11 research outputs found

    Assessment of Extreme Heat Wave Magnitude in Present Climate in the Pastoral Region of Afar, Ethiopia

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    Heatwaves have been a prominent issue in climate change studies due to the extreme heatwaves that have occurred globally over the past few decades. Extreme heat waves are hitting Ethiopia, which has led to higher rates of death and morbidity as well as higher water and energy needs. This study presents for the first time a climatological analysis of heatwave magnitude for a pastoral region of Afar using the heatwave magnitude index daily (HWMId) index. The study analyzed the intensity of heatwave for the period 1981-2020, as well as for the heatwave event in 2015 using gauged dataset. The findings showed that each year, the proportion of hot days and hot nights increased by 0.3 and 0.3 days per year. The areal aggregated temperature anomaly indicated increasing each year by +0.07 and +0.05 0 C for maximum and minimum temperature respectively. 2015, 2016, and 2015 were considered as the hottest years in the last 40 years, with 2015 being one of the warmest years on record with an anomaly of +1.8 °C for maximum temperature and 1.3 °C for minimum temperature. The finding also clearly indicated that most parts of the study area recorded severe to very extreme heatwaves scored from 4 to 16. The increase in a heatwave may have a negative impact on health, water availability and food security. Therefore, the finding of this study is very important to develop early warning systems that could manage the risk of anomalously extreme weather events. Keywords:Afar Region, Extreme climate indices, Heatwave, Heatwave magnitude index, Pastoralists, Temperature. DOI: 10.7176/JEES/13-7-02 Publication date:September 30th 202

    A Machine Learning Approach for Improving Near-Real-Time Satellite-Based Rainfall Estimates by Integrating Soil Moisture

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    Near-real-time (NRT) satellite-based rainfall estimates (SREs) are a viable option for flood/drought monitoring. However, SREs have often been associated with complex and nonlinear errors. One way to enhance the quality of SREs is to use soil moisture information. Few studies have indicated that soil moisture information can be used to improve the quality of SREs. Nowadays, satellite-based soil moisture products are becoming available at desired spatial and temporal resolutions on an NRT basis. Hence, this study proposes an integrated approach to improve NRT SRE accuracy by combining it with NRT soil moisture through a nonlinear support vector machine-based regression (SVR) model. To test this novel approach, Ashti catchment, a sub-basin of Godavari river basin, India, is chosen. Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA)-based NRT SRE 3B42RT and Advanced Scatterometer-derived NRT soil moisture are considered in the present study. The performance of the 3B42RT and the corrected product are assessed using different statistical measures such as correlation coeffcient (CC), bias, and root mean square error (RMSE), for the monsoon seasons of 2012–2015. A detailed spatial analysis of these measures and their variability across different rainfall intensity classes are also presented. Overall, the results revealed significant improvement in the corrected product compared to 3B42RT (except CC) across the catchment. Particularly, for light and moderate rainfall classes, the corrected product showed the highest improvement (except CC). On the other hand, the corrected product showed limited performance for the heavy rainfall class. These results demonstrate that the proposed approach has potential to enhance the quality of NRT SRE through the use of NRT satellite-based soil moisture estimates

    Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow- hydrological modelling in the Lake Titicaca region

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    This paper proposes a protocol to assess the space–time consistency of 12 satellite-based precipitation products (SPPs) according to various indicators, including (i) direct comparison of SPPs with 72 precipitation gauges; (ii) sensitivity of streamflow modelling to SPPs at the outlet of four basins; and (iii) the sensitivity of distributed snow models to SPPs using a MODIS snow product as reference in an unmonitored mountainous area. The protocol was applied successively to four different time windows (2000–2004, 2004–2008, 2008–2012 and 2000–2012) to account for the space–time variability of the SPPs and to a large dataset composed of 12 SPPs (CMORPH–RAW v.1, CMORPH–CRT v.1, CMORPH–BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, MSWEP v.2.1, PERSIANN, PERSIANN–CDR, TMPA–RT v.7, TMPA–Adj v.7 and SM2Rain–CCI v.2), an unprecedented comparison. The aim of using different space scales and timescales and indicators was to evaluate whether the efficiency of SPPs varies with the method of assessment, time window and location. Results revealed very high discrepancies between SPPs. Compared to precipitation gauge observations, some SPPs (CMORPH–RAW v.1, CMORPH–CRT v.1, GSMaP v.6, PERSIANN, and TMPA–RT v.7) are unable to estimate regional precipitation, whereas the others (CHIRP v.2, CHIRPS v.2, CMORPH–BLD v.1, MSWEP v.2.1, PERSIANN–CDR, and TMPA–Adj v.7) produce a realistic representation despite recurrent spatial limitation over regions with contrasted emissivity, temperature and orography. In 9 out of 10 of the cases studied, streamflow was more realistically simulated when SPPs were used as forcing precipitation data rather than precipitation derived from the available precipitation gauge networks, whereas the SPP's ability to reproduce the duration of MODIS-based snow cover resulted in poorer simulations than simulation using available precipitation gauges. Interestingly, the potential of the SPPs varied significantly when they were used to reproduce gauge precipitation estimates, streamflow observations or snow cover duration and depending on the time window considered. SPPs thus produce space–time errors that cannot be assessed when a single indicator and/or time window is used, underlining the importance of carefully considering their space–time consistency before using them for hydro-climatic studies. Among all the SPPs assessed, MSWEP v.2.1 showed the highest space–time accuracy and consistency in reproducing gauge precipitation estimates, streamflow and snow cover duration.</p

    Risk-Informed Sustainable Development in the Rural Tropics

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    Many people live in rural areas in tropical regions. Rural development is not merely a contribution to the growth of individual countries. It can be a way to reduce poverty and to increase access to water, health care, and education. Sustainable rural development can also help stop deforestation and reduce live-stock, which generate most of the greenhouse gas emissions. However, eorts to achieve a sustainable rural development are often thwarted by oods, drought, heat waves, and hurricanes, which local communities are not very prepared to tackle. Agricultural practices and local planning are still not very risk-informed. These deciencies are particularly acute in tropical regions, where many Least Developed Countries are located and where there is, however, great potential for rural development. This Special Issue contains 22 studies on best practices for risk awareness; on local risk reduction; on several cases of soil depletion, water pollution, and sustainable access to safe water; and on agronomy, earth sciences, ecology, economy, environmental engineering, geomatics, materials science, and spatial and regional planning in 12 tropical countries

    Households at Risk : Integrated Assessment of Drought Hazard and Social Vulnerability in the Cuvelai-Basin of Angola and Namibia

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    Droughts are phenomena that occur worldwide, in humid and arid environments as well as in the Global North and the Global South. They are considered as slow onset hazards that affect more people than any other natural process with an estimated economic damage of USD 135 Billion and 12 Million casualties globally between 1900 and 2013 (Masih et al., 2014, p. 3636). Sub-Saharan Africa (SSA) is a major drought hot-spot due to vulnerable livelihoods (e.g. dominance of rain-fed agriculture), limited capacities (e.g. financial, institutional), weak infrastructure (e.g. water, mobility) and political instability (e.g. conflicts, corruption). When droughts occur, as recently triggered by El Niño (2015/2016), vulnerability conditions of the affected societies determine, if drought risk manifests as a disaster. As a critical, recent example, the drought in Somalia resulted in a serious humanitarian disaster primarily as the precarious vulnerability situation was further deteriorated by political and violent conflicts (Maxwell et al., 2016). Overall, SSA faces severe challenges to manage drought risk, primarily due to two reasons: First, despite progress, the living conditions remain difficult with prevailing poverty, limited health services and ongoing political unrest in many regions (UNECA et al., 2015). This is alarming, especially against the projected population growth of about 1.3 Billion people in Africa until 2050 (UN-DESA, 2015, p. 3). Second, achieving good living conditions for all, as envisioned by the Sustainable Development Goals (SDG), is a challenge, as climate projections indicate a likely increase of drought frequency and severity in SSA. Higher rainfall variability paired with a strong increase in average temperatures (Niang et al., 2014) will render today's exceptional droughts as the new normal in the near future. These urgent problems require sustainable solutions to improve short- and long-term adaptation. Transdisciplinary science that conflates the strengths of academic disciplines and stakeholders from politics and society is needed to develop risk reduction strategies. Under the umbrella of the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL), this thesis makes a contribution to integrated drought risk management schemes by assessing the drought hazard conditions and the societal vulnerability settings in a case study region: the Cuvelai-Basin. This transnational region across Namibia and Angola regularly experiences droughts as recently during 2012 – 2015 with hundreds of thousands of people being water and food insecure (DDRM, 2013; UN-OCHA, 2012). Environmentally, it covers a gradient from humid in the north to semi-arid conditions in the south with associated vegetation patterns. The population practices subsistence agriculture and livestock herding with tendencies of urbanization and lifestyle changes. The societal pre-conditions in both countries are heterogeneous with Angola having experienced decades of civil war until 2002 while Namibia saw continuous institutional and infrastructural development particularly after independence in 1990. To capture the multi-layered impacts of droughts on people's livelihoods, the thesis follows an interdisciplinary approach in the sense of integrating methodologies from physical and human geography. Key questions to be answered are (i) how droughts impact on local livelihoods, (ii) how the environmental drought hazard manifests, (iii) which societal groups are most vulnerable and (iv) what are risk mitigation strategies. Based on the theory of societal relations to nature, a guideline for a social-ecological drought risk assessment is proposed and exemplarily carried out in this thesis. First, a qualitative research phase was conducted to gain system knowledge, followed by quantitative analyses of environmental parameters on the drought hazard and socio-economic variables for drought vulnerability. Finally, this data was conflated in the Household Drought Risk Index (HDRI) to gain orientation knowledge and quantify risk levels among the households in the basin. This provided transformation knowledge to develop and identify risk mitigation strategies. The initial qualitative survey (n = 26) explored the drought impact on local livelihoods. It revealed structural insights into people's utilization of water resources and the negative impacts of drought on physical and mental health, family/community life and livelihood maintenance. Coping mechanisms were identified on multiple levels from the household level (e.g. selling of agricultural products) via the community (e.g. neighbourly support) to the governmental level (e.g. drought relief). As critical entry point for droughts, the water and food consumption patterns were identified that shape a household either more or less sensitive. The internal capital endowment (human, social, financial, physical and natural) and the infrastructural and institutional endowment of an area determine a household's ability to cope with drought. These qualitative insights culminated in the construction of the HDRI indicator that was populated with data in the subsequent research phases. To capture the drought hazard, three common drought indicators were combined in the Blended Drought Index (BDI). This integrated drought indicator incorporates meteorological and agricultural drought characteristics that impair the population's ability to ensure food and water security. The BDI uses a copula function to combine common standardized drought indicators that describe precipitation, evapotranspiration, soil moisture and vegetation conditions. Remote sensing products were processed to analyse drought frequency, severity and duration. In this regard, the uncertainty among a range of rainfall products was evaluated to identify the product that corresponds best to local rain gauge measurements. The integrated drought hazard map indicates the north of the Etosha pan and the area along the Kunene River to be most threatened by droughts. Temporally, the BDI correlates well with millet/sorghum yield (r = 0.51) and local water consumption (r = -0.45) and outperforms conventional indicators. The vulnerability perspective was captured using primary socio-economic data from a household survey (n = 461). The consumption patterns reveal a statistically significant switch from critical sources (e.g. wells, subsistence products) during the rainy season to more reliable sources (e.g. tap water, markets) during the dry period. Households with a high dependence on critical sources are particularly sensitive to drought. The capital endowment of households is heterogeneous, especially on a rural-urban gradient and between Namibia and Angola. Human and financial capital turned out to be important control variables in addition to the infrastructural and institutional endowment of an area. Overall, the HDRI results show that the Angolan population shows higher levels of risk, particularly caused by less developed infrastructural systems, weaker institutional capabilities and less coping capacities. Urban inhabitants follow less drought-sensitive livelihood strategies, but are still connected to drought conditions in rural areas due to family relations with obligations and benefits. Furthermore, the spatial HDRI estimates point to areas in Angola and Namibia that are both drought-threatened and vulnerable. The thesis results indicate the following recommendations for policy and science: First, the continuous monitoring of drought patterns in the basin should consider drought indicators that go beyond precipitation metrics and incorporate people's vulnerability to develop integrated Drought Information Systems. Second, reducing the sensitivities of the population requires enhanced local water buffers via better water use efficiencies. This is true for both blue and green water flows. Water-saving irrigation schemes in combination with decentral rain- and floodwater harvesting are promising opportunities. Furthermore, centralized backup infrastructures of water supply and market systems need to be expanded. Third, local community solidarity is an important institutional backbone for the population to cope with drought and adapt to future changes. In particular rural development efforts should go beyond technological interventions and support community-building, collective-action and capacity development in water management and agricultural production to decouple livelihoods from local rainfall.Dürren sind Phänomene, die weltweit sowohl in humiden als auch ariden Räumen sowie im Globalen Norden und im Globalen Süden auftreten. Sie gelten als langsam einsetzende Gefahren, die mehr Menschen betreffen als jeder andere natürliche Prozess mit einem geschätzten wirtschaftlichen Schaden von 135 Mrd. US-Dollar und 12 Mio. Toten weltweit zwischen 1900 und 2013 (Masih et al., 2014, p. 3636). Sub-Sahara Afrika gilt als Krisenherd aufgrund vulnerabler Lebensgrundlagen (z.B. Dominanz des Regenfeldbaus), begrenzter Kapazitäten (z.B. finanzielle, institutionelle), schwacher Infrastruktur (z.B. Trinkwasser, Mobilität) und politischer Instabilität (z.B. Konflikte, Korruption). Treten Dürren auf, wie kürzlich verstärkt durch El Niño (2015/2016), bestimmt die Vulnerabilität der Gesellschaft, ob sich das Dürrerisiko als Katastrophe manifestiert. Ein kritisches Beispiel ist die Dürre in Somalia, die v.a. zu einer humanitären Katastrophe wurde, da die prekären Vulnerabilitäts-bedingungen durch gewaltsame, politische Konflikte weiter verschlechtert wurden (Maxwell et al., 2016). Insgesamt steht Afrika aus zwei Gründen vor großen Heraus-forderungen bei der Bewältigung des Dürrerisikos: Erstens, sind die Lebensbedingungen u.a. aufgrund anhaltender Armut, begrenzter Gesundheitsversorgung und politischer Unruhen weiterhin schwierig (UNECA et al., 2015). Dies ist alarmierend, v.a. vor dem Hintergrund eines prognostizierten Bevölkerungswachstums von 1,3 Mrd. bis 2050 (UN-DESA, 2015, p. 3). Zweitens, ist die Schaffung guter Lebensbedingungen nach den Zielen für nachhaltige Entwicklung (SDG) eine Herausforderung, da mit dem Klimawandel eine Zunahme von Dürrehäufigkeit und -stärke zu erwarten ist. Höhere Niederschlags-variabilität gepaart mit einem starken Anstieg der Durchschnittstemperatur (Niang et al., 2014) werden die heutigen extremen Dürren in Zukunft zur neuen Normalität machen. Diese Probleme erfordern nachhaltige Lösungen, um kurz- und langfristige Anpassungen zu ermöglichen. Transdisziplinäre Forschung ist gefordert, welche die Stärken wissenschaftlicher Disziplinen und Akteure aus Politik und Gesellschaft bündelt, um geeignete Strategien zur Risikominderung zu erarbeiten. Unter dem Dach des Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) leistet diese Dissertation einen Beitrag zu integrierten Managementansätzen von Dürrerisiken, indem sie die naturräumliche Gefährdung kombiniert mit der gesellschaftlichen Vulnerabilität anhand einer Fallstudie untersucht: dem Cuvelai-Becken. Diese transnationale Region in Namibia und Angola ist regelmäßig Dürren ausgesetzt, wie zuletzt in den Jahren 2012 – 2015 mit Wasser- und Ernährungsunsicherheit für Hunderttausende von Menschen (DDRM, 2013; UN-OCHA, 2012). Naturräumlich erstreckt sich die Region von einem humiden Norden in einen semi-ariden Süden mit entsprechenden Vegetationsverhältnissen. Die Bevölkerung betreibt Subsistenzland-wirtschaft und Viehzucht, wobei Urbanisierungstendenzen und Lebensstiländerungen an Dynamik gewinnen. Die gesellschaftlichen Voraussetzungen sind heterogen: Während Angola bis 2002 Jahrzehnte des Bürgerkriegs erlebte, erfuhr Namibia v.a. nach der Unabhängigkeit 1990 eine kontinuierliche institutionelle und infrastrukturelle Entwicklung. Um die vielschichtigen Auswirkungen von Dürren auf die Lebensgrundlagen zu erfassen, verfolgt diese Dissertation einen interdisziplinären Ansatz im Sinne der Integration von Methoden aus der Physischen- und Humangeographie. Kernfragen darin sind (i) wie sich Dürren auf die Lebensgrundlagen auswirken, (ii) wie sich die naturräumliche Dürregefährdung manifestiert, (iii) welche gesellschaftlichen Gruppen vulnerabel sind und (iv) welche Strategien zur Risikominderung geeignet sind. Dabei entwickelt die Dissertation auf Basis der Theorie gesellschaftlicher Naturverhältnisse einen Leitfaden für eine sozial-ökologische Risikoabschätzung und wendet diesen in der vorliegenden Fallstudie an. Zunächst wurde eine qualitative Forschungsphase durchgeführt, um Systemwissen zu gewinnen, gefolgt von einer quantitativen Analyse von Umweltparametern zur Abschätzung der Dürregefahr sowie sozioökonomischer Variablen für die Abschätzung der Vulnerabilität. Schließlich wurden diese Daten im Household Drought Risk Index (HDRI) zusammengeführt, um Orientierungswissen zu generieren und das Dürrerisiko der Haushalte zu bestimmen. Daraus abgeleitetes Transformationswissen ermöglichte dann die Identifizierung geeigneter Risikominderungsstrategien. Die qualitative Erhebung (n = 26) explorierte die Wirkung von Dürren auf die lokalen Lebensbedingungen. Sie eröffnete Einblicke in die Nutzung von Wasserressourcen und die negativen Auswirkungen von Dürren auf die körperliche/geistige Gesundheit, das Familien-/Gemeinschaftslebens sowie den Lebensunterhalts. Bewältigungsmechanismen konnten auf mehreren Ebenen identifiziert werden, vom Haushalt (z.B. Verkauf landwirtschaftlicher Produkte) über die Gemeinde (z.B. Nachbarschaftshilfe) bis hin zur staatlichen Ebene (z.B. Dürrehilfe). Als kritische Wirkpunkte für Dürren wurden Nutzungsmuster von Wasser- und Nahrungsmitteln identifiziert, die einen Haushalt mehr oder weniger anfällig machen. Die interne Kapitalausstattung (Humanes, Soziales, Finanzielles, Physisches und Natürliches) und die infrastrukturelle und institutionelle Ausstattung eines Gebiets bestimmen weiterhin die Fähigkeit eines Haushalts, mit der Dürregefahr umzugehen. Diese Erkenntnisse ermöglichten die Konstruktion des HDRI Indikators, der in den Folgephasen mit entsprechenden Daten bestückt wurde. Zur Erfassung der Dürregefahr wurden drei Dürreindikatoren im Blended Drought Index (BDI) zusammengefasst. Dieser integrierte Dürreindikator berücksichtigt meteorologische und landwirtschaftliche Merkmale, die die Ernährungs- und Wassersicherheit der Bevölkerung beeinträchtigen. Der BDI verwendet eine Copula-Funktion, um gängige Dürreindikatoren zu kombinieren, die auf Niederschlag, Evapotranspiration, Bodenfeuchte und Vegetation zurückgreifen. Fernerkundungsprodukte wurden verarbeitet, um Häufigkeit, Stärke und Dauer der Dürren zu analysieren. Dabei wurden verschiedene Niederschlagsprodukte einer Unsicherheitsanalyse unterzogen, um jenes Produkt zu identifizieren, das am besten mit lokal gemessenen Stationsdaten korrespondiert. Die resultierende, integrierte Dürregefahrenkarte zeigt den Norden der Etosha-Pfanne und das Gebiet entlang des Kunene-Flusses als am stärksten von Dürren bedroht an. Zeitlich korreliert der BDI gut mit den Daten des Hirseertrages (r = 0,51) und dem lokalen Wasserverbrauch (r = -0,45) und übertrifft dabei konventionelle Indikatoren. Die Vulnerabilität wurde anhand von sozioökonomischen Daten aus einer Haushalts-befragung (n = 461) erfasst. Die Nutzungsmuster zeigen einen statistisch signifikanten Schwenk von kritischen Wasser- und Nahrungsquellen (z.B. Brunnen, Subsistenz-produkte) hin zu verlässlichen Quellen (z.B. Leitungswasser, Märkte) während der Trockenzeit. Haushalte mit einer starken Abhängigkeit von kritischen Quellen sind besonders sensitiv gegenüber Dürren. Die Kapitalausstattung der Haushalte variiert v.a. zwischen Land und Stadt sowie zwischen Namibia und Angola. Dabei treten Human- und Finanzkapital gemeinsam mit der infrastrukturellen und institutionellen Raumausstattung als wichtige Kontrollvariablen hervor. Die HDRI Ergebnisse zeigen, dass die angolanische Bevölkerung ein höheres Risiko aufweist, was v.a. durch weniger entwickelte Infrastruktursysteme, schwächere institutionelle- und geringere Bewältigungskapazitäten verursacht wird. Insgesamt gehen Stadtbewohner weniger dürresensitiven Nutzungsmustern nach, sind aber aufgrund familiärer Beziehungen weiterhin mit den ländlichen Gebieten verbunden. Die integrierte, räumliche Risikoabschätzung zeigt Gebiete in Angola und Namibia die sowohl dürregefährdet als auch vulnerabel sind. Die Ergebnisse erlauben zentrale Empfehlungen für Politik und Wissenschaft: Erstens sollte die Dürrebeobachtung im Cuvelai-Becken ein breiteres Spektrum von Indikatoren berücksichtigen und zusätzlich die Verwundbarkeit der Bevölkerung einbeziehen. Dies ermöglicht die Entwicklung von integrierten Dürreinformationssystemen. Zweitens, zur Verringerung der Sensitivität der Bevölkerung müssen lokale Wasserspeicher durch eine verbesserte Wassernutzungseffizienz erhöht werden. Dies gilt sowohl für blaues als auch grünes Wasser. Wassersparende Bewässerungssysteme in Kombination mit dezentralen Regen- und Flutwasserspeichern sind vielversprechende Möglichkeiten. Darüber hinaus müssen zentrale Infrastrukturen der Wasserversorgung und der Marktsysteme ausgebaut werden. Drittens, ist der Zusammenhalt der lokalen Gemeinschaften ein wichtiges institutionelles Rückgrat zur Bewältigung von Dürren und zur Anpassung an künftige Veränderungen. Anstrengungen zur Entwicklung des ländlichen Raums sind erforderlich, die über technische Interventionen hinausgehen und Gemeinschaften durch kollektive Maßnahmen und Ausbildung sowohl in der Wasserwirtschaft als auch der Landwirtschaft unterstützen und so die Lebensgrundlagen von den Niederschlägen entkoppeln

    A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield

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    International audienceSatellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale
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