Water Management in Arid and Semi-Arid Regions

2006 ◽  
Author(s):  
Phoebe Koundouri ◽  
Paul Jeffrey ◽  
Manfred Lange ◽  
Katia Karousakis ◽  
Dionysis Assimacopoulos
Keyword(s):  
Water Management ◽  
Arid Regions ◽  
Semi Arid

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 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.

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

&lt;p&gt;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&lt;sup&gt;th&lt;/sup&gt; 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.&lt;/p&gt;

scholarly journals Water Management Using System Dynamics Modeling in Semi-arid Regions

2017 ◽  
Vol 3 (9) ◽  
pp. 766-778 ◽  
Author(s):  
Hamid Reza Nassery ◽  
Rouhollah Adinehvand ◽  
Abdalrahim Salavitabar ◽  
Reza Barati
Keyword(s):  
Water Management ◽  
System Dynamics ◽  
Arid Regions ◽  
System Dynamics Modeling ◽  
Dynamics Modeling ◽  
Semi Arid

Thermal and water management in irrigating lands in the arid and semi-arid regions

2003 ◽  
Vol 23 (7) ◽  
pp. 807-820 ◽  
Author(s):  
Ayoub M. Kazim
Keyword(s):  
Water Management ◽  
Arid Regions ◽  
Semi Arid

scholarly journals PRIORITIZATION OF SUSTAINABLE WATER MANAGEMENT STRATEGIES IN ARID AND SEMI-ARID REGIONS USING SWOT COUPLED AHP TECHNIQUE IN ADDRESSING SDGs

2020 ◽  
Vol 19 (2) ◽  
pp. 35-52
Author(s):  
Mohammad Banihabib ◽  
◽  
Arash Noori ◽  
Luboš Jurík ◽  
Igor Gacko ◽  
...  
Keyword(s):  
Water Management ◽  
Arid Regions ◽  
Management Strategies ◽  
Sustainable Water Management ◽  
Semi Arid

scholarly journals Uso de FAO-56 y cintilómetro para estimar la evapotranspiración de sorgo (Sorghum bicolor L.) y sus componentes: evaporación del suelo y transpiración de la planta

2019 ◽  
Vol 37 (2) ◽  
pp. 141
Author(s):  
Jesus Enrique Lopez Avendaño ◽  
Julio César Rodríguez ◽  
José Ángel Martínez Gallardo ◽  
Ramón Lizárraga Jiménez ◽  
Tomás Díaz Valdés
Keyword(s):  
Water Management ◽  
Root Mean Square Error ◽  
Arid Regions ◽  
Management Strategies ◽  
Mean Square ◽  
Water Planning ◽  
Daily Evapotranspiration ◽  
Agricultural Areas ◽  
Sorghum Bicolor L ◽  
Semi Arid

Estimating evapotranspiration (ETc) is essential for water planning and management in agricultural areas, particularly in arid and semi-arid regions; ETc partitioning into soil evaporation (E) and plant transpiration (T) would allow the use of more eff icient water management strategies. The aims of the present study were to estimate daily evapotranspiration of sorghum and its components, using the FAO-56 method with the dual crop coeff icient (dual Kc) approach and scintillometer method, and to determine the single crop coeff icient (Kc) and basal crop coeff icient (Kcb) values for different development seasons. Results have shown that using the dual Kc approach allows reasonable simulation of ETc in comparison to values estimated using the scintillometer method. ETc estimated with both methods was 413.8 and 406.3 mm, respectively, resulting in a 1.8% overestimation for FAO-56. Root mean square error (RMSE) was 0.584 mm d-1 and Willmott’s agreement coeff icient (d) was 0.91. Evaporation estimated with FAO-56 was 17.1% of ETc, while with the scintillometer it was 21.6% of ETc. The RMSE of the estimated E values was 0.397 mm d-1 and d = 0.94, while, when comparing T, calculated RMSE was 0.371 mm d-1 and d = 0.98. Kc values estimated with the FAO-56 method were 0.68, 1.06 and 0.4 for initial, middle and end season of the crop, while for the scintillometer, values were 0.75, 0.94 and 0.41, respectively.

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