Journal of Hydrologic Engineering

This study reports the performance of an M5 model tree (MT) and the effects of pruning and smoothing applied to reservoir inflow prediction. The full year and seasonal monthly time step MT predictions were compared with conventional univariate autoregressive integrated moving average (stochastic) models. It was found that stochastic models could not predict the future inflows in a better way, because the observed series had not followed any particular distribution. However, it was found that the stochastic models showed better improvement using a logarithmic-transformed series, but the logarithmic-transformed MT results showed otherwise. The model validation was performed using the comparison of goodness of fit measures, standard statistics, time series, and scatter plots of predicted inflows with observed inflows. The effect of pruning each leaf in the MT model was also studied. Instead of pruning all the leaves, leading to lesser predictive accuracy, selective pruning was carried out based on the importance of the processes, for example, peak and low flow. The performance of both stochastic and MT models showed that seasonal monthly prediction was superior to full-year monthly prediction because of large zero values in latter data set. Encouraging results indicated that the seasonal nontransformed selective-pruned MT models performed better and produced reliable forecasts of high and low inflows than the stochastic models. A pruned and smoothed MT model (PSMT) performed 79% better than the stochastic models in terms of mean square error (MSE). On the other hand, MSE was 98% better than the stochastic model in an unpruned and unsmoothed MT (UPUSMT) model. Because of better peak prediction by UPUSMT model, the MSE was 90% better than the PSMT models. The other advantage of an MT was having a set of equations and if-then rules to predict the inflow as well as peak inflow into the Pawana reservoir.

The U.S. Surface Mining Control and Reclamation Act of 1977 requires that mine operators minimize disturbances to the prevailing hydrologic balance of surface-mined sites and associated off-site areas through land reclamation. The hydrologic evaluation to support this requirement is often performed using the curve number (CN) rainfall-runoff method. Accurate application is limited by a scarcity of tabulated CN values for reclaimed mine lands, and assumptions regarding the hydrologic behavior of reclaimed mine lands may be inaccurate. Four watersheds (three reclaimed surface coal mines and one forested reference) in the Georges Creek basin of western Maryland were instrumented for rainfall and runoff. CNs calculated for the reclaimed mine land watersheds using rainfall and runoff data ($\mathrm{\text{range}}=68–92$) were generally higher than CNs estimated by prevailing engineering methods ($\mathrm{\text{range}}=65–79$). The general agreement of these results with other studies indicates that a more conservative hydrologic approach may be warranted in engineering design and hydrologic analysis of surface-mined lands. These results also indicate that surface mining and reclamation may have similar hydrologic impacts as urbanization. Whereas urbanized landscapes typically feature engineered storm water management to mitigate hydrologic change, these features are typically absent on reclaimed mine lands.

Raised roads and their appurtenances (i.e., ditches and culverts) can considerably modify the natural hydrologic processes (e.g., flow direction and runoff spatial distribution) of low-relief watersheds. However, these effects are not well understood and are poorly documented in literature. Also, there is a serious lack of effective approach that can be used to describe these effects in common simulation models, including the Soil and Water Assessment Tool (SWAT). As a result, these effects have been rarely taken into account by the existing model applications. The results from those applications are likely to be misleading for watershed management decisions. The objectives of this study were to (1) develop an approach that enables the incorporation of the aforementioned effects into hydrologic models (e.g., SWAT), and (2) evaluate whether and how a model’s simulation performance can be improved by taking these effects into account. The evaluation was conducted for the low-relief Wild Rice River watershed located in northwestern Minnesota by comparing the SWAT-NoRoad model, which is based on a “conventional flow direction map” derived using the deterministic eight-neighbor (D8) algorithm, with the SWAT-Road model, which is based on a “corrected flow direction map” generated by using the approach developed in this study. The corrected map provided more realistic flow directions for the regions adjacent to the raised roads than the conventional map. Compared with the SWAT-NoRoad model, the SWAT-Road model had a compatible performance for a calibration period but was more robust and did a better job in reproducing the observed streamflows for a validation period at two U.S. Geological Survey gauging stations, as indicated by the larger values for Nash-Sutcliffe ($E_j^2>0.60$) and determination ($R^2>0.68$) coefficients, as well as from the watershed perspective view, as indicated by the larger values for performance virtue (${\mathrm{PV}}_k>0.64$). In addition, the spatial patterns of water yield predicted by the SWAT-Road model were more accurate because they are more similar to those of the topographic wet index values than the spatial patterns predicted by the SWAT-NoRoad model. Furthermore, if the raised roads were neglected, the mean daily water yields for the study area would be erroneously predicted by up to 0.6 mm. A reasonable generalization of this study is that hydrologic effects of raised roads are important for accurately simulating watersheds with a low topographic relief and thus need to be taken into account.

It is believed that the currently increasing temperature, also known as global warming, has altered the hydrological cycle and thus the hydrometeorological extremes become frequent. In this study, the authors analyze hydrological extremes defined by 7-day high flow and low flow of the Pearl River Basin by using a copula family. The results indicate that the concurrent occurrence of extreme high and low flow is of small probability. It implies that the probability is small that the lower Pearl River Basin is attacked by heavy droughts or floods because of the combined effects of high or low flow of the two major tributaries of the Pearl River, i.e., the West and North Rivers. Therefore, the authors can conclude that the joint probability of hydrological extremes of two tributaries of a river basin could be small, albeit the occurrence of hydrological extremes of an individual river is of large probability. Besides, the results of this study also reveal increasing 7-day low flow in winter, which should be because of seasonal shifts of precipitation on the basis of the previous studies. The results of this study mean much for the sound human understanding of statistical behaviors of hydrological extremes in humid regions, and also for effective water resource management and development of human mitigation to the natural hazards in the changing environment.

Climate change will bring more severe and frequent floods to the Upper Thames River basin. The city of London, with a population of over 350,000, is one of the most vulnerable locations in the basin. This paper presents an original methodology used to prepare the input for flood risk assessment under climate change. The methodology involves integrated climate-hydrologic-hydraulic modeling analyses for floodplain mapping under the changing climatic conditions. Using 43 years of historical data at 15 stations in the Upper Thames River basin and global circulation model predictions, the potential climate change impacts on flood risk in the basin are provided. The results indicate that, under climate change, the extent of flood impacts will be larger (larger areas inundated with larger water depth), and will therefore increase the level of risk to public infrastructure. Results of the study are being used in a quantitative assessment of risk to the municipal infrastructure.