Journal of Hydrologic Engineering

In 2005–2006, a multilysimeter study was conducted to determine the effect of various water table depths (WTDs) (0.2, 0.4, 0.6, 0.8, 1.0, 2.0, 3.0, 4.0, and 5.0 m) on the growth of soybean variety Yudou 16 in the transitional zone of northern semitropical and warm temperate climatic conditions of the Huaibei Plain, Anhui Province, China. In the experiment, precipitation was accounted for and WTD was controlled. The yield of Yudou 16 soybeans was greatest with a WTD of 2 m; yield decreased when the WTD was deeper or shallower than 2 m. From 0.2 through 2.0 m soybean yield increased rapidly with increasing WTD because shallow WTDs produced an oversupply of water in the root zone. From 2 through 5 m yield decreased slowly with increasing WTD under the experimental conditions. This was apparently because deeper WTDs could not compensate (through phreatic evaporation) for rainless periods of moisture stress during the growing season. When the constant WTD changes from 0.8 to 4.0 m, the yield is equal to or greater than the local field yield, with a variable WTD of 0.3 to 3.4 m. This suggested that field production could be improved if WTD were controlled to changing within 0.8 to 4 m. These results should help to guide more precise planning and efficient management of soybean cultivation in this region.

The climate change impact on hydrology in China’s Huang-Huai-Hai (H-H-H) region was assessed in this study. Both variations in mean monthly and annual runoff and occurrences of extreme events including flood and drought were examined for two future periods (2001–2030 and 2016–2045) in the whole region. The projected daily maximum and minimum temperature and precipitation from the PRECIS (providing regional climates for impacts studies) regional climate model were used to drive the variable infiltration capacity (VIC) hydrology model. Variable infiltration capacity was run over a regional domain of 408 grid points at a spatial resolution of $50\times 50\mathrm{km}$. The result shows that PRECIS projects increase in both future temperature (0.8–1.5°C) and precipitation (3.5–7.3%) in the H-H-H region under A2 and B2 scenarios of the fourth Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). Over the entire H-H-H region, VIC projects increase 11.3 and 13.7% in mean annual runoff by the 2015s (2001–2030) and 2030s (2016–2045) under the A2 scenario, respectively. Such increases would be 5.6 and 5.9% under the B2 scenario. The spatial temporal variation of mean annual runoff is likely uneven. For example, the mean annual runoff could decrease by 10% in the south of the Haihe River basin by the 2015s under the B2 scenario. However, an increase of 10% is likely to occur in the northeast part of the same basin. For the mean monthly runoff, the increase would be significant from July through October, and the runoff could exhibit a great interannual variability. Extreme events such as droughts and severe floods could become more frequent in certain areas of the H-H-H region. The occurrence of drought events is likely to increase in summer and autumn seasons in most areas of the H-H-H region. Severe floods might also frequently occur in the Huaihe River basin.

Hydrological parameters are significant both in hydrological events and ecological conservation. The implications of hydrological statistical parameters in river ecology were investigated by considering three basic parameters, as follows: (1) mean value, (2) coefficient of variation, and (3) extreme ratio. Four typical rivers selected as case studies include the Yellow and Yiluo Rivers in north China, and the Yangtze and Oujiang Rivers in south China. Hydrological statistical parameters were calculated using monthly flow data collected from the key hydrometric stations on each of the four rivers. The results revealed that the three hydrological statistical parameters are all crucial ecological indicators that reflect the ecological conditions of river ecosystems. The mean value of the flow may be the key determinant of habitat range and aquatic biomass. The coefficient of variation may reflect the stability or vulnerability of the ecological conditions of rivers, and the extreme ratio may reflect the variation degree of the stability or vulnerability of river ecology. The results may provide some references for research in the river ecological water requirements and conservation of river ecosystems.

The flow regime of the Yangtze River (Changjiang) has been altered to some extent by intensified human activities over the past decades, particularly dam construction. To assess the impacts of dam building on the flow regime in the Yangtze River, two of the largest reservoirs on the upper reach, i.e., the Gezhouba and Three Gorges reservoirs, have been selected as case study sites. To analyze the changes in flow regime between predam and postdam periods, the whole study period was divided into three subperiods according to the years when these two reservoirs started to store water. On the basis of the time series of daily flow discharge from four key hydrological stations, i.e., Cuntan, Yichang, Hankou, and Datong, the alterations in annual, seasonal, monthly, and daily flow regimes and water rising or falling regime in different subperiods were investigated and the driving forces were explored. The results revealed the impacts of the two reservoirs on their downstream flow regime varied with reservoir storage capacity and the distance between the target reservoir and the case study site, the Gezhouba and Three Gorges reservoirs imposed various impacts on different time scales of downstream runoff regime, and the operation of these two reservoirs altered the water rising and falling regime to some degree, which is particularly critical for the spawning of Chinese sturgeon and the four major domestic carp. The output of the paper could provide references for the assessment of impacts of dam construction on the health and stability of the Yangtze River ecosystem.

This paper studied industrial structure improvement to regulate the relation between economic development and available water resources and control water pollutant from the industries. First, the paper analyzes the relationship of industrial improvement with water resources utilization by use of statistical method and points out that the primary and the secondary industry rely on water resources more closely than the tertiary industry. Second, the paper establishes optimal models to improve three industrial structures in which the target functions are restricted to the water pollutant holding capacity, the development planning of the regional economy, and the available water resources. Finally, the paper applies the models on Yingtan, a medium-sized city in China. By using the optimal model, the developing rate of some secondary and tertiary industry sectors that have good water saving and less pollutants are improved, while the developing speed of high water consumption sectors dropped. Through the optimization, water demand in 2020 and 2030 increases a little although its economy grows a lot, and COD and ${\mathrm{NH}}_3\text{-}\mathrm{N}$ discharged to the rivers in Guixi, Yujiang, and Yuehu, China, are all controlled within the water pollutant holding capacity in 2020 and 2030. The improvement of industry structure is a valid method to reduce water consumption and water pollutant.

With the goal of making full use of water resources, a risk assessment of regional water resources and a forewarning model was studied in this paper. The model is built upon risk indexes in the system, proceeding from the whole structure and its component parts at different time scales. A long-term approach is taken to establish the long-term forewarning model of regional water resources with three levels of prediction, assessment, and forewarning. An hydrological model is employed to simulate the further value of an index. Set pair analysis method is adopted to calculate the connection degree of index risk and systematic risk through a multivariate connection number, while the weight of a single index is determined on the different influences and their respective connection degrees are updated. The comprehensive assessment is made by an assessment matrix with connection degree of comprehensive index. The comparison judging method is used to compartmentalize the warning degree of water resources on risk assessment comprehensive index with forewarning standards, and then the long-term local conditions for proposing the planning scheme of water resources. A real-time forewarning approach is also used to establish the real-time forewarning model of regional water resources, which introduces the real-time correction technique of the Kalman filter based on the long-term forewarning model, and then the real-time local conditions for proposing an emergency plan for water resources. The application results show that the proposed model has strong logical superiority and regional adaptability with a strict theoretical system, flexible methods, correct and reasonable results, and simple implementation, providing a new way for researching on the risk assessment and forewarning of regional water resources.

Morphology evolution of estuarine systems is a complex phenomenon. The primary processes (involving waves, currents, sediment transport, and their interaction with topography changes) are not fully understood at different spatial and temporal scales, under either natural situations or intensified human interventions. The Mekong River Delta, one of the most socioeconomically important deltas in Vietnam, is experiencing a dramatic morphological change with natural and human interventions. For example, the Cuadai estuary, one of the biggest of the Mekong River’s estuaries, is undergoing an intricate change of river shore. The highly dynamic variation of the estuary significantly influences the local economy. Basically, there are four classified methods in research of morphology evolution, including (1) theoretical analysis, (2) field investigation, (3) physical modeling, and (4) numerical modeling. Each method has its advantages and disadvantages. Previous studies analyzed survey data or employed remote-sensing techniques. However, no sufficient and scrupulous investigation has been conducted for the effects of different factors. In this paper, an attempt is made to determine the key factors by setting up a numerical model to simulate the morphological change of this estuary with a coupled model flexible mesh. After calibration with the measured data in 2002 and 2003, it is applied to analyze the erosion/deposition pattern of this estuary. The key factors are identified and the influences of the key factors on the morphological evolution are analyzed.

There is no real periodicity in the changes of hydrological systems. Changes in a hydrological system take place with different periodic variations from time to time. In this paper, a new method was utilized to predict monthly runoff with a wavelet analysis technique. Taking advantage of localized characteristics of wavelet transform and the approximation function of an adaptive neural fuzzy inference system (ANFIS), the combined approach of wavelet transform and ANFIS was used to predict monthly runoff. The ANFIS forecast model for monthly runoff was established based on wavelet analysis. To solve the problems related to the large amplitudes of intra- and interannual variation of monthly runoff, a resolving and reconstructing technique of wavelets was utilized to decompose runoff series into different information subspaces, by which decomposition signals with different frequencies were obtained. Based on the evaluation of simulated and measured values in Yichang Station, it was found that the percent of the pass of relative error was 100% and the effect of prediction was acceptable. The certainty factor, $d_y$, was 0.91 and the prediction level was A. By comparing the measured and predicted values, it was found that with this model, the trend of originals could be forecasted, but improvements are still needed. Because the new model is sensitive to sudden changes in rainfall, combined with the irregular monthly runoff variation, it is difficult to forecast runoff with this model, which should be improved in the future.

Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of rainfall over a catchment are a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the selection of an automatic optimization algorithm to search for the parameter values that minimize the distance between the simulated and observed data. However, practical experience with model calibration suggests that traditional optimization methods, such as the Newton-Raphson, conjugate gradient, and downhill simplex methods, are easily trapped in local minimums because the objective function surface is rough, caused by model structure errors and data errors. The across-ridge calibration method (ARC), an effective and efficient methodology for searching global optimization problem, is proposed in this paper. The method searches for all local optima in a fixed boundary, which makes it less susceptible to the irregularity of the response surface. The features and capabilities of ARC are illustrated by means of a binary function, an ideal conceptual rainfall-runoff model (Xinanjiang model) without model and data errors and a real model (Xinanjiang model) with structure and data errors. The results indicate that the proposed across-ridge calibration method can converge quickly from any starting point even when the response surface is rough. The optimized parameter sets for the Xinanjiang model (XAJ) are unique and conceptually realistic; the simulation performance of these parameters is reasonable and efficient.

An analytical solution for overland flow under (upstream and downstream) moving storms that uses Laplace transformation to solve the one-dimensional (1D) linear kinematic wave equation is presented. This solution, which corresponds to a single continuous function for the total space-time domain of the overland hydrograph, enables evaluation of the discharge over time for the total drainage plane surface. The result was compared with another analytical solution, a numerical simulation, and experimental runs using a laboratory flume. The comparison showed very good fit, and the proposed analytical solution was thus regarded as validated. By applying the model to hypothetical catchments and storm patterns, distinct hydrologic responses for upstream and downstream moving storms were identified.

Surface digital elevation model (DEM) resolution receives increasing attention because of its importance in topographic analysis (e.g., quantification of surface depressions) and hydrologic modeling. Varied and even contrary conclusions have been obtained concerning the effects of DEM grid size on surface depression properties. Land surfaces are featured with a number of microtopography-controlled, localized areas, and their connections may significantly alter hydrologic and geomorphologic processes. Few efforts have been made to examine the effects of DEM resolution on surface depression properties and hydrologic connectivity. This study aimed to evaluate such resolution effects by two dimensionless parameters: the DEM representation scale ${\lambda }_L$ (the ratio of DEM grid size to correlation length, representing horizontal resolution) and the surface roughness scale ${\lambda }_R$ (the ratio of random roughness to correlation length, representing vertical topographic variability). A puddle delineation program was utilized to quantify depression properties for a variety of topographic surfaces characterized by different DEM resolutions, including small-scale surfaces with random roughness, field plots, and watershed surfaces. In particular, a puddle-to-puddle (P2P) conceptual model was used for hydrologic connectivity analysis. It was found that puddle properties depended on both dimensionless ${\lambda }_L$ and ${\lambda }_R$. The ${\lambda }_L$ significantly influenced the calculations of structural and functional hydrologic connectivity. Using DEMs with a coarser resolution or higher ${\lambda }_L$ tended to overestimate hydrologic connectivity and simplified hydrograph for a surface with numerous small-scale depressions. The DEM resolution or dimensionless ${\lambda }_L$ had significant influences on the development of functional hydrologic connectivity, especially at the early stage of the rainfall-runoff process.

In an open-loop groundwater heat pump (GHP) system, groundwater is extracted, run through a heat exchanger, and injected back into the ground, resulting in no mass balance changes to the flow system. Although the groundwater use is nonconsumptive, the withdrawal and injection of groundwater may cause negative hydraulic and thermal impacts to the flow system. Because GHPs are a relatively new technology and regulatory guidelines for determining environmental impacts for GHPs may not exist, consumptive-use metrics may need to be used for permit applications. For consumptive-use permits, a radius of influence is often used, which is defined as the radius beyond which hydraulic impacts to the system are considered negligible. In this paper, the hydraulic radius of influence concept was examined using analytical and numerical methods for a nonconsumptive GHP system in southeastern Washington State. At this location, the primary hydraulic concerns were impacts to nearby contaminant plumes and a water supply well field. The results reported in this paper show that distance drawdown methods for both analytical and numerical methods were generally unsuitable because they overpredicted the influence of the well system. Particle tracking yielded more reasonable results because flow paths demonstrated the probable impact on the flow system. In particular, the use of a capture zone analysis was identified as the best method for determining potential changes in current contaminant plume trajectories, which could be performed with both analytical and numerical techniques. Capture zone analysis is a more quantitative and reliable tool for determining the radius of influence with a greater accuracy and better insight for a nonconsumptive GHP assessment.

The design of the dams usually considers available historical data for analysis of the flood frequency. The limitation of this approach is the potential shift in flood frequency due to physically plausible factors that cannot be foreseen during design. For example, future flood extremes may change, among other factors, due to strong local atmospheric feedbacks from the reservoir and surrounding land use and land cover (LULC). Probable maximum flood (PMF), which is the key design parameter for hydraulic features of a dam, is estimated from probable maximum precipitation (PMP) and the hydrology of the watershed. Given the nonlinearity of the rainfall-runoff process, a key question that needs to be answered is How do reservoir size and/or LULC modify extreme flood patterns, specifically probable maximum flood via climatic modification of PMP? Using the American River Watershed (ARW) as a representative example of an impounded watershed with a large artificial reservoir (i.e., Folsom Dam), this study applied the distributed variable infiltration capacity (VIC) model to simulate the PMF from the atmospheric feedbacks simulated for various LULC scenarios (predam, current scenario, nonirrigation, and reservoir-double). The atmospheric feedbacks were simulated numerically as PMP using the regional atmospheric modeling system (RAMS). The RAMS-generated PMP scenarios were propagated through the VIC model to simulate the PMFs. Comparison of PMF results for predam and current scenario conditions showed that PMF peak flow can decrease by about $105{\mathrm{m}}^3/\mathrm{s}$, while comparison of current scenario with nonirrigation PMF results showed that irrigation development has increased the PMF by $125{\mathrm{m}}^3/\mathrm{s}$. On the other hand, the reservoir size had virtually no detectable impact on PMP and consequently on PMF results. Where downstream levee capacity is already underdesigned to handle a dam’s spillway capacity, such as for the case study, such increases indicate a likely impact on downstream flood risk to which any flood management protocol must adapt. The premise that modern dam design and operations should consider an integrated atmospheric-hydrologic modeling approach for estimating proactively potential extreme precipitation variation due to dam-driven LULC change is well-supported by this case study.