Model Based Estimation of a Natural Water Balance as Reference for Planning in Urban Areas

Henrichs, Malte; Steinbrich, Andreas; Leistert, Hannes; Scherer, Isabel; Schuetz, Tobias; Uhl, Mathias; Weiler, Markus

doi:10.1007/978-3-319-99867-1_164

Cited by 6 publications

(8 citation statements)

References 3 publications

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“…Conhecer o regime pluviométrico de uma bacia hidrográfica é determinante em projetos relacionados ao uso da água e de planejamento urbano (Henrichs et al, 2018), tanto para mitigar desastres relacionados a eventos extremos de precipitação, como inundações, enxurradas, alagamentos e movimentos de massa; quanto as dificuldades provocadas pela falta de chuvas, como as estiagens e as secas (Oliveira et al, 2005;Trenberth, 2011;Santos, 2015;Raghavendra et al, 2019;Zhao et al, 2019).…”

Section: Introductionunclassified

Preenchimento de Falhas e Espacialização de Dados Pluviométricos: Desafios e Perspectivas

Brubacher¹,

Oliveira²,

Guasselli³

2020

Rev. bras. meteorol.

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Resumo A precipitação é uma das variáveis climáticas mais importantes para o planejamento urbano e rural, para monitorar eventos extremos que possam causar impactos na sociedade e auxiliar em projetos de drenagem urbana, a fim de reduzir os riscos inerentes a inundações e alagamentos, ou mesmo obras de engenharia, como dimensionamento de barragens. No entanto, as falhas em séries extensas prejudicam esses estudos, sendo necessário utilizar modelos para o seu preenchimento. O presente estudo tem como objetivo revisar os métodos de preenchimento de falhas e de interpolação espacial de dados de precipitação. A revisão dos métodos foi realizada a partir da pesquisa e leitura de materiais bibliográficos, de modo a conceituar as abordagens, identificar vantagens e desvantagens de cada método e apresentar como estudos recentes, nacionais e internacionais, têm inovado ao comparar o desempenho em diferentes áreas de estudo. Com base nessa revisão, os principais métodos para o preenchimento de falhas são os seguintes: i) ponderação a partir de Regressão Linear Simples ou Múltipla; ii) modelos matemáticos baseados em aprendizagem de máquinas, tais como as Redes Neurais Artificiais; iii) interpoladores espaciais para o preenchimento de falhas (Inverso da Distância, Vizinho Natural, Krigagem). Por fim, foi verificada uma evolução das técnicas de interpolação e de preenchimento de falhas nas últimas décadas, em decorrência da evolução da capacidade computacional e tecnológica.

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Section: Introductionunclassified

Preenchimento de Falhas e Espacialização de Dados Pluviométricos: Desafios e Perspectivas

Brubacher¹,

Oliveira²,

Guasselli³

2020

Rev. bras. meteorol.

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“…The water in a basin is controlled by climatic factors and features of the basin (LULC and soil type, hydrogeological conditions). To quantify the combined effects of LULC and CC on water resources is a challenge because LULC affects water availability by altering hydrological processes through modifications of ET, soil moisture dynamics [57,58], and R u .…”

Section: Discussionmentioning

confidence: 99%

“…The impervious surfaces of urban land use can cause land degradation and increase R u [57,59] in a region, even if the R u is primarily dictated by agricultural land (which represents 38.28% of the study area). Because water demand for crops is usually high, the increase of urban cover is a challenge for water resource management.…”

Section: Discussionmentioning

confidence: 99%

Climate Change, Land Use/Land Cover Change, and Population Growth as Drivers of Groundwater Depletion in the Central Valleys, Oaxaca, Mexico

et al. 2019

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Groundwater depletion is an important problem driven by population growth, land use and land cover (LULC) change, climate change, and other factors. Groundwater depletion generates water stress and encourages unstainable resource use. The aim of this study is to determine how population growth, LULC change, and climate change relate to groundwater depletion in the Alto Atoyac sub-basin, Oaxaca, Mexico. Twenty-five years of dry season water table data from 1984 to 2009 are analyzed to examine annual groundwater depletion. Kriging is used to interpolate the region’s groundwater levels in a geographic information system (GIS) from mapped point measurements. An analysis of remotely sensed data revealed patterns of LULC change during a 34-year (1986–2018) period, using a supervised, machine-learning classification algorithm to calculate the changes in LULC. This analysis is shown to have an 85% accuracy. A global circulation model (GFDL-CM3) and the RCP4.5 and RCP8.5 scenarios were used to estimate the effects of climate change on the region’s groundwater. Estimates of evapotranspiration (using HELP3.5 code) and runoff (USDA-SCS-CN), were calculated. Since 1984, the region’s mean annual temperature has increased 1.79 °C and urban areas have increased at a rate of 2.3 km2/year. Population growth has increased water consumption by 97.93 × 106 m3/year. The volume of groundwater is shrinking at a rate of 284.34 × 106 m3/year, reflecting the extreme pressure on groundwater supply in the region. This research reveals the nature of the direct impacts that climate change, changing LULCs, and population growth have in the process of groundwater depletion.

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“…where D WB is the deviation from a targeted water balance (in percentage points), R is the runoff volume (in % of precipitation depth), ET is the evapotranspiration (in % of precipitation depth), GR is the groundwater recharge (in % of precipitation depth), sim denotes the simulated value, and t denotes the value of target state. The targeted water balance can be either defined by stakeholders based on case-specific boundary conditions like the capacity of the present sewer system or based on hydrologic simulations, aiming for natural conditions (e.g., [19]). For demonstration purposes, an arbitrary defined targeted water balance with a runoff volume of 5%, an evapotranspiration of 45%, and a groundwater recharge of 50% is used.…”

Section: Assessment and Efficiency Of Lid Strategiesmentioning

confidence: 99%

“…Therefore, in terms of an environmentally sustainable and reasonable application of LIDs, all components of the water balance have to be considered. Consequently, holistic approaches (e.g., [18,19]) are a suitable basis for planning purposes. Furthermore, the assessment of LID performance is conducted on site scale, as suggested by Burns et al [20], in order to restore/protect natural hydrologic processes at small scales.…”

Section: Introductionmentioning

confidence: 99%

Model-Based Selection of Cost-Effective Low Impact Development Strategies to Control Water Balance

et al. 2019

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Urbanization induces an increase of runoff volume and decrease of evapotranspiration and groundwater recharge. Low impact development (LID) strategies aim to mitigate these adverse impacts. Hydrologic simulation is a reasonable option to assess the LID performance with respect to the water balance and is applicable to planning purposes. Current LID design approaches are based on design storm events and focus on the runoff volume and peak, neglecting evapotranspiration and groundwater recharge. This contribution presents a model-based design approach for the selection of cost-effective LID strategies. The method is based on monitored precipitation time series and considers the complete water balance and life-cycle-costs, as well as the demand for land. The efficiency of LID strategies (ELID) is introduced as an evaluation measure which also accounts for emphasizing different goals. The results show that there exist several pareto-optimal LID strategies providing a reasonable basis for decision-making. Additionally, the application of LID treatment trains emerges as an option of high potential.

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Model Based Estimation of a Natural Water Balance as Reference for Planning in Urban Areas

Cited by 6 publications

References 3 publications

Preenchimento de Falhas e Espacialização de Dados Pluviométricos: Desafios e Perspectivas

Preenchimento de Falhas e Espacialização de Dados Pluviométricos: Desafios e Perspectivas

Climate Change, Land Use/Land Cover Change, and Population Growth as Drivers of Groundwater Depletion in the Central Valleys, Oaxaca, Mexico

Model-Based Selection of Cost-Effective Low Impact Development Strategies to Control Water Balance

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