Can the Budyko framework and satellite data help improve hydrological modeling in ungauged and poorly monitored catchments? The case study of the Lurín catchment in Peru

2020 ◽  
Author(s):  
Jan Bondy ◽  
Erwin Zehe ◽  
Jan Wienhöfer
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Temporal Dynamics ◽  
Hydrological Cycle ◽  
Monitoring Network ◽  
Remote Sensing Data ◽  
Water Balance Components ◽  
Spatial Estimates ◽  
Predictions In Ungauged Basins

<p>Predictions in ungauged basins still present one of the major challenges in hydrology. In many cases, the absence of a stream gauge also implies a low density of the meteorological monitoring network in these catchments and surroundings as well as little available data on water management infrastructure and agricultural consumptions. This combination creates a circle of uncertainties and thus individual influences of relevant water balance components are difficult to disentangle and quantify. </p><p>The original Budyko curve presents a very general model that yields, to first order, an estimate of the steady-state water balance of a catchment at the climatological scale, assuming its landscape and functioning has evolved naturally and free of anthropogenic interferences. Even at smaller time scales, the Budyko relationship allows approximating the water partitioning in the catchment, and thus helps correct erroneous assumptions[JW1]  or missing information about for instance unknown human-induced alterations. On the other hand, an increasing variety of global remote-sensing data products is becoming available providing spatial estimates of land surface properties such as for instance vegetation indexes or soil moisture. Even if the predictive power of such products in terms of absolute values remains questionable, it is possible to derive coarse spatial patterns or temporal dynamics to narrow down zones and orders of magnitude of interferences with the natural hydrological cycle such as reservoirs or irrigated lands. This study combines these two general approaches in order to improve hydrological modelling and system understanding of the semi-arid Lurín catchment in the Western Andes of Peru.</p>

scholarly journals HydroPy (v1.0): A new global hydrology model written in Python

2021 ◽  
Author(s):  
Tobias Stacke ◽  
Stefan Hagemann
Keyword(s):  
Surface Water ◽  
Water Balance ◽  
Land Surface ◽  
Max Planck ◽  
Water Balance Components ◽  
Meteorological Model ◽  
Land Surface Water ◽  
Hydrology Model ◽  
Flexible Infrastructure ◽  
The Tropics

Abstract. Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components as well as their past evolution and potential future development under various scenarios. While GHMs are a part of the Hydrologist's toolbox since several decades, the models are continuously developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max-Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge, however they can – at least to some part – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similar to MPI-HM and, thus, conclude the successful transition from MPI-HM to HydroPy.

scholarly journals What are the key drivers of regional differences in the water balance on the Tibetan Plateau?

2015 ◽  
Vol 12 (4) ◽  
pp. 4271-4314 ◽  
Author(s):  
S. Biskop ◽  
F. Maussion ◽  
P. Krause ◽  
M. Fink
Keyword(s):  
Tibetan Plateau ◽  
Water Balance ◽  
Hydrological Modeling ◽  
Integrated Approach ◽  
Water Levels ◽  
The Tibetan Plateau ◽  
Nam Co ◽  
Water Balance Components ◽  
South Central ◽  
Lake Basins

Abstract. Lake-level fluctuations in closed basins on the Tibetan Plateau (TP) indicate climate-induced changes in the regional water balance. However, little is known about the region's key hydrological parameters, hampering the interpretation of these changes. The purpose of this study is to contribute to a more quantitative understanding of these controls. Four lakes in the south-central part of the TP were selected to analyze the spatiotemporal variations of water-balance components: Nam Co and Tangra Yumco (indicating increasing water levels), and Mapam Yumco and Paiku Co (indicating stable or slightly decreasing water levels). We present the results of an integrated approach combining hydrological modeling, atmospheric-model output and remote-sensing data. The hydrological model J2000g was adapted and extended according to the specific characteristics of closed lake basins on the TP and driven with "High Asia Refined analysis (HAR)" data at 10 km resolution for the period 2001–2010. Our results reveal that because of the small portion of glacier areas (1 to 7% of the total basin area) the contribution of glacier melt water accounts for only 14–30% of total runoff during the study period. Precipitation is found to be the principal factor controlling the water-balance in the four studied basins. The positive water balance in the Nam Co and Tangra Yumco basins was primarily related to larger precipitation amounts and thus higher runoff rates in comparison with the Paiku Co and Mapam Yumco basins. This study highlights the benefits of combining atmospheric and hydrological modeling. The presented approach can be readily transferred to other ungauged lake basins on the TP, opening new directions of research. Future work should go towards increasing the atmospheric model's spatial resolution and a better assessment of the model-chain uncertainties, especially in this region where observational data is missing.

scholarly journals A worldwide analysis of trends in water-balance evapotranspiration

2013 ◽  
Vol 10 (5) ◽  
pp. 5739-5765 ◽  
Author(s):  
A. M. Ukkola ◽  
I. C. Prentice
Keyword(s):  
Water Balance ◽  
Interannual Variability ◽  
Land Surface ◽  
Time Series Data ◽  
Hydrological Cycle ◽  
Atmospheric Co2 ◽  
Series Data ◽  
Additional Control ◽  
Terrestrial Water ◽  
Strong Control

Abstract. Climate change is expected to alter the global hydrological cycle, with inevitable consequences for freshwater availability to people and ecosystems. But the attribution of recent trends in the terrestrial water balance remains disputed. This study attempts to account statistically for both trends and interannual variability in water-balance evapotranspiration (ET), estimated from the annual observed streamflow in 109 river basins during "water years" 1961–1999 and two gridded precipitation datasets. The basins were chosen based on the availability of streamflow time-series data in the Dai et al. (2009) synthesis. They were divided into water-limited "dry" and energy-limited "wet" basins following the Budyko framework. We investigated the potential roles of precipitation, aerosol-corrected solar radiation, land-use change, wind speed, air temperature, and atmospheric CO2. Both trends and variability in ET show strong control by precipitation. There is some additional control of ET trends by vegetation processes, but little evidence for control by other factors. Interannual variability in ET was overwhelmingly dominated by precipitation, which accounted on average for 52–54% of the variation in wet basins (ranging from 0 to 99%) and 84–85% in dry basins (ranging from 13 to 100%). Precipitation accounted for 39–42% of ET trends in wet basins and 69–79% in dry basins. Cropland expansion increased ET in dry basins. Net atmospheric CO2 effects on transpiration, estimated using the Land-surface Processes and eXchanges (LPX) model, did not contribute to observed trends in ET because declining stomatal conductance was counteracted by slightly but significantly increasing foliage cover.

scholarly journals Uncertainty reduction and parameters estimation of a~distributed hydrological model with ground and remote sensing data

2014 ◽  
Vol 11 (6) ◽  
pp. 6215-6271
Author(s):  
F. Silvestro ◽  
S. Gabellani ◽  
R. Rudari ◽  
F. Delogu ◽  
P. Laiolo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Remote Sensing Data ◽  
Hydrologic Model ◽  
Parameters Estimation ◽  
State Variables ◽  
Test Bed ◽  
Sensing Data

Abstract. During the last decade the opportunity and usefulness of using remote sensing data in hydrology, hydrometeorology and geomorphology has become even more evident and clear. Satellite based products often provide the advantage of observing hydrologic variables in a distributed way while offering a different view that can help to understand and model the hydrological cycle. Moreover, remote sensing data are fundamental in scarce data environments. The use of satellite derived DTM, which are globally available (e.g. from SRTM as used in this work), have become standard practice in hydrologic model implementation, but other types of satellite derived data are still underutilized. In this work, Meteosat Second Generation Land Surface Temperature (LST) estimates and Surface Soil Moisture (SSM) available from EUMETSAT H-SAF are used to calibrate the Continuum hydrological model that computes such state variables in a prognostic mode. This work aims at proving that satellite observations dramatically reduce uncertainties in parameters calibration by reducing their equifinality. Two parameter estimation strategies are implemented and tested: a multi-objective approach that includes ground observations and one solely based on remotely sensed data. Two Italian catchments are used as the test bed to verify the model capability in reproducing long-term (multi-year) simulations.

Temporal dynamics of soil water balance components in a karst range in southeastern Spain: estimation of potential recharge

2010 ◽  
Vol 55 (5) ◽  
pp. 737-753 ◽  
Author(s):  
Yolanda Cantón ◽  
Luis Villagarcía ◽  
María José Moro ◽  
Penelope Serrano-Ortíz ◽  
Ana Were ◽  
...  
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Temporal Dynamics ◽  
Soil Water Balance ◽  
Water Balance Components ◽  
Southeastern Spain ◽  
Potential Recharge

scholarly journals An Analysis of Regional Snow Assessments at Selected Hydrological Stations on the Danube and Tisza Rivers

2013 ◽  
Vol 21 (3) ◽  
pp. 43-56
Author(s):  
Beáta Hamar Zsideková ◽  
Balázs Gauzer ◽  
Gábor Bálint
Keyword(s):  
Surface Water ◽  
Water Balance ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Time Lag ◽  
Precipitation Event ◽  
Seasonal Forecasts ◽  
The Earth ◽  
Precipitation Record ◽  
The Relationship

Abstract Precipitation falling on a land surface is one of the most important elements of the hydrological cycle, and it is the only input term of the water balance on the Earth´s surface. On those areas of the Earth where a part of the annual precipitation falls in the form of snow, the rhythm of the hydrological cycle, i.e., the water balance within a year, follows a pattern that deviates from that of the precipitation record. Precipitation falling in a solid state enters the hydrological cycle with a time lag that might be as much as several months after the precipitation event. Therefore, instead of considering the observed values of precipitation when describing the various elements of the hydrological cycle, it is more expedient to take the surface water input into account. This is a fraction of the precipitation which is present on the land surface in a liquid state. Consequently, the most important task of the various snow models within the rainfall - runoff and water budget schemes is to transform the precipitation values observed into surface water input values. Spring time runoff largely depends on the snowmelt component, and it gives the possibility of estimating the expected seasonal volume of the flow and flood peaks. Seasonal forecasts based on the relationship between snow resources and expected precipitation during the spring months have been analyzed for the Danube and Tisza rivers.

Water-balance response to climate variability, a small-to-large scale Italian dataset

2021 ◽  
Author(s):  
Giulia Bruno ◽  
Francesco Avanzi ◽  
Simone Gabellani ◽  
Luca Ferraris ◽  
Edoardo Cremonese ◽  
...  
Keyword(s):  
Water Balance ◽  
Water Resource Management ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Climatic Variability ◽  
Remote Sensing Data ◽  
Data Availability ◽  
Catchment Scale ◽  
Wide Range ◽  
Mean Square Errors

<p>Understanding how deficit of precipitation impacts the hydrological cycle is of growing interest and is essential for water resource management. It has been recently observed that the relationship between precipitation and runoff during droughts is subjected to a shift in the sense that the predicted runoff is much less than the one expected due to the deficit in precipitation. Unraveling why this occurs requires an accurate knowledge of all the components of the water balance equation. However, large-scale and consistent samples of precipitation, runoff, evapotranspiration, ET and change in storage have always been challenging to collect. Here, we hypothesized that blending ground-based and remote-sensing data products could fill this gap. We present a countrywide dataset of catchment-scale water balance, covering the last 10 water years in Italy. Italy shows a broad variety of climatic and topographic features and faced several droughts over recent years. We use ground-based daily runoff data, interpolated precipitation maps, and a remote-sensed daily evapotranspiration dataset from the LSASAF ET product. The ET dataset is additionally compared with flux towers data across the country, obtaining root mean square errors on the order of 30 mm/month. Lastly, changes in storage are estimated to close the water balance. More than 100 catchments - including the major Italian basins - are selected, according to data availability and reliability. These catchments cover a wide range of size, morphologic and climatic characteristics. </p><p>This dataset is a strategic source of information to analyze catchment-scale runoff, ET and storage response to climatic variability across climates and landscapes.</p>

Data Assimilation for Estimating the Terrestrial Water Budget Using a Constrained Ensemble Kalman Filter

2006 ◽  
Vol 7 (3) ◽  
pp. 534-547 ◽  
Author(s):  
Ming Pan ◽  
Eric F. Wood
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Water Balance ◽  
Ensemble Kalman Filter ◽  
Land Surface ◽  
The United States ◽  
Surface Model ◽  
Infiltration Capacity ◽  
Water Balance Components ◽  
Terrestrial Water

Abstract A procedure is developed to incorporate equality constraints in Kalman filters, including the ensemble Kalman filter (EnKF), and is referred to as the constrained ensemble Kalman filter (CEnKF). The constraint is carried out as a two-step filtering approach, with the first step being the standard (ensemble) Kalman filter. The second step is the constraint step carried out by another Kalman filter that optimally redistributes any imbalance from the first step. The CEnKF is implemented over a 75 000 km2 domain in the southern Great Plains region of the United States, using the terrestrial water balance as the constraint. The observations, consisting of gridded fields of the upper two soil moisture layers from the Oklahoma Mesonet system, Atmospheric Radiation Measurement Program Cloud and Radiation Testbed (ARM-CART) energy balance Bowen ratio (EBBR) latent heat estimates, and U.S. Geological Survey (USGS) streamflow from unregulated basins, are assimilated into the Variable Infiltration Capacity (VIC) land surface model. The water balance was applied at the domain scale, and estimates of the water balance components for the domain are updated from the data assimilation step so as to assure closure.

scholarly journals Assessment of Wetland Restoration and Climate Change Impacts on Water Balance Components of the Heeia Coastal Wetland in Hawaii

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 37 ◽  
Author(s):  
Kariem A. Ghazal ◽  
Olkeba Tolessa Leta ◽  
Aly I. El-Kadi ◽  
Henrietta Dulai
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Balance ◽  
21St Century ◽  
Climate Changes ◽  
Hydrological Modeling ◽  
Coastal Wetland ◽  
Climate Change Scenarios ◽  
Water Balance Components ◽  
Daily Streamflow

Hydrological modeling is an important tool that can be used to assess water resources’ availability and sustainability that are necessary for food security and ecological health of coastal regions. In this study, we assessed the impacts of land use and climate changes on water balance components (WBCs) of the Heeia coastal wetland. We developed a Soil and Water Assessment Tool (SWAT) model to capture the unique characteristics of the Hawaiian Islands, including its volcanic soil’s nature and high initial infiltration rates. We used the sequential uncertainty fitting algorithm to assess the sensitivity and uncertainty of WBCs under different climate change scenarios. Results of the statistical analysis of daily streamflow simulations showed that the model performance was within the generally acceptable criteria. Under future climate scenarios, rainfall change was the determinant factor most negatively impacting WBCs. Recharge and baseflow components had the highest sensitivity to the combined effects of land use and climate changes, especially during dry season. The uncertainty analysis indicated that the streamflow is projected to slightly increase by the middle of 21st century, but expected to decline by 40% during the late 21st century of Representative Concentration Pathways (RCP) 8.5.

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