scholarly journals Climate Change Made Major Contributions to Soil Water Storage Decline in the Southwestern US during 2003–2014

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1947
Author(s):  
Jianzhao Liu ◽  
Liping Gao ◽  
Fenghui Yuan ◽  
Yuedong Guo ◽  
Xiaofeng Xu
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Water Resource Management ◽  
Time Series Data ◽  
Meteorological Data ◽  
Water Storage ◽  
Climate Change Impacts ◽  
Soil Water Storage ◽  
Series Data ◽  
Atmospheric Water

Soil water shortage is a critical issue for the Southwest US (SWUS), the typical arid region that has experienced severe droughts over the past decades, primarily caused by climate change. However, it is still not quantitatively understood how soil water storage in the SWUS is affected by climate change. We integrated the time-series data of water storage and evapotranspiration derived from satellite data, societal water consumption, and meteorological data to quantify soil water storage changes and their climate change impacts across the SWUS from 2003 to 2014. The water storage decline was found across the entire SWUS, with a significant reduction in 98.5% of the study area during the study period. The largest water storage decline occurred in the southeastern portion, while only a slight decline occurred in the western and southwestern portions of the SWUS. Net atmospheric water input could explain 38% of the interannual variation of water storage variation. The climate-change-induced decreases in net atmospheric water input predominately controlled the water storage decline in 60% of the SWUS (primarily in Texas, Eastern New Mexico, Eastern Arizona, and Oklahoma) and made a partial contribution in approximately 17% of the region (Central and Western SWUS). Climate change, primarily as precipitation reduction, made major contributions to the soil water storage decline in the SWUS. This study infers that water resource management must consider the climate change impacts over time and across space in the SWUS.

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

ASSESSMENT OF CLIMATE CHANGE IMPACTS ON AMAN AND BORO RICE YIELDS IN BANGLADESH

2016 ◽  
Vol 07 (03) ◽  
pp. 1650008 ◽  
Author(s):  
M. MEHEDI HASAN ◽  
Md. ABDUR RASHID SARKER ◽  
JEFF GOW
Keyword(s):  
Climate Change ◽  
Time Series Data ◽  
Climate Change Impacts ◽  
Series Data ◽  
Rice Varieties ◽  
Cross Sectional ◽  
Climate Conditions ◽  
Climatic Regions ◽  
Rice Yields ◽  
Boro Rice

Despite substantial volumes of research on the impacts of climate change on rice productivity little attention has been paid in evaluating how these impacts differ between traditional varieties (TVs) and high yielding varieties (HYVs). In this study, Aman and Boro rice yields are examined, as respective examples. Cross-sectional time series data over 41 years for four climatic regions of Bangladesh has been used to explore this issue. Each region was examined individually and then across region comparisons were made to try to understand the impacts of major climate variables: average temperature, temperature range, and seasonal rainfall. Using both linear regression and panel data regression models, the major findings are that HYVs for both Aman and Boro rice varieties have less capacity to cope with changing climate conditions in contrast to TVs. Therefore, government should help to promote research and development aimed at developing more climate tolerant varieties, particularly temperature tolerant HYVs which have the potential to solidify the country’s food security situation at least in terms of food availability.

scholarly journals Soil-Water Storage Predictions for Cultivated Crops on the Záhorská Lowlands

2016 ◽  
Vol 24 (2) ◽  
pp. 31-40
Author(s):  
Miroslava Jarabicová ◽  
Peter Minarič
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Climate Model ◽  
Spring Barley ◽  
Regional Climate ◽  
Water Storage ◽  
Soil Water Storage ◽  
Reference Period ◽  
The Impact ◽  
Upper Boundary

Abstract The main objective of this paper is to evaluate the impact of climate change on the soil-water regime of the Záhorská lowlands. The consequences of climate change on soil-water storage were analyzed for two crops: spring barley and maize. We analyzed the consequences of climate change on soil-water storage for two crops: spring barley and maize. The soil-water storage was simulated with the GLOBAL mathematical model. The data entered into the model as upper boundary conditions were established by the SRES A2 and SRES B1 climate scenarios and the KNMI regional climate model for the years from 2071 to 2100 (in the text called the time horizon 2085 which is in the middle this period). For the reference period the data from the years 1961-1990 was used. The results of this paper predict soil-water storage until the end of this century for the crops evaluated, as well as a comparison of the soil-water storage predictions with the course of the soil-water storage during the reference period.

ESTIMATING EVAPOTRANSPIRATION FROM IRRIGATED CROPS IN SOUTHWESTERN ONTARIO

1981 ◽  
Vol 61 (2) ◽  
pp. 425-435 ◽  
Author(s):  
C. S. TAN ◽  
J. M. FULTON
Keyword(s):  
Soil Water ◽  
Crop Yields ◽  
Root Zone ◽  
Sandy Loam ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Water Storage ◽  
Soil Water Storage ◽  
Climatic Data ◽  
Wide Range

Several years of daily evapotranspiration (ET) data for irrigated early potatoes, corn and processing tomatoes, grown on Fox sandy loam measured by floating lysimeters and estimated by meteorological data were used to evaluate an equilibrium evapotranspiration (ETeq) model. A reasonable relationship was obtained between values estimated by the model and those measured by floating lysimeters. The ETeq model can be used to estimate daily ET over a wide range of soil moisture and foliage cover conditions. ETeq can be estimated from readily available climatic data in the form: ETeq = (0.48 + 0.01 Ta) [(0.114 + 0.365n/N) K↓a − 0.039]; where Ta is the mean daily air temperature (°C); n is sunshine duration (h); N is maximum hours of bright sunshine (h); K↓a is solar energy received at the top of the atmosphere (mm/day). At high soil water storage in the root zone, the ET/ETeq remained constant, whereas, at low soil water storage, the ET/ETeq decreased linearly with decreasing soil water storage. The total crop yields were directly related to growing season accumulated ET.

scholarly journals Comparison of the monitored and modeled soil water storage of the upper soil layer: the influence of soil properties and groundwater table level

2010 ◽  
Vol 58 (4) ◽  
pp. 279-283 ◽  
Author(s):  
Július Šútor ◽  
Vlasta Štekauerová ◽  
Viliam Nagy
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Layer ◽  
Water Storage ◽  
Groundwater Table ◽  
Soil Water Balance ◽  
Soil Water Storage

Comparison of the monitored and modeled soil water storage of the upper soil layer: the influence of soil properties and groundwater table levelIn the study ofTomlain(1997) a soil water balance model was applied to evaluate the climate change impacts on the soil water storage in the Hurbanovo locality (Southwestern Slovakia), using the climate change scenarios of Slovakia for the years 2010, 2030, and 2075 by the global circulation models CCCM, GISS and GFD3. These calculations did not take into consideration neither the various soil properties, nor the groundwater table influence on soil water content. In this study, their calculated data were compared with those monitored at the same sites. There were found significant differences between resulting soil water storage of the upper 100 cm soil layer, most probably due to cappilary rise from groundwater at sites 2 and 3. It was shown, that the soil properties and groundwater table depth are importat features strongly influencing soil water content of the upper soil layer; thus the application of the soil water balance equation (Eq. (1)), neglecting the above mentioned factors, could lead to the results far from reality.

scholarly journals Developments in Climate and Soil Water Storage in the Locality of Poiplie

2013 ◽  
Vol 21 (1) ◽  
pp. 1-8
Author(s):  
Mária Pásztorová
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Emission Scenario ◽  
Water Storage ◽  
Open Water ◽  
Extreme Weather Events ◽  
Soil Water Storage ◽  
Modern World ◽  
Alluvial Forests ◽  
The Impact

Abstract Climate change is one of the largest threats to the modern world. It is primarily experienced via changes and extreme weather events, including air temperature changes, the uneven distribution of precipitation and an increase in the alteration of torrential short-term precipitation and longer non-precipitation periods. However climate change is not only a change in the weather; it also has a much larger impact on an ecosystem. As a result of expected climate change, a lack of either surface water or groundwater could occur within wetlands; thus, the existence of wetlands and their flora and fauna could be threatened. This submitted work analyses the impact of climate change on the wetland ecosystems of Poiplie, which is situated in the south of Slovakia in the Ipeľ river basin. The area is an important wetland biotope with rare plant and animal species, which mainly live in open water areas, marshes, wet meadows and alluvial forests. To evaluate any climate change, the CGCM 3.1 model, two emission scenarios, the A2 emission scenario (pessimistic) and the B1 emission scenario (optimistic), were used within the regionalization. For simulating the soil water storage, which is one of the components of a soil water regime, the GLOBAL mathematical model was used.

scholarly journals Visual Analytics for Climate Change Detection in Meteorological Time-Series

Forecasting ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 276-289
Author(s):  
Milena Vuckovic ◽  
Johanna Schmidt
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Change Detection ◽  
Visual Analytics ◽  
Structural Changes ◽  
Time Series Data ◽  
Meteorological Data ◽  
Series Data ◽  
Climate Change Signal ◽  
Climate Change Detection

The importance of high-resolution meteorological time-series data for detection of transformative changes in the climate system is unparalleled. These data sequences allow for a comprehensive study of natural and forced evolution of warming and cooling tendencies, recognition of distinct structural changes, and periodic behaviors, among other things. Such inquiries call for applications of cutting-edge analytical tools with powerful computational capabilities. In this regard, we documented the application potential of visual analytics (VA) for climate change detection in meteorological time-series data. We focused our study on long- and short-term past-to-current meteorological data of three Central European cities (i.e., Vienna, Munich, and Zürich), delivered in different temporal intervals (i.e., monthly, hourly). Our aim was not only to identify the related transformative changes, but also to assert the degree of climate change signal that can be derived given the varying granularity of the underlying data. As such, coarse data granularity mostly offered insights on general trends and distributions, whereby a finer granularity provided insights on the frequency of occurrence, respective duration, and positioning of certain events in time. However, by harnessing the power of VA, one could easily overcome these limitations and go beyond the basic observations.

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