Use Of Hydrological Models Research Articles

Pywr-DRB: An open-source Python model for water availability and drought risk assessment in the Delaware River Basin

The Delaware River Basin (DRB) in the Mid-Atlantic region of the United States is an institutionally complex water resources system that provides drinking water for 13.5 million people, plus water for energy, industry, recreation, and ecosystems. This paper introduces Pywr-DRB, an open-source Python model exploring the impacts of reservoir operations, transbasin diversions, and minimum flow targets on water availability and drought risk in the DRB. Pywr-DRB draws on streamflow estimates from emerging data resources, bridging advances in large-scale hydrologic modeling with an improved representation of the basin's evolving water infrastructure and management institutions. Our detailed model diagnostic assessment demonstrates that Pywr-DRB provides substantial improvements over sole use of hydrologic models in capturing the DRB's dynamics. We also explore how water management alters model-derived risk estimates for low flows and water demand shortfalls. Our approach to diagnostic benchmarking and water systems modeling is broadly applicable to other major basins.

Estimating Drainage from Forest Water Reclamation Facilities Based on Drain Gauge Measurements

A growing human population requires sustainable solutions to regulate and dispose of municipal wastewater. Water treatment facilities in northern Idaho are permitted to apply reclaimed wastewater to forest land during the growing season at specified monthly hydraulic loading rates. We assessed the spatial and temporal variability of drainage below the rooting zone between non-irrigated (control) and irrigated (effluent) stands during the growing and dormant seasons in 2021. No drainage was observed during the two months of annual seasonal drought, but large magnitudes of drainage were recorded during the dormant season (38–94 cm), which was consistent with seasonal precipitation. The overall effect of effluent treatment on the drain gauge measurements did not differ from the controls, as effluent only increased the drainage at some facilities. The measured drainage averaged from 35 to 62 cm among facilities. We then used the drainage measurements to calibrate hydrological models (Hydrus-1D and Water Erosion Prediction Project [WEPP]) and predict the drainage in 50 measurement plots distributed evenly among five forest water reclamation facilities. As with the observed drainage, there were no statistically significant growing season differences in the predicted monthly drainage during the growing season between the effluent and control plots, suggesting the successful use of hydrologic models to support the measured drainage findings. While both models struggled to accurately predict the quantity of drainage during the dormant season, they both successfully predicted that drainage would continue through May. WEPP also successfully predicted that the treated plots began to drain in September and October following late-season irrigation at some facilities. The models showed that the prescribed crop coefficient used by the Idaho Department of Environmental Quality was adequate in avoiding drainage during the peak summer months.

Uncertainty estimation of hydrological modelling using gridded precipitation as model inputs in the Gandaki River Basin

Study RegionFour subbasins in the Gandaki River Basin in the southern Himalayan region. Study FocusIn the southern Himalayan region, gridded precipitation datasets are often used to complement sparse gauge network observations in hydrological modelling for water resource assessment. However, the applicability and uncertainty of using these datasets in hydrological modelling remain to be evaluated. In this study, nine high spatial resolution gridded precipitation datasets were used to force a widely used hydrological model to simulate the daily runoff at four hydrological stations in this region. The accuracy of these datasets was evaluated, and the model calibration results and modelling uncertainty were analyzed. New Hydrological Insights for the RegionOur analysis revealed large differences among the nine gridded precipitation datasets, and most datasets underestimated the annual precipitation in the low-elevation regions and overestimated that in the high Himalayas. Furthermore, through the adjustments of model parameters, the underestimations of precipitation by gridded datasets were compensated for by the overestimation of glacial melt. Therefore, the model performance was better, and the model uncertainty was lower in basins with higher glacial coverage. Notably, our findings indicated that the performances of gridded precipitation datasets were heterogeneous and that their direct use in hydrological modelling may result in unreasonable hydrological process variables; thus, these datasets should be evaluated and used with caution in water resource assessments in Himalayan regions.

Use of hydrological models to calculate the ecological flow of the Jequetepeque river, upstream of the Gallito Ciego dam, Peru

The research allowed to use of hydrological models for the calculation of the ecological flow of the “Jequetepeque” river, upstream of the “Gallito Ciego” dam, Peru. Information on average monthly flows was used, which was divided into two periods (1943-1987) and (1988-2019). To calculate ecological flow, seven hydrological methods were used. For the period 1943-1987, the ecological flow was calculated with the percentage establishment method (0.47 m3s-1), followed by the Tennant method (0.57 m3s-1).The period of 1988-2019, the ecological flow was calculated with the percentage establishment method (0.36 m3s-1), followed of the Tennant method (0.59 m3s-1).The analysis of variance of one factor, significant differences were compared and verified between the ecological flow calculated of the indicated methods and the minimum low-water flow taken as a baseline for comparison. With the Tukey test, it was verified that the ecological flow estimated of the hydrological method of establishing percentages for the period (1943-1987) and (1988-2019), it did not present significant differences with respect to the minimum low-water flow. It concluded that the ecological flow of the “Jequeteque” river upstream of the “Gallito Ciego” dam is 0.36 m3s-1, it obtained through the percentage establishment method.

Application of the SMAP monthly model to the Piauitinga river basin located in the State of Sergipe, Brazil

The generation of flow data allows the assessment of the capacity to meet water demands, predict floods, and estimate the potential for hydraulic exploitation for electrical energy generation. In Brazil, precipitation data series, due to their ease of measurement, are more extensive compared to flow data series, enabling the use of hydrological models called rainfall-runoff models capable of estimating flows from precipitation data. Therefore, utilizing the Brazil Gridded Meteorological Data (BR-DWGD) database, this study aims to generate, calibrate, and validate flow data for the Piauitinga river basin located in the state of Sergipe, Brazil, using the monthly rainfall-runoff SMAP model. The soil parameters considered in the validation for the studied region showed a good fit to the observed data, achieving a Nash-Sutcliffe (NS) of 84% and log-Nash-Sutcliffe (NSLog) of 85% in calibration, and Nash-Sutcliffe (NS) of 70% and a log-Nash-Sutcliffe (NSLog) of 80% in validation. Therefore, since the rainfall-runoff model used exhibited good performance for the studied hydrographic basin, it becomes feasible to use the generated synthetic series to fill possible gaps in the historical series of monthly average flows.

Enhancing Low-Flow Forecasts: A Multi-Model Approach for Rainfall–Runoff Models

The expected change in rainfall patterns and the increase in evapotranspiration due to climate change leads to earlier droughts, which aggravate water shortages. To ensure the sustainable management of water resources in these conditions, it is necessary to forecast their evolution. The use of hydrological models is essential for monitoring the water crisis. The conceptual hydrological models used in this study are MEDOR, GR4J, and HBV. They are applied in the Nahr Ibrahim watershed, which is a typical Lebanese Mediterranean basin. While these models simplify complex natural systems, concerns persist about their reliability in addressing drought challenges. In order to reduce the uncertainties, this study develops new robust methods that can improve model simulations. First, a particular series concerning low flows is constructed with the use of hydrological low-flow indices. The multi-model approach is utilized to reach a more accurate unique series while combining the low-flow series generated from the models. This combination is accomplished by using the simple average method, weighted average, artificial neural networks, and genetic algorithms. Better results are generated with the use of these methods. Accordingly, this study led to an improvement in model performances while increasing the reliability of low-flow forecasts.

Assessing the use of digital soil maps in hydrological modeling for soil-water budget simulations - implications for water management plans in southern Portugal

Efficient water management plans are required to ensure food security in areas prone to drought and soil degradation. Hydrological modeling can help to achieve this goal by evaluating water availability for different uses, including food production. Fully distributed hydrological models using digital maps of soil properties available for the soil profile are useful for mapping soil-water balance responses, namely water content and water stress. The accuracy of these model responses depends on the quality of the input data, namely, soil hydraulic properties (SHP). Nowadays, we have free access to worldwide digital 1D SHP grids created using global soil datasets, so detailed studies are now needed to evaluate their use in hydrological modeling. We compared the use of a global and a local SHP dataset to simulate soil-water balance at the regional scale in a small irrigation district located in southern Portugal. We explicitly characterized where differences in model responses occur and related those to the variability of soil physical and hydraulic properties, and land use. Our results showed that the choice of the SHP dataset matters. The statistical and spatial variability of simulated water content and water stress for different land uses depended on the dataset used for the numerical simulation. With the global dataset, water content was higher and water stress lower, and both had less statistical and spatial variability compared to the local dataset results. A practical consequence of these findings is misadjusted irrigation schedules, which can be detrimental to crop production and soil quality. A water management plan based on the global results will determine less water requirements, which may not be realistic for the Mediterranean conditions that characterize the study area.

СИСТЕМЫ ПОДГОТОВКИ И ВЫПУСКА ГИДРОЛОГИЧЕСКИХ ПРОГНОЗОВ ГИДРОМЕТЦЕНТРА РОССИИ

Nowadays operational forecasts of river flow are implemented in the form of automated systems for issuing forecasts, as well as delivering forecast products to users. Only within the framework of these systems, using modern software, the maximum efficiency is achieved from the use of hydrological models by automating all processes, combining them with operational database management systems, as well as with modern GIS and web tools for generating forecast products and delivering them to users. Over the past decade, the Hydrometeorological Research Center of the Russian Federation (Hydrometcenter of Russia) has been actively developed automated systems for issuing hydrological forecasts and communicating them to users. The systems are based on modern hydrological models, all available hydrometeorological information, including numerical weather forecasts, as well as modern software tools, including GIS and web technologies. Such systems have been implemented for large river basins, including the basin of the Kuban and the rivers of the Black Sea coast of Russia, the Amur and Volga basins. In recent years, the system has been developed for the entire territory of Russia. These systems are actively used by the Roshydromet operational forecasting divisions, as well as by specialists from the EMERCOM of Russia.

Can continuous simulation be used as an alternative for flood regionalisation? A large sample example from Chile

Flood frequency analysis lies at the core of hydrology and water engineering as one of the most required estimates for water planning and design of hydraulic structures. For ungauged basins, where no information is available, various flood regionalisation techniques have varying degrees of complexity and resulting performance, depending on the study's goal, the region analysed, and the information available. This study evaluates the use of hydrological models for flood regionalisation in Chile, using 1) A large sample dataset of 101 catchments; 2) the continuous simulation approach with the GR4J model; 3) the leave-one-out strategy for performance testing; and, 4) two regionalisation methods: Nearest Neighbour (NN) and Physical Similarity (PS), together with several alternative objective functions for calibration purposes and regionalisation strategy (in all cases adopting a single criterion, single variable and determinist approach for the parameter’s selection). Our results showed that performance (both in calibration–validation and regionalisation) is highly variable (in terms of reproducing the runoff hydrograph and flood statistics), depending on the catchment’s aridity (e.g., around 66–82% of catchments with NSE above 0 in humid regions but it severely drops to 12–44% of catchments with NSE above 0 when evaluating arid catchments). We also found that flood-specific calibration strategies produce better results for floods but poorer performance in runoff hydrograph reproduction. Finally, we highlight that our regionalisation results were in close agreement with those from one of the currently recommended methods by Chilean engineering for flood regionalisation. This is particularly promising, considering that the continuous simulation approach gives access to the complete time series and not only flood statistics. We end this manuscript by discussing several sources of uncertainty, hoping that these can be accounted for in future studies.

Quantifying the Soil Water Storage Capacity of Flysh Catchments Surrounded by Mixed Forests in Outer Carpathians

The objective of this paper is to evaluate the retention capacity of catchments situated in the Beskid Wyspowy region of southern Poland. To accomplish this, we employed the Soil and Water Assessment Tool (SWAT+), a newly developed hydrological model. The large heterogeneity of the catchment area and the limitations of measurement techniques necessitated the use of hydrological models. The study found that forested and pasture areas had higher soil water retention potential than agricultural areas. Furthermore, surface runoff of both catchments correlated negatively with soil water retention potential and evapotranspiration, however, positively with mean annual precipitation. Soil moisture was directly related to mean annual precipitation and electrical conductivity. The research also advocates incorporating the Landscape Hydric Potential (LHP) index into existing hydrologic models, in line with the physical-based SWAT+. Future watershed models based on water balance should be developed to increase resilience to climate change manifestations in the flysh Carpathian Mountains.

Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World‐Wide?

AbstractAlthough many potential evapotranspiration (PET) formulas are available, there is still a lack of knowledge on when and where to use them in catchment modeling world‐wide. Here we experimented with three different formulas in a global hydrological model (the World‐wide HYPE), using 15 years of observations from 5,338 streamflow gauges and global evapotranspiration from Earth‐observations (MOD16). We tested model performance in a multi‐process approach to select the best formula for catchments covering the global landmass. From comparing the results with land‐cover, climate classification, water‐energy limitations, we found that climate is the main driver behind the spatial patterns in model performance. Hargreaves was the best PET formula in 50% of the catchments, most of them located in the Amazonas, central Europe, and Oceania; Jensen‐Haise was better for catchments in northern latitudes (36%). Finally, Priestley‐Taylor was the best formula for India and latitudes above 65° North. The selection of a PET formula seems to be more critical in tropical regions close to the equator, where the differences in performance are above 50%. This is also where PET is highest. We found a strong connection between the five main Köppen regions and the PET formulas, further supported by landcover analysis. Hence, the PET formulas differed in their capacity to provide useful input to the water balance modeling, with complex formulas only giving improved predictions in temperate and polar regions; however, for the rest of the globe simpler formulas were better. We thus recommend to apply different PET formulas based on climatic regions world‐wide.

Streamflow Simulation in Semiarid Data-Scarce Regions: A Comparative Study of Distributed and Lumped Models at Aguenza Watershed (Morocco)

In semi-arid regions such as the southwestern zone of Morocco, better management of water resources is crucial due to the frequent flooding phenomena. In this context, the use of hydrological models is becoming increasingly important, specifically in the Aguenza watershed. A multitude of hydrological models are available to make very efficient modeling, and from this perspective, a comparative approach was adopted using two models with different characteristics. Streamflow simulations were carried out continuously at daily time steps using GR4J and ATHYS (2002–2011). The latter was used also to simulate rainfall-runoff events (1984–2014). Simulation results using the distributed model are very efficient compared to those obtained by the lumped model “GR4J”, which shows the disadvantages of neglecting the hydrological processes during a hydrological study. However, a remarkable improvement was observed in the general appearance of the resulting hydrographs and the performance parameters after using the distributed model ((Calibration: NSE, RSR, and PBIAS increased successively by 8%, 6%, and 45.2%); (Validation: NSE, RSR, and PBIAS increased successively by 6%, 4%, and 8.9%)). In terms of flood event simulations, a good concordance between observed and simulated discharge was observed (NSEmedian = 0.7), indicating its great reliability for simulating rainfall-runoff events in semi-arid and data-scarce regions. This research highlights the importance of using hydrological models, specifically the distributed model ATHYS, for the better management of water resources in semi-arid regions with frequent flooding events.

Combined Impacts of Climate Change and Water Withdrawals on the Water Balance at the Watershed Scale—The Case of the Allier Alluvial Hydrosystem (France)

The Allier River and its alluvial aquifer constitute a shallow but highly productive water resource due to their hydrodynamic properties. This hydrosystem provides almost all of the water requirements for domestic supply and irrigation. Recent dry summers (such as those in 2015, 2019, and 2022) and the lack of winter recharge have led managers to question the sustainability of this resource. We proposed the use of hydrological modelling with Gardenia with which the water balance can be determined at the watershed scale (7020 km2) and with which forecasting simulations can be performed for 2030–2070. Thus, this work was divided into (1) model calibration (2000–2020), (2) the determination of the main drivers of the water balance (2000–2020), (3) and river flow and groundwater level simulation (2030–2070). For the latter, Gardenia was used considering a “better case”, using the RCM Aladin63 in RCP2.6, and considering a “worst case”, using the RCM RegCM4-6 in RCP8.5. The calibration for 2000–2014 showed good reproducibility of river flows (NSE = 0.91) and groundwater levels (NSE = 0.85). The model showed that the major drivers in 2000–2020 were actual evapotranspiration and effective precipitation, which, respectively, represented 68% and 32% of mean annual precipitation. Water withdrawals did not significantly contribute to the water balance with the exception of those in very dry summers, such as those in 2003, 2005, 2015, and 2019. Climate appeared, therefore, as a prevalent factor of the Allier hydrosystem functioning compared to global withdrawals except for that during these dry years. Prospective simulations showed a decline in annual river flows and groundwater levels by a maximum of −15% and −0.08 m asl (“worst case”), respectively. These simulations showed that the Allier hydrosystem will be able to meet the water needs for various uses until 2070. In detail, it is likely that summer shortages will no longer be compensated by the Naussac Dam if the hydrosystem faces more than two years of drought. In this case, water-saving solutions will have to be found. This study is, thus, a good example of the application of hydrological modelling to address management issues in such a hydrosystem.

Use of Hydrological Models in Global Stochastic Flood Modeling

AbstractTypical flood models do not take into consideration the spatial structure of flood events, which can lead to errors in the estimation of flood risk at regional to continental scales. Large‐scale stochastic flood models can simulate synthetic flood events with a realistic spatial structure, although this method is limited by the availability of gauge data. Simulated discharge from global hydrological models has been successfully used to drive stochastic modeling in data‐rich areas. This research evaluates the use of discharge hindcasts from global hydrological models in building stochastic river flood models globally: synthetic flood events in different regions of the world (Australia, South Africa, South America, Malaysia, Thailand, and Europe) are simulated using both gauged and modeled discharge. By comparing them, we analyze how a model‐based approach can simulate spatial dependency in large‐scale flood modeling. The results show a promising performance of the model‐based approach, with errors comparable to those obtained over data‐rich sites: a model‐based approach simulates the joint occurrence of relative flow exceedances at two given locations similarly to when a gauge‐based statistical model is used. This suggests that a network of synthetic gauge data derived from global hydrological models would allow the development of a stochastic flood model with detailed spatial dependency, generating realistic event sets in data‐scarce regions and loss exceedance curves where exposure data are available.

DATA TEST AND PRE-TREATMENT FOR HYDROLOGICAL MODELLING AND APPLICATIONS

The proper application of meaningful hydrological model output must be preceded by the use of reliable model inputs, the quality and behaviour, which must be ascertained by evaluating for any intrinsic quality problems. Long-term (>40 years) rainfall hydrological data for the 5 rainfall stations situated in a catchment supplying part of the larger Nairobi metropolitan and its environs are used to demonstrate the need for data quality check. Tests for outliers, trends, autocorrelation and homogeneity are performed on the data. Results indicate that one station had an outlier data point. The trends analysis using the Mann-Kendal method with the Sen slope analysis using the raw data show general non statistically significant declining rainfall over the period for both annual and seasonal rainfall and significant increase in maximum temperature at 95% confidence level. Homogeneity test using the Pettit test identified break points. Trend analysis after removal of change points returns significant trends in annual rainfall for three of the five stations and several seasonal datasets at 95% confidence level. There is therefore need to pre-treat data appropriately before application in modeling and decision support simulations. Pre-treatment of data prior to use in hydrological modelling is expected to yield more reliable/accurate model predictions by reducing errors associated with model inputs.

Modelling Water Flow and Soil Erosion in Mediterranean Headwaters (with or without Check Dams) under Land-Use and Climate Change Scenarios Using SWAT

The use of check dams is a common strategy to reduce soil erosion in the Mediterranean headwaters. However, the effects of these control works on water flow rates and sediment yields have been scarcely investigated under possible scenarios of climate and land-use changes. On this regard, the use of hydrological models, such as SWAT, provide reliable hydrological predictions under variable environmental conditions. To fill this gap, this study has evaluated the effectiveness of check dams on the hydrological response of a forest headwater in Calabria (Southern Italy) in comparison with an unregulated subcatchment with very similar environmental conditions. In this regard, the effects of different combined scenarios of climate change (through three GCMs and two RCPs applied to a time period of the next 80 years) and land use (forest, pasture, and cropland) on water flow rates and sediment yields in the two headwaters were analysed using the SWAT model. The SWAT model was first calibrated in a third headwater with very similar climatic, soil, and land-use conditions, and this verification showed a satisfactory prediction capacity of water flow rate. The water flow rate prediction capacity of the model was satisfactory (coefficients of determination and efficiency of Nash and Sutcliffe equal to 0.71 and 0.67, respectively, and percent bias of 14.9%). No significant differences were detected for the water flow rates and sediment yields between the two subcatchments (with or without check dams) among the different land-use and climate change scenarios. This was linked to the low hydrological response of both headwaters to the forcing actions, which influenced the low effectiveness of the control works. SWAT estimated higher values of both mean and maximum values of water flow rates and sediment yields under RCP2.6 compared with RCP8.5. Both water flow rates and sediment yields were predicted to be very low under all climate and land-use scenarios. The regulated headwater with check dams was predicted to always produce more runoff and erosion compared with the subcatchment without check dams. The increases were predicted to be up to 60% for the maximum flow rate and 30–35% for the sediment yield in forest land use under RCP2.6. Although there was a limitation in this study due to the lack of validation of the erosion data (due to unavailable records of sediment yield), this study demonstrated how the use of check dams in headwater catchments may be not effective for soil conservation purposes several decades after their installation in Mediterranean semiarid areas, where the water flow and erosion rate are limited.

Advances on water quality modeling in burned areas: A review

Wildfires are a recurring hazard in forested catchments representing a major threat to water security worldwide. Wildfires impacts on water quality have been thoroughly addressed by the scientific community through field studies, laboratory experiments, and, to a lesser extent, the use of hydrological models. Nonetheless, models are important tools to assess on-site and off-site wildfires impacts and provide the basis for post-fire land management decisions. This study aims to describe the current state of the art of post-fire model adaptation, understanding how wildfires impacts are simulated and the options taken by the modelers in selecting parameters. For this purpose, 42 publications on modeling wildfire impacts on the hydrologic cycle and water quality were retrieved from the SCOPUS database. Most studies simulated post-fire hydrological and erosion response in the first year after the fire, while few assessed nutrients changes and long-term impacts. In addition, most simulations ended at the watershed outlet without considering the fate of pollutants in downstream waterbodies. Ash transport was identified as a major research gap, given the difficulties of its incorporation in the current models’ structure and the high complexity in predicting the heterogeneous ash layer. Including such layer would improve models’ ability to simulate water quality in post-fire conditions, being ash a source of nutrients and contaminants. Model complexity and data limitations influenced the spatial and temporal scale chosen for simulations. Post-fire model adaptations to simulate on-site soil erosion are well established, mainly using empirical equations extensively calibrated in the literature. At the watershed level, however, physical and process-based models are preferred for their ability to simulate more complex burned area characteristics. Future research should focus on the simulation of the ash transport and the development of integrated modelling frameworks, combining watershed and aquatic ecosystem models to link the on and off-site impacts of fires.

Use of Hydrological Models to Predict Risk for Rutting in Logging Operations

Using hydrological models with a high temporal resolution to predict risk for rutting may be a possible method to improve planning of forwarder trails or to schedule logging operations in sites with low bearing capacity to periods when soil moisture content is at a minimum. We have studied whether descriptions of rut variations, collected in 27 logging sites, can be improved by using hydrological data, modeled by Swedish HYdrological Prediction for Environment (S-HYPE). Other explanatory variables, such as field-surveyed data and spatial data, were also used to describe rut variations within and across logging sites. The results indicated that inclusion of S-HYPE data led to only marginal improvement in explaining the observed variations of the ruts in terms of both “rut depths” within the logging sites and “proportion of forwarder trails with ruts” across the logging sites. However, application of S-HYPE data for adapting depth-to-water (DTW) maps to temporal changes of soil moisture content may be a way to develop more dynamic soil moisture maps for forestry applications.

Hydrological modeling of hydrographic basin in the northeast semiarid region of Brazil

The use of hydrological models allows to understand, evaluate and anticipate events of natural or man-made origin in a simpler and more economical way for the quantity and quality of resources in a hydrographic basin. The present work aims to perform a hydrological modeling in the hydrographic basin in the semiarid, using the SWAT model, to verify the influence of the use and exploitation of water production on the land. For this, the SWAT hydrological model (Soil Water Assessment Tool) was used. A study area located in the Jacaré Curitiba Basin, in Poço Redondo-SE, a semi-arid region of the state, inserted in the Caatinga biome and in the lower São Francisco. The adopted methodology was used for bibliographic survey, field work, hydrological monitoring, chemical and physical medicine of soil and soil, survey of land use and exploration, calibration and validation of hydrological model. The SWAT model successfully simulated or hydrographed the flow for the period from Nov/2015 to Jul/2018, duly calibrated and validated. As simulations of different land use scenarios, the greatest production of water in agricultural areas stands out, which can cause greater generation of sediments. The calibrated and validated SWAT model means a possibility for future studies in non-semiarid watersheds and then contributes to studies on water and soil management.

SUPPLEMENTARY TOOLS IN BASELINE INFORMATION BUILDING FOR WATER RESOURCES PROJECTS UNDER THE NEW NORMAL

Research and industry-related engineering projects are affected in many ways by the COVID-19 pandemic. For example, data gathering becomes more challenging in recent times. The main objective of this paper is to demonstrate alternative ways to gather baseline data related to water resources projects. There are supplemental open-source tools available for baseline information building that are used in the past years that are expected to play more significant roles now. The data gathering phase of some projects were used as examples. Firstly, the importance and basic know-hows of Google Earth Pro ™ in the context of rapid reconnaissance and appraisal (RRA) are portrayed. Google Earth Pro’s Street View and available historical satellite images enable spatially and temporally varied virtual tour of study areas, which can help in site characterization and identification of important study and design parameters. Secondly, the use of hydrologic modeling to obtain estimates of flow data is illustrated. Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS) is shown to be capable of generating approximate flood hydrographs for ungaged rivers and flow duration curves for water supply studies. Lastly, the capability of hydraulic models to estimate water levels is presented. Instead of getting anecdotal water levels in the field, hydraulic modeling packages such as Hydrologic Engineering Center – River Analysis System (HEC-RAS) and SOBEK-River are technically feasible to get water levels for water resources projects. Although the results are subjected to some limitations, as in the case of uncalibrated models, these provide opportunities to obtain valuable information amidst the pandemic.