Journal of Hydrologic Engineering

This paper aims to develop an accurate and efficient numerical model for three-dimensional transient thermal groundwater flow problems. The modified Richards equation and heat transport equation are considered to govern the thermal groundwater flows. For modeling water flows in the subsurface saturated-unsaturated porous media, we combined the method of characteristics (MOC) and a meshless localized radial basis function collocation method (LRBFCM). In order to implement the MOC scheme, the modified Richards equation is reformulated to an advection form and then computed by the particle tracking technique via MOC. We will then solve the heat equation and remaining terms of the temporal Richards equation by the LRBFCM. Seven benchmark subsurface flow problems with and without temperature effects are simulated and discussed to verify the feasibility and efficiency of this novel three-dimensional (3D) numerical model.

In recent years, climate change has caused extreme weather all over the world, including in Taiwan. Rainfall in Taiwan is distributed unevenly in both time and space, leading to a shortage of water resources which has become a pressing issue for the island. Groundwater plays a vital role as a backup and supplementary water resource. This study proposes a method that combines the seepage theorem, field observations, and a numerical simulation to identify high-potential groundwater resource regions to meet the demand for water supplies in future development. The Taichung Chingshui Coastal Plain (TCCP) was selected as a study area for testing the method. Two new wells were drilled in the area to obtain additional information to supplement the analysis of groundwater levels (GLs). Results indicate that the hydrological and hydrogeological parameters (e.g., Manning’s coefficients, hydraulic conductivity, and formation thickness) can be obtained reasonably by comparing the numerical simulation with the observed GLs. It was found that the Dadu, Waipu, and Qingshui districts are the top three areas with higher potential groundwater resources in the TCCP. Data from the observations wells and in situ pumping stations verified our simulation results, which showed that our proposed methodology is advantageous. The research results can help improve the effective use of existing groundwater resources and assist with water resource development and sustainable usage.

In a river cross section or segment that has attained an equilibrium flow regime, the relationship between geometric (river depth, width, hydraulic radius, bed slope, etc.) and/or hydraulic (velocity, roughness, shear stress, etc.) factors in relation to the river’s equilibrium discharge (i.e., flows of fixed nominal return period or at bankfull depth) is termed hydraulic geometry (HG). HG relations have been proposed from a multitude of approaches: empirical, statistical, physically based, and extremal. Furthermore, multiple extremal hypotheses exist, depending on the variable to be optimized (maximized or minimized). In this study, we (1) present a unified framework by invoking the principle of maximum entropy (or, equivalently, Laplace’s law of insufficient reason), that is, assuming that individual contributions by geometric and hydraulic factors to HG through the optimization of extremal hypotheses (Froude number, frictional resistance, mobility index, stream power, sediment flux, etc.) presumably stem from equiprobable contributions of these factors—in other words, entropy is maximized; (2) enumerate 26 combinations (groups of sizes two to five) of the five basic HG variables, namely depth, width, slope, velocity, and friction, and analyze their interrelations; and (3) relax our initial equiprobability assumption by plugging in a scaling (weighting) parameter and show that 11 special cases of the 26 unique combinations lead to reasonable approximations of benchmark empirical results in the literature in at least one instance for each of the five extremal hypotheses considered here. The benefits of the unified framework include providing a theoretical basis to bring together various hypotheses that result in HG relations and providing an analytical way to quantify (or explain) epistemic uncertainty therein. Ultimately, this unified framework improves our understanding of HG and provides an analytical framework for improving predictions of river flows.

Application of aquifer storage and recovery (ASR) is difficult in highly saline groundwater regions because the recharged freshwater mixes with saline groundwater and makes a thin layer below the capillary fringe. The recovery efficiency (RE) of ASR can be improved by customizing the operational factors and well design of the ASR scheme according to the regional hydrogeology. The RE can be raised in different ways, such as adjusting the operational factors to reduce the mixing or using multiple wells to reduce gravitational segregation. This study developed a variable-density groundwater flow modeling framework for ASR performance estimation in saline groundwater regions, which examined the combined influence of operational factors and well design on RE. The density-driven effect during freshwater injection and its storage within saline groundwater on RE were also investigated. ASR systems with single fully penetrating wells (SFPWs) and multiple partially penetrating wells (MPPWs) were evaluated with respect to operational factors, that is, injection and recovery rates, the volume of injected freshwater, storage duration, and successive number of ASR cycles. The results showed that losses due to mixing are significantly influenced and controlled by successive ASR cycles followed by injection and recovery rates, injection volume, and storage duration. The results also revealed that losses due to gravity could be controlled by using MPPW systems in place of a SFPW system. The model results showed that in three subsequent cycles, no more than 45% of the yearly injected water could be recovered by the SFPW well–type model, which is less than the MPPW case by 11% for the baseline parameters of representative hydrogeology. The results of this study will help in the operational management of ASR schemes to achieve higher RE in the saline groundwater regions.

Abstract

Two of the most challenging issues in building robust hydrological models are determining model parameter uncertainty and examining parameter sensitivity to the system forcing data. These are especially important in dry regions with scarce data. Addressing them requires accurate forcing and basin data, usually from several different sources. The main goal of this research was to show how to construct a coherent hydrological model by (1) quantifying the sensitivity of the variable infiltration capacity (VIC) model parameters in the Lesser Zab River Basin in Iraq; and (2) implementing a complete and accurate set of forcing data by testing the validity of two sources, the National Centers for Environmental Prediction (NCEP) and Global Implemented Data (GIDAL). Although results are for a case in Iraq, the approach is valid in other regions with similar conditions and challenges. A predeveloped technique was applied to adjust the forcing data to have properties similar to the in situ observations. The parameter sensitivity was evaluated using generalized likelihood uncertainty estimation (GLUE) for seven candidate parameters of the VIC random sets for the year 2000. The VIC model was calibrated using the Kling–Gupta efficiency (KGE) for both daily and monthly time scale. Results indicated that on the average NCEP outperformed GIDAL, implying and that these data sources should not be utilized without thorough evaluation. The uncertainty analysis demonstrated the VIC model’s validity in producing realistic forecasts. Calibration of the VIC model’s daily outputs using the KGE was 0.49; this value was 0.63 for monthly runs. The calibrated model residuals lacked nonnormality, heteroscedasticity, and autocorrelation, indicating that the outcomes are reliable outside the calibrated time frame.

Abstract

The practical applications of this work stem from the fact that many regions of the world have scarce data but require accurate hydrological models for diverse management purposes. By showing how to augment scarce data in Iraq, new methods will be made available to others. The study did not aim to provide a data set framework, but to pave the road for future data implementation in the region and in similar regions. This study can be considered as a reference for future comparison by using similar approach to overcome data scarcity. The study is part of collaborative work by IHE-Delft and the Iraqi Ministry of Water Resources (MoWR) to examine the impact of climate change on water availability. It will be followed by a study to analyze the climate change impact using a bottom-up approach for the study area. The outcomes will be beneficial to decision makers to understand undesirable future impacts and select the most promising adaptation strategies. This shared problem requires cooperation among researchers to develop improved data preparation procedures such as those presented in this study.

Modeling methodologies capable of coping with changing catchment conditions are becoming more important and are critical to ensure credible model predictions because the hydrologic process of the catchment is inevitably affected by climate change and human activities. A recently developed hydrological modeling framework that treats model parameters to be time-variant by building functions based on identified catchment properties is applied to the Upper Ganjiang River Basin in China experienced soil and water conservation constructions. The efficacy of the time-variant parameter method is investigated, and we further explore the impacts of model structure on hydrological modeling through this method. The approach is tested using two conceptual monthly water balance models, i.e., the $ab$ model derived from the $abcd$ model, and a two-parameter monthly water balance model (TWBM), which have the same model inputs and outputs, number of parameters and state variables. Results of the case study show that through the comparative analysis with the constant parameter models, both time-variant parameter models provide improved runoff simulations, especially for low and high flows. Moreover, the time-variant parameter method brings relatively larger runoff improvements for the TWBM model. For the actual evapotranspiration simulations, the ab model can yield improvements by treating parameter $b$ (i.e., upper soil zone water holding capacity) to be time-variant, whereas the time-variant parameter method shows no efficacy in that for the TWBM model. The results demonstrate that the choice of hydrological model plays an important role in modeling performance of the time-variant parameter framework under a changing environment. Modification of the evapotranspiration calculation module for the TWBM model could be considered as further study to investigate the potential model improvement that compared with only time-variant parameters. This study can provide beneficial reference to comprehensively understand the impacts of changing environment on catchment hydrological modeling and thus improve the regional strategy for future water resource management.

Flood frequency estimation in the United States has been primarily driven by statistical analysis for the past one hundred years. For ungauged locations, the regionalized equations are developed to provide annual exceedance probability discharge estimates. These equations establish a relationship between discharge quantiles and drainage area through statistical regression. Predictors consisting of catchment physical properties can also be included based on minimization of residuals. For Iowa, only one-third of developed regional equations use a climatic parameter (i.e., precipitation), which is a critical driver of hydrologic processes. The authors explore an alternative approach to regional flood quantile estimation analysis by analyzing the performance of the Iowa Flood Center’s physically based, calibration-free, and spatially distributed Hillslope-Link Model (HLM). They conducted continuous simulations for a 40-year period across the state of Iowa. Compared to the observations, the HLM can accurately capture the observed magnitude of annual maximum discharge, making it a viable physically based alternative to regional regression. In the study, regional flood quantile estimation is conducted at 445 ungauged communities to compare flood frequency estimates using HLM simulations with regionally developed regression equations. The results show similar discharge values between simulation and regional regression models for all annual exceedance probability where regional equations contain rainfall as a predictor. However, in areas where regional equations are only based on catchment properties, regional regression equations overestimated discharge for all quantiles. These results highlight inconsistencies in current regional regression equations for flood quantile estimates in Iowa and provide support for the reevaluation of flood quantile estimates with physically based hydrologic models.

Meiyu is a unique weather phenomenon in East Asia that affects the middle and lower reaches of the Yangtze River in China, as well as Taiwan, central and southern Japan, and southern South Korea. It typically occurs from June to July every year. Rainfall during the Meiyu season causes disasterous floods in southern Jiangsu, China. To improve the effectiveness of flood disaster planning in southern Jiangsu, an understanding of the probability of regional rainstorms during Meiyu is needed. Analytical results based on 16 symmetric and asymmetric Archimedes copula functions show that the overall performance of predicting probability using multiparametric asymmetric Archimedean copulas is better than that of single-parameter symmetric Archimedean copulas. In asymmetric Archimedean copulas, the Type II Gumbel distribution was most effective. Based on the joint rainfall distributions in the study area, a rainfall combination design method with an adjustment factor $\phi$ is proposed. Factors inherent in the adjustment factor $\phi$ (e.g., different return period design standards and increases in extreme rainfall) are discussed.