Next Issue
Volume 9, September
Previous Issue
Volume 9, July
 
 

Hydrology, Volume 9, Issue 8 (August 2022) – 22 articles

Cover Story (view full-size image): This work aims to involve water resource decision makers in the process of understanding and acknowledging the benefits of probabilistic predictions. Decision makers take risk-minimizing, no-regret decisions without any certainty of future events, and the dispersion of potential states due to the chaotic nature of atmospheric processes highly increases uncertainty. Thus, the uncertainty of future states, in the form of a predictive probability distribution, must be assessed using model forecasts adequately corrected to generate observations and projections into the future. Based on predictive distributions’ ability to encapsulate the best information on future events, users might then estimate “expected” benefits (or losses) and formulate planning/management strategies via optimizing them as Bayesian decision problems. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
Article
Prediction at Ungauged Catchments through Parameter Optimization and Uncertainty Estimation to Quantify the Regional Water Balance of the Ethiopian Rift Valley Lake Basin
Hydrology 2022, 9(8), 150; https://doi.org/10.3390/hydrology9080150 - 19 Aug 2022
Viewed by 750
Abstract
Quantifying uncertainties in water resource prediction in data-scarce regions is essential for resource development. We use globally available datasets of precipitation and potential evapotranspiration for the regionalization of model parameters in the data-scarce regions of Ethiopia. A regional model was developed based on [...] Read more.
Quantifying uncertainties in water resource prediction in data-scarce regions is essential for resource development. We use globally available datasets of precipitation and potential evapotranspiration for the regionalization of model parameters in the data-scarce regions of Ethiopia. A regional model was developed based on 14 gauged catchments. Three possible parameter sets were tested for regionalization: (1) the best calibration parameters, (2) the best validation parameter set derived from behavioral parameters during the validation period, and (3) the stable parameter sets. Weighted multiple linear regression was applied by assigning more weight to identifiable parameters, using a novel leave-one-out cross-validation technique for evaluation and uncertainty quantification. The regionalized parameter sets were applied to the remaining 35 ungauged catchments in the Ethiopian Rift Valley Lake Basin (RVLB) to provide regional water balance estimations. The monthly calibration of the gauged catchments resulted in Nash Sutcliffe Efficiencies (NSE) ranging from 0.53 to 0.86. The regionalization approach provides acceptable regional model performances with a median NSE of 0.63. The results showed that, other than the commonly used best-calibrated parameters, the stable parameter sets provide the most robust estimates of regionalized parameters. As this approach is model-independent and the input data used are available globally, it can be applied to any other data-scarce region. Full article
Show Figures

Figure 1

Article
Streamflow Analysis in Data-Scarce Kabompo River Basin, Southern Africa, for the Potential of Small Hydropower Projects under Changing Climate
Hydrology 2022, 9(8), 149; https://doi.org/10.3390/hydrology9080149 - 18 Aug 2022
Viewed by 643
Abstract
In developing countries with data scarcity challenges, an integrated approach is required to enhance the estimation of streamflow variability for the design of water supply systems, hydropower generation, environmental flows, water allocation and pollution studies. The Flow Duration Curve (FDC) was adopted as [...] Read more.
In developing countries with data scarcity challenges, an integrated approach is required to enhance the estimation of streamflow variability for the design of water supply systems, hydropower generation, environmental flows, water allocation and pollution studies. The Flow Duration Curve (FDC) was adopted as a tool that is influenced by topography, land use land cover, discharge and climate change. The data from Global Climate Model (GCM) projections, based on Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 climate scenarios, were used as input data for the SWAT model for the simulation of streamflow. The FDCs were then derived from the simulated streamflow. The FDC for RCP 4.5 showed insignificant differences, whilst for RCP 8.5 it showed an increase of 5–10% in FDC from the baseline period, which is likely to increase the hydropower generation potential with some considerable streamflow variability. The integrated approach of utilizing FDC, GIS and SWAT for the estimation of flow variability and hydropower generation potential could be useful in data scarce regions. Full article
Show Figures

Figure 1

Article
River Flow Measurements Utilizing UAV-Based Surface Velocimetry and Bathymetry Coupled with Sonar
Hydrology 2022, 9(8), 148; https://doi.org/10.3390/hydrology9080148 - 17 Aug 2022
Viewed by 666
Abstract
Water velocity and discharge are essential parameters for monitoring water resources sustainably. Datasets acquired from Unoccupied Aerial Systems (UAS) allow for river monitoring at high spatial and temporal resolution, and may be the only alternative in areas that are difficult to access. Image [...] Read more.
Water velocity and discharge are essential parameters for monitoring water resources sustainably. Datasets acquired from Unoccupied Aerial Systems (UAS) allow for river monitoring at high spatial and temporal resolution, and may be the only alternative in areas that are difficult to access. Image or video-based methods for river flow monitoring have become very popular since they are not time-consuming or expensive in contrast to traditional methods. This study presents a non-contact methodology to estimate streamflow based on data collected from UAS. Both surface velocity and river geometry are measured directly in field conditions via the UAS while streamflow is estimated with a new technique. Specifically, surface velocity is estimated by using image-based velocimetry software while river bathymetry is measured with a floating sonar, tethered like a pendulum to the UAV. Traditional field measurements were collected along the same cross-section of the Aggitis River in Greece in order to assess the accuracy of the remotely sensed velocities, depths, and discharges. Overall, the new technique is very promising for providing accurate UAV-based streamflow results compared to the field data. Full article
Show Figures

Figure 1

Article
A Fast Data-Driven Tool for Flood Risk Assessment in Urban Areas
Hydrology 2022, 9(8), 147; https://doi.org/10.3390/hydrology9080147 - 16 Aug 2022
Viewed by 777
Abstract
Post-disaster flood risk assessment is extremely difficult owing to the great uncertainties involved in all parts of the assessment exercise, e.g., the uncertainty of hydrologic–hydraulic models and depth–damage curves. In the present study, a robust and fast data-driven tool for residential flood risk [...] Read more.
Post-disaster flood risk assessment is extremely difficult owing to the great uncertainties involved in all parts of the assessment exercise, e.g., the uncertainty of hydrologic–hydraulic models and depth–damage curves. In the present study, a robust and fast data-driven tool for residential flood risk assessment is introduced. The proposed tool can be used by scientists, practitioners and/or stakeholders as a first step for better understanding and quantifying flood risk in monetary terms. Another contribution of the present study is the fitting of an equation through depth–damage points provided by the Joint Research Center (JRC). The approach is based on hydrologic simulations for different return periods, employing a free and widely used software, HEC-HMS. Moreover, flood depths for the study area are estimated based on hydrodynamic simulations employing the HEC-RAS software and the Inverse Distance Weighting (IDW) interpolation method. Finally, flood risk, in monetary terms, is determined based on the flood depths derived by the coupling of hydrodynamic simulations and the IDW method, depth–damage curves reported in the literature, vulnerability of residential areas and the residential exposure derived by employing GIS tools. The proposed tool is applied in a highly urbanized and flood-prone area, Mandra city, in the Attica region of Greece. The results are maps of flood depths and flood risk maps for specific return periods. Overall, the results derived from the application of the proposed approach reveal that the tool can be highly effective for post-disaster flood risk management. However, it must be noted that additional information and post-disaster data are needed for the verification of the damages from floods. Additional information can result in better calibration, validation and overall performance of the proposed flood risk assessment tool. Full article
(This article belongs to the Special Issue Urban Flood Mitigation and Stormwater Management)
Show Figures

Figure 1

Article
Evaluating Magnitude Agreement and Occurrence Consistency of CHIRPS Product with Ground-Based Observations over Medium-Sized River Basins in Nepal
Hydrology 2022, 9(8), 146; https://doi.org/10.3390/hydrology9080146 - 16 Aug 2022
Viewed by 750
Abstract
High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent advent of improved higher-resolution open-access satellite-based rainfall products has emerged as a viable [...] Read more.
High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent advent of improved higher-resolution open-access satellite-based rainfall products has emerged as a viable complementary to ground-based observations that can often not capture the rainfall variability on a spatial scale. In a developing country such as Nepal, where the rain-gauge monitoring network is sparse and unevenly distributed, satellite rainfall estimates are crucial. However, substantial errors associated with such satellite rainfall estimates pose a challenge to their application, particularly in complex orographic regions such as Nepal. Therefore, these precipitation products must be validated before practical usage to check their accuracy and occurrence consistency. This study aims to assess the reliability of the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) product against ground-based observations from 1986 to 2015 in five medium-sized river basins in Nepal, namely, Babai, Bagmati, Kamala, Kankai, and the West Rapti river basin. A set of continuous evaluation metrics (correlation coefficient, root mean square error, relative bias, and Kling-Gupta efficiency) were used in analyzing the accuracy of CHIRPS and categorical metrics (probability of detection, critical success index, false alarm ratio, and frequency bias index). The Probability of Detection and Critical Success Index values were found to be considerably low (<0.4 on average), while the false alarm ratio was significant (>0.4 on average). It was found that CHIRPS showed better performance in seasonal and monthly time scales with high correlation and indicated greater consistency in non-monsoon seasons. Rainfall amount (less than 10 mm and greater than 150 mm) and rainfall frequency was underestimated by CHIRPS in all basins, while the overestimated rainfall was between 10 and 100 mm in all basins except Kamala. Additionally, CHIRPS overestimated dry days and maximum consecutive dry days in the study area. Our study suggests that CHIRPS rainfall products cannot supplant the ground-based observations but complement rain-gauge networks. However, the reliability of this product in capturing local extreme events (such as floods and droughts) seems less prominent. A high-quality rain gauge network is essential to enhance the accuracy of satellite estimations. Full article
(This article belongs to the Special Issue The Application of Remote Sensing in Hydrology)
Show Figures

Figure 1

Article
Flood Exposure of Residential Areas and Infrastructure in Greece
Hydrology 2022, 9(8), 145; https://doi.org/10.3390/hydrology9080145 - 13 Aug 2022
Viewed by 890
Abstract
Worldwide, floods are the most common and widespread type of disaster during the 21st century. These phenomena have caused human fatalities, destruction of infrastructures and properties, and other significant impacts associated with human socioeconomic activities. In this study, the exposure of infrastructure (social, [...] Read more.
Worldwide, floods are the most common and widespread type of disaster during the 21st century. These phenomena have caused human fatalities, destruction of infrastructures and properties, and other significant impacts associated with human socioeconomic activities. In this study, the exposure of infrastructure (social, industrial and commercial, transportation) and residential areas to floods in Greek territory was considered. To accomplish the goal of the current study, freely available data from OpenStreetMap and Corine 2018 databases were collected and analyzed, as well as the flood extent zones derived under the implementation of the European Union’s (EU) Floods Directive. The results will be useful for policy-making and prioritization of prone areas based not only on the extent of flood cover but also on the possible affected infrastructure types. Moreover, the aforementioned analysis could be the first step toward an integrated national-wide flood risk assessment. Full article
(This article belongs to the Special Issue Modern Developments in Flood Modelling)
Show Figures

Figure 1

Article
Extreme Wave Analysis for the Dubai Coast
Hydrology 2022, 9(8), 144; https://doi.org/10.3390/hydrology9080144 - 12 Aug 2022
Viewed by 658
Abstract
This paper aims to present the result of commonly used extreme wave analysis distribution methods applied to a long-term wave hindcast at a point in the Arabian Gulf near the coastline of Dubai, United Arab Emirates. The wave data were hindcasted for a [...] Read more.
This paper aims to present the result of commonly used extreme wave analysis distribution methods applied to a long-term wave hindcast at a point in the Arabian Gulf near the coastline of Dubai, United Arab Emirates. The wave data were hindcasted for a total period of 40 years, starting from 1 January 1979 to 31 December 2018. This analysis aims to support the design, repair, and maintenance of coastal structures near the Dubai coast. A 2.5 m threshold is selected using the Peak Over Threshold method to filter the storm data for the extreme wave analysis. Different distribution methods are used for this analysis such as Log-normal, Gumbel, Weibull, Exponential, and Generalized Pareto Distribution (GPD). The significant wave heights are predicted for different return periods. The GPD distribution appears to fit the data best compared to the other distribution methods. Many coastal projects are being planned near the Dubai coastline. Hence, the analysis presented in this paper would be useful in designing safe and efficiently designed projects. Full article
(This article belongs to the Special Issue Climate Change Effects on Coastal Management)
Show Figures

Figure 1

Article
Combining Sea Level Rise Inundation Impacts, Tidal Flooding and Extreme Wind Events along the Abu Dhabi Coastline
Hydrology 2022, 9(8), 143; https://doi.org/10.3390/hydrology9080143 - 11 Aug 2022
Viewed by 635
Abstract
This paper describes the development of a two-dimensional, basin-scale tidal model with waves and wave run-up to determine the inundation impacts on the Abu Dhabi coastline due to the combined effect of sea level rise, tidal flooding, storm surge and waves. The model [...] Read more.
This paper describes the development of a two-dimensional, basin-scale tidal model with waves and wave run-up to determine the inundation impacts on the Abu Dhabi coastline due to the combined effect of sea level rise, tidal flooding, storm surge and waves. The model combines a hydrodynamics model (DELFT3D), a spectral wave model (SWAN) and wave run-up. A high horizontal resolution (down to about 30 m) is employed in the vicinity of Abu Dhabi—a city built on a system of mangrove islands along the Arabian Gulf coast—to enable prediction of impact at the scale of the local infrastructure, such as individual highway links. The model confirms that, with a rise in sea level of 0.5 m, the islands along the outer coast of Abu Dhabi will experience inundation due to tidal flooding, wind, and high Shamal-induced waves. The incorporation of the wind and waves results in a prediction of more than double the area found underwater within the study area (from 82 to 188 km2). The inner water channel regions of Abu Dhabi, while mostly unaffected by wind-driven wave events, are still vulnerable to tidal flooding. Finally, the paper demonstrates the use of the model to predict whether protection of one segment of the city’s coastline will adversely affect the inundation potential of nearby unprotected segments. Full article
(This article belongs to the Special Issue Climate Change Effects on Coastal Management)
Show Figures

Figure 1

Editorial
Advances in Modelling of Rainfall Fields
Hydrology 2022, 9(8), 142; https://doi.org/10.3390/hydrology9080142 - 10 Aug 2022
Viewed by 631
Abstract
Rainfall is the main input for all hydrological models, such as rainfall–runoff models and the forecasting of landslides triggered by precipitation, with its comprehension being clearly essential for effective water resource management as well [...] Full article
Article
Does Flash Flood Model Performance Increase with Complexity? Signature and Sensitivity-Based Comparison of Conceptual and Process-Oriented Models on French Mediterranean Cases
Hydrology 2022, 9(8), 141; https://doi.org/10.3390/hydrology9080141 - 08 Aug 2022
Viewed by 661
Abstract
We compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently they simulate the catchment’s behavior, in terms of outlet discharge and internal dynamics, [...] Read more.
We compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently they simulate the catchment’s behavior, in terms of outlet discharge and internal dynamics, and how these can help to improve the relevance of the models. The methodology involved global sensitivity analysis, calibration/validation, and signature comparison at the event scale with good performances. For all models, we found transfer parameters to be sensitive in the case of Gardon and production parameters in the case of Ardeche. The non-conservative flow component of GR4H was found to be sensitive and could benefit the distributed models. At the event scale, the process-based MARINE model at finer resolution outperformed the two continuous hourly models at flood peak and its timing. SMASH, followed by GR4H, performed better in the volume of water exported. Using the operational surface model SIM2 to benchmark the soil moisture simulated by the three models, MARINE (initialized with SIM1) emerged as the most accurate. GR4H followed closely, while SMASH was the least accurate. Flexible modeling and regionalization should be developed based on multi-source signatures and worldwide physiographic databases. Full article
(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)
Show Figures

Figure 1

Article
The Recent Decline of Apalachicola–Chattahoochee–Flint (ACF) River Basin Streamflow
Hydrology 2022, 9(8), 140; https://doi.org/10.3390/hydrology9080140 - 05 Aug 2022
Viewed by 620
Abstract
The Apalachicola–Chattahoochee–Flint (ACF) basin is arguably the most litigated interstate river system in the eastern United States. Given the complicated demands for water use within this basin, it has been difficult to ascertain if the recent multi-decadal decline in streamflow is a product [...] Read more.
The Apalachicola–Chattahoochee–Flint (ACF) basin is arguably the most litigated interstate river system in the eastern United States. Given the complicated demands for water use within this basin, it has been difficult to ascertain if the recent multi-decadal decline in streamflow is a product of human disturbance, changing climate, natural variability, or some combination of the above factors. To overcome these challenges, we examined unimpaired streamflow and precipitation within and adjacent to the ACF basin, upstream of the Apalachicola River at Chattahoochee, and the Florida streamflow station (ARCF), which has historically been identified to be representative of hydrologic variability in the ACF basin. Several of the upstream, unimpaired, streamflow stations selected were identified in rural watersheds where land-cover changes and human disturbance were minimal during the study period. When applying a series of statistical evaluations, ARCF streamflow variability generally reflects the natural variability of the ACF basin. Additionally, unimpaired streamflow variability from the neighboring Choctawhatchee River compared favorably with ARCF variability. The recent multi-decadal decline was consistent in all records, with the 2000s being the most severe in the historic record. Full article
Show Figures

Figure 1

Article
Evaluating the Response of Hydrological Stress Indices Using the CHyM Model over a Wide Area in Central Italy
Hydrology 2022, 9(8), 139; https://doi.org/10.3390/hydrology9080139 - 04 Aug 2022
Viewed by 660
Abstract
Central Italy is characterized by complex orography. The territorial response to heavy precipitation may activate different processes in terms of hydrogeological hazards. Floods, flash floods, and wet mass movements are the main ground effects triggered by heavy or persistent rainfall. The main aim [...] Read more.
Central Italy is characterized by complex orography. The territorial response to heavy precipitation may activate different processes in terms of hydrogeological hazards. Floods, flash floods, and wet mass movements are the main ground effects triggered by heavy or persistent rainfall. The main aim of this work is to present a unique tool that is based on a distributed hydrological model, able to predict different rainfall-induced phenomena, and essential for the civil protection early warning activity. The Cetemps Hydrological Model is applied to the detection of hydrologically stressed areas over a spatial domain covering the central part of Italy during a weather event that occurred in 2014. The validation of three hydrological stress indices is proposed over a geographical area of approximately 64,500 km2 that includes catchments of varying size and physiography. The indices were used to identify areas subject to floods, flash floods, or landslides. Main results showed very high accuracies (~90%) for all proposed indices, with flood false alarms growing downstream to larger basins, but very close to zero in most cases. The three indices can give complementary information about the predominant phenomenon and are able to distinguish fluvial floods from pluvial floods. Nevertheless, the results were influenced by the presence of artificial reservoirs that regulated flood wave propagation, therefore, indices timing slightly worsen downstream in larger basins. Full article
Show Figures

Figure 1

Article
Long Term (1998–2019) Changes in Water Quality Parameters as a Function of Freshwater Inflow in a River–Bay Continuum
Hydrology 2022, 9(8), 138; https://doi.org/10.3390/hydrology9080138 - 03 Aug 2022
Viewed by 593
Abstract
Freshwater inflow is important in transporting nutrients to a bay. We hypothesized that freshwater inflow was transporting dissolved nitrogen and phosphorus to the Inland Bays. We analyzed long term (1998–2019) water quality data collected from Indian River, Indian River Bay, Lewes-Rehoboth Canal, Little [...] Read more.
Freshwater inflow is important in transporting nutrients to a bay. We hypothesized that freshwater inflow was transporting dissolved nitrogen and phosphorus to the Inland Bays. We analyzed long term (1998–2019) water quality data collected from Indian River, Indian River Bay, Lewes-Rehoboth Canal, Little Assawoman Bay, and Rehoboth Bay watersheds. Freshwater inflow altered nitrite+nitrate (N-NO2_3) concentrations in all but Lewes-Rehoboth Canal watershed, whereas phosphate (P-PO4) concentrations in all watersheds were altered by freshwater inflow and metabolic processes in the water. The average N-NO2_3 and P-PO4 were higher than the standard (0.14 and 0.01 mg/L for N-NO2_3+N-NH3 and P-PO4, respectively) for growing seasons (March–October) i.e., 0.83 + 0.14 and 0.09 mg/L in Indian River; 0.79 + 0.10 and 0.06 mg/L in Indian River Bay; 0.21 + 0.15 and 0.09 mg/L in Lewes-Rehoboth Canal; 0.49 + 0.10 and 0.11 mg/L in Little Assawoman Bay; 1.0 + 0.08 and 0.06 mg/L in Rehoboth Bay. Average total suspended solids in the Indian River (33), Indian River Bay (22), and Lewes-Rehoboth Canal (31) were higher than the standard concentrations, i.e., 20 mg/L for the Inland Bays. With the evidence of higher dissolved nutrients and low dissolved oxygen concentrations, need for nutrient load reduction and water quality monitoring are paramount for the sustainable management of Inland Bays. Full article
(This article belongs to the Section Ecohydrology)
Show Figures

Figure 1

Article
Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data
Hydrology 2022, 9(8), 137; https://doi.org/10.3390/hydrology9080137 - 31 Jul 2022
Viewed by 685
Abstract
In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar system [...] Read more.
In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar system challenging. This research focused on the analysis of the spatiotemporal variability of the parameters for a newly installed X-Band weather radar in Athens, Greece, by performing correlation and optimization analyses between high temporal resolution weather radar and rain gauge datasets. The correlation analysis was performed to assess the available datasets and provide the base of quality control. Multiple Z-R relationships were then derived for the following three optimization procedures; event-based relationships, station-based relationships, and a single area-based relationship. The results highlighted the region’s spatial variability regarding the Z-R relationship and the correlation between the station location and its parameter values. Moreover, it was found that stations near the coast and the front end of precipitation systems featured parameter values typical of convective type events. Finally, a single Z-R relationship was determined under a calibration and validation scheme, Z = 321R1.53,, which was validated with good agreement. Full article
(This article belongs to the Section Hydrological Measurements and Instrumentation)
Show Figures

Figure 1

Article
Towards Informed Water Resources Planning and Management
Hydrology 2022, 9(8), 136; https://doi.org/10.3390/hydrology9080136 - 30 Jul 2022
Viewed by 731
Abstract
In Water Resources Planning and Management, decision makers, although unsure of future outcomes, must take the most reliable and assuring decisions. Deterministic and probabilistic prediction techniques, combined with optimization tools, have been widely used to meet the objective of improving planning as well [...] Read more.
In Water Resources Planning and Management, decision makers, although unsure of future outcomes, must take the most reliable and assuring decisions. Deterministic and probabilistic prediction techniques, combined with optimization tools, have been widely used to meet the objective of improving planning as well as management. Bayesian decision approaches are available to link probabilistic predictions to optimized decision schemes, but scientists are not fully able to express themselves in a language familiar to decision makers, who fear basing their decisions on “uncertain” forecasts in the vain belief that deterministic forecasts are more informative and reliable. This situation is even worse in the case of climate change projections, which bring additional degrees of uncertainty into the picture. Therefore, a need emerges to create a common approach and means of communication between scientists, who deal with optimization tools, probabilistic predictions and long-term projections, and operational decision makers, who must be facilitated in understanding, accepting, and acknowledging the benefits arising from operational water resources management based on probabilistic predictions and projections. Our aim here was to formulate the terms of the problem and the rationale for explaining and involving decision makers with the final objective of using probabilistic predictions/projections in their decision-making processes. Full article
(This article belongs to the Collection Feature Papers of Hydrology)
Show Figures

Figure 1

Article
Google Earth Engine for Monitoring Marine Mucilage: Izmit Bay in Spring 2021
Hydrology 2022, 9(8), 135; https://doi.org/10.3390/hydrology9080135 - 28 Jul 2022
Viewed by 659
Abstract
Global warming together with environmental pollution threatens marine habitats and causes an increasing number of environmental disasters. Periodic monitoring of coastal water quality is of critical importance for the effective management of water resources and the sustainability of marine ecosystems. The use of [...] Read more.
Global warming together with environmental pollution threatens marine habitats and causes an increasing number of environmental disasters. Periodic monitoring of coastal water quality is of critical importance for the effective management of water resources and the sustainability of marine ecosystems. The use of remote sensing technologies provides significant benefits for detecting, monitoring, and analyzing rapidly occurring and displaced natural phenomena, including mucilage events. In this study, five water indices estimated from cloud-free and partly cloudy Sentinel-2 images acquired from May to July 2021 were employed to effectively map mucilage aggregates on the sea surface in the Izmit Bay using the cloud-based Google Earth Engine (GEE) platform. Results showed that mucilage aggregates started with the coverage of about 6 km² sea surface on 14 May, reached the highest level on 24 May and diminished at the end of July. Among the applied indices, the Adjusted Floating Algae Index (AFAI) was superior for producing the mucilage maps even for the partly cloudy image, followed by Normalized Difference Turbidity Index (NDTI) and Mucilage Index (MI). To be more specific, indices using green channel were found to be inferior for extracting mucilage information from the satellite images. Full article
(This article belongs to the Special Issue Climate Change Effects on Coastal Management)
Show Figures

Figure 1

Article
Methods for Characterizing Groundwater Resources with Sparse In Situ Data
Hydrology 2022, 9(8), 134; https://doi.org/10.3390/hydrology9080134 - 27 Jul 2022
Viewed by 685
Abstract
Accurate characterization of groundwater resources is required for sustainable management. Due to the cost of installing monitoring wells and challenges in collecting and managing in situ data, groundwater data are sparse—especially in developing countries. In this study, we demonstrate an analysis of long-term [...] Read more.
Accurate characterization of groundwater resources is required for sustainable management. Due to the cost of installing monitoring wells and challenges in collecting and managing in situ data, groundwater data are sparse—especially in developing countries. In this study, we demonstrate an analysis of long-term groundwater storage changes using temporally sparse but spatially dense well data, where each well had as few as one historical groundwater measurement. We developed methods to synthetically estimate groundwater table elevation (WTE) times series by clustering wells using two different methods; a uniform grid and k-means-constrained clustering to create pseudo-wells. These pseudo-wells had a more complete groundwater level time history, which we then temporally and spatially interpolated to analyze groundwater storage changes in an aquifer. We demonstrated these methods on the Beryl-Enterprise aquifer in Utah, USA, where other researchers quantified the groundwater storage depletion rate, and the wells had a large number of historical measurements. We randomly used one measurement per well and showed that our methods yielded storage depletion rates similar to published values. We applied the method to a region in southern Niger where wells had only one measurement per well, and showed that our estimated groundwater storage change trend reasonably matched that which was calculated using GRACE satellite data. Full article
(This article belongs to the Special Issue Groundwater Decline and Depletion)
Show Figures

Figure 1

Article
A Comparative Evaluation of Using Rain Gauge and NEXRAD Radar-Estimated Rainfall Data for Simulating Streamflow
Hydrology 2022, 9(8), 133; https://doi.org/10.3390/hydrology9080133 - 26 Jul 2022
Viewed by 620
Abstract
Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in Southern Ontario, Canada, using the Hydrologic [...] Read more.
Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in Southern Ontario, Canada, using the Hydrologic Engineering Center’s event-based distributed Hydrologic Modeling System (HEC-HMS). The model was run using the curve number (CN) and the Green and Ampt infiltration methods. The results show that the streamflow simulated with rain gauge data compared better with the observed streamflow than the streamflow simulated using radar data. However, when the Mean Field Bias (MFB) corrections were applied, the quality of the streamflow results obtained from radar rainfall data improved. The results showed no significant difference between the simulated streamflow using the SCS and the Green and Ampt infiltration approach. However, the SCS method is reasonably more appropriate for modeling the runoff at the sub-basin-scale than the Green and Ampt infiltration approach. With the SCS method, the simulated and observed runoff amount obtained using rain gauge rainfall showed an R2 value of 0.88 and 0.78 for MFB-corrected radar and 0.75 for radar only. For the Green and Ampt modeling option, the R2 value for the simulated and observed runoff amounts were 0.87 with rain gauge, 0.66 with radar only, and 0.68 with MFB-corrected radar rainfall inputs. The NSE values for rain gauge input ranged from 0.65 to 0.35. Overall, three values were less than 0.5 for streamflow for both the methods. For seven radar rainfall events, the NSE was greater than 0.5, with a range of very good to satisfactory. The analysis of RSR showed a very good comparison of stream flow using the SCS curve number method and Green and Ampt method using different rainfall inputs. Only one value, the 2 November 2003 event, was above 0.7 for rain gauge-based streamflow. The other RSR values were in the range of “very good”. Overall, the study showed better results for the simulated runoff with the MFB-corrected radar rainfall when compared with the simulations obtained using radar rainfall only. Therefore, MFB-corrected radar could be explored as a substitute rainfall source. Full article
Show Figures

Figure 1

Article
Impact of Climate Change on Water Resources and Crop Production in Western Nepal: Implications and Adaptation Strategies
Hydrology 2022, 9(8), 132; https://doi.org/10.3390/hydrology9080132 - 26 Jul 2022
Viewed by 1041
Abstract
Irrigation-led farming system intensification and efficient use of ground and surface water resources are currently being championed as a crucial ingredient for achieving food security and reducing poverty in Nepal. The potential scope and sustainability of irrigation interventions under current and future climates [...] Read more.
Irrigation-led farming system intensification and efficient use of ground and surface water resources are currently being championed as a crucial ingredient for achieving food security and reducing poverty in Nepal. The potential scope and sustainability of irrigation interventions under current and future climates however remains poorly understood. Potential adaptation options in Western Nepal were analyzed using bias-corrected Regional Climate Model (RCM) data and the Soil and Water Assessment Tool (SWAT) model. The RCM climate change scenario suggested that average annual rainfall will increase by about 4% with occurrence of increased number and intensity of rainfall events in the winter. RCM outputs also suggested that average annual maximum temperature could decrease by 1.4 °C, and average annual minimum temperature may increase by 0.3 °C from 2021 to 2050. Similarly, average monthly streamflow volume could increase by about 65% from March–April, although it could decrease by about 10% in June. Our results highlight the tight hydrological coupling of surface and groundwater. Farmers making use of surface water for irrigation in upstream subbasins may inadvertently cause a decrease in average water availability in downstream subbasins at approximately 14%, which may result in increased need to abstract groundwater to compensate for deficits. Well-designed irrigated crop rotations that fully utilize both surface and groundwater conversely may increase groundwater levels by an average of 45 mm from 2022 to 2050, suggesting that in particular subbasins the cultivation of two crops a year may not cause long-term groundwater depletion. Modeled crop yield for the winter and spring seasons were however lower under future climate change scenarios, even with sufficient irrigation application. Lower yields were associated with shortened growing periods and high temperature stress. Irrigation intensification appears to be feasible if both surface and groundwater resources are appropriately targeted and rationally used. Conjunctive irrigation planning is required for equitable and year-round irrigation supply as neither the streamflow nor groundwater can provide full and year-round irrigation for intensified cropping systems without causing the degradation of natural resources. Full article
(This article belongs to the Section Hydrology–Climate Interactions)
Show Figures

Figure 1

Article
A Decade of Cave Drip Hydrographs Shows Spatial and Temporal Variability in Epikarst Storage and Recharge to Appalachian Karst Systems
Hydrology 2022, 9(8), 131; https://doi.org/10.3390/hydrology9080131 - 25 Jul 2022
Viewed by 567
Abstract
We conducted recession analyses on cave drip hydrographs from a 10-year record (2008–2018) of three drip monitoring stations within James Cave (Pulaski County, VA, USA) to examine differences in hydrologic characteristics of the epikarst and quantify the storage volume of the epikarst feeding [...] Read more.
We conducted recession analyses on cave drip hydrographs from a 10-year record (2008–2018) of three drip monitoring stations within James Cave (Pulaski County, VA, USA) to examine differences in hydrologic characteristics of the epikarst and quantify the storage volume of the epikarst feeding the drips. We used two recession analysis methods (correlation and matching strip) to calculate recession coefficients for multiple hydrographs at each site. Results show subtle differences between the three drip sites, suggestive of spatial heterogeneity in permeability and storage in the overlying epikarst. Storage volume calculations show that during the recharge season, up to 95% of recharge through the epikarst to the cave occurs through rapid pathways (i.e., fractures), and 5% of recharge occurs through diffuse pathways (i.e., pores). However, during the recession period, recharge through rapid pathways in the epikarst decreases and occurs predominantly through diffuse flow. Combined, these results underscore the importance of documenting spatial and temporal characterization of drip rates and other recharge inputs into karst systems. Full article
(This article belongs to the Special Issue Hydro-Geology of Karst Areas)
Show Figures

Figure 1

Article
Maximum Extreme Flow Estimations in Historical Hydrological Series under the Influence of Decadal Variations
Hydrology 2022, 9(8), 130; https://doi.org/10.3390/hydrology9080130 - 25 Jul 2022
Viewed by 690
Abstract
The hypothesis of stationarity is a fundamental condition for the application of the statistical theory of extreme values, especially for climate variables. Decadal-scale fluctuations commonly affect maximum and minimum river discharges. Thus, the probability estimates of extreme events need to be considered to [...] Read more.
The hypothesis of stationarity is a fundamental condition for the application of the statistical theory of extreme values, especially for climate variables. Decadal-scale fluctuations commonly affect maximum and minimum river discharges. Thus, the probability estimates of extreme events need to be considered to enable the selection of most appropriate time series. The current study proposed a methodology to detect the fluctuation of long wet and dry periods. The study was carried out at the gauging station 4C-001 in Pardo River, State of São Paulo, Brazil. The Spearman, Mann–Kendall and Pettitt’s non-parametric tests were also performed to verify the existence of a temporal trend in the maximum annual daily flows. The graph achieved from the Pettitt’s statistical variable allowed for the identification and separation of the longest dry period (1941 to 1975) and the longest wet period (1976 to 2011), decreasing again in 2012. Analysing the series separately, it was observed that both mean and standard deviation were higher than those corresponding to the dry period. The probable maximum flows for the corrected series showed estimates 10% higher than those estimated for the uncorrected historical series. The proposed methodology provided more realistic estimates for the extreme maximum flows. Full article
(This article belongs to the Special Issue Stochastic and Deterministic Modelling of Hydrologic Variables)
Show Figures

Figure 1

Article
Growing Crops in Arid, Drought-Prone Environments: Adaptation and Mitigation
Hydrology 2022, 9(8), 129; https://doi.org/10.3390/hydrology9080129 - 22 Jul 2022
Viewed by 599
Abstract
Drought poses significant risks to society, in particular irrigated-crop production, which accounts for a large share of global freshwater use. Given its key role in the production of food, feed and fiber crops, there exists a need for policy measures to prevent and [...] Read more.
Drought poses significant risks to society, in particular irrigated-crop production, which accounts for a large share of global freshwater use. Given its key role in the production of food, feed and fiber crops, there exists a need for policy measures to prevent and mitigate the impacts of drought on irrigated agriculture. This paper proposes that the design of drought policy should take into account actual farmer behavior in response to water scarcity. To this end, we offer a detailed analysis of land allocation and crop-choice decisions over time in an irrigation district located in the dry plains of Northern Mexico. We find that farmers systematically change their crop mix in response to water availability. In particular, in times of drought, irrigation water flows to higher-yield and higher-price crops (which also require more intense irrigation) to the detriment of less water-demanding (but lower value) crops. Farmers use water with the goal of earning a living—economizing on water per se has no relevance in that context. Policies that do not explicitly recognize this may result in ineffective, inefficient and/or unfair outcomes. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop