Impact of Eastern Redcedar Proliferation on Water Resources in the Great Plains USA—Current State of Knowledge

In the Great Plains of the central United States, water resources for human and aquatic life rely primarily on surface runoff and local recharge from rangelands that are under rapid transformation to woodland by the encroachment of Eastern redcedar (redcedar; Juniperus virginiana) trees. In this synthesis, the current understanding and impact of redcedar encroachment on the water budget and water resources available for non-ecosystem use are reviewed. Existing studies concluded that the conversion from herbaceous-dominated rangeland to redcedar woodland increases precipitation loss to canopy interception and vegetation transpiration. The decrease of soil moisture, particularly for the subsurface soil layer, is widely documented. The depletion of soil moisture is directly related to the observed decrease in surface runoff, and the potential of deep recharge for redcedar encroached watersheds. Model simulations suggest that complete conversion of the rangelands to redcedar woodland at the watershed and basin scale in the South-central Great Plains would lead to reduced streamflow throughout the year, with the reductions of streamflow between 20 to 40% depending on the aridity of the climate of the watershed. Recommended topics for future studies include: (i) The spatial dynamics of redcedar proliferation and its impact on water budget across a regional hydrologic network; (ii) the temporal dynamics of precipitation interception by the herbaceous canopy; (iii) the impact of redcedar infilling into deciduous forests such as the Cross Timbers and its impact on water budget and water availability for non-ecosystem use; (iv) land surface and climate interaction and cross-scale hydrological modeling and forecasting; (v) impact of redcedar encroachment on sediment production and water quality; and (vi) assessment and efficacy of different redcedar control measures in restoring hydrological functions of watershed.

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Assimilation of Satellite-Derived Soil Moisture for Improved Forecasts of the Great Plains Low-Level Jet

Monthly Weather Review ◽

10.1175/mwr-d-20-0185.1 ◽

2020 ◽

Vol 148 (11) ◽

pp. 4607-4627

Author(s):

Craig R. Ferguson ◽

Shubhi Agrawal ◽

Mark C. Beauharnois ◽

Geng Xia ◽

D. Alex Burrows ◽

...

Keyword(s):

Soil Moisture ◽

Wind Speed ◽

Data Assimilation ◽

Great Plains ◽

Wrf Model ◽

Added Value ◽

Low Level ◽

Convective Systems ◽

South Central ◽

Mesoscale Convective

AbstractIn the context of forecasting societally impactful Great Plains low-level jets (GPLLJs), the potential added value of satellite soil moisture (SM) data assimilation (DA) is high. GPLLJs are both sensitive to regional soil moisture gradients and frequent drivers of severe weather, including mesoscale convective systems. An untested hypothesis is that SM DA is more effective in forecasts of weakly synoptically forced, or uncoupled GPLLJs, than in forecasts of cyclone-induced coupled GPLLJs. Using the NASA Unified Weather Research and Forecasting (NU-WRF) Model, 75 GPLLJs are simulated at 9-km resolution both with and without NASA Soil Moisture Active Passive SM DA. Differences in modeled SM, surface sensible (SH) and latent heat (LH) fluxes, 2-m temperature (T2), 2-m humidity (Q2), PBL height (PBLH), and 850-hPa wind speed (W850) are quantified for individual jets and jet-type event subsets over the south-central Great Plains, as well as separately for each GPLLJ sector (entrance, core, and exit). At the GPLLJ core, DA-related changes of up to 5.4 kg m−2 in SM can result in T2, Q2, LH, SH, PBLH, and W850 differences of 0.68°C, 0.71 g kg−2, 59.9 W m−2, 52.4 W m−2, 240 m, and 4 m s−1, respectively. W850 differences focus along the jet axis and tend to increase from south to north. Jet-type differences are most evident at the GPLLJ exit where DA increases and decreases W850 in uncoupled and coupled GPLLJs, respectively. Data assimilation marginally reduces negative wind speed bias for all jets, but the correction is greater for uncoupled GPLLJs, as hypothesized.

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Evaluation of the Impact of Climate Change on Runoff Generation in an Andean Glacier Watershed

Water ◽

10.3390/w12123547 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3547

Author(s):

Rossana Escanilla-Minchel ◽

Hernán Alcayaga ◽

Marco Soto-Alvarez ◽

Christophe Kinnard ◽

Roberto Urrutia

Keyword(s):

Climate Change ◽

Water Resources ◽

Emission Scenario ◽

Water Discharge ◽

Climate Change Scenarios ◽

Climate Trend ◽

Snow Storage ◽

South Central ◽

Recent Climate ◽

The Impact

Excluding Antarctica and Greenland, 3.8% of the world’s glacier area is concentrated in Chile. The country has been strongly affected by the mega drought, which affects the south-central area and has produced an increase in dependence on water resources from snow and glacier melting in dry periods. Recent climate change has led to an elevation of the zero-degree isotherm, a decrease in solid-state precipitation amounts and an accelerated loss of glacier and snow storage in the Chilean Andes. This situation calls for a better understanding of future water discharge in Andean headwater catchments in order to improve water resources management in glacier-fed populated areas. The present study uses hydrological modeling to characterize the hydrological processes occurring in a glacio-nival watershed of the central Andes and to examine the impact of different climate change scenarios on discharge. The study site is the upper sub-watershed of the Tinguiririca River (area: 141 km2), of which nearly 20% is covered by Universidad Glacier. The semi-distributed Snowmelt Runoff Model + Glacier (SRM+G) was forced with local meteorological data to simulate catchment runoff. The model was calibrated on even years and validated on odd years during the 2008–2014 period and found to correctly reproduce daily runoff. The model was then forced with downscaled ensemble projected precipitation and temperature series under the RCP 4.5 and RCP 8.5 scenarios, and the glacier adjusted using a volume-area scaling relationship. The results obtained for 2050 indicate a decrease in mean annual discharge (MAD) of 18.1% for the lowest emission scenario and 43.3% for the most pessimistic emission scenario, while for 2100 the MAD decreases by 31.4 and 54.2%, respectively, for each emission scenario. Results show that decreasing precipitation lead to reduced rainfall and snowmelt contributions to discharge. Glacier melt thus partly buffers the drying climate trend, but our results show that the peak water occurs near 2040, after which glacier depletion leads to reducing discharge, threatening the long-term water resource availability in this region.

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Impacts of Crop Variety and Time of Inoculation on the Susceptibility and Tolerance of Winter Wheat to Wheat streak mosaic virus

Plant Disease ◽

10.1094/pdis-12-13-1210-re ◽

2014 ◽

Vol 98 (8) ◽

pp. 1060-1065 ◽

Cited By ~ 6

Author(s):

Z. Miller ◽

F. Menalled ◽

D. Ito ◽

M. Moffet ◽

M. Burrows

Keyword(s):

Winter Wheat ◽

Mosaic Virus ◽

Great Plains ◽

Disease Risk ◽

Wheat Yield ◽

Wheat Streak Mosaic Virus ◽

Northern Great Plains ◽

Yield Losses ◽

South Central ◽

The Impact

Plant genotype, age, size, and environmental factors can modify susceptibility and tolerance to disease. Understanding the individual and combined impacts of these factors is needed to define improved disease management strategies. In the case of Wheat streak mosaic virus (WSMV) in winter wheat, yield losses and plant susceptibility have been found to be greatest when the crop is exposed to the virus in the fall in the central and southern Great Plains. However, the seasonal dynamics of disease risk may be different in the northern Great Plains, a region characterized by a relatively cooler fall conditions, because temperature is known to modify plant–virus interactions. In a 2-year field study conducted in south-central Montana, we compared the impact of fall and spring WSMV inoculations on the susceptibility, tolerance, yield, and grain quality of 10 winter wheat varieties. Contrary to previous studies, resistance and yields were lower in the spring than in the fall inoculation. In all, 5 to 7% of fall-inoculated wheat plants were infected with WSMV and yields were often similar to uninoculated controls. Spring inoculation resulted in 45 to 57% infection and yields that were 15 to 32% lower than controls. Although all varieties were similarly susceptible to WSMV, variations in tolerance (i.e., yield losses following exposure to the virus) were observed. These results support observations that disease risk and impacts differ across the Great Plains. Possible mechanisms include variation in climate and in the genetic composition of winter wheat and WSMV across the region.

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Future Climate Change Impact on the Nyabugogo Catchment Water Balance in Rwanda

Water ◽

10.3390/w13243636 ◽

2021 ◽

Vol 13 (24) ◽

pp. 3636

Author(s):

Adeline Umugwaneza ◽

Xi Chen ◽

Tie Liu ◽

Zhengyang Li ◽

Solange Uwamahoro ◽

...

Keyword(s):

Climate Change ◽

Water Resources ◽

Water Balance ◽

Surface Runoff ◽

Hydrological Cycle ◽

Swat Model ◽

Global Climate Models ◽

Future Climate Change ◽

Baseline Scenario ◽

The Impact

Droughts and floods are common in tropical regions, including Rwanda, and are likely to be aggravated by climate change. Consequently, assessing the effects of climate change on hydrological systems has become critical. The goal of this study is to analyze the impact of climate change on the water balance in the Nyabugogo catchment by downscaling 10 global climate models (GCMs) from CMIP6 using the inverse distance weighting (IDW) method. To apply climate change signals under the Shared Socioeconomic Pathways (SSPs) (low and high emission) scenarios, the Soil and Water Assessment Tool (SWAT) model was used. For the baseline scenario, the period 1950–2014 was employed, whereas the periods 2020–2050 and 2050–2100 were used for future scenario analysis. The streamflow was projected to decrease by 7.2 and 3.49% under SSP126 in the 2020–2050 and 2050–2100 periods, respectively; under SSP585, it showed a 3.26% increase in 2020–2050 and a 4.53% decrease in 2050–2100. The average annual surface runoff was projected to decrease by 11.66 (4.40)% under SSP126 in the 2020–2050 (2050–2100) period, while an increase of 3.25% in 2020–2050 and a decline of 5.42% in 2050–2100 were expected under SSP585. Climate change is expected to have an impact on the components of the hydrological cycle (such as streamflow and surface runoff). This situation may, therefore, lead to an increase in water stress, calling for the integrated management of available water resources in order to match the increasing water demand in the study area. This study’s findings could be useful for the establishment of adaptation plans to climate change, managing water resources, and water engineering.

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Indications of Surface and Sub-Surface Hydrologic Properties from SMAP Soil Moisture Retrievals

Hydrology ◽

10.3390/hydrology5030036 ◽

2018 ◽

Vol 5 (3) ◽

pp. 36 ◽

Cited By ~ 5

Author(s):

Paul Dirmeyer ◽

Holly Norton

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Soil Column ◽

Remotely Sensed ◽

Subsurface Geology ◽

South Central ◽

Significant Relationships ◽

The Impact ◽

Soil Moisture Variability ◽

Moisture Variability

Variability and covariability of land properties (soil, vegetation and subsurface geology) and remotely sensed soil moisture over the southeast and south-central U.S. are assessed. The goal is to determine whether satellite soil moisture memory contains information regarding land properties, especially the distribution karst formations below the active soil column that have a bearing on land-atmosphere feedbacks. Local (within a few tens of km) statistics of land states and soil moisture are considered to minimize the impact of climatic variations, and the local statistics are then correlated across the domain to illuminate significant relationships. There is a clear correspondence between soil moisture memory and many land properties including karst distribution. This has implications for distributed land surface modeling, which has not considered preferential water flows through geologic formations. All correspondences are found to be strongest during spring and fall, and weak during summer, when atmospheric moisture demand appears to dominate soil moisture variability. While there are significant relationships between remotely-sensed soil moisture variability and land properties, it will be a challenge to use satellite data for terrestrial parameter estimation as there is often a great deal of correlation among soil, vegetation and karst property distributions.

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The SMOS-Derived Soil Water EXtent and equivalent layer thickness facilitate determination of soil water resources

Scientific Reports ◽

10.1038/s41598-020-75475-x ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Boguslaw Usowicz ◽

Mateusz Lukowski ◽

Jerzy Lipiec

Keyword(s):

Soil Moisture ◽

Water Resources ◽

Soil Water ◽

Penetration Depth ◽

Layer Thickness ◽

Classical Statistics ◽

Soil Water Resources ◽

The Impact ◽

Equivalent Layer ◽

Smos Satellite

Abstract The assessment of water resources in soil is important in understanding the water cycle in the natural environment and the processes of water exchange between the soil and the atmosphere. The main objective of the study was to assess water resources (in 2010–2013) in the topsoil from satellite (SMOS) and in situ (ground) measurements using the SWEX_PD approach (Soil Water EXtent at Penetration Depth). The SWEX_PD is a result of multiplying soil moisture (SM) and radiation penetration depth (PD) for each pixel derived from the SMOS satellite. The PD, being a manifold of the wavelength λ0 equal to 21 cm, was determined from the weekly SMOS L2 measurement data based on the real and imaginary part of complex dielectric constant. The SWEX_PD data were compared with soil water resources (WR) calculated from the sum of components derived from multiplication of soil moisture (SM) and layer thickness in nine agrometeorological stations located along the eastern border of Poland. Each study site consisted of seven neighbouring Discrete Global Grid pixels (nodes spaced at 15 km) including the central ones with agrometeorological stations. The study area included different types of soils and land covers. The agreement between the water resources obtained from the SWEX_PD and ground measurements (WR) was quantified using classical statistics and Bland–Altman's plots. Calibrated Layer Thickness (CLT = dbias) from 8 to 28 cm was obtained with a low values of bias (close to zero), limits of agreements, and confidence intervals for all the SWEX_PD, depending on the pixel location. The results revealed that the use of the SWEX_PD for assessing soil water resources is the most reliable approach in the study area. Additionally, the data from Bland–Altman plots and the equation proposed in these studies allowed calculation of the Equivalent Layer Thickness (ELT = $$d_{ei}^{SWEX}$$ d ei SWEX ), which corresponds to the water resources derived from the SMOS satellite at the same time as (SM) measurements performed in the agrometeorological stations. The ranges of the mean, standard deviation, minimum, maximum, and coefficient of variation (CV) of ELT among all pixels and stations were 8.28–28.7 cm, 3.27–12.66 cm, 3.03–10.87 cm, 19.23–94.97 cm, and 24.72–98.79%, respectively. The ranges of the characteristics depended on environmental conditions and their means were close to the values of the calibrated layer thickness. The impacts of soil texture, organic matter, vegetation, and their interactive effects on the differentiation and agreement of soil water resources obtained from SWEX_PD vs. data from ground measurements in the study area are discussed. Further studies are required to address the impact of the environmental factors to improve the assessment of soil water resources based on satellite SM products (retrievals).

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Ten fundamental questions for water resources development in the Ganges: myths and realities

Water Policy ◽

10.2166/wp.2013.006 ◽

2013 ◽

Vol 15 (S1) ◽

pp. 147-164 ◽

Cited By ~ 30

Author(s):

Claudia Sadoff ◽

Nagaraja Rao Harshadeep ◽

Donald Blackmore ◽

Xun Wu ◽

Anna O'Donnell ◽

...

Keyword(s):

Water Resources ◽

Policy Makers ◽

Ganges Basin ◽

Systems Perspective ◽

Low Flows ◽

Basin Scale ◽

Modelling Techniques ◽

The Ganges ◽

The Impact ◽

Resources Planning

This paper summarizes the results of the Ganges Strategic Basin Assessment (SBA), a 3-year, multi-disciplinary effort undertaken by a World Bank team in cooperation with several leading regional research institutions in South Asia. It begins to fill a crucial knowledge gap, providing an initial integrated systems perspective on the major water resources planning issues facing the Ganges basin today, including some of the most important infrastructure options that have been proposed for future development. The SBA developed a set of hydrological and economic models for the Ganges system, using modern data sources and modelling techniques to assess the impact of existing and potential new hydraulic structures on flooding, hydropower, low flows, water quality and irrigation supplies at the basin scale. It also involved repeated exchanges with policy makers and opinion makers in the basin, during which perceptions of the basin could be discussed and examined. The study's findings highlight the scale and complexity of the Ganges basin. In particular, they refute the broadly held view that upstream water storage, such as reservoirs in Nepal, can fully control basin-wide flooding. In addition, the findings suggest that such dams could potentially double low flows in the dry months. The value of doing so, however, is surprisingly unclear and similar storage volumes could likely be attained through better groundwater management. Hydropower development and trade are confirmed to hold real promise (subject to rigorous project level assessment with particular attention to sediment and seismic risks) and, in the near to medium term, create few significant tradeoffs among competing water uses. Significant uncertainties – including climate change – persist, and better data would allow the models and their results to be further refined.

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Investigating the Impact of Climate Change on Future Runoff of River Satluj

Journal of Hydrology and Meteorology ◽

10.3126/jhm.v8i1.15568 ◽

2016 ◽

Vol 8 (1) ◽

pp. 10-21

Author(s):

Narayan P Gautam ◽

Manohar Arora ◽

N.K. Goel ◽

A.R.S. Kumar

Keyword(s):

Climate Change ◽

Water Resources ◽

General Circulation ◽

Circulation Model ◽

Climate Change Scenarios ◽

Impact Of Climate Change ◽

Basin Scale ◽

The Future ◽

Future Climatic Condition ◽

The Impact

Climate change has been emerging as one of the challenges in the global environment. Information of predicted climatic changes in basin scale is highly useful to know the future climatic condition in the basin that ultimately becomes helpful to carry out planning and management of the water resources available in the basin. Climatic scenario is a plausible and often simplified representation of the future climate, based on an internally consistent set of climatological relationships that has been constructed for explicit use in investigating the potential consequences of anthropogenic climate change. This study based on statistical downscaling, provide good example focusing on predicting the rainfall and runoff patterns, using the coarse general circulation model (GCM) outputs. The outputs of the GCMs are utilized to study the impact of climate change on water resources. The present study has been taken up to identify the climate change scenarios for Satluj river basin, India.Journal of Hydrology and Meteorology, Vol. 8(1) p.10-21

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Land use and water quality in watersheds in the State of São Paulo, based on GIS and SWAT data

Ambiente e Agua - An Interdisciplinary Journal of Applied Science ◽

10.4136/ambi-agua.2325 ◽

2019 ◽

Vol 14 (5) ◽

pp. 1

Author(s):

Denise Piccirillo Barbosa da Veiga ◽

Manuel Enrique Gamero Guandique ◽

Adelaide Cassia Nardocci

Keyword(s):

Land Use ◽

Water Resources ◽

Surface Runoff ◽

Integrated Management ◽

Swat Model ◽

Land Use Classification ◽

Hydrological Simulation ◽

Hydrological Balance ◽

Gis Tools ◽

The Impact

Land use influences the quality and availability of water resources, but Brazil has made little progress in integrated watershed management. This study therefore applied geoprocessing for land-use classification and evaluated the impact on the hydrological balance in order to contribute to the integrated management of water resources. Using GIS tools, two drainage areas from the water catchment points of two municipalities, Santa Cruz das Palmeiras and Piedade, were delimited; land-use mapping was carried out using the supervised classification method of satellite images, and the SWAT model was applied for hydrological simulation. The methods used were appropriate. The surface runoff was related to the absence of vegetation and the predominance of exposed soil. The relationship between land use/land cover and the hydrological balance was evidenced, especially the impact of agricultural activities and the lack of natural vegetation in the surface runoff.

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Revealing the impact of deforestation on hydrology using remote sensing and land surface modeling

10.5194/egusphere-egu2020-9612 ◽

2020 ◽

Author(s):

Michiel Maertens ◽

Gabrielle De Lannoy ◽

Sebastian Apers ◽

Sujay Kumar

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Land Cover ◽

Land Surface ◽

Water Budget ◽

Land Surface Modeling ◽

Operational Level ◽

Vegetation Parameters ◽

The Impact ◽

Level 2

<p>This study aims at better understanding the impact of deforestation on the local hydrology over the Argentinian Chaco, using land surface modeling and remote sensing data. The Chaco is an ecoregion characterized by unprecedented deforestation since the 1980s, mainly for cattle ranging and soybean production. More specifically, default climatological vegetation parameters (LAI, GVF) and static land cover in state-of-the-art land surface models (LSM), grouped within the NASA Land Information System (LIS), are updated using satellite-based dynamic vegetation parameters and yearly land use maps to feed the models with deforestation.</p><p>The presentation will show a spatio-temporal analysis of long-term water budget simulations using a range of LSMs (Noah, CLM, CLSM) in which dynamically updated vegetation and land cover parameters are included. Our simulations indicate that different LSMs result in a different partitioning of the total water budget, but all indicate an increase in soil moisture and percolation over the deforested areas. &#160;Model output is evaluated using in situ soil moisture data, and various soil moisture retrieval products from SMOS (operational Level 2 and SMOS-IC) and SMAP (operational Level 2) and evapotranspiration data from GLEAM.</p>

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