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The Budyko framework was first developed to estimate actual evaporation as a function of precipitation and the aridity index at steady state conditions. Based on this framework, the water storage change in the watershed is assumed to be negligible at large spatial and temporal scales. However, steady state conditions are not valid for many watersheds worldwide or at finer temporal or spatial scales. Accordingly, the application of the Budyko framework has become challenging for these situations. Therefore, many researchers have tried to extend the Budyko framework for non-steady state conditions. The aim of this study is to provide a review of the extended equations and to discuss about using the Budyko framework in a changing world. While the extended equations are more complex than the original ones, they require less data. Thus, the Budyko framework, either the original or the extended can be a very useful tool for hydrological modeling with lots of applications, especially in data scarce regions.


• The Budyko framework can help to find the source of abnormal behavior of the basins.
• Steady state conditions in Budyko curve are violated for many watersheds worldwide.
• Uncertainty assessment of complex models with budyko curve is highly effective.
• The next generation of hydrological modeling may take advantage of this framework.


The canopy layer urban heat island (UHI) effect, as manifested by elevated near-surface air temperatures in urban areas, exposes urban dwellers to additional heat stress in many cities, specially during heat waves. We simulate the urban climate of various generated cities under the same weather conditions. For mono-centric cities, we propose a linear combination of logarithmic city area and logarithmic gross building volume, which also captures the influence of building density. By studying various city shapes, we generalise and propose a reduced form to estimate UHI intensities based only on the structure of urban sites, as well as their relative distances. We conclude that in addition to the size, the UHI intensity of a city is directly related to the density and an amplifying effect that urban sites have on each other. Our approach can serve as a UHI rule of thumb for the comparison of urban development scenarios.
Hydrological sciences / Observing Rivers with Varying Spatial Scales
« Last post by Pankaj Dey on May 25, 2020, 09:45:45 AM »
Information about the amount of fresh water in rivers is decreasing globally due to a loss of maintained gauges. Remote sensors, such as the NASA/CNES Surface Water and Ocean Topography (SWOT) mission, offer the possibility of extending the decaying gauge network by providing global open data access to rivers. However, the SWOT data is unlike the data that hydrologists know. Due to instrument noise, the river width, elevation, and slope, will need to be averaged over distances as long as 10\,km. Here, we show that these average parameters can be treated using the equations for point measurements, provided the equations replace the friction from the river bed by a larger effective friction. This increase accounts for the river scales that are unobserved due to averaging. We relate the increase in effective friction to river width, area, and slope variability that may be available through statistical studies or data from complimentary sensors. We find that the effective friction is dependent on the depth of the river, increasing as the river discharge decreases. The predictions from this paper can be incorporated to improve river discharge retrievals from the SWOT mission that will improve our understanding of global river networks.
Hydrological sciences / A Snapshot of the World's Groundwater Challenges
« Last post by Pankaj Dey on May 24, 2020, 09:58:02 AM »
Depletion and pollution of groundwater, Earth's largest and most accessible freshwater stock, is a global sustainability concern. A changing climate, marked by more frequent and intense hydrologic extremes, poses threats to groundwater recharge and amplifies groundwater use. However, widespread human development and contamination of groundwater reservoirs pose an immediate threat of resource extinction with impacts in many regions with dense population or intensive agriculture. A rapid increase in global groundwater studies has emerged, but this has also highlighted the extreme paucity of data for substantive trend analyses and assessment of the state of the global resource. Noting the difficulty in seeing and measuring this typically invisible resource, we discuss factors that determine the current state of global groundwater, including the uncertainties accompanying data and modeling, with an eye to identifying emerging issues and the prospects for informing local to global resource management in critical regions. We comment on some prospective management strategies.

There remains large intersimulation spread in the hydrologic responses to tropical volcanic eruptions, and identifying the sources of diverse responses has important implications for assessing the side effects of solar geoengineering and improving decadal predictions. Here, we show that the intersimulation spread in the global monsoon drying response strongly relates to diverse El Niño responses to tropical eruptions. Most of the coupled climate models simulate El Niño–like equatorial eastern Pacific warming after volcanic eruptions but with different amplitudes, which drive a large spread of summer monsoon weakening and corresponding precipitation reduction. Two factors are further identified for the diverse El Niño responses. Different volcanic forcings induce systematic differences in the Maritime Continent drying and subsequent westerly winds over equatorial western Pacific, varying El Niño intensity. The internally generated warm water volume over the equatorial western Pacific in the pre-eruption month also contributes to the diverse El Niño development.
Interesting information / Global threat of arsenic in groundwater
« Last post by Pankaj Dey on May 23, 2020, 08:48:39 AM »
Arsenic is a metabolic poison that is present in minute quantities in most rock materials and, under certain natural conditions, can accumulate in aquifers and cause adverse health effects. Podgorski and Berg used measurements of arsenic in groundwater from ∼80 previous studies to train a machine-learning model with globally continuous predictor variables, including climate, soil, and topography (see the Perspective by Zheng). The output global map reveals the potential for hazard from arsenic contamination in groundwater, even in many places where there are sparse or no reported measurements. The highest-risk regions include areas of southern and central Asia and South America. Understanding arsenic hazard is especially essential in areas facing current or future water insecurity.


Naturally occurring arsenic in groundwater affects millions of people worldwide. We created a global prediction map of groundwater arsenic exceeding 10 micrograms per liter using a random forest machine-learning model based on 11 geospatial environmental parameters and more than 50,000 aggregated data points of measured groundwater arsenic concentration. Our global prediction map includes known arsenic-affected areas and previously undocumented areas of concern. By combining the global arsenic prediction model with household groundwater-usage statistics, we estimate that 94 million to 220 million people are potentially exposed to high arsenic concentrations in groundwater, the vast majority (94%) being in Asia. Because groundwater is increasingly used to support growing populations and buffer against water scarcity due to changing climate, this work is important to raise awareness, identify areas for safe wells, and help prioritize testing.

Link to paper:
Global climate models (GCMs) are developed to simulate past climate and produce projections of climate in future. Their roles in ascertaining regional issues and possible solutions in water resources planning/management are appreciated across the world. However, there is substantial uncertainty in the future projections of GCM(s) for practical and regional implementation which has attracted criticism by the water resources planners. The present paper aims at reviewing the selection of GCMs and focusing on performance indicators, ranking of GCMs and ensembling of GCMs and covering different geographical regions. In addition, this paper also proposes future research directions. 
Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders were closed and populations were confined to their homes, which reduced transport and changed consumption patterns. Here we compile government policies and activity data to estimate the decrease in CO2 emissions during forced confinements. Daily global CO2 emissions decreased by –17% (–11 to –25% for ±1σ) by early April 2020 compared with the mean 2019 levels, just under half from changes in surface transport. At their peak, emissions in individual countries decreased by –26% on average. The impact on 2020 annual emissions depends on the duration of the confinement, with a low estimate of –4% (–2 to –7%) if prepandemic conditions return by mid-June, and a high estimate of –7% (–3 to –13%) if some restrictions remain worldwide until the end of 2020. Government actions and economic incentives postcrisis will likely influence the global CO2 emissions path for decades.
The drought‐pluvial seesaw ‐‐ defined as the phenomenon of pluvials (wet spells) following droughts (dry spells) ‐‐ magnifies the impact of individual pluvial and drought events, yet has not been systematically evaluated, especially at the global scale. We apply an event coincidence analysis to explore the aggregated seesaw behavior based on land surface model simulations for the past seven decades (1950‐2016). We find that globally, about 5.9% and 7.6% of the land surface has experienced statistically significant (p<0.10) drought‐pluvial seesaw behavior during the boreal spring‐summer and fall‐winter, with an average 11.1% and 11.4% of all droughts being followed by pluvials in the following season, respectively. Although this global frequency pattern is modest and coherent changes cannot be detected at the sub‐continental scale, local hotspots of drought‐pluvial seesaw have become more frequent than either droughts or pluvials alone in the last three decades, albeit with a small percentage of area coverage.
Hydrological sciences / Community Water Model
« Last post by Pankaj Dey on May 18, 2020, 06:41:45 PM »
Opensource model to examine how future water demand will evolve in response to socioeconomic change and how water availability will change in response to climate.
The Community Water Model allows the assessment of water supply and human and environmental water demands at both global and regional levels.
The hydrological model is open source and has been designed to link to other models, enabling the analysis of many different aspects of the water-energy-food-ecosystem nexus.

The model is the first step towards developing a next-generation global hydro-economic modeling framework, that can explore the economic trade-offs among different water management options, encompassing both water supply infrastructure and demand management.

The integrated modeling framework will consider water demand from agriculture, domestic, energy, industry, and the environment. It will also take into account the investment needed to alleviate future water scarcity, and provide a portfolio of economically optimal solutions. In addition, it will be able to track the energy requirements associated with the water supply system; for example, pumping, desalination, and inter-basin transfer. 

Rising population and growing economic development mean that water demand is expected to increase significantly, especially in developing regions. At the same time, climate change will have global, regional, and local impacts on water availability. Ensuring this changing supply can meet the increasing demand, without compromising the aquatic environment from which it is derived, is a huge challenge.  Accurate assessment of water supply, human water demand and the water demand of the environment required to maintain this supply, is essential to devise and assess potential strategies to overcome this challenge.
The Community Water Model is the first step towards developing an integrated modelling framework, which will be able to provide vital information to decision and policy makers.

Link to Tutorial and Source Code:

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