scholarly journals Global Irrigation Characteristics and Effects Simulated by Fully Coupled Land Surface, River, and Water Management Models in E3SM

2020 ◽  
Vol 12 (10) ◽  
Author(s):  
Tian Zhou ◽  
L. Ruby Leung ◽  
Guoyong Leng ◽  
Nathalie Voisin ◽  
Hong‐Yi Li ◽  
...  
Keyword(s):  
Water Management ◽  
Land Surface ◽  
Management Models ◽  
Fully Coupled

Simulated and Observed Preindustrial to Modern Vegetation and Climate Changes*

2005 ◽  
Vol 18 (17) ◽  
pp. 3650-3671 ◽  
Author(s):  
Michael Notaro ◽  
Zhengyu Liu ◽  
Robert Gallimore ◽  
Stephen J. Vavrus ◽  
John E. Kutzbach ◽  
...  
Keyword(s):  
Land Surface ◽  
Boreal Forests ◽  
Ring Width ◽  
Warming Trend ◽  
Physiological Effect ◽  
Co2 Fertilization ◽  
Vegetation Growth ◽  
Fully Coupled ◽  
Global Surface ◽  
Vegetation And Climate

Abstract Rising levels of carbon dioxide since the preindustrial era have likely contributed to an observed warming of the global surface, and observations show global greening and an expansion of boreal forests. This study reproduces observed climate and vegetation trends associated with rising CO2 using a fully coupled atmosphere–ocean–land surface GCM with dynamic vegetation and decomposes the effects into physiological and radiative components. The simulated warming trend, strongest at high latitudes, was dominated by the radiative effect, although the physiological effect of CO2 on vegetation (CO2 fertilization) contributed to significant wintertime warming over northern Europe and central and eastern Asia. The net global greening of the model was primarily due to the physiological effect of increasing CO2, while the radiative and physiological effects combined to produce a poleward expansion of the boreal forests. Observed and simulated trends in tree ring width are consistent with the enhancement of vegetation growth by the physiological effect of rising CO2.

scholarly journals High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

2020 ◽  
Author(s):  
Benjamin Fersch ◽  
Alfonso Senatore ◽  
Bianca Adler ◽  
Joël Arnault ◽  
Matthias Mauder ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Weather Prediction ◽  
Surface Model ◽  
Near Surface ◽  
Ground Heat Flux ◽  
The Impact ◽  
Fully Coupled ◽  
Regional Water

<p>The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.</p>

scholarly journals GIS and Remote Sensing Application in Water Management in Agriculture Field

2020 ◽  
Author(s):  
Sassi Mohamed Taher
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Resources ◽  
Land Surface ◽  
Remotely Sensed ◽  
Irrigated Agriculture ◽  
Accurate Information ◽  
Remotely Sensed Data ◽  
Gis And Remote Sensing ◽  
Practical Applications

This document is meant to demonstrate the potential uses of remote sensing in managing water resources for irrigated agriculture and to create awareness among potential users. Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere transfer processes can lead to a better understanding of the relationships between crop growth and water management. Remote sensing and GIS was used to map the agriculture area and for detect the change. This was very useful for mapping availability and need of water resources but the problem was concentrating in data collection and analysis because this kind of information and expertise are not available in all country in the world mainly in the developing and under developed country or third world country. However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing.

scholarly journals Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach

2020 ◽  
Vol 24 (11) ◽  
pp. 5251-5277 ◽  
Author(s):  
Oliver Miguel López Valencia ◽  
Kasper Johansen ◽  
Bruno José Luis Aragón Solorio ◽  
Ting Li ◽  
Rasmus Houborg ◽  
...  
Keyword(s):  
Water Management ◽  
Saudi Arabia ◽  
Land Surface ◽  
Landsat 8 ◽  
Groundwater Abstraction ◽  
Model Fusion ◽  
Center Pivot ◽  
Gravimetric Data ◽  
Water Accounting ◽  
Fusion Approach

Abstract. The agricultural sector in Saudi Arabia has witnessed rapid growth in both production and area under cultivation over the last few decades. This has prompted some concern over the state and future availability of fossil groundwater resources, which have been used to drive this expansion. Large-scale studies using satellite gravimetric data show a declining trend over this region. However, water management agencies require much more detailed information on both the spatial distribution of agricultural fields and their varying levels of water exploitation through time than coarse gravimetric data can provide. Relying on self-reporting from farm operators or sporadic data collection campaigns to obtain needed information are not feasible options, nor do they allow for retrospective assessments. In this work, a water accounting framework that combines satellite data, meteorological output from weather prediction models, and a modified land surface hydrology model was developed to provide information on both irrigated crop water use and groundwater abstraction rates. Results from the local scale, comprising several thousand individual center-pivot fields, were then used to quantify the regional-scale response. To do this, a semi-automated approach for the delineation of center-pivot fields using a multi-temporal statistical analysis of Landsat 8 data was developed. Next, actual crop evaporation rates were estimated using a two-source energy balance (TSEB) model driven by leaf area index, land surface temperature, and albedo, all of which were derived from Landsat 8. The Community Atmosphere Biosphere Land Exchange (CABLE) model was then adapted to use satellite-based vegetation and related surface variables and forced with a 3 km reanalysis dataset from the Weather Research and Forecasting (WRF) model. Groundwater abstraction rates were then inferred by estimating the irrigation supplied to each individual center pivot, which was determined via an optimization approach that considered CABLE-based estimates of evaporation and TSEB-based satellite estimates. The framework was applied over two study regions in Saudi Arabia: a small-scale experimental facility of around 40 center pivots in Al Kharj that was used for an initial evaluation and a much larger agricultural region in Al Jawf province comprising more than 5000 individual fields across an area exceeding 2500 km2. Total groundwater abstraction for the year 2015 in Al Jawf was estimated at approximately 5.5 billion cubic meters, far exceeding any recharge to the groundwater system and further highlighting the need for a comprehensive water management strategy. Overall, this novel data–model fusion approach facilitates the compilation of national-scale groundwater abstractions while also detailing field-scale information that allows both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.

Comparing urban sub-catchment delineation approaches for dynamic hydrological modelling

2021 ◽  
Author(s):  
Yannick Back ◽  
Fabian Funke ◽  
Peter Marcus Bach ◽  
Joao Paulo Leitao ◽  
Wolfgang Rauch ◽  
...  
Keyword(s):  
Water Management ◽  
Urban Areas ◽  
Hydrological Cycle ◽  
Geographical Information ◽  
Surface Model ◽  
Urban Water ◽  
Rainfall Runoff ◽  
Management Models ◽  
Catchment Delineation ◽  
The Way

<p>In the face of rapid urban and population growth and with climate change altering precipitation patterns, urban water management is becoming increasingly demanding. Numerous software, tools and approaches to study urban water flow behaviour and model hydrological processes exist. However, the understanding of water movement in urban areas, especially during extreme events, and the physical principles behind them, as well as the interaction between the natural and the urban hydrological cycle is still incomplete. For decades, models suited for urban hydrological analysis greatly impacted the improvement of flood protection, public health and environmental protection, changing the way we look at urban water and stormwater management. In order to calculate accurate quantities of runoff in any rainfall/runoff model, information about urban sub-catchment characteristics plays an important role. Size, shape, topography, as well as land use influencing infiltration rates and evapotranspiration, are of great importance to calculate accurate runoff quantities on the urban scale. New implementations to reduce runoff towards the sewer system, such as decentralised stormwater techniques, increase the urgent need for accurate and high-resolution local/neighbourhood-scale information. Spatial and temporal developments require water management models to be connected with GIS (Geographical Information Systems). Initially not being developed to interact with each other, multiple approaches exist to combine GIS with water management models. Nevertheless, defining urban sub-catchments for rainfall-runoff modelling is often still performed manually using specific maps or using simple surface partitioning algorithms such as the Thiessen polygons. A significant disadvantage in generating urban sub-catchments manually is the fact that natural surface inclination is usually not considered, influencing the size and shape of the delineated sub-catchments. So far, only a few studies have devoted attention to improving the way urban sub-catchments are delineated and the information about their surface characteristics is generated. This study evaluates a GIS-based approach to automatically delineate urban sub-catchments accounting for the location of nodes (actual manholes or drain inlets) as sub-catchment outlets. In order to compare the influence of the sub-catchment delineation methods (1 to 3), we use (1) a digital surface model (DSM) and (2) a digital elevation model (DEM) to automatically delineate the urban sub-catchments and compare these two methods with each other as well as with (3) already manually derived sub-catchments of a specific case study. Furthermore, we compare hydraulic simulation results from the software SWMM with measured flow data to infer the most accurate sub-catchment delineation method.</p>

scholarly journals MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change

2020 ◽  
Vol 13 (10) ◽  
pp. 4713-4747
Author(s):  
Tokuta Yokohata ◽  
Tsuguki Kinoshita ◽  
Gen Sakurai ◽  
Yadu Pokhrel ◽  
Akihiko Ito ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Land Use ◽  
Land Use Change ◽  
Land Surface ◽  
Crop Yields ◽  
Land Surface Model ◽  
Climate System ◽  
Surface Model ◽  
Earth System

Abstract. Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. On the one hand, future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human-induced land-use change can affect the climate system through biogeophysical and biogeochemical effects. To investigate these interrelationships, we developed MIROC-INTEG-LAND (MIROC INTEGrated LAND surface model version 1), an integrated model that combines the land surface component of global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land-use models. The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balance, human water management, and crop growth incorporates a land use decision-making model based on economic activities. In MIROC-INTEG-LAND, spatially detailed information regarding water resources and crop yields is reflected in the prediction of future land-use change, which cannot be considered in the conventional integrated assessment models. In this paper, we introduce the details and interconnections of the submodels of MIROC-INTEG-LAND, compare historical simulations with observations, and identify various interactions between the submodels. By evaluating the historical simulation, we have confirmed that the model reproduces the observed states well. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand. The newly developed MIROC-INTEG-LAND could be combined with atmospheric and ocean models to develop an integrated earth system model to simulate the interactions among coupled natural–human earth system components.

Understanding uses and implications of water forecasting in multisectoral research

2021 ◽  
Author(s):  
Sean Turner ◽  
Nathalie Voisin
Keyword(s):  
Water Management ◽  
Large Scale ◽  
River Flow ◽  
Electrical Power ◽  
Water Reservoir ◽  
Temporal Distribution ◽  
Water Withdrawal ◽  
Water Release ◽  
Management Models ◽  
Research Activities

<p>The increasing availability and reliability of river flow forecasts has coincided with forecast-guided operating arrangements that seek to enhance the benefits of water reservoir operations. In the western United States, where winter snowpack depth indicates spring and summer flow, water release decisions may be informed with estimates of incoming water out to weeks and months ahead. Understanding how such medium to long-range forecasts affect the spatial and temporal distribution of water availability at across large basins and regions is necessary to accurately drive and constrain expansive, water-dependent system simulations, such grid-scale electrical power dispatch. This presentation will encompass recent research activities aimed at characterizing the use of forecasts and simulating their effects in large scale hydrological and water management models. Results show that forecasts must be included in reservoir models to accurately reproduce release decisions. Implementing these operations in large-scale hydrological models remains a significant challenge to be tackled by the community. Problems of simulated streamflow bias and lack of accurate data describing water withdrawal and consumption means must be addressed to harness realistic, forecast-based operations in large-scale water management models.</p>

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