Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Abstract. Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access (e.g., high elevation zones). Recently, satellite-based rainfall estimates (SRE) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods. This study attempts to exhaustively evaluate -for the first time- the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE. The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, several categorical indices were used to assess the ability of each SRE to correctly identify different precipitation intensities. Results revealed that most SRE products performed better for the humid South (36.4–43.7° S) and Central Chile (32.18–36.4° S), in particular at low- and mid-elevation zones (0–1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (MAM-JJA) compared to summer (DJF) and autumn (SON). In addition, all SREs were able to correctly identify the occurrence of no rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all time scales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR and PERSIANN-CCS-adj were not able to represent observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resources assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

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Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Hydrology and Earth System Sciences ◽

10.5194/hess-21-1295-2017 ◽

2017 ◽

Vol 21 (2) ◽

pp. 1295-1320 ◽

Cited By ~ 100

Author(s):

Mauricio Zambrano-Bigiarini ◽

Alexandra Nauditt ◽

Christian Birkel ◽

Koen Verbist ◽

Lars Ribbe

Keyword(s):

Grid Cell ◽

Catchment Scale ◽

The Real ◽

Wide Range ◽

Northern Regions ◽

Specific Assessment ◽

Spatio Temporal ◽

Rain Events ◽

A Site ◽

Rainfall Estimates

Abstract. Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate – for the first time – the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25° grid if necessary). The modified Kling–Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4–43.7° S) and Central Chile (32.18–36.4° S), in particular at low- and mid-elevation zones (0–1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM–JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all timescales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by the research products CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR, and the real-time PERSIANN-CCS-Adj were less skillful in representing observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resource assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

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Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

Hydrology and Earth System Sciences ◽

10.5194/hess-21-3543-2017 ◽

2017 ◽

Vol 21 (7) ◽

pp. 3543-3555 ◽

Cited By ~ 29

Author(s):

Ricardo Zubieta ◽

Augusto Getirana ◽

Jhan Carlo Espinoza ◽

Waldo Lavado-Casimiro ◽

Luis Aragon

Keyword(s):

Amazon Basin ◽

Hydrological Modeling ◽

Precipitation Data ◽

Distributed Hydrological Model ◽

Precipitation Measurement ◽

Ecuadorian Amazon ◽

Northern Regions ◽

Rain Events ◽

Global Precipitation ◽

Rainfall Estimates

Abstract. In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM) have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM) mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG) (product/final run) as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015) when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets) and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively). In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %). Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin). GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins), probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

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The importance of spatio-temporal snowmelt variability for isotopic hydrograph separation in a high-elevation catchment

10.5194/hess-2016-128 ◽

2016 ◽

Cited By ~ 1

Author(s):

Jan Schmieder ◽

Florian Hanzer ◽

Thomas Marke ◽

Jakob Garvelmann ◽

Michael Warscher ◽

...

Keyword(s):

High Elevation ◽

Hydrograph Separation ◽

Catchment Scale ◽

Isotopic Signatures ◽

The North ◽

Stable Isotopic ◽

Spatio Temporal ◽

Snow Model ◽

North And South ◽

Seasonal Snow Cover

Abstract. Seasonal snow cover is an important temporary water storage in high-elevation regions. Especially in remote areas, the available data is often insufficient to explicitly quantify snowmelt contributions to streamflow. The unknown spatio-temporal variability of the snowmelt isotopic content, as well as pronounced spatial variations of snowmelt rates lead to high uncertainties in applying the isotopic hydrograph separation method. This study presents an approach that uses a distributed snowmelt model to support the traditional isotopic hydrograph separation technique. The stable isotopic signatures of snowmelt water samples collected during two spring 2014 snowmelt events at a north- and a south-facing slope were volume-weighted with snowmelt rates derived from a distributed physics-based snow model in order to transfer the measured plot-scale isotopic content of snowmelt water to the catchment scale. The observed δ18O values and modelled snowmelt rates showed distinct inter- and intra-event variations, as well as marked differences between north- and south-facing slopes. Accounting for those differences, two-component isotopic hydrograph separation revealed snowmelt contributions of 35 &pm; 3 % and 75 &pm; 14 % for the early and peak melt season, respectively. Differences to formerly used weighting methods (e.g. using observed plot-scale melt rates) or considering either the north- or south-facing slope were up to 5 and 15 %, respectively.

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Hydrological modeling of the Peruvian-Ecuadorian Amazon basin using GPM-IMERG satellite-based precipitation dataset

10.5194/hess-2016-656 ◽

2016 ◽

Author(s):

Ricardo Zubieta ◽

Augusto Getirana ◽

Jhan Carlo Espinoza ◽

Waldo Lavado-Casimiro ◽

Luis Aragon

Keyword(s):

Amazon Basin ◽

Hydrological Modeling ◽

Precipitation Data ◽

Distributed Hydrological Model ◽

Precipitation Measurement ◽

Ecuadorian Amazon ◽

Northern Regions ◽

Rain Events ◽

Global Precipitation ◽

Rainfall Estimates

Abstract. In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM) have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM) mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG) (product/final run) as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015) when all datasets are available. TRMM products (TMPA V7, TMPA RT datasets) and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, in comparison to observed rainfall (by 11.1 % and 15.7 %, respectively). In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected (~ 20 %). Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali basin). GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins), probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

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How does initial soil moisture influence the hydrological response? A case study from southern France

Hydrology and Earth System Sciences ◽

10.5194/hess-22-6127-2018 ◽

2018 ◽

Vol 22 (12) ◽

pp. 6127-6146 ◽

Cited By ~ 8

Author(s):

Magdalena Uber ◽

Jean-Pierre Vandervaere ◽

Isabella Zin ◽

Isabelle Braud ◽

Maik Heistermann ◽

...

Keyword(s):

Soil Moisture ◽

Hydrological Response ◽

Hydrograph Separation ◽

Catchment Scale ◽

Southern France ◽

Initial Soil Moisture ◽

Wide Range ◽

Initial Soil ◽

Rain Events ◽

The Impact

Abstract. The Cévennes–Vivarais region in southern France is prone to heavy rainfall that can lead to flash floods which are one of the most hazardous natural risks in Europe. The results of numerous studies show that besides rainfall and physical catchment characteristics the catchment's initial soil moisture also impacts the hydrological response to rain events. The aim of this paper is to analyze the relationship between catchment mean initial soil moisture θ̃ini and the hydrological response that is quantified using the event-based runoff coefficient ϕev in the two nested catchments of the Gazel (3.4 km2) and the Claduègne (43 km2). Thus, the objectives are twofold: (1) obtaining meaningful estimates of soil moisture at catchment scale from a dense network of in situ measurements and (2) using this estimate of θ̃ini to analyze its relation with ϕev calculated for many runoff events. A sampling setup including 45 permanently installed frequency domain reflectancy probes that continuously measure soil moisture at three depths is applied. Additionally, on-alert surface measurements at ≈10 locations in each one of 11 plots are conducted. Thus, catchment mean soil moisture can be confidently assessed with a standard error of the mean of ≤1.7 vol % over a wide range of soil moisture conditions. The ϕev is calculated from high-resolution discharge and precipitation data for several rain events with a cumulative precipitation Pcum ranging from less than 5 mm to more than 80 mm. Because of the high uncertainty of ϕev associated with the hydrograph separation method, ϕev is calculated with several methods, including graphical methods, digital filters and a tracer-based method. The results indicate that the hydrological response depends on θ̃ini: during dry conditions ϕev is consistently below 0.1, even for events with high and intense precipitation. Above a threshold of θ̃ini=34 vol % ϕev can reach values up to 0.99 but there is a high scatter. Some variability can be explained with a weak correlation of ϕev with Pcum and rain intensity, but a considerable part of the variability remains unexplained. It is concluded that threshold-based methods can be helpful to prevent overestimation of the hydrological response during dry catchment conditions. The impact of soil moisture on the hydrological response during wet catchment conditions, however, is still insufficiently understood and cannot be generalized based on the present results.

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Performing Hydrological Monitoring at a National Scale by Exploiting Rain-Gauge and Radar Networks: The Italian Case

Atmosphere ◽

10.3390/atmos12060771 ◽

2021 ◽

Vol 12 (6) ◽

pp. 771

Author(s):

Giulia Bruno ◽

Flavio Pignone ◽

Francesco Silvestro ◽

Simone Gabellani ◽

Federico Schiavi ◽

...

Keyword(s):

Large Scale ◽

Early Warning Systems ◽

Rain Gauge ◽

Climatic Conditions ◽

National Scale ◽

Catchment Scale ◽

Event Scale ◽

Wide Range ◽

Hydrological Monitoring ◽

Rainfall Estimates

Hydrological monitoring systems relying on radar data and distributed hydrological models are now feasible at large-scale and represent effective early warning systems for flash floods. Here we describe a system that allows hydrological occurrences in terms of streamflow at a national scale to be monitored. We then evaluate its operational application in Italy, a country characterized by various climatic conditions and topographic features. The proposed system exploits a modified conditional merging (MCM) algorithm to generate rainfall estimates by blending data from national radar and rain-gauge networks. Then, we use the merged rainfall fields as input for the distributed and continuous hydrological model, Continuum, to obtain real-time streamflow predictions. We assess its performance in terms of rainfall estimates from MCM, using cross-validation and comparison with a conditional merging technique at an event-scale. We also assess its performance against rainfall fields from ground-based data at catchment-scale. We further evaluate the performance of the hydrological system in terms of streamflow against observed data (relative error on high flows less than 25% and Nash–Sutcliffe Efficiency greater than 0.5 for 72% and 46% of the calibrated study sections, respectively). These results, therefore, confirm the suitability of such an approach, even at national scale, over a wide range of catchment types, climates, and hydrometeorological regimes, and for operational purposes.

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Kinematic Analysis of Lower Limb Joint Asymmetry during Gait in People with Multiple Sclerosis

Symmetry ◽

10.3390/sym13040598 ◽

2021 ◽

Vol 13 (4) ◽

pp. 598

Author(s):

Massimiliano Pau ◽

Bruno Leban ◽

Michela Deidda ◽

Federica Putzolu ◽

Micaela Porta ◽

...

Keyword(s):

Multiple Sclerosis ◽

Lower Limb ◽

Sagittal Plane ◽

Cross Sectional Study ◽

Camera Motion ◽

Cross Sectional ◽

Temporal Parameters ◽

Wide Range ◽

Edss Score ◽

Spatio Temporal

The majority of people with Multiple Sclerosis (pwMS), report lower limb motor dysfunctions, which may relevantly affect postural control, gait and a wide range of activities of daily living. While it is quite common to observe a different impact of the disease on the two limbs (i.e., one of them is more affected), less clear are the effects of such asymmetry on gait performance. The present retrospective cross-sectional study aimed to characterize the magnitude of interlimb asymmetry in pwMS, particularly as regards the joint kinematics, using parameters derived from angle-angle diagrams. To this end, we analyzed gait patterns of 101 pwMS (55 women, 46 men, mean age 46.3, average Expanded Disability Status Scale (EDSS) score 3.5, range 1–6.5) and 81 unaffected individuals age- and sex-matched who underwent 3D computerized gait analysis carried out using an eight-camera motion capture system. Spatio-temporal parameters and kinematics in the sagittal plane at hip, knee and ankle joints were considered for the analysis. The angular trends of left and right sides were processed to build synchronized angle–angle diagrams (cyclograms) for each joint, and symmetry was assessed by computing several geometrical features such as area, orientation and Trend Symmetry. Based on cyclogram orientation and Trend Symmetry, the results show that pwMS exhibit significantly greater asymmetry in all three joints with respect to unaffected individuals. In particular, orientation values were as follows: 5.1 of pwMS vs. 1.6 of unaffected individuals at hip joint, 7.0 vs. 1.5 at knee and 6.4 vs. 3.0 at ankle (p < 0.001 in all cases), while for Trend Symmetry we obtained at hip 1.7 of pwMS vs. 0.3 of unaffected individuals, 4.2 vs. 0.5 at knee and 8.5 vs. 1.5 at ankle (p < 0.001 in all cases). Moreover, the same parameters were sensitive enough to discriminate individuals of different disability levels. With few exceptions, all the calculated symmetry parameters were found significantly correlated with the main spatio-temporal parameters of gait and the EDSS score. In particular, large correlations were detected between Trend Symmetry and gait speed (with rho values in the range of –0.58 to –0.63 depending on the considered joint, p < 0.001) and between Trend Symmetry and EDSS score (rho = 0.62 to 0.69, p < 0.001). Such results suggest not only that MS is associated with significantly marked interlimb asymmetry during gait but also that such asymmetry worsens as the disease progresses and that it has a relevant impact on gait performances.

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The Adjustment of China’s Grain Planting Structure Reduced the Consumption of Cropland and Water Resources

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18147352 ◽

2021 ◽

Vol 18 (14) ◽

pp. 7352

Author(s):

Yu Zhang ◽

Jieyong Wang ◽

Chun Dai

Keyword(s):

Water Resources ◽

Structural Adjustment ◽

Land Reclamation ◽

National Level ◽

Cumulative Effect ◽

Northern China ◽

Semiarid Region ◽

Market Demand ◽

Continuous Growth ◽

Northern Regions

Driven by technological progress and market demand, the optimization and adjustment of grain planting structure played an important role in increasing grain output. Due to the great difference between the yield per unit area of different types of food crops, the consumption of cropland and water resources has a significant change during the grain growth. From the perspective of structural adjustment, rather than the usual productive factor input, we analyze the process of adjustment for grain planting structure in China and its effect on the consumption of cropland and water resources by using the scenario comparative analysis method. The results show that: (1) From 2003 to 2019, China’s grain output has increased steadily and the planting structure has changed greatly. Rice was replaced by corn to become the grain crop with the maximum proportion of planting area since 2007. The increase of corn planting structure proportion is concentrated in the northern regions. (2) At the national level, according to the adjustment of grain planting structure, the saving of cropland and water resources consumption showed a “cumulative effect” as time went on. (3) The saving effects of structural adjustment in the northern regions on cropland and water resources consumption are better than that in the southern regions, such as Northeast China Plain, Northern arid and semiarid region and Loess Plateau. (4) In reality, although the adjustment of grain planting structure saved lots of cropland and water resources, the continuous growth of grain output has increased the pressure on the ecological environment in the northern regions according to theirs water limits. Therefore, it is necessary to continuously optimize the grain planting structure and restrict land reclamation in northern China. In addition, to ensure food security, it is feasible to encourage the southern regions with abundant water and heat resources to increase the grain planting area and meet its self-sufficiency in grain demand.

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Interruptions: Affective futures and uncanny presences at Giemaš, Finnmark

Polar Record ◽

10.1017/s0032247420000443 ◽

2021 ◽

Vol 57 ◽

Author(s):

Marianne Elisabeth Lien

Keyword(s):

Open Pit ◽

Open Pit Mining ◽

Mining Company ◽

Mining Site ◽

Wide Range ◽

Migratory Movement ◽

A Site ◽

Affective Relations ◽

North Norway

Abstract This paper concerns affective relations and unexpected interruptions as the planned expansion of an extractive open-pit mining site gathers momentum. The site is a mountain in Varanger, North Norway, criss-crossed by a sand-coloured meshwork of roads that are part of the current infrastructure of a quartzite quarry. Recently purchased by Chinese investors, the mining company Elkem plans a massive expansion of the operations, which will interrupt a wide range of practices and projects, including the migratory movement of reindeer, as well as their grazing patterns. Known as Giemaš amongst Sámi speakers, the mountain is also alluded to as a site of other powers, manifesting as unexpected accidents. In this article, I explore how the planned expansion evokes this contested site as more than a singular mountain, and how divergent epistemic formations interrupt the making of extractive resources in multiple ways.

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Forest path condition monitoring based on crowd-based trajectory data analysis

Journal of Ambient Intelligence and Smart Environments ◽

10.3233/ais-200586 ◽

2020 ◽

pp. 1-18

Author(s):

Francisco Arcas-Tunez ◽

Fernando Terroso-Saenz

Keyword(s):

Information Acquisition ◽

Road Network ◽

Road Networks ◽

Trajectory Data ◽

Country Road ◽

Wide Range ◽

Sport Activities ◽

Path Condition ◽

Spatio Temporal ◽

The City

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.

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