Upmanu Lall | Columbia University (original) (raw)
Papers by Upmanu Lall
Water Resources Research, 2017
Storage and controlled distribution of water have been key elements of a human strategy to overco... more Storage and controlled distribution of water have been key elements of a human strategy to overcome the space and time variability of water, which have been marked by catastrophic droughts and floods throughout the course of civilization. In the United States, the peak of dam building occurred in the mid‐20th century with knowledge limited to the scientific understanding and hydrologic records of the time. Ecological impacts were considered differently than current legislative and regulatory controls would potentially dictate. Additionally, future costs such as maintenance or removal beyond the economic design life were not fully considered. The converging risks associated with aging water storage infrastructure and uncertainty in climate in addition to the continuing need for water storage, flood protection, and hydropower result in a pressing need to address the state of dam infrastructure across the nation. Decisions regarding the future of dams in the United States may, in turn,...
Hydrology and Earth System Sciences, 2013
Snowmelt dominated streamflow of the Western Himalayan Rivers is an important water resource duri... more Snowmelt dominated streamflow of the Western Himalayan Rivers is an important water resource during the dry pre-monsoon spring months to meet the irrigation and hydropower needs in Northern India. Here we study the seasonal prediction of meltdominated total inflow into the Bhakra Dam in Northern India based on statistical relationships with meteorological variables during the preceding winter. Total inflow into the Bhakra dam includes the Satluj River flow together with a flow diversion from its tributary, the Beas River. Both are tributaries of the Indus River that originate from the Western Himalayas, which is an under-studied region. Average measured winter snow volume at the upper elevation stations and corresponding lower elevation rainfall and temperature of the Satluj River basin were considered as empirical predictors. Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) were used to select the best subset of inputs from all the possible combinations of predictors for a multiple linear regression framework. To test for potential issues arising due to multi-collinearity of the predictor variables, cross-validated prediction skills of best subset were also compared with the prediction skills of Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR) techniques, which yielded broadly similar results. As a whole, the forecasts of the melt season at the end of winter and as the melt season commences were shown to have potential skill for guiding the development of stochastic optimization models to manage the trade-off between irrigation and hydropower releases versus flood control during the annual fill cycle of the Bhakra reservoir, a major energy and irrigation source in the region.
The time-lagged relationship between global flood occurrence and spatial-temporal climate data ar... more The time-lagged relationship between global flood occurrence and spatial-temporal climate data are explored using a graph based approach based upon the concept of reciprocity to generate cluster pairs of locations with similar pattern at any time lag. The overall goal of work is (1) to find the time-lagged relationship between extreme precipitation induced
A statistically and physically based framework is put forward that investigates the 10 relationsh... more A statistically and physically based framework is put forward that investigates the 10 relationship between Tropical Moisture Exports (TME), and extreme Precipitation and floods in the
Recent advances in paleoclimatology have revealed dramatic long-term hydroclimatic variations tha... more Recent advances in paleoclimatology have revealed dramatic long-term hydroclimatic variations that provide a context for limited historical records. A notable data set derived from a relatively dense network of paleoclimate proxy records in North America is the Living Blended Drought Atlas (LBDA): a gridded tree-ring-based reconstruction of summer Palmer Drought Severity Index. This index has been used to assess North American drought frequency, persistence, and spatial extent over the past two millennia. Here, we explore whether the LBDA can be used to reconstruct annual streamflow. Relative to streamflow reconstructions that use tree rings within the river basin of interest, the use of a gridded proxy poses a novel challenge. The gridded series have high spatial correlation, since they rely on tree rings over a common radius of influence. A novel algorithm for reconstructing streamflow using regularized canonical regression and inputs of local and global covariates is developed and applied over the Missouri River Basin, as a test case. Effectiveness in reconstruction is demonstrated with reconstructions showing periods where streamflow deficits may have been more severe than during recent droughts (e.g., the Civil War, Dust Bowl, and 1950s droughts). The maximum persistence of droughts and floods over the past 500 years far exceeds those observed in the instrumental record and periods of multidecadal variability in the 1500s and 1600s are detected. Challenges for an extension to a national streamflow reconstruction or applications using other gridded paleoclimate data sets such as adequate spatial coverage of streamflow and applicability of annual reconstructions are discussed.
Algae reduce and methylate arsenate, producing arsenite (As(III)) when the growth rates are high ... more Algae reduce and methylate arsenate, producing arsenite (As(III)) when the growth rates are high and dimethy-larsinic acid (DMA) when the growth rates are low. In lakes, this leads to high As(III) concentrations in the early stages of spring and fall blooms and high DMA concentrations in the summer. We hypothesize that under phosphorus (P)-limited conditions, which usually exist in the summer, algae take up phosphate (PO,) and, because of similar chemical characteristics, As(V) as well. Inside the cell, As(V) is reduced to As(III), methylated to monomethylar-sonic acid (MMA) and DMA, and then excreted. However, under non-P-limited conditions, which exist in the early stages of blooms, algae up-regulate their PO, transport system to take up excess P, a phenomenon known as luxury uptake. Since As(V) is taken up by the PO4 transport system, As(V) uptake also increases at this time. Within the cell, the reduction of As(V) to As(III) is fast, but methylation is slower, causing As(III) to build up in the cell and be excreted, which, in turn, causes an increase in extracellular As(III). This mechanism permits the synergistic (luxury uptake) and antagonistic (competition) effects of P04 on As(V) uptake and can therefore explain the seemingly contradictory results found in the literature. A mathematical model is constructed on the basis of existing established algal-nutrient interaction models and is used to simulate As transformation in two laboratory batch experiments. In addition to algal and P responses, the model can reasonably well reproduce the observed As(III) peak during the log growth phase and the more gradual appearance of DMA during the stationary phase. It has been >20 yr since Sanders and Windom (1980) pointed to a pattern in As transformation by algae. In their words, "Arsenic reduction takes place only when the phy-toplankton assemblage is in the log phase of growth, therefore the spring bloom [...] should contribute a large majority of the reduced arsenic species, with a smaller contribution from the smaller fall bloom." After the log phase, As reduction ceases, and the reduced As(III) is oxidized to As(V), often at comparable rates, leading to As(III) peaks in the spring and fall. Subsequently, Howard et al. (1982) observed the occurrence of methylated As, mostly DMA, during the
China has a large economic and demographic exposure to extreme events that is increasing rapidly ... more China has a large economic and demographic exposure to extreme events that is increasing rapidly due to its fast development, and climate change may further aggravate the situation. This paper investigates China's socioeconomic risk from extreme events under climate change over the next few decades with a focus on sub-national heterogeneity. The empirical relationships between socioeconomic damages and their determinants are identified using a hierarchical Bayesian approach, and are used to estimate future damages as well as associated uncertainty bounds given specified climate and development scenarios. Considering projected changes in exposure, we find that the southwest and central regions and Hainan Island of China are likely to have a larger percentage of population at risk, while most of the southwest and central regions could generally have higher economic losses. Finally, the analysis suggests that increasing income can significantly decrease the number of people affected by extremes.
Flood estimation and flood management have traditionally been the domain of hydrologists, water r... more Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics , such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We come to the following conclusions: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the
Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drough... more Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drought in this region is characterized by multi-decadal variability, as seen from one of the longest systematic records available in Asia from 1770-2015. This paper explores how the return period of the 2013-2015 drought varies over this historical period to provide a context for the changing climate and drought severity in the region. A nonstationary, multivariate, Bayesian copula model for drought severity and duration is developed and applied. Given the wetting trend over the last 50 years, the recent drought appears quite extreme, while such droughts were common in the 18th and 19th centuries.
Using a multicentury reconstruction of drought, we investigate how rare the 2012–2015 Cali-fornia... more Using a multicentury reconstruction of drought, we investigate how rare the 2012–2015 Cali-fornia drought is. A Bayesian approach to a nonstationary, bivariate probabilistic model, including the estimation of copula parameters is used to assess the time-varying return period of the current drought. Both the duration and severity of drought exhibit similar multicentury trends. The period from 800 to 1200 A.D. was perhaps more similar to the recent period than the period from 1200 to 1800 A.D. The median return period of the recent drought accounting for both duration and severity, varies from approximately 667– 2652 years, if the model parameters from the different time periods are considered. However, we find that the recent California drought is of unprecedented severity, especially given the relatively modest duration of the drought. The return period of the severity of the recent drought given its 4 year duration is estimated to be nearly 21,000 years.
[1] Recognizing that the frequency distribution of annual maximum floods at a given location may ... more [1] Recognizing that the frequency distribution of annual maximum floods at a given location may change over time in response to interannual and longer climate fluctuations, we compare two approaches for the estimation of flood quantiles conditional on selected ''climate indices'' that carry the signal of structured low-frequency climate variation, and influence the atmospheric mechanisms that modify local precipitation and flood potential. A parametric quantile regression approach and a semiparametric local likelihood approach are compared using synthetic data sets and for data from a streamflow gauging station in the western United States. Their relative utility in different settings for seasonal flood risk forecasting as well as for the assessment of long-term variation in flood potential is discussed.
Concerns about the potential effects of anthro-pogenic climate change have led to a closer examin... more Concerns about the potential effects of anthro-pogenic climate change have led to a closer examination of how climate varies in the long run, and how such variations may impact rainfall variations at daily to seasonal time scales. For South Florida in particular, the influences of the low-frequency climate phenomena, such as the El Nino Southern Oscillation (ENSO) and the Atlantic Multi-dec-adal Oscillation (AMO), have been identified with aggregate annual or seasonal rainfall variations. Since the combined effect of these variations is manifest as persistent multi-year variations in rainfall, the question of modeling these variations at the time and space scales relevant for use with the daily time step-driven hydrologic models in use by the South Florida Water Management District (SFWMD) has arisen. To address this problem, a general methodology for the hierarchical modeling of low-and high-frequency phenomenon at multiple rain gauge locations is developed and illustrated. The essential strategy is to use long-term proxies for regional climate to first develop stochastic scenarios for regional climate that include the low-frequency variations driving the regional rainfall process, and then to use these indicators to condition the concurrent simulation of daily rainfall at all rain gauges under consideration. A newly developed methodology, called Wavelet Autore-gressive Modeling (WARM), is used in the first step after suitable climate proxies for regional rainfall are identified. These proxies typically have data available for a century to four centuries so that long-term quasi-periodic climate modes of interest can be identified more reliably. Correlation analyses with seasonal rainfall in the region are used to identify the specific proxies considered as candidates for subsequent conditioning of daily rainfall attributes using a Non-homogeneous hidden Markov model (NHMM). The combined strategy is illustrated for the May–June–July (MJJ) season. The details of the modeling methods and results for the MJJ season are presented in this study.
Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drough... more Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drought in this region is characterized by multi-decadal variability, as seen from one of the longest systematic records available in Asia from 1770-2015. This paper explores how the return period of the 2013-2015 drought varies over this historical period to provide a context for the changing climate and drought severity in the region. A nonstationary, multivariate, Bayesian copula model for drought severity and duration is developed and applied. Given the wetting trend over the last 50 years, the recent drought appears quite extreme, while such droughts were common in the 18th and 19th centuries.
Tropical moisture exports (TMEs) may play an important role in extreme precipitation. An analysis... more Tropical moisture exports (TMEs) may play an important role in extreme precipitation. An analysis of the spatiotemporal structure of precipitation associated with TMEs for the eastern United States at seasonal and daily time scales is presented. TME-based precipitation is characterized based on the change in specific humidity along TME tracks delineated in a Lagrangian analysis of the ERA-Interim dataset. The empirical orthogonal functions (EOFs) of seasonal TME-based precipitation are analyzed separately for each season to identify the dominant modes of interannual variability. Loading patterns for the first EOF show a distinct seasonal cycle in the core region of TME-based precipitation across the eastern United States, while the second EOF describes a northwest–southeast oscillation in the center of TME-induced precipitation occurrence. The EOFs for TMEs are compared against EOFs of gauged flood count data, which exhibit similar spatial structures. Correlations between TME EOFs, geopotential heights, and sea surface temperatures suggest a strong connection between TME-based precipitation, the Pacific–North American (PNA) pattern, Pacific decadal oscillation (PDO), and the Intra-Americas Sea patterns for much of the calendar year. Daily TME-based and total precipitation is projected onto the leading seasonal EOFs to examine the characteristics of upper-quantile daily events. The daily analysis suggests that the PNA can potentially provide information regarding heavy TME-based precipitation at a lead time of 1–10 days or more in most seasons and total precipitation in the winter. The potential for subseasonal, seasonal, and decadal forecasts or conditional simulations of precipitation in the study region is discussed.
Warm, moist, and longitudinally confined tropical air masses are being linked to some of the most... more Warm, moist, and longitudinally confined tropical air masses are being linked to some of the most extreme precipitation and flooding events in the midlatitudes. The interannual frequency and intensity of such atmospheric rivers (ARs), or tropical moisture exports (TMEs), are connected to the risk of extreme precipitation events in areas where moisture convergence occurs. This study presents a nonstation-ary, regional frequency analysis of precipitation extremes in Northern California that is conditioned on the interannual variability of TMEs entering the region. Parameters of a multisite peaks-over-threshold model are allowed to vary conditional on the integrated moisture delivery from TMEs over the area. Parameters are also related to time-invariant, local characteristics to facilitate regionalization to ungaged sites. The model is developed and calibrated in a hierarchical Bayesian framework to support partial pooling and enhance regionalization skill. The model is cross validated along with two alternative, increasingly parsimonious formulations to assess the additional skill provided by the covariates. Climate diagnostics are also used to better understand the instances where TMEs fail to explain variations in rainfall extremes to provide a path forward for further model improvement. The modeling structure is designed to link seasonal forecasting and long-term projections of TMEs directly to regional models of extremes used for risk estimation. Results suggest that the inclusion of TME-based information greatly improves the characterization of extremes, particularly for their frequency of occurrence. Diagnostics indicate that the model could be further improved by considering an index for frontal systems as an additional covariate.
The article advances the hypothesis that the seasonal and inter-annual variability of rainfall is... more The article advances the hypothesis that the seasonal and inter-annual variability of rainfall is a significant and measurable factor in the economic development of nations. An analysis of global datasets reveals a statistically significant relationship between greater rainfall variability and lower per capita GDP. Having established this correlation, we construct a water resources development index that highlights areas that have the greatest need for storage infrastructure to mitigate the impacts of rainfall variability on water availability for food and basic livelihood. The countries with the most critical infrastructure needs according to this metric are among the poorest in the world, and the majority of them are located in Africa. The importance of securing water availability in these nations increases every day in light of current population growth, economic development, and climate change projections.
A new multilevel, hierarchical Bayesian model is developed to simultaneously identify clusters of... more A new multilevel, hierarchical Bayesian model is developed to simultaneously identify clusters of stations with similar temporal patterns, the trend associated with each cluster and for the individual stations within each cluster. An application to the annual maximum daily precipitation in the United States for a common 70 year (1941–2010) period across the HADEX2 sites is presented. The model identifies statistically homogeneous regions, spatially clustering the data into groups according to the intensity and the trend. Partial pooling of model parameters for each group is considered. Spatially consistent trends are detected in the Midwest and Northeast U.S., at the cluster and at the station level. The new approach can dramatically improve trend identification for precipitation extremes; e.g., all 14 stations in the Midwest report a significant trend as opposed to only 4 stations based on single site analysis. The method is generally applicable for improving trend identification over a heterogeneous region.
Key Points: Relationship between groundwater levels and a demand sensitive drought index is exa... more Key Points: Relationship between groundwater levels and a demand sensitive drought index is examined Depletion of groundwater continues even when agricultural demands are reduced Storage of winter precipitation critical to supplying agricultural water demands Abstract Agricultural, industrial and urban water use in the Conterminous United States (CONUS) is highly dependent on groundwater that is largely drawn from non-surficial wells (>30 m). We use a Demand Sensitive Drought Index to examine the impacts of agricultural water needs, driven by low precipitation, high agricultural water demand, or a combination of both, on the temporal variability of depth to groundwater across the CONUS. We characterize the relationship between changes in groundwater levels, agricultural water deficits relative to precipitation during the growing season and winter precipitation. We find that declines in groundwater levels in the High Plains aquifer and around the Mississippi River Valley are driven by groundwater withdrawals used to supplement agricultural water demands. Reductions in agricultural water demands for crops do not, however, lead to immediate recovery of groundwater levels due to the demand for groundwater in other sectors in regions such as Utah, Maryland, and Texas.
While secular changes in regional sea levels and their implications for coastal zone management h... more While secular changes in regional sea levels and their implications for coastal zone management have been studied extensively, less attention is being paid to natural fluctuations in sea levels, whose interaction with a higher mean level could have significant impacts on low-lying areas, such as wetlands. Here, the long record of sea level at Key West, FL is studied in terms of both the secular trend and the multi-scale sea level variations. This analysis is then used to explore implications for the Ever-glades National Park (ENP), which is recognized internationally for its ecological significance, and is the site of the largest wetland restoration project in the world. Very shallow topographic gradients (3–6 cm per km) make the region susceptible to small changes in sea level. Observations of surface water levels from a monitoring network within ENP exhibit both the long-term trends and the interannual-to-(multi)decadal variability that are observed in the Key West record. Water levels recorded at four long-term monitoring stations within ENP exhibit increasing trends approximately equal to or larger than the long-term trend at Key West. Time-and frequency-domain analyses highlight the potential influence of climate mechanisms, such as the El Niño/Southern Oscillation and the North Atlantic Oscillation (NAO), on Key West sea levels and marsh water levels, and the potential modulation of their influence by the background state of the North Atlantic Sea Surface Temperatures. In particular, the Key West sea levels are found to be positively correlated with the NAO index, while the two series exhibit high spectral power during the transition to a cold Atlantic Multidecadal Oscillation (AMO). The correlation between the Key West sea levels and the NINO3 Index reverses its sign in coincidence with a reversal of the AMO phase. Water levels in ENP are also influenced by precipitation and freshwater releases from the northern boundary of the Park. The analysis of both climate variability and climate change in such wetlands is needed to inform management practices in coastal wetland zones around the world. Keywords Sea level fluctuations Á Key West Á ENSO Á NAO Á AMO Á Everglades National Park
Water Resources Research, 2017
Storage and controlled distribution of water have been key elements of a human strategy to overco... more Storage and controlled distribution of water have been key elements of a human strategy to overcome the space and time variability of water, which have been marked by catastrophic droughts and floods throughout the course of civilization. In the United States, the peak of dam building occurred in the mid‐20th century with knowledge limited to the scientific understanding and hydrologic records of the time. Ecological impacts were considered differently than current legislative and regulatory controls would potentially dictate. Additionally, future costs such as maintenance or removal beyond the economic design life were not fully considered. The converging risks associated with aging water storage infrastructure and uncertainty in climate in addition to the continuing need for water storage, flood protection, and hydropower result in a pressing need to address the state of dam infrastructure across the nation. Decisions regarding the future of dams in the United States may, in turn,...
Hydrology and Earth System Sciences, 2013
Snowmelt dominated streamflow of the Western Himalayan Rivers is an important water resource duri... more Snowmelt dominated streamflow of the Western Himalayan Rivers is an important water resource during the dry pre-monsoon spring months to meet the irrigation and hydropower needs in Northern India. Here we study the seasonal prediction of meltdominated total inflow into the Bhakra Dam in Northern India based on statistical relationships with meteorological variables during the preceding winter. Total inflow into the Bhakra dam includes the Satluj River flow together with a flow diversion from its tributary, the Beas River. Both are tributaries of the Indus River that originate from the Western Himalayas, which is an under-studied region. Average measured winter snow volume at the upper elevation stations and corresponding lower elevation rainfall and temperature of the Satluj River basin were considered as empirical predictors. Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) were used to select the best subset of inputs from all the possible combinations of predictors for a multiple linear regression framework. To test for potential issues arising due to multi-collinearity of the predictor variables, cross-validated prediction skills of best subset were also compared with the prediction skills of Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR) techniques, which yielded broadly similar results. As a whole, the forecasts of the melt season at the end of winter and as the melt season commences were shown to have potential skill for guiding the development of stochastic optimization models to manage the trade-off between irrigation and hydropower releases versus flood control during the annual fill cycle of the Bhakra reservoir, a major energy and irrigation source in the region.
The time-lagged relationship between global flood occurrence and spatial-temporal climate data ar... more The time-lagged relationship between global flood occurrence and spatial-temporal climate data are explored using a graph based approach based upon the concept of reciprocity to generate cluster pairs of locations with similar pattern at any time lag. The overall goal of work is (1) to find the time-lagged relationship between extreme precipitation induced
A statistically and physically based framework is put forward that investigates the 10 relationsh... more A statistically and physically based framework is put forward that investigates the 10 relationship between Tropical Moisture Exports (TME), and extreme Precipitation and floods in the
Recent advances in paleoclimatology have revealed dramatic long-term hydroclimatic variations tha... more Recent advances in paleoclimatology have revealed dramatic long-term hydroclimatic variations that provide a context for limited historical records. A notable data set derived from a relatively dense network of paleoclimate proxy records in North America is the Living Blended Drought Atlas (LBDA): a gridded tree-ring-based reconstruction of summer Palmer Drought Severity Index. This index has been used to assess North American drought frequency, persistence, and spatial extent over the past two millennia. Here, we explore whether the LBDA can be used to reconstruct annual streamflow. Relative to streamflow reconstructions that use tree rings within the river basin of interest, the use of a gridded proxy poses a novel challenge. The gridded series have high spatial correlation, since they rely on tree rings over a common radius of influence. A novel algorithm for reconstructing streamflow using regularized canonical regression and inputs of local and global covariates is developed and applied over the Missouri River Basin, as a test case. Effectiveness in reconstruction is demonstrated with reconstructions showing periods where streamflow deficits may have been more severe than during recent droughts (e.g., the Civil War, Dust Bowl, and 1950s droughts). The maximum persistence of droughts and floods over the past 500 years far exceeds those observed in the instrumental record and periods of multidecadal variability in the 1500s and 1600s are detected. Challenges for an extension to a national streamflow reconstruction or applications using other gridded paleoclimate data sets such as adequate spatial coverage of streamflow and applicability of annual reconstructions are discussed.
Algae reduce and methylate arsenate, producing arsenite (As(III)) when the growth rates are high ... more Algae reduce and methylate arsenate, producing arsenite (As(III)) when the growth rates are high and dimethy-larsinic acid (DMA) when the growth rates are low. In lakes, this leads to high As(III) concentrations in the early stages of spring and fall blooms and high DMA concentrations in the summer. We hypothesize that under phosphorus (P)-limited conditions, which usually exist in the summer, algae take up phosphate (PO,) and, because of similar chemical characteristics, As(V) as well. Inside the cell, As(V) is reduced to As(III), methylated to monomethylar-sonic acid (MMA) and DMA, and then excreted. However, under non-P-limited conditions, which exist in the early stages of blooms, algae up-regulate their PO, transport system to take up excess P, a phenomenon known as luxury uptake. Since As(V) is taken up by the PO4 transport system, As(V) uptake also increases at this time. Within the cell, the reduction of As(V) to As(III) is fast, but methylation is slower, causing As(III) to build up in the cell and be excreted, which, in turn, causes an increase in extracellular As(III). This mechanism permits the synergistic (luxury uptake) and antagonistic (competition) effects of P04 on As(V) uptake and can therefore explain the seemingly contradictory results found in the literature. A mathematical model is constructed on the basis of existing established algal-nutrient interaction models and is used to simulate As transformation in two laboratory batch experiments. In addition to algal and P responses, the model can reasonably well reproduce the observed As(III) peak during the log growth phase and the more gradual appearance of DMA during the stationary phase. It has been >20 yr since Sanders and Windom (1980) pointed to a pattern in As transformation by algae. In their words, "Arsenic reduction takes place only when the phy-toplankton assemblage is in the log phase of growth, therefore the spring bloom [...] should contribute a large majority of the reduced arsenic species, with a smaller contribution from the smaller fall bloom." After the log phase, As reduction ceases, and the reduced As(III) is oxidized to As(V), often at comparable rates, leading to As(III) peaks in the spring and fall. Subsequently, Howard et al. (1982) observed the occurrence of methylated As, mostly DMA, during the
China has a large economic and demographic exposure to extreme events that is increasing rapidly ... more China has a large economic and demographic exposure to extreme events that is increasing rapidly due to its fast development, and climate change may further aggravate the situation. This paper investigates China's socioeconomic risk from extreme events under climate change over the next few decades with a focus on sub-national heterogeneity. The empirical relationships between socioeconomic damages and their determinants are identified using a hierarchical Bayesian approach, and are used to estimate future damages as well as associated uncertainty bounds given specified climate and development scenarios. Considering projected changes in exposure, we find that the southwest and central regions and Hainan Island of China are likely to have a larger percentage of population at risk, while most of the southwest and central regions could generally have higher economic losses. Finally, the analysis suggests that increasing income can significantly decrease the number of people affected by extremes.
Flood estimation and flood management have traditionally been the domain of hydrologists, water r... more Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics , such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We come to the following conclusions: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the
Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drough... more Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drought in this region is characterized by multi-decadal variability, as seen from one of the longest systematic records available in Asia from 1770-2015. This paper explores how the return period of the 2013-2015 drought varies over this historical period to provide a context for the changing climate and drought severity in the region. A nonstationary, multivariate, Bayesian copula model for drought severity and duration is developed and applied. Given the wetting trend over the last 50 years, the recent drought appears quite extreme, while such droughts were common in the 18th and 19th centuries.
Using a multicentury reconstruction of drought, we investigate how rare the 2012–2015 Cali-fornia... more Using a multicentury reconstruction of drought, we investigate how rare the 2012–2015 Cali-fornia drought is. A Bayesian approach to a nonstationary, bivariate probabilistic model, including the estimation of copula parameters is used to assess the time-varying return period of the current drought. Both the duration and severity of drought exhibit similar multicentury trends. The period from 800 to 1200 A.D. was perhaps more similar to the recent period than the period from 1200 to 1800 A.D. The median return period of the recent drought accounting for both duration and severity, varies from approximately 667– 2652 years, if the model parameters from the different time periods are considered. However, we find that the recent California drought is of unprecedented severity, especially given the relatively modest duration of the drought. The return period of the severity of the recent drought given its 4 year duration is estimated to be nearly 21,000 years.
[1] Recognizing that the frequency distribution of annual maximum floods at a given location may ... more [1] Recognizing that the frequency distribution of annual maximum floods at a given location may change over time in response to interannual and longer climate fluctuations, we compare two approaches for the estimation of flood quantiles conditional on selected ''climate indices'' that carry the signal of structured low-frequency climate variation, and influence the atmospheric mechanisms that modify local precipitation and flood potential. A parametric quantile regression approach and a semiparametric local likelihood approach are compared using synthetic data sets and for data from a streamflow gauging station in the western United States. Their relative utility in different settings for seasonal flood risk forecasting as well as for the assessment of long-term variation in flood potential is discussed.
Concerns about the potential effects of anthro-pogenic climate change have led to a closer examin... more Concerns about the potential effects of anthro-pogenic climate change have led to a closer examination of how climate varies in the long run, and how such variations may impact rainfall variations at daily to seasonal time scales. For South Florida in particular, the influences of the low-frequency climate phenomena, such as the El Nino Southern Oscillation (ENSO) and the Atlantic Multi-dec-adal Oscillation (AMO), have been identified with aggregate annual or seasonal rainfall variations. Since the combined effect of these variations is manifest as persistent multi-year variations in rainfall, the question of modeling these variations at the time and space scales relevant for use with the daily time step-driven hydrologic models in use by the South Florida Water Management District (SFWMD) has arisen. To address this problem, a general methodology for the hierarchical modeling of low-and high-frequency phenomenon at multiple rain gauge locations is developed and illustrated. The essential strategy is to use long-term proxies for regional climate to first develop stochastic scenarios for regional climate that include the low-frequency variations driving the regional rainfall process, and then to use these indicators to condition the concurrent simulation of daily rainfall at all rain gauges under consideration. A newly developed methodology, called Wavelet Autore-gressive Modeling (WARM), is used in the first step after suitable climate proxies for regional rainfall are identified. These proxies typically have data available for a century to four centuries so that long-term quasi-periodic climate modes of interest can be identified more reliably. Correlation analyses with seasonal rainfall in the region are used to identify the specific proxies considered as candidates for subsequent conditioning of daily rainfall attributes using a Non-homogeneous hidden Markov model (NHMM). The combined strategy is illustrated for the May–June–July (MJJ) season. The details of the modeling methods and results for the MJJ season are presented in this study.
Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drough... more Recently, the Korean peninsula faced severe drought for more than three years (2013-2015). Drought in this region is characterized by multi-decadal variability, as seen from one of the longest systematic records available in Asia from 1770-2015. This paper explores how the return period of the 2013-2015 drought varies over this historical period to provide a context for the changing climate and drought severity in the region. A nonstationary, multivariate, Bayesian copula model for drought severity and duration is developed and applied. Given the wetting trend over the last 50 years, the recent drought appears quite extreme, while such droughts were common in the 18th and 19th centuries.
Tropical moisture exports (TMEs) may play an important role in extreme precipitation. An analysis... more Tropical moisture exports (TMEs) may play an important role in extreme precipitation. An analysis of the spatiotemporal structure of precipitation associated with TMEs for the eastern United States at seasonal and daily time scales is presented. TME-based precipitation is characterized based on the change in specific humidity along TME tracks delineated in a Lagrangian analysis of the ERA-Interim dataset. The empirical orthogonal functions (EOFs) of seasonal TME-based precipitation are analyzed separately for each season to identify the dominant modes of interannual variability. Loading patterns for the first EOF show a distinct seasonal cycle in the core region of TME-based precipitation across the eastern United States, while the second EOF describes a northwest–southeast oscillation in the center of TME-induced precipitation occurrence. The EOFs for TMEs are compared against EOFs of gauged flood count data, which exhibit similar spatial structures. Correlations between TME EOFs, geopotential heights, and sea surface temperatures suggest a strong connection between TME-based precipitation, the Pacific–North American (PNA) pattern, Pacific decadal oscillation (PDO), and the Intra-Americas Sea patterns for much of the calendar year. Daily TME-based and total precipitation is projected onto the leading seasonal EOFs to examine the characteristics of upper-quantile daily events. The daily analysis suggests that the PNA can potentially provide information regarding heavy TME-based precipitation at a lead time of 1–10 days or more in most seasons and total precipitation in the winter. The potential for subseasonal, seasonal, and decadal forecasts or conditional simulations of precipitation in the study region is discussed.
Warm, moist, and longitudinally confined tropical air masses are being linked to some of the most... more Warm, moist, and longitudinally confined tropical air masses are being linked to some of the most extreme precipitation and flooding events in the midlatitudes. The interannual frequency and intensity of such atmospheric rivers (ARs), or tropical moisture exports (TMEs), are connected to the risk of extreme precipitation events in areas where moisture convergence occurs. This study presents a nonstation-ary, regional frequency analysis of precipitation extremes in Northern California that is conditioned on the interannual variability of TMEs entering the region. Parameters of a multisite peaks-over-threshold model are allowed to vary conditional on the integrated moisture delivery from TMEs over the area. Parameters are also related to time-invariant, local characteristics to facilitate regionalization to ungaged sites. The model is developed and calibrated in a hierarchical Bayesian framework to support partial pooling and enhance regionalization skill. The model is cross validated along with two alternative, increasingly parsimonious formulations to assess the additional skill provided by the covariates. Climate diagnostics are also used to better understand the instances where TMEs fail to explain variations in rainfall extremes to provide a path forward for further model improvement. The modeling structure is designed to link seasonal forecasting and long-term projections of TMEs directly to regional models of extremes used for risk estimation. Results suggest that the inclusion of TME-based information greatly improves the characterization of extremes, particularly for their frequency of occurrence. Diagnostics indicate that the model could be further improved by considering an index for frontal systems as an additional covariate.
The article advances the hypothesis that the seasonal and inter-annual variability of rainfall is... more The article advances the hypothesis that the seasonal and inter-annual variability of rainfall is a significant and measurable factor in the economic development of nations. An analysis of global datasets reveals a statistically significant relationship between greater rainfall variability and lower per capita GDP. Having established this correlation, we construct a water resources development index that highlights areas that have the greatest need for storage infrastructure to mitigate the impacts of rainfall variability on water availability for food and basic livelihood. The countries with the most critical infrastructure needs according to this metric are among the poorest in the world, and the majority of them are located in Africa. The importance of securing water availability in these nations increases every day in light of current population growth, economic development, and climate change projections.
A new multilevel, hierarchical Bayesian model is developed to simultaneously identify clusters of... more A new multilevel, hierarchical Bayesian model is developed to simultaneously identify clusters of stations with similar temporal patterns, the trend associated with each cluster and for the individual stations within each cluster. An application to the annual maximum daily precipitation in the United States for a common 70 year (1941–2010) period across the HADEX2 sites is presented. The model identifies statistically homogeneous regions, spatially clustering the data into groups according to the intensity and the trend. Partial pooling of model parameters for each group is considered. Spatially consistent trends are detected in the Midwest and Northeast U.S., at the cluster and at the station level. The new approach can dramatically improve trend identification for precipitation extremes; e.g., all 14 stations in the Midwest report a significant trend as opposed to only 4 stations based on single site analysis. The method is generally applicable for improving trend identification over a heterogeneous region.
Key Points: Relationship between groundwater levels and a demand sensitive drought index is exa... more Key Points: Relationship between groundwater levels and a demand sensitive drought index is examined Depletion of groundwater continues even when agricultural demands are reduced Storage of winter precipitation critical to supplying agricultural water demands Abstract Agricultural, industrial and urban water use in the Conterminous United States (CONUS) is highly dependent on groundwater that is largely drawn from non-surficial wells (>30 m). We use a Demand Sensitive Drought Index to examine the impacts of agricultural water needs, driven by low precipitation, high agricultural water demand, or a combination of both, on the temporal variability of depth to groundwater across the CONUS. We characterize the relationship between changes in groundwater levels, agricultural water deficits relative to precipitation during the growing season and winter precipitation. We find that declines in groundwater levels in the High Plains aquifer and around the Mississippi River Valley are driven by groundwater withdrawals used to supplement agricultural water demands. Reductions in agricultural water demands for crops do not, however, lead to immediate recovery of groundwater levels due to the demand for groundwater in other sectors in regions such as Utah, Maryland, and Texas.
While secular changes in regional sea levels and their implications for coastal zone management h... more While secular changes in regional sea levels and their implications for coastal zone management have been studied extensively, less attention is being paid to natural fluctuations in sea levels, whose interaction with a higher mean level could have significant impacts on low-lying areas, such as wetlands. Here, the long record of sea level at Key West, FL is studied in terms of both the secular trend and the multi-scale sea level variations. This analysis is then used to explore implications for the Ever-glades National Park (ENP), which is recognized internationally for its ecological significance, and is the site of the largest wetland restoration project in the world. Very shallow topographic gradients (3–6 cm per km) make the region susceptible to small changes in sea level. Observations of surface water levels from a monitoring network within ENP exhibit both the long-term trends and the interannual-to-(multi)decadal variability that are observed in the Key West record. Water levels recorded at four long-term monitoring stations within ENP exhibit increasing trends approximately equal to or larger than the long-term trend at Key West. Time-and frequency-domain analyses highlight the potential influence of climate mechanisms, such as the El Niño/Southern Oscillation and the North Atlantic Oscillation (NAO), on Key West sea levels and marsh water levels, and the potential modulation of their influence by the background state of the North Atlantic Sea Surface Temperatures. In particular, the Key West sea levels are found to be positively correlated with the NAO index, while the two series exhibit high spectral power during the transition to a cold Atlantic Multidecadal Oscillation (AMO). The correlation between the Key West sea levels and the NINO3 Index reverses its sign in coincidence with a reversal of the AMO phase. Water levels in ENP are also influenced by precipitation and freshwater releases from the northern boundary of the Park. The analysis of both climate variability and climate change in such wetlands is needed to inform management practices in coastal wetland zones around the world. Keywords Sea level fluctuations Á Key West Á ENSO Á NAO Á AMO Á Everglades National Park
Water security in the U.S. is increasingly threatened. Many utilities are facing major supply iss... more Water security in the U.S. is increasingly threatened. Many utilities are facing major supply issues (water quantity and/or water quality), aging infrastructure, and major funding shortfalls. In the last decade, prolonged droughts and floods from Texas to California to Colorado to the Mississippi to the North--East have stressed our water storage and flood control infrastructure, and led to considerable environmental, social and economic impacts. Groundwater depletion continues unabated in much of the country. The pollution of water bodies and their ecosystem impacts are increasing costs for the treatment and supply of urban water. Aging pipes and urban water infrastructure lead to increasing rates of main breaks and the potential for contamination of treated water supplies. On top of all this, water revenues have been declining due to decreasing per capita demands and political pressure in many areas. Historically, the federal government was a major investor in public works and water infrastructure, securing the health of the citizenry. Today, local communities and states struggle with the increasing costs of providing water, and the maintenance of these aging systems. The tragedy of Flint, Michigan reflects the confluence of these economic and physical factors. Yet, threats to water supply and quality violations may be set to repeat in different ways across the nation. A fragmentation of responsibility for addressing floods, droughts, reservoir operation, ecosystem demand, water allocation, and water and wastewater provision, across a myriad local, state and federal agencies, whose mandate relates to water, contributes to the challenge of developing water solutions locally or nationally. Water is seen as a local issue, until it is a regional, national, or global concern.