Hydrology

Coffee (Coffea spp.) represents one of the most important sources of income and goods for the agricultural sector in Central America, Colombia, and the Caribbean region. The sustainability of coffee production at the global and regional scale is under threat by climate change, with a major risk of losing near to 50% of today’s suitable area for coffee by 2050. Rain-fed coffee production dominates in the region, and under increasing climate variability and climate change impacts, these production areas are under threat due to air temperature increase and changes in rainfall patterns and volumes. Identification, evaluation, and implementation of adaptation strategies for growers to cope with climate variability and change impacts are relevant and high priority. Incremental adaptation strategies, including proper soil and water management, contribute to improved water use efficiency (WUE) and should be the first line of action to adapt the coffee crop to the changing growing conditions. This research’s objective was to evaluate at field level over five years the influence of fertilization with calcium (Ca⁺²) and potassium (K⁺) on WUE in two coffee arabica varieties: cv. Castillo and cv. Caturra. Castillo has resistance against coffee leaf rust (CLR) (Hemileia vastatrix Verkeley and Brome), while Caturra is not CLR-resistant. WUE was influenced by yield changes during the years by climate variability due to El Niño–ENSO conditions and CLR incidence. Application of Ca⁺² and K⁺ improved the WUE under such variable conditions. The highest WUE values were obtained with an application of 100 kg CaO ha⁻¹ year⁻¹ and between 180 to 230 kg K2O ha⁻¹ year⁻¹. The results indicate that adequate nutrition with Ca⁺² and K⁺ can improve WUE in the long-term, even underwater deficit conditions and after the substantial incidence. Hence, an optimum application of Ca⁺² and K⁺ in rain-fed coffee plantations can be regarded as an effective strategy to adapt to climate variability and climate change. Full article

Rainfall simulators are research devices that can be used for studying runoff and sediment transport on the plot scale. This technical note introduces a new solution that combines the two most commonly used methods for generating artificial rain—swinging and pulse jet systems. Reasons for developing this device are its universal use, simple construction, and reduction of water consumption, with better spatial distribution of rain and rainfall kinetic energy close to that of natural conditions. Routine operations of this device are expected for plots of 1 × 1 m, with a height 2–2.5 m. The rained surface could be extended to 2 × 2 m with lower spatial distribution. The sprinkled area in this case was limited by the drain box that also collected the remaining water. The principle of the presented single-nozzle simulator can be extended to multi-nozzle simulators for larger experimental plots. Full article

The present work focuses on two recent flash floods in coastal Benguela (Angola), both triggered by moderate rainfall but which had disastrous consequences for local populations (namely 71 deaths in 2015 and 17 in 2019). The research involved a regional survey to establish the effects of these floods combined with a geomorphological and socio-economic analysis of the most affected areas to understand the main forcing factors. The two flash floods produced major damage in restricted sectors within very small coastal catchments (<16 km²). The prevalence of fine-grained sedimentary rocks, relatively steep hills, thin soil cover, and vegetation scarcity are natural factors that promote surface runoff. However, socio-economic conditions are most likely the main reasons of flood damage. Namely, rapid population growth with poor planning and making use of low-quality construction materials, the high waste yields that are not properly managed and the absence of flood risk awareness. In the small valleys around the fast-growing cities of coastal Benguela, hazardous flash floods occur recurrently, even after moderate precipitation. Most affected areas are determined by local conditions that compromise drainage at the time of the rainfall event, being very difficult to predict. Full article

This paper concerns the design of a geographic location system to identify urban road sections susceptible to runoff accumulation through the analysis of the efficiency of surface drainage networks. To this end, a combination of Geographic Information Systems (GISs) and stormwater models was proposed. First, GIS hydrology tools were employed to generate all the information required to characterise urban catchments geometrically. Then, a synthetic storm was created from precipitation data obtained through spatial interpolation for a given return period. Finally, the three main hydrological processes occurring in catchments (precipitation loss, transformation and routing) were simulated using the Hydrologic Modeling System (HEC-HMS). The system was tested through a case study of an urban catchment located in the city of Santander (Spain). The results demonstrate its usefulness in detecting critical points in terms of runoff accumulation, according to the efficiency of the existing surface drainage network. Full article

We present the development and testing of a web application called the historical validation tool (HVT) that processes and visualizes observed and simulated historical stream discharge data from the global GEOGloWS ECMWF streamflow services (GESS), performs seasonally adjusted bias correction, computes goodness-of-fit metrics, and performs forward bias correction on subsequent forecasts. The HVT corrects GESS output at a local scale using a technique that identifies and corrects model bias using observed hydrological data that are accessed using web services. HVT evaluates the performance of the GESS historic simulation data and provides more accurate historic simulation and bias-corrected forecast data. The HVT also allows users of the GEOGloWS historical streamflow data to use local observed data to both validate and improve the accuracy of local streamflow predictions. We developed the HVT using Tethys Platform, an open-source web application development framework. HVT presents data visualization using web mapping services and data plotting in the web map interface while functions related to bias correction, metrics reporting, and data generation for statistical analysis are computed by the back end. We present five case studies using the HVT in Australia, Brazil, Colombia, the Dominican Republic, and Peru. In these case studies, in addition to presenting the application, we evaluate the accuracy of the method we implemented in the HVT for bias correction. These case studies show that the HVT bias correction in Brazil, Colombia, and Peru results in significant improvement in historic simulation across the countries, while bias correction only resulted in marginal historic simulation improvements in Australia and the Dominican Republic. The HVT web application allows users to use local data to adjust global historical simulation and forecasts and validate the results, making the GESS modeling results more useful at a local scale. Full article

Extreme rainfall events have made significant damages to properties, public infrastructure and agriculture in some provinces of South Africa notably in KwaZulu-Natal and Gauteng among others. The general global increase in the frequency and intensity of extreme precipitation events in recent years is raising a concern that human activities might be heavily disturbed. This study attempts to model long-term monthly rainfall variability in the selected provinces of South Africa using various statistical techniques. The study investigates the normality and stationarity of the underlying distribution of the whole body of rainfall data for each selected province, the long-term trends of the rainfall data and the extreme value distributions which model the tails of the rainfall distribution data. These approaches were meant to help achieve the broader purpose of this study of investigating the long-term rainfall trends, stationarity of the rainfall distributions and extreme value distributions of monthly rainfall records in the selected provinces of South Africa in this era of climate change. The five provinces considered in this study are Eastern Cape, Gauteng, KwaZulu-Natal, Limpopo and Mpumalanga. The findings revealed that the long-term rainfall distribution for all the selected provinces does not come from a normal distribution. Furthermore, the monthly rainfall data distribution for the majority of the provinces is not stationary. The paper discusses the modelling of monthly rainfall extremes using the non-stationary generalised extreme value distribution (GEVD) which falls under the block maxima extreme value theory (EVT) approach. The maximum likelihood estimation method was used to obtain the estimates of the parameters. The stationary GEVD was found as the best distribution model for Eastern Cape, Gauteng, and KwaZulu-Natal provinces. Furthermore, model fitting supported non-stationary GEVD model for maximum monthly rainfall with nonlinear quadratic trend in the location parameter and a linear trend in the scale parameter for Limpopo, while in Mpumalanga the non-stationary GEVD model with a nonlinear quadratic trend in the scale parameter and no variation in the location parameter fitted well to the monthly rainfall data. The negative values of the shape parameters for Eastern Cape and Mpumalanga suggest that the data follow the Weibull distribution class, while the positive values of the shape parameters for Gauteng, KwaZulu-Natal and Limpopo suggest that the data follow the Fréchet distribution class. The findings from this paper could give information that can assist decision makers establish strategies for proper planning of agriculture, infrastructure, drainage system and other water resource applications in the South African provinces. Full article

The river habitat survey (RHS) system is a method used to assess the physical features and quality of rivers, which was developed to assist in the conservation and recovery of riverside habitats. The RHS takes into account the need to characterize areas of intervention from a hydromorphological point of view, in order to introduce corrective measures aimed at restoring degraded sections and habitats, and increasing local biodiversity. In this paper, we present the results obtained from the application of the RHS methodology to the River Selho, in the municipality of Guimarães (Portugal). The transects that we defined were strongly influenced by anthropic actions that have modified the riverside habitats, the artificialization of the river channel, and the urban occupation of the banks. Taking into account the results, we can point out the main problems that currently affect the hydromorphological quality of the transects analyzed in the River Selho, as well as identify the originating factors: the excessive silting of the watercourse; morphometric changes, with an emphasis on the narrowing and modification of the channel and the banks; as well as the massive destruction of the riparian zone. This study shows that the application of the RHS methodology is a useful tool for the management of degraded riverside areas. Full article

A comprehensive assessment of the stable isotope distribution in the groundwater systems of South Africa was conducted in relation to the diversity in the aquifer lithology and corresponding hydraulic characteristics. The stable isotopes of oxygen (¹⁸O) and hydrogen (²H) in groundwater show distinct spatial variation owing to the recharge source and possibly mixing effect in the aquifers with the existing water, where aquifers are characterized by diverse hydraulic conductivity and transmissivity values. When the shallow aquifer that receives direct recharge from rainfall shows a similar isotopic signature, it implies less mixing effect, while in the case of deep groundwater interaction between recharging water and the resident water intensifies, which could change the isotope signature. As aquifer depth increases the effect of mixing tends to be minimal. In most cases, the isotopic composition of recharging water shows depletion in the interior areas and western arid zones which is attributed to the depleted isotopic composition of the moisture source. The variations in the stable isotope composition of groundwater in the region are primarily controlled by the isotope composition of the rainfall, which shows variable isotope composition as it was observed from the local meteoric water lines, in addition to the evaporation, recharge and mixing effects. Full article

Time series analysis is a major mathematical tool in hydrology, with the moving average being the most popular model type for this purpose due to its simplicity. During the last 20 years, various studies have focused on an important statistical characteristic, namely the long-term persistence and the simultaneous statistical consistency at all timescales, when different timescales are involved in the simulation. Though these issues have been successfully addressed by various researchers, the solutions that have been suggested are mathematically advanced, which poses a challenge regarding their adoption by practitioners. In this study, a multilayer perceptron network is used to obtain synthetic daily values of rainfall. In order to develop this model, first, an appropriate set of features was selected, and then, a custom cost function was crafted to preserve the important statistical properties in the synthetic time series. This approach was applied to two locations of different climatic conditions that have a long record of daily measurements (more than 100 years for the first and more than 40 years for the second). The results indicate that the suggested methodology is capable of preserving all important statistical characteristics. The advantage of this model is that, once it has been trained, it is straightforward to apply and can be modified easily to analyze other types of hydrologic time series. Full article

Water resource management policies impact how water supplies are protected, collected, stored, treated, distributed, and allocated among multiple users and purposes. Water resource policies influence the decisions made regarding the siting, design, and operation of infrastructure needed to achieve the underlying goals of these policies. Water management policies vary by region depending on particular hydrologic, economic, environmental, and social conditions, but in all cases they will have multiple impacts affecting these conditions. Science can provide estimates of various economic, ecologic, environmental, and even social impacts of alternative policies, impacts that determine how effective any particular policy may be. These impact estimates can be used to compare and evaluate alternative policies in the search for identifying the best ones to implement. Among all scientists providing inputs to policy making processes are analysts who develop and apply models that provide these estimated impacts and, possibly, their probabilities of occurrence. However, just producing them is not a guarantee that they will be considered by policy makers. This paper reviews various aspects of the science-policy interface and factors that can influence what information policy makers need from scientists. This paper suggests some ways scientists and analysts can contribute to and inform those making water management policy decisions. Brief descriptions of some water management policy making examples illustrate some successes and failures of science informing and influencing policy. Full article

The height above nearest drainage (HAND) model is frequently used to calculate properties of the soil and predict flood inundation extents. HAND is extremely useful due to its lack of reliance on prior data, as only the digital elevation model (DEM) is needed. It is close to optimal, running in linear or linearithmic time in the number of cells depending on the values of the heights. It can predict watersheds and flood extent to a high degree of accuracy. We applied a client-side HAND model on the web to determine extent of flood inundation in several flood prone areas in Iowa, including the city of Cedar Rapids and Ames. We demonstrated that the HAND model was able to achieve inundation maps comparable to advanced hydrodynamic models (i.e., Federal Emergency Management Agency approved flood insurance rate maps) in Iowa, and would be helpful in the absence of detailed hydrological data. The HAND model is applicable in situations where a combination of accuracy and short runtime are needed, for example, in interactive flood mapping and supporting mitigation decisions, where users can add features to the landscape and see the predicted inundation. Full article

Studies have shown that salt concentrations are increasing in waterbodies such as lakes, rivers, wetlands, and streams in areas where deicers are commonly applied for winter road maintenance, resulting in degraded water quality. As the salt concentration varies spatially and temporally based on environmental and hydrological characteristics, we monitored high resolution (15 min) salt concentrations for a relatively long period (winter and spring season) at different sites (i.e., stream, urban-stream, roadside drain, and parking-lot drain) using multiple electric conductivity-based sensors. The salt concentrations were significantly different from each other considering individual sensors and different sites in both winter and spring seasons, which support past research results that concentration varies spatially. Parking-lot (1136 ± 674 ppm) and Roadside (701 ± 263 ppm) drain measured significantly higher concentration than for Stream (260 ± 60 ppm) and Urban-stream (562 ± 266 ppm) in the winter season. Similar trends were observed for the spring season, however, the mean concentrations were lower in the spring. Furthermore, salt concentrations were significantly higher during the winter (242 ± 47 ppm to 1695 ± 629 ppm) than for the spring (140 ± 23 ppm to 863 ± 440 ppm) season considering different sites, which have been attributed to the winter snow maintenance practice using deicers in past studies. All sites exceed the United States Environmental Protection Agency (USEPA) threshold (salt concentration higher than 230 mg/L) for chronic exposure level for 59% to 94% and 10% to 83% of days in winter and spring seasons, respectively. The study has highlighted the usefulness and advantages of high resolution (spatially and temporally) salt concentration measurement using sensor technology. Furthermore, the salt concentration in waterbodies can vary spatially and temporally within a small spatial scale, which may be important information for managing water quality locally. The high resolution measurements (i.e., 15 min) were helpful to capture the highest potential salt concentrations in the waterbody. Therefore, the sensor technology can help to measure high resolution salt concentrations, which can be used to quantify impacts of high salt concentrations, e.g., application of deicer for winter road maintenance on aquatic systems based on the criteria developed by USEPA. Full article

We investigate the impact of time’s arrow on the hourly streamflow process. Although time asymmetry, i.e., temporal irreversibility, has been previously implemented in stochastics, it has only recently attracted attention in the hydrological literature. Relevant studies have shown that the time asymmetry of the streamflow process is manifested at scales up to several days and vanishes at larger scales. The latter highlights the need to reproduce it in flood simulations of fine-scale resolution. To this aim, we develop an enhancement of a recently proposed simulation algorithm for irreversible processes, based on an asymmetric moving average (AMA) scheme that allows for the explicit preservation of time asymmetry at two or more time-scales. The method is successfully applied to a large hourly streamflow time series from the United States Geological Survey (USGS) database, with time asymmetry prominent at time scales up to four days. Full article

The separate and synergistic effects of land use and climate change on water quality variables in Old Woman Creek (OWC) watershed were evaluated using a hydrological model set up in Soil and Water Assessment Tool (SWAT) for the OWC watershed. Model calibration was done using a multi-objective evolutionary algorithm and pareto optimization. The Parameter-Elevation Regressions on Independent Slopes Model (PRISM) climate data and the 20 different Global Circulation Models (GCMs) developed by the Coupled Model Intercomparison Project Phase five (CMIP5) were used. Validation was done using the streamflow data from USGS gaging station and water quality data from the water quality lab, Heidelberg University. The simulation was divided into two land use scenarios: Scenario 1 for constant land use and Scenario 2 where land use was varied. Both land use simulations were run in four time periods to account for climate change: historical (1985–2014), current to near future (2018–2045), mid-century (2046–2075), and late-century (2076–2100) climate windows. For the historical period, the average of all the simulations made from the 20 different CMIP5 GCMs shows good agreement with the PRISM results for flow and the water quality variables of interest with smaller inter-model variability compared to PRISM results. For the other three climate windows, the results of Scenario 1 show an increase in flow and eight water quality variables (sediment (total suspended sediment), organic nitrogen, organic phosphorus (particulate p), mineral phosphorus (soluble reactive p), chlorophyll a, carbonaceous biochemical oxygen demand (CBOD), dissolved oxygen, total nitrogen) across the climate windows but a slight decrease in one water quality variable, mineral phosphorus in the mid-century. The results of Scenario 2 show a greater increase in flow, and the eight water quality variables across the climate windows show a relatively larger decrease in one water quality variable (mineral phosphorus). The projected land use change has little impact compared to the projected climate change on OWC watershed in the 21st century. Full article

Exploring the dynamic mechanisms of coupled sociohydrologic systems is necessary to solve future water sustainability issues. This paper employs system dynamics modeling to determine hydrologic and economic implications of an irrigation efficiency (IE) policy (increased conveyance efficiency and field efficiency) in a coupled sociohydrologic system with three climate scenarios. Simulations are conducted within the lower Rio Grande region (LRG) of New Mexico for the years 1969 to 2099, including water, land, capital, and population modules. Quadrant analysis is utilized to compare the IE policy outcomes with the base case and to categorize results of simulations according to hydrologic and economic sustainability. The four categories are beneficial, unacceptable, unsustainable agricultural development, and unsustainable hydrology. Simulation results for the IE policy analyzed here fall into the categories of unsustainable agricultural development or unacceptable, suggesting there are long-term negative effects to regional economies in all scenarios with mixed results for hydrologic variables. IE policy can yield water for redistribution as increased unit water supply in the field produces more deep percolation; however, IE policy sacrifices regional connectivity. Specifically, simulation results show that the policy increases abundance by 4.7–74.5% and return flow by −3.0–9.9%. These positive results, however, come at the cost of decreased hydrologic connectivity (−31.5 to −25.1%) and negative economic impacts (−32.7 to −5.7%). Long-term net depletions in groundwater are also observed from loss of hydrologic connectivity and increased agricultural water demand from projections of increased consumptive use of crops. Adaptive water management that limits water use in drought years and replenishes groundwater in abundant years as well as economic incentives to offset the costs of infrastructure improvements will be necessary for the IE policy to result in sustainable agriculture and water resources. Full article

In South Korea, groundwater intended for use in greenhouse cultivation is collected from shallow riverside aquifers as part of agricultural activities during the winter season. This study quantified the effects of intensive groundwater intake on aquifers during the winter and examined the roles of nearby rivers in this process. Observation data were collected for approximately two years from six wells and two river-level observation points on the study site. Furthermore, the river water levels before and after the weir structures were examined in detail, because they are determined by artificial structures in the river. The structures have significant impacts on the inflow and outflow from the river to the groundwater reservoirs. As a result, a decline in groundwater levels owing to groundwater depletion was observed during the water curtain cultivation (WCC) period in the winter season. In addition, we found that the groundwater level increased owing to groundwater recharge due to rainfall and induced recharge by rivers during the spring–summer period after the end of the WCC period. MODFLOW, a three-dimensional difference model, was used to simulate the groundwater level decreases and increases around the WCC area in Cheongwon-gun. Time-variable recharge data provided by the soil and water assessment tool model, SWAT for watershed hydrology, was used to determine the amount of groundwater recharge that was input to the groundwater model. The groundwater level time series observations collected from observation wells during the two-year simulation period (2012 to 2014) were compared with the simulation values. In addition, to determine the groundwater depletion of the entire demonstration area and the sustainability of the WCC, the quantitative water budget was analyzed using integrated hydrologic analysis. The result indicated that a 2.5 cm groundwater decline occurred on average every year at the study site. Furthermore, an analysis method that reflects the stratification and boundary conditions of underground aquifers, hydrogeologic properties, hydrological factors, and artificial recharge scenarios was established and simulated with injection amounts of 20%, 40%, and 60%. This study suggested a proper artificial recharge method of injecting water by wells using riverside groundwater in the study area. Full article

To seek stochastic analogies in key processes related to the hydrological cycle, an extended collection of several billions of data values from hundred thousands of worldwide stations is used in this work. The examined processes are the near-surface hourly temperature, dew point, relative humidity, sea level pressure, and atmospheric wind speed, as well as the hourly/daily streamflow and precipitation. Through the use of robust stochastic metrics such as the K-moments and a second-order climacogram (i.e., variance of the averaged process vs. scale), it is found that several stochastic similarities exist in both the marginal structure, in terms of the first four moments, and in the second-order dependence structure. Stochastic similarities are also detected among the examined processes, forming a specific hierarchy among their marginal and dependence structures, similar to the one in the hydrological cycle. Finally, similarities are also traced to the isotropic and nearly Gaussian turbulence, as analyzed through extensive lab recordings of grid turbulence and of turbulent buoyant jet along the axis, which resembles the turbulent shear and buoyant regime that dominates and drives the hydrological-cycle processes in the boundary layer. The results are found to be consistent with other studies in literature such as solar radiation, ocean waves, and evaporation, and they can be also justified by the principle of maximum entropy. Therefore, they allow for the development of a universal stochastic view of the hydrological-cycle under the Hurst–Kolmogorov dynamics, with marginal structures extending from nearly Gaussian to Pareto-type tail behavior, and with dependence structures exhibiting roughness (fractal) behavior at small scales, long-term persistence at large scales, and a transient behavior at intermediate scales. Full article

It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment. Full article

The identification and recognition of temporal rainfall patterns is important and useful not only for climatological studies, but mainly for supporting rainfall–runoff modeling and water resources management. Clustering techniques applied to rainfall data provide meaningful ways for producing concise and inclusive pattern classifications. In this paper, a timeseries of rainfall data coming from the Greek National Bank of Hydrological and Meteorological Information are delineated to independent rainstorms and subjected to cluster analysis, in order to identify and extract representative patterns. The computational process is a custom-developed, domain-specific algorithm that produces temporal rainfall patterns using common characteristics from the data via fuzzy clustering in which (a) every storm may belong to more than one cluster, allowing for some equivocation in the data, (b) the number of the clusters is not assumed known a priori but is determined solely from the data and, finally, (c) intra-storm and seasonal temporal distribution patterns are produced. Traditional classification methods include prior empirical knowledge, while the proposed method is fully unsupervised, not presupposing any external elements and giving results superior to the former. Full article