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Special Issue "Hydrological Modelling and Remote Sensing: Selected Papers from the 2017 and 2018 SWAT International Conferences"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 15 April 2019

Special Issue Editors

Guest Editor
Prof. Balaji Narasimhan

Indian Institute of Technology – Madras, Chennai - 600036, India
Website | E-Mail
Interests: hydrological modelling; remote Sensing; large-scale simulations; climate/landuse change impact studies
Guest Editor
Dr. Paul Wagner

Department of Hydrology and Water Resources Management, Kiel University, 24118 Kiel, Germany
Website | E-Mail
Phone: +49 431 880 1237
Interests: hydrologic modeling; impacts of land use change and climate change on water resources; integration of remote sensing and modeling
Guest Editor
Prof. Claire Baffaut

USDA-Agricultural Research Service - Cropping and Water Quality Research Unit, USA
Website | E-Mail
Phone: 573-882-1114 x315
Interests: hydrological modeling at plot, field and watershed scale; simulation and evaluation of management practices; impacts of climate change
Guest Editor
Dr. Mou Leong Tan

Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia
Website | E-Mail
Phone: +604-653 6036
Interests: hydrological modelling; remote sensing; climate/land use change impact analysis
Guest Editor
Dr. Abeyou Wale Worqlul

Blackland Research and Extension Center, Texas A&M Agrilife Research, USA
Website | E-Mail
Interests: watershed hydrology; GIS and remote sensing; crop yield; biomass simulation

Special Issue Information

Dear Colleagues,

Although considerable improvement has been made in hydrologic sciences, and the representation of the processes within the models, this has also led to increased data requirements for the spatial representation of a study area and model parameterization.  In the past decade, remote sensing data have become increasingly available to the hydrologic community for developing a representative spatially-distributed model for assessing the impacts of landuse change, and land and water management practices on water resources at the river basin scale. Further, data on hydrologic state variables, such as evapotranspiration from thermal sensors and soil moisture from microwave sensors, are also being explored for calibration and validation of hydrological models, either independently or within a data assimilation framework. Many research challenges are being actively explored, which aim toward calibration of hydrological models for watersheds and river basins taking into account the true spatial variability of observed processes as opposed to lumped calibration of the model parameters at the point of discharge measurements. This Special Issue of Water is envisioned to showcase the state of the art in the adaptation and use of remotely sensed data for hydrologic modelling using SWAT at different scales and climatic regions for model parameterization, calibration, validation and data assimilation. We sincerely hope that these research papers would address the lacuna that exists in the use of remote sensing data with the hydrologic models, methods to overcome them and identify issues that need further research.

Prof. Balaji Narasimhan
Dr. Paul Wagner
Prof. Claire Baffaut
Dr. Mou Leong Tan
Dr. Abeyou Wale Worqlul
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Model Parameterization
  • Calibration and Validation
  • Data Assimilation
  • Large-Scale Modelling
  • Climate Change Impact
  • SWAT Model
  • Remote Sensing

Published Papers (8 papers)

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Research

Open AccessArticle Assessing the Impact of Site-Specific BMPs Using a Spatially Explicit, Field-Scale SWAT Model with Edge-of-Field and Tile Hydrology and Water-Quality Data in the Eagle Creek Watershed, Ohio
Water 2018, 10(10), 1299; https://doi.org/10.3390/w10101299
Received: 7 August 2018 / Revised: 31 August 2018 / Accepted: 17 September 2018 / Published: 21 September 2018
PDF Full-text (8999 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded
[...] Read more.
The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded through GLRI at the field and watershed scales. The location and quantity of BMPs were obtained from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) database. A Soil and Water Assessment Tool (SWAT) model was built and calibrated for this predominantly agricultural Eagle Creek watershed, incorporating NCP BMPs and monitoring data at the watershed outlet, an edge-of-field (EOF), and tile monitoring sites. Input air temperature modifications were required to induce simulated tile flow to match monitoring data. Calibration heavily incorporated tile monitoring data to correctly proportion surface and subsurface flow, but calibration statistics were unsatisfactory at the EOF and tile monitoring sites. At the watershed outlet, satisfactory to very good calibration statistics were achieved over a 2-year calibration period, and satisfactory statistics were found in the 2-year validation period. SWAT fixes parameters controlling nutrients primarily at the watershed level; a refinement of these parameters at a smaller-scale could improve field-level calibration. Field-scale modeling results indicate that filter strips (FS) are the most effective single BMPs at reducing dissolved reactive phosphorus, and FS typically decreased sediment and nutrient yields when added to any other BMP or BMP combination. Cover crops were the most effective single, in-field practice by reducing nutrient loads over winter months. Watershed-scale results indicate BMPs can reduce sediment and nutrients, but reductions due to NCP BMPs in the Eagle Creek watershed for all water-quality constituents were less than 10%. Hypothetical scenarios simulated with increased BMP acreages indicate larger investments of the appropriate BMP or BMP combination can decrease watershed level loads. Full article
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Open AccessArticle Evaluation of the Climate Forecast System Reanalysis Weather Data for Watershed Modeling in Upper Awash Basin, Ethiopia
Water 2018, 10(6), 725; https://doi.org/10.3390/w10060725
Received: 19 March 2018 / Revised: 31 May 2018 / Accepted: 31 May 2018 / Published: 3 June 2018
PDF Full-text (3589 KB) | HTML Full-text | XML Full-text
Abstract
Availability of reliable meteorological data for watershed modeling is one of the considerable challenges in the Awash River Basin in Ethiopia. To overcome this challenge, the Climate Forecast System Reanalysis (CFSR) global weather data was evaluated and compared with the limited conventional weather
[...] Read more.
Availability of reliable meteorological data for watershed modeling is one of the considerable challenges in the Awash River Basin in Ethiopia. To overcome this challenge, the Climate Forecast System Reanalysis (CFSR) global weather data was evaluated and compared with the limited conventional weather data available in the Upper Awash Basin. The main objective of this study was to search for an optional data source for hydrological modeling, instead of using the limited available data, and for data-scarce areas of the basin. The Soil and Water Assessment Tool model was used to compare the performance of the two weather datasets at simulating monthly streamflow. For calibration, validation, and uncertainty analysis, the sequential uncertainty fitting algorithm was used. The model evaluation statistics showed that the CFSR global weather data performed similarly to the conventional weather data for simulating the observed streamflow at Melka Kunture. At Keleta, where the conventional data is scarce, the CFSR performed better. The CFSR performance at the two sub-basins indicated that it performed better for the large sub-basin, Melka Kunture. Generally, the CFSR weather data are a good addition to the dataset for areas where no reliable weather data exists for hydrological modeling in the basin. The precipitation data of the CFSR are slightly higher than that of the conventional data, which also resulted in a relatively higher water balance components. Full article
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Open AccessArticle Use of Decision Tables to Simulate Management in SWAT+
Water 2018, 10(6), 713; https://doi.org/10.3390/w10060713
Received: 9 May 2018 / Revised: 24 May 2018 / Accepted: 28 May 2018 / Published: 31 May 2018
Cited by 1 | PDF Full-text (1215 KB) | HTML Full-text | XML Full-text
Abstract
Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river–reservoir models
[...] Read more.
Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river–reservoir models simulate complex land management operations and reservoir management in highly regulated river systems. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. In this study, we discuss the suitability of decision tables to simulate management in the river basin scale Soil and Water Assessment Tool (SWAT+) model. Decision tables are developed to simulate automated irrigation and reservoir releases. A simple auto irrigation application of decision tables was developed using plant water stress as a condition for irrigating corn in Texas. Sensitivity of the water stress trigger and irrigation application amounts were shown on soil moisture and corn yields. In addition, the Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. The release rules as implemented by the decision table realistically simulated flood releases as evidenced by a daily Nash–Sutcliffe Efficiency (NSE) of 0.52 and a percent bias of −1.1%. Using decision tables to simulate management in land, river, and reservoir models was shown to have several advantages over current approaches, including: (1) mature technology with considerable literature and applications; (2) ability to accurately represent complex, real world decision-making; (3) code that is efficient, modular, and easy to maintain; and (4) tables that are easy to maintain, support, and modify. Full article
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Open AccessArticle Hydrological Modeling in Data-Scarce Catchments: The Kilombero Floodplain in Tanzania
Water 2018, 10(5), 599; https://doi.org/10.3390/w10050599
Received: 3 March 2018 / Revised: 24 April 2018 / Accepted: 1 May 2018 / Published: 4 May 2018
Cited by 2 | PDF Full-text (10088 KB) | HTML Full-text | XML Full-text
Abstract
Deterioration of upland soils, demographic growth, and climate change all lead to an increased utilization of wetlands in East Africa. This considerable pressure on wetland resources results in trade-offs between those resources and their related ecosystem services. Furthermore, relationships between catchment attributes and
[...] Read more.
Deterioration of upland soils, demographic growth, and climate change all lead to an increased utilization of wetlands in East Africa. This considerable pressure on wetland resources results in trade-offs between those resources and their related ecosystem services. Furthermore, relationships between catchment attributes and available wetland water resources are one of the key drivers that might lead to wetland degradation. To investigate the impacts of these developments on catchment-wetland water resources, the Soil and Water Assessment Tool (SWAT) was applied to the Kilombero Catchment in Tanzania, which is like many other East African catchments, as it is characterized by overall data scarcity. Due to the lack of recent discharge data, the model was calibrated for the period from 1958–1965 (R2 = 0.86, NSE = 0.85, KGE = 0.93) and validated from 1966–1970 (R2 = 0.80, NSE = 0.80, KGE = 0.89) with the sequential uncertainty fitting algorithm (SUFI-2) on a daily resolution. Results show the dependency of the wetland on baseflow contribution from the enclosing catchment, especially in dry season. Main contributions with regard to overall water yield arise from the northern mountains and the southeastern highlands, which are characterized by steep slopes and a high share of forest and savanna vegetation, respectively. Simulations of land use change effects, generated with Landsat images from the 1970s up to 2014, show severe shifts in the water balance components on the subcatchment scale due to anthropogenic activities. Sustainable management of the investigated catchment should therefore account for the catchment–wetland interaction concerning water resources, with a special emphasis on groundwater fluxes to ensure future food production as well as the preservation of the wetland ecosystem. Full article
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Open AccessArticle Assessing Long-Term Hydrological Impact of Climate Change Using an Ensemble Approach and Comparison with Global Gridded Model-A Case Study on Goodwater Creek Experimental Watershed
Water 2018, 10(5), 564; https://doi.org/10.3390/w10050564
Received: 19 March 2018 / Revised: 19 April 2018 / Accepted: 24 April 2018 / Published: 26 April 2018
PDF Full-text (12262 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Potential impacts of climate change on the hydrological components of the Goodwater Creek Experimental Watershed were assessed using climate datasets from the Coupled Model Intercomparison Project Phase 5 and Soil and Water Assessment Tool (SWAT). Historical and future ensembles of downscaled precipitation and
[...] Read more.
Potential impacts of climate change on the hydrological components of the Goodwater Creek Experimental Watershed were assessed using climate datasets from the Coupled Model Intercomparison Project Phase 5 and Soil and Water Assessment Tool (SWAT). Historical and future ensembles of downscaled precipitation and temperature, and modeled water yield, surface runoff, and evapotranspiration, were compared. Ensemble SWAT results indicate increased springtime precipitation, water yield, surface runoff and a shift in evapotranspiration peak one month earlier in the future. To evaluate the performance of model spatial resolution, gridded surface runoff estimated by Lund–Potsdam–Jena managed Land (LPJmL) and Jena Diversity-Dynamic Global Vegetation model (JeDi-DGVM) were compared to SWAT. Long-term comparison shows a 6–8% higher average annual runoff prediction for LPJmL, and a 5–30% lower prediction for JeDi-DGVM, compared to SWAT. Although annual runoff showed little change for LPJmL, monthly runoff projection under-predicted peak runoff and over-predicted low runoff for LPJmL compared to SWAT. The reasons for these differences include differences in spatial resolution of model inputs and mathematical representation of the physical processes. Results indicate benefits of impact assessments at local scales with heterogeneous sets of parameters to adequately represent extreme conditions that are muted in global gridded model studies by spatial averaging over large study domains. Full article
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Open AccessArticle Assessment of Suitable Areas for Home Gardens for Irrigation Potential, Water Availability, and Water-Lifting Technologies
Water 2018, 10(4), 495; https://doi.org/10.3390/w10040495
Received: 21 February 2018 / Revised: 6 April 2018 / Accepted: 13 April 2018 / Published: 17 April 2018
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Abstract
The study was conducted in Lake Tana Basin of Ethiopia to assess potentially irrigable areas for home gardens, water availability, and feasibility of water-lifting technologies. A GIS-based Multi-Criteria Evaluation (MCE) technique was applied to access the potential of surface and groundwater sources for
[...] Read more.
The study was conducted in Lake Tana Basin of Ethiopia to assess potentially irrigable areas for home gardens, water availability, and feasibility of water-lifting technologies. A GIS-based Multi-Criteria Evaluation (MCE) technique was applied to access the potential of surface and groundwater sources for irrigation. The factors affecting irrigation practice were identified and feasibility of water-lifting technologies was evaluated. Pairwise method and expert’s opinion were used to assign weights for each factor. The result showed that about 345,000 ha and 135,000 ha of land were found suitable for irrigation from the surface and groundwater sources, respectively. The rivers could address about 1–1.2% of the irrigable land during dry season without water storage structure whereas groundwater could address about 2.2–2.4% of the irrigable land, both using conventional irrigation techniques. If the seven major dams within the basin were considered, surface water potential would be increased and satisfy about 21% of the irrigable land. If rainwater harvesting techniques were used, about 76% of the basin would be suitable for irrigation. The potential of surface and groundwater was evaluated with respect to water requirements of dominant crops in the region. On the other hand, rope pump and deep well piston hand pump were found with relatively the most (26%) and the least (9%) applicable low-cost water-lifting technologies in the basin. Full article
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Open AccessArticle Multi-Objective Validation of SWAT for Sparsely-Gauged West African River Basins—A Remote Sensing Approach
Water 2018, 10(4), 451; https://doi.org/10.3390/w10040451
Received: 22 February 2018 / Revised: 15 March 2018 / Accepted: 5 April 2018 / Published: 9 April 2018
PDF Full-text (9790 KB) | HTML Full-text | XML Full-text
Abstract
Predicting freshwater resources is a major concern in West Africa, where large parts of the population depend on rain-fed subsistence agriculture. However, a steady decline in the availability of in-situ measurements of climatic and hydrologic variables makes it difficult to simulate water resource
[...] Read more.
Predicting freshwater resources is a major concern in West Africa, where large parts of the population depend on rain-fed subsistence agriculture. However, a steady decline in the availability of in-situ measurements of climatic and hydrologic variables makes it difficult to simulate water resource availability with hydrological models. In this study, a modeling framework was set up for sparsely-gauged catchments in West Africa using the Soil and Water Assessment Tool (SWAT), whilst largely relying on remote sensing and reanalysis inputs. The model was calibrated using two different strategies and validated using discharge measurements. New in this study is the use of a multi-objective validation conducted to further investigate the performance of the model, where simulated actual evapotranspiration, soil moisture, and total water storage were evaluated using remote sensing data. Results show that the model performs well (R2 calibration: 0.52 and 0.51; R2 validation: 0.63 and 0.61) and the multi-objective validation reveals good agreement between predictions and observations. The study reveals the potential of using remote sensing data in sparsely-gauged catchments, resulting in good performance and providing data for evaluating water balance components that are not usually validated. The modeling framework presented in this study is the basis for future studies, which will address model response to extreme drought and flood events and further examine the coincidence with Gravity Recovery and Climate Experiment (GRACE) total water storage retrievals. Full article
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Open AccessArticle A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain
Water 2018, 10(2), 192; https://doi.org/10.3390/w10020192
Received: 18 December 2017 / Revised: 8 February 2018 / Accepted: 9 February 2018 / Published: 11 February 2018
Cited by 3 | PDF Full-text (4291 KB) | HTML Full-text | XML Full-text
Abstract
Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) models have been evaluated and compared to find
[...] Read more.
Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) models have been evaluated and compared to find a method to improve streamflow estimation. For a more complete evaluation, the accuracy and ability of these streamflow estimation models was also established separately based on their performance during different periods of flows using regional flow duration curves (FDCs). Specifically, the FDCs were divided into five sectors: very low, low, medium, high and very high flow. This segmentation of flow allows analysis of the model performance for every important discharge event precisely. In this study, the models were applied in two catchments in Peninsular Spain with contrasting climatic conditions: Atlantic and Mediterranean climates. The results indicate that SWAT and ANNs were generally good tools in daily streamflow modelling. However, SWAT was found to be more successful in relation to better simulation of lower flows, while ANNs were superior at estimating higher flows in all cases. Full article
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