Implementation of Snowpack Treatment in the CPC Water Balance Model and Its Impact on Drought Assessment

2021 ◽  
Author(s):  
Jorge Arevalo ◽  
Josh Welty ◽  
Yun Fan ◽  
Xubin Zeng
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Water Balance Model ◽  
Balance Model ◽  
Drought Indices ◽  
Leaky Bucket ◽  
Drought Assessment ◽  
Temperature And Precipitation ◽  
Drought Conditions

AbstractDroughts are a worldwide concern, thus assessment efforts are conducted by many centers around the world, mainly through simple drought indices which usually neglect important hydrometeorological processes or require variables available only from complex Land Surface Models (LSMs). The U.S. Climate Prediction Center (CPC) uses the Leaky Bucket (LB) water-balance model to post-process temperature and precipitation, providing soil moisture (SM) anomalies to assess drought conditions. However, despite its crucial role in the water cycle, snowpack has been neglected by LB and most drought indices.Taking advantage of the high-quality snow water equivalent (SWE) data from the University of Arizona (UA), a single-layer snow scheme, forced by daily temperature and precipitation only, is developed for LB implementation and tested with two independent forcing datasets. Compared against the UA and SNOTEL SWE data over CONUS, LB outperforms a sophisticated LSM (Noah/NLDAS-2), with the median LB vs SNOTEL correlation (RMSE) about 40% (26%) higher (lower) than that from Noah/NLDAS-2, with only slight differences due to different forcing datasets.The changes in the temporal variability of SM due to the snowpack treatment lead to improved temporal and spatial distribution of drought conditions in the LB simulations compared to the reference U.S. Drought Monitor maps, highlighting the importance of snowpack inclusion in drought assessment. The simplicity but reasonable reliability of the LB with snowpack treatment makes it suitable for drought monitoring and forecasting in both snow-covered and snow-free areas, while only requiring precipitation and temperature data (markedly less than other water-balance-based indices).

scholarly journals Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data

2010 ◽  
Vol 14 (10) ◽  
pp. 2141-2151 ◽  
Author(s):  
C. Corbari ◽  
J. A. Sobrino ◽  
M. Mancini ◽  
V. Hidalgo
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model ◽  
Hydrological Process ◽  
Distributed Hydrological Model ◽  
Data Set

Abstract. Land surface temperature is the link between soil-vegetation-atmosphere fluxes and soil water content through the energy water balance. This paper analyses the representativeness of land surface temperature (LST) for a distributed hydrological water balance model (FEST-EWB) using LST from AHS (airborne hyperspectral scanner), with a spatial resolution between 2–4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the representative equilibrium temperature that closes the energy balance equation in the distributed hydrological model. Diurnal and nocturnal images are analyzed due to the non stable behaviour of the thermodynamic temperature and to the non linear effects induced by spatial heterogeneity. Spatial autocorrelation and scale of fluctuation of land surface temperature from FEST-EWB and AHS are analysed at different aggregation areas to better understand the scale of representativeness of land surface temperature in a hydrological process. The study site is the agricultural area of Barrax (Spain) that is a heterogeneous area with a patchwork of irrigated and non irrigated vegetated fields and bare soil. The used data set was collected during a field campaign from 10 to 15 July 2005 in the framework of the SEN2FLEX project.

scholarly journals Land Surface Controls on Hydroclimatic Means and Variability

2012 ◽  
Vol 13 (5) ◽  
pp. 1604-1620 ◽  
Author(s):  
Randal D. Koster ◽  
Sarith P. P. Mahanama
Keyword(s):  
Soil Moisture ◽  
Simple Model ◽  
Water Balance ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model ◽  
Surface Moisture ◽  
Surface Models ◽  
Moisture Fluxes ◽  
Further Development

Abstract Hydroclimatic means and variability are determined in large part by the control of soil moisture on surface moisture fluxes, particularly evapotranspiration and runoff. This control is examined here using a simple water balance model and multidecadal observations covering the conterminous United States. Under the assumption that the relevant soil moisture–evapotranspiration and soil moisture–runoff relationships are, to first order, universal, the simple model illustrates the degree to which they interact to determine spatial distributions of hydroclimatic means and variability. In the process, the simple model provides estimates for the underlying relationships that operate in nature. The hydroclimatic sensitivities established with the simple water balance model can be used to evaluate more complex land surface models and to guide their further development, as demonstrated herein with an example.

scholarly journals Land surface temperature representativeness in an heterogeneous area through a distributed energy-water balance model and remote sensing data

2010 ◽  
Vol 7 (4) ◽  
pp. 5335-5368 ◽  
Author(s):  
C. Corbari ◽  
J. A. Sobrino ◽  
M. Mancini ◽  
V. Hidalgo
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model ◽  
Hydrological Process ◽  
Distributed Hydrological Model ◽  
Data Set

Abstract. Land surface temperature is the link between soil-vegetation-atmosphere fluxes and soil water content through the energy water balance. This paper analyses the representativeness of land surface temperature (LST) for a distributed hydrological water balance model (FEST-EWB) using LST from AHS (airborne hyperspectral scanner), with a spatial resolution between 2–4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the representative equilibrium temperature that closes the energy balance equation in the distributed hydrological model. Diurnal and nocturnal images are analyzed due to the non stable behaviour of the thermodynamic temperature and to the non linear effects induced by spatial heterogeneity. Spatial autocorrelation and scale of fluctuation of land surface temperature from FEST-EWB and AHS are analysed at different aggregation areas to better understand the scale of representativeness of land surface temperature in an hydrological process. The study site is the agricultural area of Barrax (Spain) that is a heterogeneous area with an alternation of irrigated and non irrigated vegetated field and bare soil. The used data set was collected during a field campaign from 10 to 15 July 2005 in the framework of the SEN2FLEX project.

Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin

2021 ◽  
Vol 188 ◽  
pp. 104466
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Guangcheng Hu ◽  
Chaolei Zheng ◽  
Massimo Menenti ◽  
...  
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model

scholarly journals Evapotranspiration Estimates at High Spatial and Temporal Resolutions from an Energy–Water Balance Model and Satellite Data in the Capitanata Irrigation Consortium

2020 ◽  
Vol 12 (24) ◽  
pp. 4083
Author(s):  
Chiara Corbari ◽  
Drazen Skokovic Jovanovic ◽  
Luigi Nardella ◽  
Josè Sobrino ◽  
Marco Mancini
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Flash Flood ◽  
Calibration Procedure ◽  
Water Balance Model ◽  
Balance Model

The feasibility of combining remotely sensed land surface temperature data (LST) and an energy–water balance model for improving evapotranspiration estimates over time distributed in space in the Capitanata irrigation consortium is analysed. The energy–water balance FEST-EWB model (flash flood event-based spatially distributed rainfall–runoff transformation—energy–water balance model) computes continuously in time and is distributed in space soil moisture (SM) and evapotranspiration (ET) fluxes solving for a land surface temperature that closes the energy–water balance equations. The comparison between modelled and observed LST was used to calibrate the model soil parametres with a newly developed pixel to pixel calibration procedure. The effects of the calibration procedure were analysed against ground measures of soil moisture and evapotranspiration. The FEST-EWB model was run at 30 m of spatial resolution for the period between 2013 and 2018. Absolute errors of 2.5 °C were obtained for LST estimates against satellite data; while RMSE around 0.06 and 40 Wm−2 are found for ground measured soil moisture and latent heat flux, respectively.

Remote Sensing Based Assessment of Agricultural Droughts in Sub-Watersheds of Upper Bhima Basin, India

2019 ◽  
Vol 2 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Nayan Zagade ◽  
Ajaykumar Kadam ◽  
Bhavana Umrikar ◽  
Bhagyashri Maggirwar
Keyword(s):  
Remote Sensing ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Agricultural Sector ◽  
Health Index ◽  
Drought Assessment ◽  
Drought Conditions ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Vegetation Health Index

Drought assessment for agricultural sector is vital in order to deal with the water scarcity in Ahmednagar and Pune districts, particularly in sub-watersheds of upper catchment of the River Bhima. Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite data (2000, 2002, 2009, 2014, 2015 and 2017) for the years receiving less rainfall have been procured and various indices were computed to understand the intensity of agricultural droughts in the area. Vegetation health index (VHI) is computed on the basis of vegetation moisture, vegetation condition and land surface temperature condition. Most of the reviewed area shows moderate to extreme drought conditions.

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