Jenq Tzong Shiau

Assessing Multi-site Drought Connections in Iran Using Empirical Copula

Drought is a multi-dimensional natural hazard with stochastic characteristics usually related to each other. Separate univariate statistical models cannot capture the important relationships among drought characteristics, that is, severity and duration. In this study, an empirical copula is employed to construct a bivariate model of droughts, where droughts are defined as continuously negative standardized precipitation index (SPI) periods with one SPI value reaching −1 or less. Bivariate frequency analyses in terms of recurrence intervals are performed using the established empirical copula-based bivariate drought model. The inter-connection among different regions of droughts is explored by a lower tail dependence coefficient. A nonparametric estimation based on an empirical copula is employed pairwisely to calculate the lower tail dependence coefficient among stations. The proposed method is applied to six rainfall gauge stations in Iran to explore drought properties of single sites as well as the inter-connection among multi-sites. The results show that greater mean drought severity and duration are associated with the least arrival rate of drought events, which occurs at the Ahwaz station. The tail dependence analysis reveals that distance between stations is not a key parameter. Generally, the Ahwaz and Isfahan stations have the highest probability of simultaneous droughts among the six stations.

Assessment of climate change impacts on flooding vulnerability for lowland management in southwestern Taiwan

Taiwan suffers from losses of economic property and human lives caused by flooding almost every year. Flooding is an inevitable, reoccurring, and the most damaging disaster in Taiwan since Taiwan is located in the most active tropic cyclone formation region of the Western Pacific. Flooding problem is further worse in land subsidence areas along southwestern coast of Taiwan due to groundwater overdraft. Increasing number of people is threatened with floods owing to climate change since it would induce sea level rise and intensify extreme rainfall. Assessments of flooding vulnerability depend not only on flooding severity, possible damage of assets exposed to floods should also be simultaneously considered. This paper aims at exploring how climate change might impact the flooding vulnerability of lowland areas in Taiwan. A flooding vulnerability evaluation scheme is proposed in this study which incorporates flooding severity (the maximum inundation depth determined by a two-dimensional model) and potential economic losses for various land uses. Effects of climate change on flooding vulnerability focus on alterations of rainfall depth for various recurrence intervals. The flood-prone Yunlin coastal area, located in southwestern Taiwan, is chosen to illustrate the proposed methodology. The results reveal that reducing flooding vulnerability can be achieved by either reducing flooding severity (implementation of flood-mitigation measures) or decreasing assets exposed to floods (suspension of land uses for flood-detention purpose). Performance of currently implemented flood-mitigation measures is insufficient to reduce flooding vulnerability when facing with climate change. However, the scenario suggested in this study to sustain room for floods efficiently reduces flooding vulnerability in both without- and with climate change situations. The suggestions provided in this study could support decision processes and help easing flooding problems of lowland management in Taiwan under climate change.

Detecting Multi-Purpose Reservoir Operation Induced Time-Frequency Alteration Using Wavelet Transform

It is well recognized that natural flow variability is an inherent characteristic of rivers. Altered natural flow regime caused by anthropogenic regulations would threaten ecosystem biodiversity and deteriorate riverine health. Wavelet transform is a newly-developed tool that extracts dominant modes of variability by decomposing a non-stationary series into time-frequency space, which can be used to detect hydrologic alteration at various scales caused by reservoir operation. Continuous wavelet transform is simultaneously applied to recorded hourly inflow and outflow series of 1998–2008 for the Feitsui Reservoir located in northern Taiwan. Differences between wavelet power spectrum obtained for outflow and inflow series denote severity of hydrologic alteration. Greater spectral alteration is observed at less-than-1-day scales due to peak-load hydropower releases. The spectral alteration gradually declines with increasing scales. Different variation patterns for the yearly time-averaged spectral difference also reveal that the altered spectrum depends on hydrologic conditions. The index of spectral alteration (ISA), defined as the mean absolute deviations of power spectrum for all scales over a certain time period, is proposed to quantitatively assess severity of altered natural flow regime. ISA of 5 can be roughly recognized as the division of dry and non-dry years for the Feitsui Reservoir case. The obtained results offer decision makers useful information to adopt adaptive operating strategies to mitigate negative impacts of altered natural flow regime and derive optimal trade-off between human and environmental needs.

Clustering Quantile Regression-Based Drought Trends in Taiwan

Drought is a normal, recurring climatic feature and occurs in all climatic zones. Imbalanced water availability induced by droughts has far-reaching and adverse impacts both on human lives and natural environments. This study aims to summarize temporal and spatial drought variations in Taiwan by combining quantile regression and cluster analysis. Three-monthly rainfall series covering the 1947–2012 period for 12 rainfall stations are used in this study. Quantile regression is applied to 3-month SPI, drought duration, drought severity, and drought frequency series for exploring temporal drought trends at different quantiles. Various quantile slopes for these 12 stations are then analyzed by hierarchical agglomerative clustering algorithm to detect regional variation patterns. The results show considerable spatial diversity over Taiwan. Stations along east coast are prone to more severity due to declined SPI trends associated with increasing drought duration and severity. Positive SPI slope associated with decreasing drought duration and severity are noted at stations located in the west and lead to lessened droughts. However, temporal variations in drought-duration and drought-severity series are insignificant at most quantiles and stations. In addition, a distinct behavior is found in drought frequency since severe droughts may not accompany frequent droughts.

Physiographic Drainage-Inundation Model Based Flooding Vulnerability Assessment

Flooding vulnerability assessment is an important issue in Taiwan since Taiwan lies within the most active tropical cyclone formation zone of the Western Pacific. Huge economic damages and losses of human lives are occurred almost every year. This study aims to evaluate flooding vulnerability of a given area subject to large-scale land developments. A scoring-based approach associated with a physiographic drainage-inundation model is developed to quantitatively evaluate vulnerability for flooding. The flooding vulnerability index defined as the product of an exposure score and a hazard score. The exposure score assesses relative losses exposed to flooding, which is determined by land-uses classification. The hazard score measures flooding severity, which is simultaneously determined by inundation depth and duration that are obtained from the inundation model for a design storm. The Yenshui River basin located in southwestern Taiwan is used an example to illustrate the proposed method. The results show that the projected urbanization plan within the Yenshui River basin would increase flooding vulnerability from 0.371 to 0.472. However, this value is reduced to 0.388 when the mitigation measure has been implemented. The obtained spatial distribution of flooding vulnerability for a design storm provides decision-makers useful information to identify hotspots of the study area and evaluate effects of flood-mitigation measure on flooding risk-reduction.

Suitability of ANN-Based Daily Streamflow Extension Models: a Case Study of Gaoping River Basin, Taiwan

It is well known that sufficiently long and continuous streamflow data are required for accurate estimations and informed decisions in water-resources planning, design, and management. Although streamflow data are measured and available at most river basins, streamflow records often suffer from insufficient length or missing data. In this work, artificial neural networks (ANNs) are applied to extend daily streamflow records at Lilin station located in Gaoping River basin, southern Taiwan. Two ANNs, including feed forward back propagation (FFBP) and radial basis function (RBF) networks, associated with various time-lagged streamflow and rainfall inputs of nearby long-record stations are employed to extend short daily streamflow records. Performances of ANNs are evaluated by root-mean-square error (RMSE), coefficient of efficiency (CE), and histogram-matching dissimilarity (HMD). Inconsistency among these evaluation measures is solved by the technique for order performance by similarity to ideal solution (TOPSIS), a widely used multi-criteria decision-making approach, to find an optimal model. The results indicate that RBF-E1 (entire-year data training with Qt and Qt−1 inputs) has the minimum RMSE of 104.4 m3/s, second highest CE of 0.956, and third lowest HMD of 0.0096, which outperforms other ANNs and provide the most accurate reconstruction of daily streamflow records at Lilin station.

Quantile Regression-Based Probabilistic Estimation Scheme for Daily and Annual Suspended Sediment Loads

Assessing suspended sediment loads in rivers is important since it affects water quality, hydraulic-facility design, and many other sediment-induced problems. Sediment-load estimation heavily depends upon empirical approaches such as a sediment rating curve, which is the empirical relationship between sediment load and river discharge. However, the sediment rating curve is insufficient to describe the inevitable scatter between sediment and discharge. This study aims to develop a probabilistic estimation scheme for daily and annual suspended sediment loads using quantile regression. All recorded daily suspended sediment load and discharge data are employed to construct quantile-dependent sediment rating curves. The empirical probability distribution of daily suspended sediment load is then built by integrating the conditional estimations associated with the corresponding quantiles for a given discharge. The probability distribution of a cumulative sediment load over a longer period can also be derived by the obtained daily sediment-load probability distributions and convolution theorem. The proposed approach is applied to the Laonung station located in southern Taiwan. The results indicate that the proposed approach provides not only the probabilistic description for daily and annual suspended sediment loads, but also the single estimations including the mean, median, and mode of the derived probability distribution. For the 1,110 recorded data of Laonung station during the 1959–2008 period, the proposed mean and median estimation schemes outperform the traditional sediment-rating-curve approach for less mean absolute errors.

Basin-scale optimal trade-off between human and environmental water requirements in Hsintien Creek basin, Taiwan

Reallocating water resources to satisfy human and environmental water requirements in a balanced manner within a basin constitutes a challenge task in water resources management. This study aims to develop a basin-scale multi-purposes operation model coupled with a multi-criteria optimization framework to investigate values of coordinated releasing rules for maintaining streamflow variability at different river reaches. The proposed approach is applied to the Hsintien Creek basin (northern Taiwan) to explore four management scenarios. The results indicate that the no-environmental-flow scenario is most favorable to human benefits. But severe hydrologic alteration at all reaches leads to the worst overall performance of 0.521, which is a multi-criteria index based on normalized human-benefit and environmental objectives and ranges between 0 and 1. The current rule releasing minimum environmental flows at some reaches receives an improvement at those reaches and has a slightly improved overall index of 0.530. Sustaining minimum environmental flows at all reaches does not provide a further overall improvement of 0.530 since mitigation of hydrologic alteration at those reaches is offset by deterioration of human benefits. The best overall performance of 0.620 is achieved by the basin-scale optimization for deriving the coordinated operation rules and time-varying environmental flow releases that lead to the most compromising alternative between conflicting human and environmental objectives.

Assessment of flow regime alterations over a spectrum of temporal scales using wavelet‐based approaches

The full range of natural flow regime is essential for sustaining the riverine ecosystems and biodiversity, yet there are still limited tools available for assessment of flow regime alterations over a spectrum of temporal scales. Wavelet analysis has proven useful for detecting hydrologic alterations at multiple scales via the wavelet power spectrum (WPS) series. The existing approach based on the global WPS (GWPS) ratio tends to be dominated by the rare high-power flows so that alterations of the more frequent low-power flows are often underrepresented. We devise a new approach based on individual deviations between WPS (DWPS) that are root-mean-squared to yield the global DWPS (GDWPS). We test these two approaches on the three reaches of the Feitsui Reservoir system (Taiwan) that are subjected to different classes of anthropogenic interventions. The GDWPS reveal unique features that are not detected with the GWPS ratios. We also segregate the effects of individual subflow components on the overall flow regime alterations using the subflow GDWPS. The results show that the daily hydropeaking waves below the reservoir not only intensified the flow oscillations at daily scale but most significantly eliminated subweekly flow variability. Alterations of flow regime were most severe below the diversion weir, where the residual hydropeaking resulted in a maximum impact at daily scale while the postdiversion null flows led to large hydrologic alterations over submonthly scales. The smallest impacts below the confluence reveal that the hydrologic alterations at scales longer than 2 days were substantially mitigated with the joining of the unregulated tributary flows, whereas the daily-scale hydrologic alteration was retained because of the hydropeaking inherited from the reservoir releases. The proposed DWPS approach unravels for the first time the details of flow regime alterations at these intermediate scales that are overridden by the low-frequency high-power flows when the long-term averaged GWPS are used.

Effects of Hedging Factors and Fuzziness on Shortage Characteristics During Droughts

Frequently suffering from water deficits induced by prolonged and severe droughts in Taiwan, hedging rules become an important component in reservoir operation to ensure stable water supplies during droughts. Conventional zone-based rule-curve operation is an easy rule to guide water releases since fixed rationing factors are assigned for various zones. A drawback for such hedging is abrupt changes of rationing factors from one zone to another. Fuzzified rule curves provide an alternative to create gradually varied rationing factors. In this study, impacts of hedging factors including rule curves, rationing factors, and fuzziness on water-deficit characteristics are explored. The method presented in this study is illustrated through an application to the Nanhua Reservoir located in southern Taiwan. The results reveal that different hedging factors have different impacts on shortage indices. More hedging factors involved in optimization models leads to more compromising hedging among conflicting shortage indices. According to the proposed overall index, which is a multi-criteria index based on normalized shortage indices, the current operation leads to the worst overall performance of 0.480. One-optimized-hedging-factor scenarios receive an improvement and range between 0.541 and 0.607, while the two-optimized-hedging-factor scenarios have a further improved overall index of 0.603−0.659. The best overall performance of 0.679 is achieved by optimizing three hedging factors and results in the most compromising alternative among all scenarios.