scholarly journals Interannual Variability of Water Demand and Summer Climate in Albuquerque, New Mexico

2005 ◽  
Vol 44 (12) ◽  
pp. 1777-1787 ◽  
Author(s):  
David S. Gutzler ◽  
Joshua S. Nims
Keyword(s):  
New Mexico ◽  
Climate Variability ◽  
Regression Model ◽  
Interannual Variability ◽  
Water Conservation ◽  
Water Demand ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Short Term ◽  
Residential Demand

Abstract The effects of interannual climate variability on water demand in Albuquerque, New Mexico, are assessed. This city provides an ideal setting for examining the effects of climate on urban water demand, because at present the municipal water supply is derived entirely from groundwater, making supply insensitive to short-term climate variability. There is little correlation between interannual variability of climate and total water demand—a result that is consistent with several previous studies. However, summertime residential demand, which composes about one-quarter of total annual demand in Albuquerque, is significantly correlated with summer-season precipitation and average daily maximum temperature. Furthermore, regressions derived from year-to-year changes in these variables are shown to isolate the climatic modulation of residential water demand effectively. Over 60% of the variance of year-to-year changes in summer residential demand is accounted for by interannual temperature and precipitation changes when using a straightforward linear regression model, with precipitation being the primary correlate. Long-term trends in water demand follow population growth closely until 1994, after which time a major water conservation effort led to absolute decreases in demand in subsequent years. The effectiveness of the conservation efforts can be quantified by applying the regression model, thus removing the year-to-year variations associated with short-term climate fluctuations estimated from the preconservation period. The preconservation regression provides a good fit to interannual summer residential demand in subsequent years, demonstrating that the regression model has successfully isolated the climatic component of water demand. The quality of this fit during a period of sharply reduced demand suggests that the conservation program has effectively targeted the nonclimatically sensitive component of water demand and has sharpened the climatically sensitive component of demand to a level closer to the consumption that is “climatically needed.”

Historical climate and stream flow trends and future water demand analysis in the Calgary region, Canada

2006 ◽  
Vol 53 (10) ◽  
pp. 1-11 ◽  
Author(s):  
Z. Chen ◽  
S.E. Grasby ◽  
K.G. Osadetz ◽  
P. Fesko
Keyword(s):  
Population Growth ◽  
Water Conservation ◽  
Water Demand ◽  
Stream Flow ◽  
Sustainable Growth ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Trend ◽  
Sustainable Water Supply

The city of Calgary has been one of fastest growing cities in Canada in recent years. Rapid population growth and a warming climate trend have raised concerns about sustainable water supply. In this study, historic climate, stream flow and population data are analyzed in order to develop models of future climate trends and river-water resource availability. Daily water demands for the next 60 years were projected using the relationship between daily maximum temperature and water demand under simulated climate and population growth scenarios. To maintain sustainable growth Calgary will require water conservation efforts that reduce per capita water use to less than half of the current level over the next 60 years, an interval when the civic population is expected to be doubled.

scholarly journals Rainfall Variability across the Agro-Climatic Zones of a Tropical Highland: The Case of the Jema Watershed, Northwestern Ethiopia

Environments ◽  
2019 ◽  
Vol 6 (11) ◽  
pp. 118 ◽  
Author(s):  
Taye ◽  
Simane ◽  
Zaitchik ◽  
Selassie ◽  
Setegn
Keyword(s):  
Climate Variability ◽  
Coefficient Of Variation ◽  
Rainfall Variability ◽  
Arithmetic Functions ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Climatic Zones ◽  
Climate Indicators

The objective of the study was to analyze the variability of various climate indicators across the agro-climatic zones (ACZs) of the Jema watershed. The variability was analyzed considering mean annual rainfall (MARF, mm), mean daily minimum temperature (MDMinT, °C), and mean daily maximum temperature (MDMaxT, °C). A one-way analysis of variance (ANOVA) was employed to test whether group mean differences exist in the values of the indicated climatic indicators among the ACZs of the watershed. The coefficient of variation was computed to analyze the degree of climate variability among the ACZs. Rainfall and temperature data sets from 1983 to 2017 were obtained from nearby meteorological stations. The effect of climate variability in the farming system was assessed with reference to local farmers’ experience. Ultimately, the values of the stated indicators of exposure to climate variability were indexed (standardized) in order to run arithmetic functions. The MARF decreases towards sub-alpine ACZs. Based on the result of the ANOVA, the two-tailed p-value (≤ 0.04) was less than 0.05; that is, there was a significant variation in MARF, MDMaxT (°C), and MDMinT (°C) among the ACZs. The coefficient of variation showed the presence of variations of 0.18–0.88 for MARF, 0.18 to 0.85 for MDMaxT, and 0.02–0.95 for MDMinT across the ACZs. In all of the indicators of exposure to climate variability, the lowest and highest indexed values of coefficient of variation were observed in the moist–cool and sub-alpine ACZs, respectively. Overall, the aggregate indexed values of exposure to various climate indicators ranged from 0.13–0.89 across the ACZs. The level of exposure to climate variability increased when moving from moist–cool to sub-alpine ACZs. The overall crop diversity declined across the ACZs of the watershed. Nevertheless, mainly because of the rise in temperature, the climate became suitable for cultivating maize and tef even at higher elevations. In order to adapt to the inter-annual variability of the rainy season, the process of adapting early-maturing crops and the use of improved seeds needs to be enhanced in the watershed, especially in the higher-elevation zones. It is also essential to revise traditional crop calendars and crop zones across the ACSz.

Research on the Prediction Model of Urban Power Grid Short-Term Load Based on BP Neural Network Algorithm

2014 ◽  
Vol 926-930 ◽  
pp. 954-957
Author(s):  
Pei Long Xu
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Bp Neural Network ◽  
Power Grid ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Short Term ◽  
Network Algorithm ◽  
Neural Network Algorithm

Objective: The paper aims to establish the prediction model of urban power grid short-term load based on BP neural network algorithm. Method: Five factors influencing the urban power grid short-term load are used to establish the neural network model: date type, weather, daily maximum temperature, daily minimum temperature and daily average temperature. Matlab toolbox is used to develop the testing platform through VC++ programming. Result: The variable learning rates are 0.35 and 0.64. With 23410 iterations, the model is converged, and the global error is 0.00032. Conclusion: Through the data comparison and analysis, the relative error is within 5%, thus indicating the model is accurate and effective, and it can be used to predict the change of urban power grid short-term load.

Simulation-based indices for a climate-resilient agriculture - insights from ADAPTER

2021 ◽  
Author(s):  
Sebastian Bathiany ◽  
Diana Rechid ◽  
Klaus Goergen ◽  
Patrizia Ney ◽  
Alexandre Belleflamme
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Indices ◽  
Agricultural System ◽  
Daily Maximum ◽  
Public Attention ◽  
Genetic Traits ◽  
Changing Climate

<p>Agriculture is among the sectors that are most vulnerable to extreme weather conditions and climate change. In Germany, the dry and hot summers 2018, 2019, and 2020 have brought this into the focus of public attention. Agricultural actors like farmers, advisors or companies are concerned to adapt to interannual climate variability and extremes. In the ADAPTER project, we collaborate with stakeholders from these groups and generate practically relevant information, tailored climate change indices and usable information products.</p> <p> </p> <p>The challenges of climate change for agriculture are manifold. The genetic traits of crops need to be adapted to a new climatic average, for instance by breeding new sorts of crops that are specialised for warmer and dryer conditions (i.e. maximising average yields). Agricultural practises need to be adapted to changing seasonal weather patterns under changing climate conditions. It is also vital to ensure the resilience to climate extremes by aiming for a low inter-annual yield variability, in order to prevent price shocks or food shortages.</p> <p> </p> <p>In order to adequately determine the optimal balance between specialisation and risk diversification, the agricultural sector hence requires knowledge not only about changes in the mean climate, but also on the variance around the changing mean. In this contribution, we focus on this second aspect by analysing the potential impact of forced changes in climate variability on the stability of crop yields in central Europe.</p> <p> </p> <p>We analyse the changing climate variability in 85 regional climate model projections from Coordinated Downscaling Experiments over Europe (EURO-CORDEX). We first show how the projections indicate a general increase in climate variability during critical development stages of wheat, rapeseed and maize in Europe. Second, we determine several more specific agronomic climate indices that capture events that have previously been shown to be critical for yields, for instance the occurrence of high daily maximum temperature, the seasonal sum of rainfall, the number of dry days, or the occurrence of compound events with simultaneous drought and increased temperatures. Finally, we illustrate how the results can be made accessible to practitioners in the agriculture sector by co-designing interactive browser applications, thus directly supporting the adaptation of the agricultural system to climate change.</p> <p> </p>

scholarly journals Improving Short-Term Forecasts of Daily Maximum Temperature with the Kalman Filter with GMM Estimation

2021 ◽  
pp. 552-562
Author(s):  
Marco Costa ◽  
Fernanda Catarina Pereira ◽  
A. Manuela Gonçalves
Keyword(s):  
Kalman Filter ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Short Term ◽  
Gmm Estimation

Assessment and prioritization of community soil and water conservation measures for adaptation to climatic stresses in Makawanpur district of Nepal

2012 ◽  
Vol 6 ◽  
pp. 44-51 ◽  
Author(s):  
Prashant Paudel ◽  
Gandhiv Kafle
Keyword(s):  
Climate Change ◽  
Water Conservation ◽  
Local Community ◽  
Soil And Water Conservation ◽  
Preference Ranking ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Conservation Measures ◽  
Adaptation Options ◽  
Soil And Water

Climate change is the global concern of our sustainable development whose impact is of great concern to humanity. In Nepal, we are already starting to become aware of recent changes and developing the mechanism to adapt. A study was carried out in Bramha Thakur Community Forest User Group of Makawanpur district with an objective of assessing and prioritizing adaptation options by local community using soil and water conservation measures on climate change. Primary data were collected from direct observation, focus group discussion, key informant interview, preference ranking and transect walk. Meteorological data on temperature and rainfall of 30 years was collected from government sources and climatic trend was analyzed. Prioritization of adaptation options was done using Index of Usefulness of Practices to Adaptation (IUPA) tool developed by Debels et al. (2010). Monthly maximum value of daily maximum temperature and minimum temperature has increased by 0.0461°C and 0.12°C respectively. Numbers of warm days are increasing. Annual precipitation has increased steadily whereas maximum five days and monthly precipitation trend is increasing at high rate, alarming to hazards induced by climate change. Local people were found very resourceful in using various adaptation practices to deal with impacts of climate change. IUPA scoring provided important rankings on the adaptation options. Conservation pond was highly prioritized for drought management. To adapt with flood, engineering structures with or without vegetation were highly used as adaptation option. Bamboo plantation was highly preferred by local community to reduce the impacts of landslide and to prevent its occurrence. Bioengineering structures are highly recommended for long term stability in flooded and landslide affected areas. Further studies on adaptation options and their prioritization in more areas are recommended for comprehensive database and generalization. DOI: http://dx.doi.org/10.3126/jowe.v6i0.6997 J Wet Eco 2012 (6): 44-51

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals Climate Variability Since 1970 and Farmers’ Observations in Northern Ghana

2016 ◽  
Vol 5 (2) ◽  
pp. 41 ◽  
Author(s):  
Emmanuel Nyadzi
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Water Conservation ◽  
Crop Production ◽  
Meteorological Data ◽  
Northern Region ◽  
Northern Ghana ◽  
Climate Variability And Change ◽  
Urban Centers ◽  
Access To Credit

<p>The study examines how farmers’ observations of climate variability and change correspond with 42 years (1970-2011) meteorological data of temperature and rainfall. It shows how farmers in the Northern Region of Ghana adjust to the changing climate and explore the various obstacles that hinder the implementation of their adaptation strategies. With the help of an extension officer, 200 farmers from 20 communities were randomly selected based on their farming records. Temperatures over the last four decades (1970-2009) increased at a rate of 0.04 (± 0.41) ˚C and 0.3(± 0.13)˚C from 2010-2011 which is consistent to the farmers (82.5%) observations. Rainfall within the districts are characterised by inter-annual and monthly variability. It experienced an increased rate of 0.66 (± 8.30) mm from 1970-2009, which was inconsistent with the farmers (81.5%) observation. It however decreased from 2010-2011 at a huge rate of -22.49 (±15.90) mm which probably was the reason majority of the respondents claim rainfall was decreasing. Only 64.5% of the respondents had adjusted their farming activities because of climate variability and change. They apply fertilizers and pesticides, practice soil and water conservation, and irrigation for communities close to dams. Respondents desire to continue their current adaptation methods but may in the future consider changing crop variety, water-harvesting techniques, change crop production to livestock keeping, and possibly migrate to urban centers. Lack of climate change education, low access to credit and agricultural inputs are some militating factors crippling the farmers’ effort to adapt to climate change.</p>

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