scholarly journals Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions

2020 ◽  
Author(s):  
Christof Lorenz ◽  
Tanja C. Portele ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Water Management ◽  
Spatial Resolution ◽  
Arid Regions ◽  
Maximum Temperature ◽  
Test Bed ◽  
Seasonal Forecasts ◽  
Blue Nile ◽  
Model Biases ◽  
The World ◽  
Semi Arid

Abstract. Seasonal forecasts have the potential to substantially improve water management particularly in water scarce regions. However, global seasonal forecasts are usually not directly applicable as they are provided at coarse spatial resolutions of at best 36 km and suffer from model biases and drifts. In this study, we therefore apply a bias-correction and spatial-disaggregation (BCSD) approach to seasonal precipitation, temperature and radiation forecasts of the latest long-range seasonal forecasting system SEAS5 of the European Centre for Medium Range Weather Forecasts (ECMWF). As reference we use data from the ERA5-Land offline land surface re-run of the latest ECMWF reanalysis ERA5. By that, we correct for model biases and drifts and improve the spatial resolution from 36 km to 0.1°. This is exemplary performed over 4 predominately semi-arid study domains across the world, which include the river basins of the Karun (Iran), the São Francisco (Brazil), the Tekeze-Atbara and Blue Nile (Sudan, Ethiopia and Eritrea), and the Catamayo-Chira (Ecuador and Peru). Compared against ERA5-Land, the bias-corrected and spatially disaggregated forecasts have a higher spatial resolution and show reduced biases and better agreement of spatial patterns than the raw forecasts. Furthermore, the lead-dependent drift effects are remarkably reduced in the BCSD-forecasts. However, our analysis also showed that computing monthly averages from daily bias-corrected forecasts can lead to statistical inconsistencies particularly during periods and seasons with strong temporal climate gradients or heteroscedasticity. During such periods, particularly the lowest- and highest-lead forecasts can show remaining biases. Our dataset covers the whole (re-)forecast period from 1981 to 2019, for which we provide bias-corrected and spatially disaggregated daily ensemble forecasts for precipitation, average, minimum and maximum temperature as well as for shortwave radiation from the initial date to the coming 214 days. This sums up to more than 100,000 forecasted days for each of the 25 (until the year 2016) and 51 (from the year 2017) ensemble members and each of the 5 analyzed variables. The full repository is made freely available to the public via the World Data Centre for Climate at https://doi.org/10.26050/WDCC/SaWaM_D01_SEAS5_BCSD (Domain D01, Karun Basin (Iran), Lorenz et al., 2020b), https://doi. org/10.26050/WDCC/SaWaM_D02_SEAS5_BCSD (Domain D02: São Francisco Basin (Brazil), Lorenz et al., 2020c), https://doi.org/10.26050/WDCC/SaWaM_D03_SEAS5_BCSD (Domain D03: Tekeze-Atbara and Blue Nile Basins (Ethiopia, Eritrea, Sudan), Lorenz et al., 2020d), and https://doi.org/10.26050/WDCC/SaWaM_D04_SEAS5_BCSD (Domain D04: Catamayo-Chira Basin (Ecuador, Peru), Lorenz et al., 2020a). It is currently the first publicly available daily high-resolution seasonal forecast product that covers multiple regions and variables for such a long period. It hence provides a unique test-bed for evaluating the performance of seasonal forecasts over semi-arid regions and as driving data for hydrological, ecosystem or climate impact models. Therefore, our forecasts provide a crucial contribution for the disaster preparedness and, finally, climate proofing of the regional water management in climatically sensitive regions.

scholarly journals Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions

2021 ◽  
Vol 13 (6) ◽  
pp. 2701-2722
Author(s):  
Christof Lorenz ◽  
Tanja C. Portele ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Water Management ◽  
Spatial Resolution ◽  
Arid Regions ◽  
Maximum Temperature ◽  
Test Bed ◽  
Seasonal Forecasts ◽  
Blue Nile ◽  
Model Biases ◽  
The World ◽  
Semi Arid

Abstract. Seasonal forecasts have the potential to substantially improve water management particularly in water-scarce regions. However, global seasonal forecasts are usually not directly applicable as they are provided at coarse spatial resolutions of at best 36 km and suffer from model biases and drifts. In this study, we therefore apply a bias-correction and spatial-disaggregation (BCSD) approach to seasonal precipitation, temperature and radiation forecasts of the latest long-range seasonal forecasting system SEAS5 of the European Centre for Medium-Range Weather Forecasts (ECMWF). As reference we use data from the ERA5-Land offline land surface rerun of the latest ECMWF reanalysis ERA5. Thereby, we correct for model biases and drifts and improve the spatial resolution from 36 km to 0.1∘. This is performed for example over four predominately semi-arid study domains across the world, which include the river basins of the Karun (Iran), the São Francisco River (Brazil), the Tekeze–Atbara river and Blue Nile (Sudan, Ethiopia and Eritrea), and the Catamayo–Chira river (Ecuador and Peru). Compared against ERA5-Land, the bias-corrected and spatially disaggregated forecasts have a higher spatial resolution and show reduced biases and better agreement of spatial patterns than the raw forecasts as well as remarkably reduced lead-dependent drift effects. But our analysis also shows that computing monthly averages from daily bias-corrected forecasts particularly during periods with strong temporal climate gradients or heteroscedasticity can lead to remaining biases especially in the lowest- and highest-lead forecasts. Our SEAS5 BCSD forecasts cover the whole (re-)forecast period from 1981 to 2019 and include bias-corrected and spatially disaggregated daily and monthly ensemble forecasts for precipitation, average, minimum, and maximum temperature as well as for shortwave radiation from the issue date to the next 215 d and 6 months, respectively. This sums up to more than 100 000 forecasted days for each of the 25 (until the year 2016) and 51 (from the year 2017) ensemble members and each of the five analyzed variables. The full repository is made freely available to the public via the World Data Centre for Climate at https://doi.org/10.26050/WDCC/SaWaM_D01_SEAS5_BCSD (Domain D01, Karun Basin (Iran), Lorenz et al., 2020b), https://doi.org/10.26050/WDCC/SaWaM_D02_SEAS5_BCSD (Domain D02: São Francisco Basin (Brazil), Lorenz et al., 2020c), https://doi.org/10.26050/WDCC/SaWaM_D03_SEAS5_BCSD (Domain D03: basins of the Tekeze–Atbara and Blue Nile (Ethiopia, Eritrea, Sudan), Lorenz et al., 2020d), and https://doi.org/10.26050/WDCC/SaWaM_D04_SEAS5_BCSD (Domain D04: Catamayo–Chira Basin (Ecuador, Peru), Lorenz et al., 2020a). It is currently the first publicly available daily high-resolution seasonal forecast product that covers multiple regions and variables for such a long period. It hence provides a unique test bed for evaluating the performance of seasonal forecasts over semi-arid regions and as driving data for hydrological, ecosystem or climate impact models. Therefore, our forecasts provide a crucial contribution for the disaster preparedness and, finally, climate proofing of the regional water management in climatically sensitive regions.

From global forecasts towards regional decision support: development of a full-fledged seasonal forecasting framework for semi-arid regions

2021 ◽  
Author(s):  
Christof Lorenz ◽  
Tanja Portele ◽  
Thomas Kukuk ◽  
Harald Kunstmann
Keyword(s):  
Water Management ◽  
Decision Support ◽  
Decision Support System ◽  
Spatial Resolution ◽  
Support System ◽  
Land Surface ◽  
Disaster Preparedness ◽  
Arid Regions ◽  
Seasonal Forecasts ◽  
Semi Arid

<p>Seasonal hydrometeorological forecasts have the potential to significantly improve the regional water management, disaster preparedness and climate proofing, particularly in water-scarce regions. They also allow for the development of forecast-based action plans for extreme climatic events like droughts and anomalous wet conditions. However, raw global products from data providers like the European Centre for Medium Range Weather Forecasts (ECMWF) cannot be directly used for regional applications due to model biases and drifts as well as a coarse spatial resolution of 35km and more. Furthermore, for transferring the information from ensemble-based forecasts into practice, we have to provide derived and tailormade forecast quantities for the water management in a user-friendly way. In this study, we hence present an operational post-processing and online decision support system with which we a) regionalize ECMWF’s latest seasonal forecast system SEAS5 through a Bias-Correction and Spatial Disaggregation (BCSD) technique, b) compute tailored forecast measures like categorical forecast and drought indicators and c) visualize this information through an online platform. As reference, we are using the offline re-run of ERA5’s land surface component, namely ERA5-Land. Our final forecast product comprises daily ensemble forecasts for precipitation, temperature, and radiation, has a spatial resolution of 0.1°, covers the whole period from 1981 to the present and is provided for several climate-sensitive river-basins including the Rio São Francisco (Brazil), the Blue Nile (Sudan / Ethiopia) and the Karun (Iran). Derived forecast quantities are operationally computed and visualized through an online decision support system, that was jointly developed with water experts from the different study regions. As both the forecast repository and the online decision support system are publicly available, they provide a comprehensive framework for demonstrating how seasonal forecasts can be post-processed and tailored for the day-to-day water management. They further allow for the training and education of local stakeholders and water experts how to deal with seasonal forecasts. Our forecasting system is already used by several authorities and weather services in Iran, Sudan and Brazil. It thereby constitutes a large step towards an improved disaster preparedness and, hence, the climate proofing of the water sector particularly in these semi-arid regions.</p>

Proactive Drought and Extreme Event Preparedness: Seasonal Climate Forecasts offer Benefit for Decision Making in Water Management in Semi-arid Regions

2020 ◽  
Author(s):  
Tanja Portele ◽  
Christof Lorenz ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Water Management ◽  
Arid Regions ◽  
Extreme Event ◽  
Seasonal Forecast ◽  
Seasonal Forecasts ◽  
Seasonal Climate ◽  
Early Action ◽  
Climate Forecasts ◽  
Semi Arid ◽  
Seasonal Climate Forecasts

<p>Semi-arid regions are the regions mostly affected by drought. In these climatically sensitive regions, the frequency and intensity of drought and hot extremes is projected to increase. With increasing precipitation variability in semi-arid regions, sustainable water management is required. Proactive drought and extreme event preparedness, as well as damage mitigation could be provided by the use of seasonal climate forecasts. However, their probabilistic nature, the lack of clear action derivations and institutional conservatism impedes their application in decision making of the water management sector. Using the latest global seasonal climate forecast product (SEAS5) at 35 km resolution and 7 months forecast horizon of the European Centre for Medium-Range Weather Forecasts, we show that seasonal-forecast-based actions offer potential economic benefit and allow for climate proofing in semi-arid regions in the case of drought and extreme events. Our analysis includes 7 semi-arid, in parts highly managed river basins with extents from tens of thousands to millions of square kilometers in Africa, Asia and South America. The value of the forecast-based action is derived from the skill measures of hit (worthy action) and false alarm (action in vain) rate and is related to economic expenses through ratios of associated costs and losses of an early action. For water management policies, forecast probability triggers for early action plans can be offered based on expense minimization and event maximization criteria. Our results show that even high lead times and long accumulation periods attain value for a range of users and cost-loss situations. For example, in the case of extreme wet conditions (monthly precipitation above 90<sup>th</sup> percentile), seasonal-forecast-based action in 5 out of 7 regions can still achieve more than 50 % of saved expenses of a perfect forecast at 6 months in advance. The utility of seasonal forecasts strongly depends on the user, the cost-loss situation, the region and the concrete application. In general, seasonal forecasts allow decision makers to save expenses, and to adapt to and mitigate damages of extreme events related to climate change.</p>

scholarly journals Survey of ancient water technologies in semi-arid and arid regions: traditional knowledge for the future

2017 ◽  
Vol 17 (5) ◽  
pp. 1278-1286 ◽  
Author(s):  
Larry W. Mays
Keyword(s):  
Water Resources ◽  
Traditional Knowledge ◽  
Arid Regions ◽  
Poor People ◽  
Water Shortages ◽  
The Poor ◽  
The World ◽  
Sustainability Problems ◽  
Semi Arid ◽  
Water Resources Sustainability

There are many people on Earth today that live with severe water shortages and severe lack of sanitation, particularly among the poor. These people for the most part do not understand the knowledge base of methodologies of harvesting and conveying water and sanitation methods that have been around for thousands of years. A survey of ancient water technologies used in semi-arid and arid regions is presented in this paper. The survey will include methodologies used by Mesopotamians, the Persians, the Egyptians, and the Nabataeans. The attempt here is to explore how these traditional methods developed by the ancients in semi-arid and arid regions of the world could possibly be used to help solve the present-day water resources sustainability problems, especially in developing parts of the world. The advantages of the traditional knowledge of ancient water technologies are explored with the goal of determining ways to help poor people with water shortages and sanitation.

scholarly journals Effects of model calibration on hydrological and water resources management simulations under climate change in a semi-arid watershed

2020 ◽  
Vol 163 (3) ◽  
pp. 1247-1266 ◽  
Author(s):  
Hagen Koch ◽  
Ana Lígia Chaves Silva ◽  
Stefan Liersch ◽  
José Roberto Gonçalves de Azevedo ◽  
Fred Fokko Hattermann
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Water Resources ◽  
Water Resources Management ◽  
Model Calibration ◽  
Arid Regions ◽  
Discharge Data ◽  
Resources Management ◽  
North Eastern ◽  
Semi Arid

AbstractSemi-arid regions are known for erratic precipitation patterns with significant effects on the hydrological cycle and water resources availability. High temporal and spatial variation in precipitation causes large variability in runoff over short durations. Due to low soil water storage capacity, base flow is often missing and rivers fall dry for long periods. Because of its climatic characteristics, the semi-arid north-eastern region of Brazil is prone to droughts. To counter these, reservoirs were built to ensure water supply during dry months. This paper describes problems and solutions when calibrating and validating the eco-hydrological model SWIM for semi-arid regions on the example of the Pajeú watershed in north-eastern Brazil. The model was calibrated to river discharge data before the year 1983, with no or little effects of water management, applying a simple and an enhanced approach. Uncertainties result mainly from the meteorological data and observed river discharges. After model calibration water management was included in the simulations. Observed and simulated reservoir volumes and river discharges are compared. The calibrated and validated models were used to simulate the impacts of climate change on hydrological processes and water resources management using data of two representative concentration pathways (RCP) and five earth system models (ESM). The differences in changes in natural and managed mean discharges are negligible (< 5%) under RCP8.5 but notable (> 5%) under RCP2.6 for the ESM ensemble mean. In semi-arid catchments, the enhanced approach should be preferred, because in addition to discharge, a second variable, here evapotranspiration, is considered for model validation.

scholarly journals Production System Diversification and Livelihood in the Drylands of North Central Mexico

2019 ◽  
Vol 11 (10) ◽  
pp. 2750
Author(s):  
Benjamín Figueroa-Sandoval ◽  
Martín A. Coronado-Minjarez ◽  
Eduviges J. García-Herrera ◽  
Artemio Ramírez-López ◽  
Dora M. Sangerman-Jarquín ◽  
...  
Keyword(s):  
Social Capital ◽  
Arid Regions ◽  
Production Systems ◽  
Farm Income ◽  
Central Mexico ◽  
North Central ◽  
Livelihood Security ◽  
The World ◽  
Semi Arid Region ◽  
Semi Arid

Drylands (arid and semi-arid regions) are important regions in the world; they have been disregarded and considered poor undeveloped regions due to their ecological limitations. Farmers in these regions tend towards diversification of production systems in order to achieve livelihood security, and this phenomenon has not been extensively studied. The objective of this study was to create a typology of the production systems present in the Mexican north central drylands, using variables related to production, socioeconomics, and social capital. 1044 interviews were conducted in the semi-arid region of north central Mexico. Analysis of the data allowed for the observation of nine types of production systems distributed in three groups: Subsistence, commercial, and off-farm income systems. The differences observed within these systems are due to generational gaps, gender differences, market orientation, and social capital. It can be concluded that the diversification of the dryland production systems allows for an understanding of why generic public policies have failed to mitigate poverty in these regions. The implications of the study refer to the reconfiguration of Mexican policies for the development of the drylands.

scholarly journals THE IMPORTANCE OF QUINOA (QUINOA CHENOPODIUM WILLD.) CULTIVATION IN DEVELOPING COUNTRIES: A REVIEW

2020 ◽  
Vol 53 (3) ◽  
pp. 337-356
Author(s):  
A. FATHI ◽  
F. KARDONI
Keyword(s):  
Food Security ◽  
Water Resources ◽  
Arid Regions ◽  
Environmental Changes ◽  
Limiting Factors ◽  
Soil Conditions ◽  
World Population ◽  
Cereal Grain ◽  
The World ◽  
Semi Arid

Quinoa is a dicotyledonous species for seeds and, therefore, is not known as a cereal grain and is a pseudograin, which is introduced nowadays as a new crop in the world. Population growth and the need for more food put additional pressure on the environment, especially on water resources and agronomic ecosystems. This has led to more attention to plants that grow at different latitudes and altitudes. Climatic and environmental changes affect agricultural inputs, especially water resources. So, the best way of adapting to the current situation is the introduction of low-water, salt resistant, and drought-tolerant plants to the recent climatic changes. Water scarcity has become a serious problem in many countries. This restriction has had a significant impact on the development of countries. The plants which grow in arid and semi-arid regions are often exposed to adverse environmental factors, such as drought or salinity. Salinity and drought stress, more than any other factor, decrease crop yields around the world. These two abiotic stresses are the main limiting factors for crop production, especially in arid and semi-arid regions of the world. Quinoa is an exceptional plant that can adapt to adverse conditions and can serve as a solution to the challenge of global food security. Recent droughts that occurred in the world have prompted governments to include plants in their development plans, which are adapted to the country's existing water and soil conditions and have high nutritional value. This way, quinoa cultivation can ensure their food security in the coming years.

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