@article{TaffarelloSrinivasanSamprognaMohoretal.2018,
author = {Taffarello, Denise and Srinivasan, Raghavan and Samprogna Mohor, Guilherme and Bittencourt Guimaraes, Joao Luis and Calijuri, Maria do Carmo and Mendiondo, Eduardo Mario},
title = {Modeling freshwater quality scenarios with ecosystem-based adaptation in the headwaters of the Cantareira system, Brazil},
series = {Hydrology and earth system sciences : HESS},
volume = {22},
journal = {Hydrology and earth system sciences : HESS},
number = {9},
publisher = {Copernicus},
address = {G{\"o}ttingen},
issn = {1027-5606},
doi = {10.5194/hess-22-4699-2018},
pages = {4699 -- 4723},
year = {2018},
abstract = {Although hydrologic models provide hypothesis testing of complex dynamics occurring at catchments, fresh-water quality modeling is still incipient at many subtropical headwaters. In Brazil, a few modeling studies assess freshwater nutrients, limiting policies on hydrologic ecosystem services. This paper aims to compare freshwater quality scenarios under different land-use and land-cover (LULC) change, one of them related to ecosystem-based adaptation (EbA), in Brazilian headwaters. Using the spatially semi-distributed Soil and Water Assessment Tool (SWAT) model, nitrate, total phosphorous (TP) and sediment were modeled in catchments ranging from 7.2 to 1037 km(2). These head-waters were eligible areas of the Brazilian payment for ecosystem services (PES) projects in the Cantareira water supply system, which had supplied water to 9 million people in the Sao Paulo metropolitan region (SPMR). We considered SWAT modeling of three LULC scenarios: (i) recent past scenario (S1), with historical LULC in 1990; (ii) current land-use scenario (S2), with LULC for the period 2010-2015 with field validation; and (iii) future land-use scenario with PES (S2 + EbA). This latter scenario proposed forest cover restoration through EbA following the river basin plan by 2035. These three LULC scenarios were tested with a selected record of rainfall and evapotranspiration observed in 2006-2014, with the occurrence of extreme droughts. To assess hydrologic services, we proposed the hydrologic service index (HSI), as a new composite metric comparing water pollution levels (WPL) for reference catchments, related to the grey water footprint (greyWF) and water yield. On the one hand, water quality simulations allowed for the regionalization of greyWF at spatial scales under LULC scenarios. According to the critical threshold, HSI identified areas as less or more sustainable catchments. On the other hand, conservation practices simulated through the S2 + EbA scenario envisaged not only additional and viable best management practices (BMP), but also preventive decision-making at the headwaters of water supply systems.},
language = {en}
}
@misc{TaffarelloSrinivasanSamprognaMohoretal.2018,
author = {Taffarello, Denise and Srinivasan, Raghavan and Samprogna Mohor, Guilherme and Guimar{\~a}es, Jo{\~a}o Luis Bittencourt and Calijuri, Maria do Carmo and Mendiondo, Eduardo Mario},
title = {Modeling freshwater quality scenarios with ecosystem-basedadaptation in the headwaters of the Cantareira system, Brazil},
series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
number = {935},
issn = {1866-8372},
doi = {10.25932/publishup-45925},
url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459253},
pages = {4699 -- 4723},
year = {2018},
abstract = {Although hydrologic models provide hypothesis testing of complex dynamics occurring at catchments, fresh-water quality modeling is still incipient at many subtropical headwaters. In Brazil, a few modeling studies assess freshwater nutrients, limiting policies on hydrologic ecosystem services. This paper aims to compare freshwater quality scenarios under different land-use and land-cover (LULC) change, one of them related to ecosystem-based adaptation (EbA), in Brazilian headwaters. Using the spatially semi-distributed Soil and Water Assessment Tool (SWAT) model, nitrate, total phosphorous (TP) and sediment were modeled in catchments ranging from 7.2 to 1037 km(2). These head-waters were eligible areas of the Brazilian payment for ecosystem services (PES) projects in the Cantareira water supply system, which had supplied water to 9 million people in the Sao Paulo metropolitan region (SPMR). We considered SWAT modeling of three LULC scenarios: (i) recent past scenario (S1), with historical LULC in 1990; (ii) current land-use scenario (S2), with LULC for the period 2010-2015 with field validation; and (iii) future land-use scenario with PES (S2 + EbA). This latter scenario proposed forest cover restoration through EbA following the river basin plan by 2035. These three LULC scenarios were tested with a selected record of rainfall and evapotranspiration observed in 2006-2014, with the occurrence of extreme droughts. To assess hydrologic services, we proposed the hydrologic service index (HSI), as a new composite metric comparing water pollution levels (WPL) for reference catchments, related to the grey water footprint (greyWF) and water yield. On the one hand, water quality simulations allowed for the regionalization of greyWF at spatial scales under LULC scenarios. According to the critical threshold, HSI identified areas as less or more sustainable catchments. On the other hand, conservation practices simulated through the S2 + EbA scenario envisaged not only additional and viable best management practices (BMP), but also preventive decision-making at the headwaters of water supply systems.},
language = {en}
}
@article{GuzmanSamprognaMohorMendiondo2020,
author = {Guzman, Diego A. and Samprogna Mohor, Guilherme and Mendiondo, Eduardo Mario},
title = {Multi-year index-based insurance for adapting Water Utility Companies to hydrological drought},
series = {Water},
volume = {12},
journal = {Water},
number = {11},
publisher = {MDPI},
address = {Basel},
issn = {2073-4441},
doi = {10.3390/w12112954},
pages = {22},
year = {2020},
abstract = {The sustainability of water utility companies is threatened by non-stationary drivers, such as climate and anthropogenic changes. To cope with potential economic losses, instruments such as insurance are useful for planning scenarios and mitigating impacts, but data limitations and risk uncertainties affect premium estimation and, consequently, business sustainability. This research estimated the possible economic impacts of business interruption to the Sao Paulo Water Utility Company derived from hydrological drought and how this could be mitigated with an insurance scheme. Multi-year insurance (MYI) was proposed through a set of "change" drivers: the climate driver, through forcing the water evaluation and planning system (WEAP) hydrological tool; the anthropogenic driver, through water demand projections; and the economic driver, associated with recent water price policies adopted by the utility company during water scarcity periods. In our study case, the evaluated indices showed that MYI contracts that cover only longer droughts, regardless of the magnitude, offer better financial performance than contracts that cover all events (in terms of drought duration). Moreover, through MYI contracts, we demonstrate solvency for the insurance fund in the long term and an annual average actuarially fair premium close to the total expected revenue reduction.},
language = {en}
}
@article{SamprognaMohorHudsonThieken2020,
author = {Samprogna Mohor, Guilherme and Hudson, Paul and Thieken, Annegret},
title = {A comparison of factors driving flood losses in households affected by different flood types},
series = {Water resources research},
volume = {56},
journal = {Water resources research},
number = {4},
publisher = {American Geophysical Union},
address = {Washington},
issn = {0043-1397},
doi = {10.1029/2019WR025943},
pages = {20},
year = {2020},
abstract = {Flood loss data collection and modeling are not standardized, and previous work has indicated that losses from different flood types (e.g., riverine and groundwater) may follow different driving forces. However, different flood types may occur within a single flood event, which is known as a compound flood event. Therefore, we aimed to identify statistical similarities between loss-driving factors across flood types and test whether the corresponding losses should be modeled separately. In this study, we used empirical data from 4,418 respondents from four survey campaigns studying households in Germany that experienced flooding. These surveys sought to investigate several features of the impact process (hazard, socioeconomic, preparedness, and building characteristics, as well as flood type). While the level of most of these features differed across flood type subsamples (e.g., degree of preparedness), they did so in a nonregular pattern. A variable selection process indicates that besides hazard and building characteristics, information on property-level preparedness was also selected as a relevant predictor of the loss ratio. These variables represent information, which is rarely adopted in loss modeling. Models shall be refined with further data collection and other statistical methods. To save costs, data collection efforts should be steered toward the most relevant predictors to enhance data availability and increase the statistical power of results. Understanding that losses from different flood types are driven by different factors is a crucial step toward targeted data collection and model development and will finally clarify conditions that allow us to transfer loss models in space and time.
Key Points
Survey data of flood-affected households show different concurrent flood types, undermining the use of a single-flood-type loss model Thirteen variables addressing flood hazard, the building, and property level preparedness are significant predictors of the building loss ratio Flood type-specific models show varying significance across the predictor variables, indicating a hindrance to model transferability},
language = {en}
}
@article{SamprognaMohorThiekenKorup2021,
author = {Samprogna Mohor, Guilherme and Thieken, Annegret and Korup, Oliver},
title = {Residential flood loss estimated from Bayesian multilevel models},
series = {Natural Hazards and Earth System Sciences},
volume = {21},
journal = {Natural Hazards and Earth System Sciences},
publisher = {European Geophysical Society},
address = {Katlenburg-Lindau},
issn = {2195-9269},
doi = {10.5194/nhess-21-1599-2021},
pages = {1599 -- 1614},
year = {2021},
abstract = {Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.},
language = {en}
}
@misc{SamprognaMohorThiekenKorup2021,
author = {Samprogna Mohor, Guilherme and Thieken, Annegret and Korup, Oliver},
title = {Residential flood loss estimated from Bayesian multilevel models},
series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
issn = {1866-8372},
doi = {10.25932/publishup-51774},
url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517743},
pages = {1599 -- 1614},
year = {2021},
abstract = {Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.},
language = {en}
}
@techreport{BerghaeuserSchoppaUlrichetal.2021,
author = {Bergh{\"a}user, Lisa and Schoppa, Lukas and Ulrich, Jana and Dillenardt, Lisa and Jurado, Oscar E. and Passow, Christian and Samprogna Mohor, Guilherme and Seleem, Omar and Petrow, Theresia and Thieken, Annegret},
title = {Starkregen in Berlin},
doi = {10.25932/publishup-50056},
url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-500560},
pages = {44},
year = {2021},
abstract = {In den Sommern der Jahre 2017 und 2019 kam es in Berlin an mehreren Orten zu {\"U}berschwemmungen in Folge von Starkregenereignissen. In beiden Jahren f{\"u}hrte dies zu erheblichen Beeintr{\"a}chtigungen im Alltag der Berliner:innen sowie zu hohen Sachsch{\"a}den. Eine interdisziplin{\"a}re Taskforce des DFG-Graduiertenkollegs NatRiskChange untersuchte (1) die meteorologischen Eigenschaften zweier besonders eindr{\"u}cklicher Unwetter, sowie (2) die Vulnerabilit{\"a}t der Berliner Bev{\"o}lkerung gegen{\"u}ber Starkregen. Eine vergleichende meteorologische Rekonstruktion der Starkregenereignisse von 2017 und 2019 ergab deutliche Unterschiede in der Entstehung und den {\"U}berschreitungswahrscheinlichkeiten der beiden Unwetter. So war das Ereignis von 2017 mit einer relativ großen r{\"a}umlichen Ausdehnung und langer Dauer ein untypisches Starkregenereignis, w{\"a}hrend es sich bei dem Unwetter von 2019 um ein typisches, kurzzeitiges Starkregenereignis mit ausgepr{\"a}gter r{\"a}umlicher Heterogenit{\"a}t handelte. Eine anschließende statistische Analyse zeigte, dass das Ereignis von 2017 f{\"u}r l{\"a}ngere Niederschlagsdauern (>=24 h) als großfl{\"a}chiges Extremereignis mit {\"U}berschreitungswahrscheinlichkeiten von unter 1 \% einzuordnen ist (d.h. Wiederkehrperioden >=100 Jahre). Im Jahr 2019 wurden dagegen {\"a}hnliche {\"U}berschreitungswahrscheinlichkeiten nur lokal und f{\"u}r k{\"u}rzere Zeitr{\"a}ume (1-2 h) berechnet. Die Vulnerabilit{\"a}tsanalyse basiert auf einer von April bis Juni 2020 in Berlin durchgef{\"u}hrten Onlinebefragung. Diese richtete sich an Personen, die bereits von vergangenen Starkregenereignissen betroffen waren und thematisierte das Schadensereignis selbst, daraus entstandene Beeintr{\"a}chtigungen und Sch{\"a}den, Risikowahrnehmung sowie Notfall- und Vorsorgemaßnahmen. Die erhobenen Umfragedaten (n=102) beziehen sich vornehmlich auf die Ereignisse von 2017 und 2019 und zeigen, dass die Berliner Bev{\"o}lkerung sowohl im Alltag (z.B. bei der Beschaffung von Lebensmitteln) als auch im eigenen Haushalt (z.B. durch {\"U}berschwemmungssch{\"a}den) von den Unwettern beeintr{\"a}chtigt war. Zudem deuteten die Antworten der Betroffenen auf M{\"o}glichkeiten hin, die Vulnerabilit{\"a}t der Gesellschaft gegen{\"u}ber Starkregen weiter zu reduzieren - etwa durch die Unterst{\"u}tzung besonders betroffener Gruppen (z.B. Pflegende), durch gezielte Informationskampagnen zum Schutz vor Starkregen oder durch die Erh{\"o}hung der Reichweite von Unwetterwarnungen. Eine statistische Analyse zur Effektivit{\"a}t privater Notfall- und Vorsorgemaßnahmen auf Grundlage der Umfragedaten best{\"a}tigte vorherige Studienergebnisse. So gab es Anhaltspunkte daf{\"u}r, dass durch das Umsetzen von Vorsorgemaßnahmen wie beispielsweise das Installieren von R{\"u}ckstauklappen, Barriere-Systemen oder Pumpen Starkregensch{\"a}den reduziert werden k{\"o}nnen. Die Ergebnisse dieses Berichts unterstreichen die Notwendigkeit f{\"u}r ein integriertes Starkregenrisikomanagment, das die Risikokomponenten Gef{\"a}hrdung, Vulnerabilit{\"a}t und Exposition ganzheitlich und auf mehreren Ebenen (z.B. staatlich, kommunal, privat) betrachtet.},
language = {de}
}
@article{DeusdaraLealSamprognaMohorCuartasetal.2022,
author = {Deusdar{\´a}-Leal, Karinne and Samprogna Mohor, Guilherme and Cuartas, Luz Adriana and Seluchi, Marcelo E. and Marengo, Jose A. and Zhang, Rong and Broedel, Elisangela and Amore, Diogo de Jesus and Alval{\´a}, Regina C. S. and Cunha, Ana Paula M. A. and Gon{\c{c}}alves, Jos{\´e} A. C.},
title = {Trends and climate elasticity of streamflow in south-eastern Brazil basins},
series = {Water},
volume = {14},
journal = {Water},
number = {14},
publisher = {MDPI},
address = {Basel},
issn = {2073-4441},
doi = {10.3390/w14142245},
pages = {25},
year = {2022},
abstract = {Trends in streamflow, rainfall and potential evapotranspiration (PET) time series, from 1970 to 2017, were assessed for five important hydrological basins in Southeastern Brazil. The concept of elasticity was also used to assess the streamflow sensitivity to changes in climate variables, for annual data and 5-, 10- and 20-year moving averages. Significant negative trends in streamflow and rainfall and significant increasing trend in PET were detected. For annual analysis, elasticity revealed that 1\% decrease in rainfall resulted in 1.21-2.19\% decrease in streamflow, while 1\% increase in PET induced different reductions percentages in streamflow, ranging from 2.45\% to 9.67\%. When both PET and rainfall were computed to calculate the elasticity, results were positive for some basins. Elasticity analysis considering 20-year moving averages revealed that impacts on the streamflow were cumulative: 1\% decrease in rainfall resulted in 1.83-4.75\% decrease in streamflow, while 1\% increase in PET induced 3.47-28.3\% decrease in streamflow. This different temporal response may be associated with the hydrological memory of the basins. Streamflow appears to be more sensitive in less rainy basins. This study provides useful information to support strategic government decisions, especially when the security of water resources and drought mitigation are considered in face of climate change.},
language = {en}
}
@phdthesis{SamprognaMohor2022,
author = {Samprogna Mohor, Guilherme},
title = {Exploring the transferability of flood loss models across flood types},
doi = {10.25932/publishup-55714},
url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-557141},
school = {Universit{\"a}t Potsdam},
pages = {XXIV, 182},
year = {2022},
abstract = {The estimation of financial losses is an integral part of flood risk assessment. The application of existing flood loss models on locations or events different from the ones used to train the models has led to low performance, showing that characteristics of the flood damaging process have not been sufficiently well represented yet. To improve flood loss model transferability, I explore various model structures aiming at incorporating different (inland water) flood types and pathways. That is based on a large survey dataset of approximately 6000 flood-affected households which addresses several aspects of the flood event, not only the hazard characteristics but also information on the affected building, socioeconomic factors, the household's preparedness level, early warning, and impacts. Moreover, the dataset reports the coincidence of different flood pathways. Whilst flood types are a classification of flood events reflecting their generating process (e.g. fluvial, pluvial), flood pathways represent the route the water takes to reach the receptors (e.g. buildings). In this work, the following flood pathways are considered: levee breaches, river floods, surface water floods, and groundwater floods. The coincidence of several hazard processes at the same time and place characterises a compound event. In fact, many flood events develop through several pathways, such as the ones addressed in the survey dataset used. Earlier loss models, although developed with one or multiple predictor variables, commonly use loss data from a single flood event which is attributed to a single flood type, disregarding specific flood pathways or the coincidence of multiple pathways. This gap is addressed by this thesis through the following research questions: 1. In which aspects do flood pathways of the same (compound inland) flood event differ? 2. How much do factors which contribute to the overall flood loss in a building differ in various settings, specifically across different flood pathways? 3. How well can Bayesian loss models learn from different settings? 4. Do compound, that is, coinciding flood pathways result in higher losses than a single pathway, and what does the outcome imply for future loss modelling? Statistical analysis has found that households affected by different flood pathways also show, in general, differing characteristics of the affected building, preparedness, and early warning, besides the hazard characteristics. Forecasting and early warning capabilities and the preparedness of the population are dominated by the general flood type, but characteristics of the hazard at the object-level, the impacts, and the recovery are more related to specific flood pathways, indicating that risk communication and loss models could benefit from the inclusion of flood-pathway-specific information. For the development of the loss model, several potentially relevant predictors are analysed: water depth, duration, velocity, contamination, early warning lead time, perceived knowledge about self-protection, warning information, warning source, gap between warning and action, emergency measures, implementation of property-level precautionary measures (PLPMs), perceived efficacy of PLPMs, previous flood experience, awareness of flood risk, ownership, building type, number of flats, building quality, building value, house/flat area, building area, cellar, age, household size, number of children, number of elderly residents, income class, socioeconomic status, and insurance against floods. After a variable selection, descriptors of the hazard, building, and preparedness were deemed significant, namely: water depth, contamination, duration, velocity, building area, building quality, cellar, PLPMs, perceived efficacy of PLPMs, emergency measures, insurance, and previous flood experience. The inclusion of the indicators of preparedness is relevant, as they are rarely involved in loss datasets and in loss modelling, although previous studies have shown their potential in reducing losses. In addition, the linear model fit indicates that the explanatory factors are, in several cases, differently relevant across flood pathways. Next, Bayesian multilevel models were trained, which intrinsically incorporate uncertainties and allow for partial pooling (i.e. different groups of data, such as households affected by different flood pathways, can learn from each other), increasing the statistical power of the model. A new variable selection was performed for this new model approach, reducing the number of predictors from twelve to seven variables but keeping factors of the hazard, building, and preparedness, namely: water depth, contamination, duration, building area, PLPMs, insurance, and previous flood experience. The new model was trained not only across flood pathways but also across regions of Germany, divided according to general socioeconomic factors and insurance policies, and across flood events. The distinction across regions and flood events did not improve loss modelling and led to a large overlap of regression coefficients, with no clear trend or pattern. The distinction of flood pathways showed credibly distinct regression coefficients, leading to a better understanding of flood loss modelling and indicating one potential reason why model transferability has been challenging. Finally, new model structures were trained to include the possibility of compound inland floods (i.e. when multiple flood pathways coincide on the same affected asset). The dataset does not allow for verifying in which sequence the flood pathway waves occurred and predictor variables reflect only their mixed or combined outcome. Thus, two Bayesian models were trained: 1. a multi-membership model, a structure which learns the regression coefficients for multiple flood pathways at the same time, and 2. a multilevel model wherein the combination of coinciding flood pathways makes individual categories. The multi-membership model resulted in credibly different coefficients across flood pathways but did not improve model performance in comparison to the model assuming only a single dominant flood pathway. The model with combined categories signals an increase in impacts after compound floods, but due to the uncertainty in model coefficients and estimates, it is not possible to ascertain such an increase as credible. That is, with the current level of uncertainty in differentiating the flood pathways, the loss estimates are not credibly distinct from individual flood pathways. To overcome the challenges faced, non-linear or mixed models could be explored in the future. Interactions, moderation, and mediation effects, as well as non-linear effects, should also be further studied. Loss data collection should regularly include preparedness indicators, and either data collection or hydraulic modelling should focus on the distinction of coinciding flood pathways, which could inform loss models and further improve estimates. Flood pathways show distinct (financial) impacts, and their inclusion in loss modelling proves relevant, for it helps in clarifying the different contribution of influencing factors to the final loss, improving understanding of the damaging process, and indicating future lines of research.},
language = {en}
}
@article{GuzmanAriasSamprognaMohorMendiondo2022,
author = {Guzman Arias, Diego Alejandro and Samprogna Mohor, Guilherme and Mendiondo, Eduardo Mario},
title = {Multi-driver ensemble to evaluate the water utility business interruption cost induced by hydrological drought risk scenarios in Brazil},
series = {Urban water journal},
journal = {Urban water journal},
publisher = {Routledge, Taylor \& Francis Group},
address = {Abingdon},
issn = {1573-062X},
doi = {10.1080/1573062X.2022.2058564},
pages = {15},
year = {2022},
abstract = {Climate change and increasing water demand in urban environments necessitate planning water utility companies' finances. Traditionally, methods to estimate the direct water utility business interruption costs (WUBIC) caused by droughts have not been clearly established. We propose a multi-driver assessment method. We project the water yield using a hydrological model driven by regional climate models under radiative forcing scenarios. We project water demand under stationary and non-stationary conditions to estimate drought severity and duration, which are linked with pricing policies recently adopted by the Sao Paulo Water Utility Company. The results showed water insecurity. The non-stationary trend imposed larger differences in the drought resilience financial gap, suggesting that the uncertainties of WUBIC derived from demand and climate models are greater than those associated with radiative forcing scenarios. As populations increase, proactively controlling demand is recommended to avoid or minimize reactive policy changes during future drought events, repeating recent financial impacts.},
language = {en}
}
@article{ArguellodeSouzaSamprognaMohorGuzmanAriasetal.2023,
author = {Arguello de Souza, Felipe Augusto and Samprogna Mohor, Guilherme and Guzman Arias, Diego Alejandro and Sarmento Buarque, Ana Carolina and Taffarello, Denise and Mendiondo, Eduardo Mario},
title = {Droughts in S{\~a}o Paulo},
series = {Urban water journal},
volume = {20},
journal = {Urban water journal},
number = {10},
publisher = {Taylor \& Francis},
address = {London [u.a.]},
issn = {1573-062X},
doi = {10.1080/1573062X.2022.2047735},
pages = {1682 -- 1694},
year = {2023},
abstract = {Literature has suggested that droughts and societies are mutually shaped and, therefore, both require a better understanding of their coevolution on risk reduction and water adaptation. Although the Sao Paulo Metropolitan Region drew attention because of the 2013-2015 drought, this was not the first event. This paper revisits this event and the 1985-1986 drought to compare the evolution of drought risk management aspects. Documents and hydrological records are analyzed to evaluate the hazard intensity, preparedness, exposure, vulnerability, responses, and mitigation aspects of both events. Although the hazard intensity and exposure of the latter event were larger than the former one, the policy implementation delay and the dependency of service areas in a single reservoir exposed the region to higher vulnerability. In addition to the structural and non-structural tools implemented just after the events, this work raises the possibility of rainwater reuse for reducing the stress in reservoirs.},
language = {en}
}