Journal of Hydrologic Engineering

Assessment of stationarity in any hydroclimatic time series is a vital task for hydrologic design and climate change assessments. Methods that rely on the presence of statistically significant trends or change points to derive inferences about stationarity may fail to check for all the time-invariant characteristics of time series. An approach that uses nonoverlapping stratified random sampling blocks of time series and nonparametric tests is proposed and evaluated in this study to assess stationarity. Chronologically continuous data from contiguous blocks are evaluated using two-sample and multisample nonparametric tests for the assessment of distributional, median and variance similarity, invariance of statistical moments, and autocorrelation at several lags. Explicit methods for the evaluation of different characteristics of time series are also developed to assess the two forms (viz., weak and strict) of stationarity. The multiple test evaluations are weighted using the analytical hierarchy process (AHP) to draw conclusions about stationarity. The proposed approach is tested using several real-world and synthetically generated hydroclimatic data sets through extensive simulations. Stationarity assessments derived from nonparametric trend and unit root tests have been compared to those from the approach developed. Results from this study point to the correct identification of weak and strict stationarity in real-world hydroclimatic time series compared to similar evaluations from unit root and trend tests. The robustness of the approach is also confirmed by an accurate assessment of the stationarity of several synthetic time series representing various hydroclimatic processes at different time scales. The proposed approach is a conceptually simple and superior alternative to trend and unit root tests since it provides a comprehensive assessment of stationarity using multiple nonparametric tests.

The digital elevation model (DEM) has been widely used in hydrological analysis and flood assessment. While DEMs, derived from airborne light detection and ranging (lidar) technology, have sufficient accuracy for large-scale floodplain management practices, their utility in supporting high-resolution hydrologic simulations is disputable due to their limitations in resolution. In contrast, terrestrial laser scanning (TLS) is capable of conducting very dense point measurements, especially in close distance, generating high-resolution point clouds that may support high-fidelity hydrologic modeling for small areas. The study takes a case study approach in which we delineate boundaries of a catchment area for a small-scale ($\mathrm{1,450}{\mathrm{m}}^2$) stormwater management measure (porous parking lot) under different DEM resolutions generated from TLS with the end goal of understanding the utility of TLS for high-fidelity hydrologic modeling. Results showed that the 0.03-m resolution provided an accurate representation of terrain surface. Larger raster cell–size DEMs generated greater uncertainties on boundaries and streamlines. DEMs with resolutions below $0.2\mathrm{m}$ have small differences of 1%, while larger cell–size DEMs ($0.96\mathrm{m}$) could have as high as 13%. Excluding the depressed parking lot of a constrained area, the remaining drainage area could be overestimated by 43% at a 0.96-m resolution. These findings indicate that a fine resolution DEM is necessary for quantifying the drainage area of small flat watersheds.

Meteorological droughts abetted by hot events could instigate an agricultural drought that eventually affects crop yield. Different types of droughts may coexist or occur in succession. A single index based on one particular variable may not be sufficient to quantify such compound drought events. Therefore, this study embedded drought indexes ofstandardized precipitation index (SPI), standardized soil-moisture index (SSI), and standardized temperature index (STI) with Gaussian copula functions to study compound agrometeorological drought and hot events in India from 1948 to 2014. By standardizing the joint probability of the SPI, SSI, and STI time series, the standardized compound drought and hot index (SCDHI) was developed. The SCDHI values in the monsoon months of different climatic zones have a strong correlation of about 0.95 with other well-established indexes such as the standardized compound event indicator (SCEI), which incorporates SPI and STI, and the multivariate standardized drought index (MSDI), which incorporates SPI and SSI. Based on the areal extent, 1965–1966, 1972, 1987, and 2002 were identified as significant compound drought years in India. The index also identified three successive compound events of the 2012–2014 northest monsoon in the southern peninsular region. A notable increase in the frequency of compound drought and hot events was found post-2000. The case studies of the major drought events and the dependent pattern of SCDHI on its constituent indexes indicate that SCDHI performs well as an indicator of compound agrometeorological and hot events across different climatic regions and in both southwest and northeast monsoons.

Combining fractional continuity and motion equations, the space and time fractional governing equations of unsteady overland flow were derived. The kinematic and diffusion wave approximations were obtained from the space and time fractional continuity and motion equations of the overland flow process. When the fractional powers of space and time derivatives go to 1, the fractional governing equations become the conventional governing equations of unsteady overland flow, and the conventional equations can be obtained as the special cases of the proposed fractional governing equations. Similar to findings of the fractional open channel flow process reported previously, the numerical example herein demonstrated that as the fractional powers of the space and time derivatives decrease from 1, overland flows have longer durations, and both the occurrence time and magnitude of the peak flows decrease. The proposed space and time fractional unsteady overland flow equations may allow modeling anomalous hydrographs by taking into account nonlocality in time and space, and may provide further insights into nonlocal transport in hillslopes reported in the literature.

Flood events may be caused by different runoff generating processes and can be differentiated in their genesis by the application of flood types. Additionally, the spatial interaction of catchments can play a crucial role in the flood generation. Flood wave superposition can increase the flood peak and volume downstream. The magnitude of increase and the probability of superposition depends on the shape of the upstream hydrographs. This study simulated different superposition scenarios, distinguished by flood types. These scenarios then were incorporated in a type-differentiated statistical model. Uncertainty ranges for design floods were obtained that can be used for an improved consideration of flood protection differentiated by the flood type. It was demonstrated that, although for central German catchments the superposition of floods caused by heavy rainfall is the least probable of all scenarios, this flood type leads to highest increase of the peak. Hence, heavy-rainfall floods could lead to underestimated design floods downstream. With the newly proposed range of design-flood return periods, the uncertainty caused by flood superposition can be incorporated in flood protection measures.

Reservoirs are important water conservancy constructions for flood prevention and disaster reduction in a region. The prediction of reservoir storage is a key task to ensure its safe management and operation. In this study, an innovative modified tank model was developed for the reservoir storage prediction affected by precipitation, natural drainage, and human flood adjustment factors. By transforming the conventional tank model property from a rectangle to a trapezoid as the model characters and incorporating the influence of human flood adjustment factors, the accuracy and especially the physical meaning of the tank model to predict the storage are improved. The case of Huanggang Reservoir, Fujian, China, was used to validate the model prediction ability. The results showed that the average relative error of the improved model was reduced by $2.87\%–14.94\%$ compared with the original model. In addition, the value of the average relative error of the optimized tank model during the typhoon season decreased by $3.93\%–23.48\%$, thereby providing a more accurate prediction of water storage in the flood season.

This work presents web mapping of extreme daily precipitation values in central and northern Argentina, including values of both annual maximum precipitation (AMP) for different return periods, and probable maximum precipitation (PMP) estimated following a statistical approach proposed in previous work. Historical daily precipitation records of 1,564 stations were used in this work and universal kriging was used for interpolating local estimates in the study area, which includes different topographic and climatic regions (Subandean, Subtropical plains, and the Pampas). The AMP and PMP $5\text{-}\mathrm{km}$ grid maps show a clear west-east gradient, although AMP for higher return periods and PMP show more uniform spatial pattern. The kriging variance maps show the highest uncertainties in regions that have no gages at the mainly higher elevations (regions not included in the final version of the maps). The web-mapping application was developed to make the maps available for project designers and risk managers, and represents an important innovation in Argentina.

Despite limitations in reproducing complex bedload sediment transport processes in rivers, formulas have been preferred over collection and analysis of field data due to the high cost and time-consuming nature of bedload discharge measurements. However, the performance of such formulas depends on the hydraulic and sedimentological conditions they attempt to describe. The availability of field measurements provides a unique opportunity to test bedload transport formulas to better guide formula selection. Hydraulic parameters and bedload discharge data from the Lower Minnesota River and two of its tributaries were used to evaluate nine bedload transport formulas using three different indices. The bedload data for the different sites were collected by the United States Geological Survey (USGS) from 2011 through 2014, with bed material varying from very coarse to medium sand. The formulas calculated higher bedload rates than were measured due to a combination of site-specific physical characteristics, including the presence of bed forms (dunes), and sampling uncertainties. Because of the lack of reproducibility of the tested formulas, five power functions, based on the relation between the specific unit power (independent hydraulic variable) and the USGS measured data (dependent variable), were derived as provisional equations to estimate the bedload discharge on the Lower Minnesota River and tributaries.

Groundwater is a major resource of freshwater that provides additional resilience to agricultural drought during rainfall deficit and also helps in understanding the nature of the hydrological drought risk of an area. This study investigated the response of groundwater drought to meteorological drought and local aquifer properties by considering monthly groundwater levels of a tropical river basin in India. Further, bivariate frequency analysis was carried out for groundwater drought to develop severity–duration–frequency curves by considering the copula function. Long-term monthly groundwater levels were procured, and cluster analysis was performed on groundwater observations to classify the wells. Standardized Groundwater level Index (SGI) was used to evaluate groundwater drought for each cluster, and the same was compared with the meteorological drought of different association periods. The cluster analysis conveyed that wells can be grouped into three clusters optimally. Based on the comparison of groundwater drought with meteorological drought, it was inferred that SGI is well harmonized with the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) in humid and semiarid regions, respectively. Analysis of hydraulic diffusivity with the autocorrelation structure of SGI emphasizes the crucial role of aquifer characteristics in local groundwater droughts. The results of joint and conditional return periods obtained from bivariate frequency analysis conveyed that high severity and high-duration droughts were more frequent in the well of Clusters 1 as well as Cluster 3 and comparatively less for the well of Cluster 2. The outcome of the study will be helpful to design proactive drought mitigation and preparedness strategies by considering conjunctive use of surface and groundwater. It also provides a framework to evaluate groundwater drought risk in other parts of the world.

In this study, methods were developed to create and evaluate the performance of the Soil and Water Assessment Tool (SWAT) in southern Peru where commonly used input data sources were not available. Soil classes were defined based on regional soil taxonomy and suitability maps combined with soil profiles. Local land cover and remotely sensed satellite data were used to develop a land cover database. Water balance analysis of the reservoir as well as satellite evapotranspiration data were used for model performance assessment. Results showed that these strategies provided reliable predictions of hydrology in this region, with the uncertainty quantified based on the range of inputs. Overall, this semiarid watershed was base flow driven and average annual surface runoff contribution to streamflow was less than 9%. Assessment of water pathways and their uncertainties based on the uncertainty of estimated inputs also showed that 62% of precipitation was removed by evapotranspiration with up to 16% uncertainty. The methods introduced in this study can be applied to other data-scarce watersheds, and findings provide insights on the hydrology of the Peruvian Andes region.

Restoring tidal flow to anthropogenically flow-restricted waterways provides ecological benefits while also changing the flood risk of adjacent lands. Our research evaluated the flooding risk on Tremley in Linden, New Jersey if the adjacent Marshes Creek’s tidal flow is fully restored. A hydrological/hydraulic model of Marshes Creek was used to simulate the peak water surface elevations (WSELs) generated by existing restricted and fully unrestricted conveyance options under dry and wet weather scenarios. Model results indicated that simulated peak WSELs generated by the fully unrestricted conveyance option versus the existing restricted option (1) were higher under dry weather conditions, (2) increased at a slower rate under wet conditions, (3) were equal under wet conditions at a threshold rainfall depth, and (4) were lower under wet conditions for rainfall exceeding the threshold rainfall depth. It is intuitive that if the simulated common WSEL generated by both conveyance options is lower than the adjacent minimum grade elevation, then full tidal flow restoration reduces flooding risks. Alternatively, if the simulated common WSEL was higher than the adjacent minimum grade elevation, then full tidal flow restoration will increase flooding risk. A simple procedure based on this finding is provided in this paper, which identifies the maximum tidal conveyance level that generates a common peak water surface lower than the adjacent minimum grade elevation at the threshold rainfall depth.