Journal of Hydrologic Engineering

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

The margin of safety (MOS) accounts for uncertainties in the total maximum daily load (TMDL) development process and the variabilities involved in simulating systems, providing a complete description of the degree of protection for a waterbody. Despite numerous discussions on the estimation and incorporation of MOS in TMDLs, there are few post-TMDL studies about the MOS selection process, and there are limited guidelines for selecting MOS values. In this study, natural language processing was employed to review MOS values of TMDLs approved between 2002 and 2016. Reasons such as type of impairment, waterbody types, and designated waterbody given by TMDL developers for chosen MOS values uses were explored. MOS values across states and United States Environmental Protection Agency regions were also analyzed and compared. The results suggested the MOS value of 10% of the estimated load capacity of a waterbody is the most used value across the states and territories of the United States and that 84% of the explicit MOS values selected were not based on any uncertainty estimation method. In addition, the waterbody type and the designated water-use category appear to be correlated with MOS values, and lakes and designated use for aquatic life protection generally had larger MOS values.

India is one of the most drought-vulnerable countries in the world and faces at least one drought in one region or another every 3 years. To alleviate drought risk, an efficient policy framework is needed for water resources management, which in turn needs future projections of the spatiotemporal distribution of droughts. This study presents a spatiotemporal analysis of drought occurrence, frequency, and hazard. Meteorological data from a selected regional climate model for representative concentration pathways (RCP 8.5) was used to compute the Standardized Precipitation Evapotranspiration Index (SPEI) at a 12-month scale to characterize drought in different regions of India. An improved methodology was then developed to improve the current framework used for the development of severity–duration–frequency (SDF) curves. The improved methodology for developing SDF curves is copula based and uses Markov chain Monte Carlo (MCMC) simulation for parameter estimation under the Bayesian framework. Moreover, an improved fuzzy clustering-based drought hazard assessment measure, known as the Modified Drought Hazard Index (MDHI), is also presented. It was found that drought frequency is increasing with time for all the regions of India except for Region 2, i.e., Western Ghats. Further, a significant increase in potential evapotranspiration would cause a prolonged dryness in most of the regions during the twenty-first century. With the progression of time, drought severity associated with various durations is expected to significantly increase with the increase in duration for most of the regions. Drought hazard is expected to be the highest for the period 2071–2100 as compared to two other analyzed periods.

The Green-Ampt method is a physically based model for partitioning rainfall into surface runoff and infiltration. This method is widely used in infiltration practice because of its simplicity and the ease of obtaining the required hydraulic soil properties. The method assumes that the soil is homogeneous. This, however, limits its application to layered soils. In this paper, a simple procedure for applying the Green-Ampt method to two-layered soils was examined under both steady and unsteady rain. For a given design storm, the maximum saturated depth of the top layer was estimated and was used to identify whether the soil profile behaved as a single-layered or two-layered profile. For a two-layered soil profile, the overall effective Green-Ampt parameters were then estimated considering different parameters such as rainfall characteristics, the hydraulic properties of both layers, the thickness of the top layer, and the maximum saturated depth. The cumulative infiltrated volumes with effective Green-Ampt parameters were compared with MIKE SHE simulation results based on the Richards equation with two-layered soils for different layer thicknesses and rainfall hyetographs. The results showed that the proposed simple procedure for estimating the effective soil parameters using the Green-Ampt method showed a good agreement with that computed using the Richards equation in terms of the volume of infiltration water. This approach is expected to provide researchers and engineers a more practical tool in estimating infiltration in two-layered soils than what is presently available.

Assessing rainfall-runoff model performance and selecting the model best suited are important considerations in operational hydrology. However, model choice often is heuristic and based on a simplistic comparison of a single performance criterion without considering the statistical significance of differences in performance. This potentially is problematic because interpretation of a single performance criterion is subjective to the user. This paper removed the subjectivity by applying a jackknife split-sample calibration method to create a sample mean of performance for competing models which are used in a paired $t$-test, allowing statements of statistical significance to be made. A second method was presented based on a hypothesis test in the binomial distribution, considering model performance across a group of catchments. A case study comparing the performance of two rainfall-runoff models across 27 urban catchments within the Thames basin showed that although the urban signal was difficult to detect on single catchment, it was significant across the group of catchments depending upon the choice of performance criteria. These results demonstrated the operational applicability of the new tools and the benefits of considering model performance in a probabilistic framework.

In this study, we explore the use of different multi- and many-objective calibration approaches in hydrological modeling when considering both observed streamflow and remotely sensed actual evapotranspiration (ETa). Eight remotely sensed ETa and an Ensemble products were used in a watershed in Michigan. Regarding the calibration process, the Unified-Non-dominated Sorting Genetic Algorithm III was integrated with the soil and water assessment tool (SWAT). The first nine calibrations used a multi-objective approach with two variables, one being streamflow and the other being a remotely sensed ETa products/Ensemble. The tenth calibration was a many-objective calibration with nine objective functions that represented observed streamflow and all eight of the remotely sensed evapotranspiration datasets. Results showed that the multi-objective calibrations were able to successfully calibrate both streamflow and ETa. However, the highest model performances were achieved using the Ensemble ETa product. Meanwhile, the required computational time for the many-objective calibration is significantly higher than the multi-objective calibration. In addition, the overall performance of many-objective method can be improved by considering weighting factors and constraining the search space.

Dam construction has significantly altered natural flow regimes and caused various environmental problems. This study analyzes hydrologic changes on a national scale using indicators of hydrologic alteration (IHA) and the range of variability approach (RVA) with data from 35 monitoring stations in China. The majority of these stations see reductions in extreme maximum flows, flood flows, low pulse duration, high pulse number and duration, and rise and fall rates, while the extreme minimum flow, flows from December through March, low pulse number, and number of reversals increase. In general, river hydrologic regimes in China are moderately altered by reservoir impoundment, with an average overall alteration degree of 52%. The mean alteration degree of IHAs ranges from 36% to 63%. Reservoir impoundment has a large impact on the number of reversals, the change rate, and extreme minimum flows, which have significant environmental effects and should be analyzed. These change characteristics could help provide a reference for scientific decision-making concerning water resource management in China.