. Determination of these water balance components helps to study direct and indirect factors affecting characteristics of selected watersheds. Manjira River contains total 28 watersheds among them 2 were selected having watershed code as MNJR008 and MNJR011 specified by the Central Ground Water Board. The SWAT input data such as Digital elevation model (DEM), land use and land cover (LU/LC), Soil classification, slope and weather data was collected. Using these inputs in SWAT the different water balancing components such as rainfall, baseflow, surface runoff, evapotranspiration (ET), potential evapotranspiration (PET) and water yield for each watershed were determined. The evaluated data is then validated by Regression analysis, in which two datasets were compared. Simulated rain data from SWAT simulation and observed rain data from Global Weather Data for SWAT was selected for comparison for each watershed.

Simulating continental scale hydrology under projected climate change conditions: The search for the optimal parameterization

2020 ◽  
Author(s):  
Wendy Sharples ◽  
Andrew Frost ◽  
Ulrike Bende-Michl ◽  
Ashkan Shokri ◽  
Louise Wilson ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
High Resolution ◽  
Water Balance ◽  
Large Scale ◽  
Model Parameters ◽  
Hydrological Models ◽  
Water Balance Components ◽  
Impacts Of Climate Change

<p>Australia has scarce freshwater resources and is already becoming drier under the impacts of climate change. Climate change impacts and other important hydrological processes occur on multiple temporal and spatial scales, prompting the need for large-scale, high-resolution, multidecadal hydrological models. Large-scale hydrological models rely on accurate process descriptions and inputs to be able to simulate realistic multi-scale processes, however parameterization is required to account for limitations in observational inputs and sub-grid scale processes. For example, defining the soil hydraulic boundary conditions at multiple depths using soil input maps at high-resolution across an entire continent is subject to uncertainty. A common way to reduce uncertainty associated with static inputs and parameterization, thereby improving model accuracy and reliability, is to optimize the model parameters toward a long record of historical data, namely calibration. The Australian Bureau of Meteorology’s operational hydrological model (The Australian Water Resources Assessment model: AWRA-L, www.bom.gov.au/water/landscape), which provides real-time monitoring of the continental water balance, is calibrated to a combined performance metric. This metric optimizes model performance against catchment based streamflow and satellite based evaporation and soil moisture observations for 295 sites across the country, where 21 separate parameters are calibrated continentally. Using this approach, AWRA-L has been shown to reproduce independent, historical in-situ data accurately across the water balance.</p><p>Additionally, the AWRA-L model is being used to project future hydrological fluxes and states using bias corrected meteorological inputs from multiple global climate models. Towards improving AWRA-L’s performance and stability for use in hydrological projections, we aim to generate a set of model parameters that perform well under conditions of climate variability as well as under historical conditions, with a two-stage approach. Firstly, a variance based sensitivity analysis for water balance components (e.g. low/mean/high flow, soil moisture and evapotranspiration) is performed, to rank the most influential parameters affecting the water balance components and to subsequently decrease the number of calibratable parameters, thus decreasing dimensionality and uncertainty in the calibration process. Secondly, the reduced parameter set is put through a multi-objective evolutionary algorithm (Borg MOEA, www.borgmoea.org), to capture the tradeoffs between the water balance component performance objectives. The tradeoffs between the water balance component objective functions and in-situ validation data are examined, including evaluation of performance in: a) Climate zones, b) Seasons, c) Wet and dry periods, and d) Trend reproduction. This comprehensive evaluation was undertaken to choose a model parameterization (or set thereof) which produces reasonable hydrological responses under future climate variability across the water balance. The outcome is a suite of parameter sets with improved performance across varying and non-stationary climate conditions. We propose this approach to improve confidence in hydrological models used to simulate future impacts of climate change.</p>

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