Integrating climate models to confront the illusion of certainty in water planning: evidence from Morocco

The uncertainties associated with global climate models pose substantial hurdles for urban water planning. Despite growing consensus among climatologists that the American Southwest is headed for a warmer and drier future, water planners in metropolitan Phoenix and elsewhere are reluctant to consider long-term climate change as a significant factor in increased risk of future water scarcity. A new paradigm for climate research and water planning is needed—one that is based on an assumption of uncertainty and a vision of multiple plausible futures, managing risk, and adaptive behaviors. To this end, we downscaled global climate models from the Intergovernmental Panel on Climate Change Third and Fourth Assessment Reports for the watersheds north of Phoenix and estimated changes in runoff using a hydrological model. Results then were used as inputs to WaterSim, an integrated simulation model of water supply and demand in Phoenix. The model simulated “what if” scenarios under varying policy decisions and future climates. Results of simulation experiments suggest that (1) current levels of per capita water consumption cannot be supported without unsustainable groundwater use under most climate model scenarios, (2) feasible reductions in residential water consumption allow the region to weather the most pessimistic of the climate projections, (3) delaying action reduces long-term sustainability of the groundwater resource under some climate scenarios, and (4) adaptive policy with appropriate monitoring to track groundwater provides warning that the need for use restrictions is approaching and avoids the need for drastic, ad hoc actions.

North American water systems are inadequately prepared to deal with an uncertain future climate and other uncertainties relevant to long-term sustainability. Despite Milly et al.’s (2008) dramatic proclamation in the February 2008 issue of Science that stationarity—the idea that natural systems function within a known envelope of variability—is dead, the water resources community has been slow to embrace new paradigms for long-term water planning and policy. Too much attention has been focused on reducing, clarifying, and representing climatic uncertainty and too little attention has been directed to building capacity to accommodate uncertainty and change. Given the limited ability to forecast the future climate, emphasis must shift to the human actors and social dynamics of water systems, including planning processes, work practices, operational rules, public attitudes, and stakeholder engagement. Many in the water management community have been led to believe that climate adaptation is primarily a science problem—that we need to wait for the results of new rounds of climate modeling and downscaling to reduce uncertainties about future climate conditions. Trenberth (2010), however, has noted that, as our knowledge of the climate system increases, so also has our understanding of factors we previously did not account for or even recognize, such as the release of greenhouse gases from melting permafrost, the fertilizing effect of atmospheric carbon dioxide on vegetation, and the effects of aerosols on clouds. As climate models begin to incorporate these processes, they will inevitably disagree about the nature, extent, and geographic patterns of climate-change impacts. Decision makers will be confronted with more, not less, uncertainty about the future climate. This uncertainty is problematic for an industry that has traditionally relied on predict-andplan methods of operations and management. Water planning usually involves forecasting future trends or desired states and then identifying the infrastructure needed to support them. Optimization models, the favored tools of water planners worldwide, seek the most efficient Water Resour Manage (2013) 27:955–957 DOI 10.1007/s11269-012-0222-y

Long‐range water planning is complicated by factors that are rapidly changing in the 21st century, including climate, population, and water use. Here, we analyze climate factors and drought projections for Texas as an example of a diverse society straddling an aridity gradient to examine how the projections can best serve water stakeholder needs. We find that climate models are robust in projecting drying of summer‐season soil moisture and decreasing reservoir supplies for both the eastern and western portions of Texas during the 21st century. Further, projections indicate drier conditions during the latter half of the 21st century than even the most arid centuries of the last 1,000 years that included megadroughts. To illustrate how accounting for drought nonstationarity may increase water resiliency, we consider generalized case studies involving four key stakeholder groups: agricultural producers, large surface water suppliers, small groundwater management districts, and regional water planning districts. We also examine an example of customized climate information being used as input to long‐range water planning. We find that while stakeholders value the quantitative capability of climate model outputs, more specific climate‐related information better supports resilience planning across multiple stakeholder groups. New suites of tools could provide necessary capacity for both short‐ and long‐term, stakeholder‐specific adaptive planning.

.Numerous climate change studies have recently, and are currently, being carried out across many regions of the world. However, is there sufficient confidence in the outputs of global climate models (GCMs) to make use of their projections at a regional scale; and secondly, if these results are to be used, how can researchers make the data directly usable by water managers? This paper shows results from a water availability study recently carried out across south-eastern Australia, and demonstrates how the results of this study were used by water resource managers in the State of Victoria in far southern south-east Australia. Across Victoria, there is a near unanimous agreement among climate model outputs of the direction of change of future rainfall, with 14 of the 15 AR4 GCMs examined projecting a reduction in rainfall across this region. Additionally, as these reductions in rainfall are quite high over the major runoff-generating areas, reductions in runoff (and therefore water availability) are also projected across the vast majority of the State. Climate change projections for this region were summarised by creating ‘dry’, ‘wet’ and ‘median’ future water availability scenarios for 2030 and 2060 based on results from the 2 nd driest, 2 nd wettest and 8 th wettest (or driest) GCM. These results were then averaged across 27 catchments covering the State of Victoria so that they could easily be used by urban and rural water corporations in their future water planning. Of the 27 catchments covering Victoria, reductions in annual water availability (relative to the long term historical average) are projected for all 27 under both the ‘dry’ and ‘median’ future climate scenario for both 2030 and 2060. For the dry future scenario for 2030, projected reductions in water availability range from 18% to 34%, while for 2060, the reductions range from 34% to 58%. For the median future climate scenario, for 2030, reductions in water availability range from 8% to 22%, and 9% to 36% in 2060. Under the ‘wet’ future climate scenario, only 5 catchments project an increase in water availability for 2030 and 2060. These catchments are located in the far north and east of the State. The remaining 22 catchments project reductions in water availability of up to 11% by 2030 and 19% by 2060. These results have been used in defining a range of plausible water availability futures which Victorian water corporations are using in preparing updated Water Supply-Demand Strategies for all the supply systems that they manage. These strategies aim to balance supply and demand over the next 50 years. The reductions in water availability projected under the dry climate change scenario by 2060 are smaller than the reductions in water availability experienced during the recent drought (1997-2009) across much of the State. As climate research has shown that this drought appears to be at least partly linked to global warming, a future scenario based on a return to the dry conditions of the recent drought (1997-2009) in the short-term has also been included in the planning process. In those regions where there is near-unanimous agreement among GCMs as to the direction of climate change impacts on rainfall, projected changes in water availability can be used by water resource planners to assist them in better planning for future changes in supply. Even then however, climate researchers and hydrologists must work closely with water managers to ensure that the information is provided in a usable way.

New projections of 21st century climate and hydrology for Alaska and Hawaiʻi

수자원의 수요 증가와 ENSO (El Ni<TEX>$\tilde{n}$</TEX>o/La Ni<TEX>$\tilde{n}$</TEX>a Southern Oscillation) 등의 기후변화 현상으로 인한 수자원 공급의 불안정 요소가 제기됨에 따라, 수자원 관리 계획 수립 시 장/단기강우 모의의 중요성이 강조되고 있다. 본 연구에서는 미국 플로리다 템파 지역의 두 개 유역을 대상으로 1986년부터 2008년까지의 MM5 지역기후모델을 이용한 강우모의 결과를 시험지역의 33개 관측자료와 CDF-mapping 기법을 이용하여 통계적으로 보정하였으며 그 결과를 바탕으로 ENSO 패턴에 따른 모델의 성능을 평가하였다. 보정된 MM5일 강우 모의결과는 대체적으로 각 관측소의 월 평균 강우량 (ME: 1.0mm)을 잘 모의하는 것으로 나타났다. 블락-크리깅 기법을 이용하여 추정된 유역 평균 일/월 강우량 또한 관측치를 잘 재현하였다(일 강우 ME: 0.8mm, 월 강우 ME: 7.1mm). 한편, ONI (Oceanic Ni<TEX>$\tilde{n}$</TEX>o index)를 이용하여 구분한 ENSO 패턴에 따른 강우 모의치를 분석한 결과, 월별 엘리뇨/라니냐 해에 대한 유역 단위의 강우량 모의 성능이 상이한 것으로 나타났다. 이 원인으로 한정된 모수화 적용 및 모델 경계자료 오차 등을 제시하고 이에 대한 보정 방법개선 등의 추가 연구의 필요성을 지적하였다. 본 연구는 ENSO 패턴을 고려한 월별 기후모델 결과를 활용함에 있어 유의점을 제시하였기에, 우기와 건기에 대한 수자원 관리를 위한 적용 등에 유용하게 활용될 것으로 기대된다. As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni<TEX>$\tilde{n}$</TEX>o and La Ni<TEX>$\tilde{n}$</TEX>a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

Climate change impact assessment is crucial for strategic planning in many areas, including water management, agriculture and forestry. Water planning has a long tradition in the Czech Republic, who has implemented the requirements of the Water Framework Directive since 2000. Following the expected impacts of climate change on the hydrological regime, adaptation measures in the water sector are being prepared as part of strategic plans. This contribution studies the uncertainty propagation of climate scenarios in hydrological data, which are then used to assess the reliability of water resources and to design appropriate adaptation measures. The results are being discussed for a case study in the deficit area of Rakovnický stream and Blšanska river basins, which are among the driest areas in the Czech Republic. Research of the impact of climate change on the reliability of water resources has been prepared using ensembles of selected regional climate models. This approach has allowed a probabilistic assessment of the impact on the hydrology regime and the reliability of water supply from reservoirs for various time horizons of climate change. In view of the relatively large variance of potential impacts on water resources, options for further strategic planning in the water management area are being discussed.

Statistical precipitation downscaling for small-scale hydrological impact investigations of climate change

The snowpack is a critical component of the hydrologic cycle in cold regions, the change in which becomes important for proper planning and management of water. The Tibetan Plateau provides significant amount of water to most Asian rivers, and consequently the downstream population is dependent on its availability. Despite its importance, potential change in snowpack in this region due to climate change is poorly understood to date, largely because of remoteness and the orographic complexity of the area. This study inspects the impact of climate change on snowpack change over the Tibetan Plateau considering historical simulations (1981–2004), near future projections (2041–2064), and far future projections (2071–2094) from global climate models (GCMs) and regional climate models (RCMs) of derived temperature, precipitation, and snow water equivalent (SWE). A multivariate nesting bias correction approach (MRNBC) was employed to correct possible biases in GCM and RCM derived temperature, precipitation, and SWE jointly over multiple time scales to preserve interdependencies among the variables while enabling simulation of year‐to‐year persistence, which is of importance in water security assessments. MRNBC reduced the bias in model simulations significantly and improved projections of the snow climatology. The results indicate that the annual maximum spell of snow‐free days will increase over the region whereas the snowy day fraction will decrease in the future compared to the historical period. In addition, annual SWE are noted to be decreasing in both the near future and far future with respect to historical averages. Changes in SWE will result from warming temperatures and also from changes in precipitation, which will lead to more rainfall than snowfall thus affecting snowmelt processes.

Climate change can alter the spatial and temporal distribution of aridity around the world through a combination of factors such as reduced precipitation, rising temperatures and decreased evapotranspiration. Especially the Mediterranean region has been identified as vulnerable to anthropogenic climate change due to a significant reduction in precipitation compared to other land regions in all climate models operated under different scenarios. Despite numerous studies on aridity trends, few have focused specifically on Türkiye and considered a comprehensive range of aridity indices and scenarios. This study aims to fill this research gap by providing a more detailed understanding of future aridity trends in Türkiye under various climate change scenarios and using multiple aridity indices. A novelty of this study lies in the simultaneous examination of three aridity indices (PCI, EAI and UNEP AI) for Türkiye, allowing for a more comprehensive assessment of future aridity trends. Furthermore, this study considers three future time periods (2011–2040, 2041–2070 and 2071–2100) and three shared socioeconomic pathways (SSPs) to evaluate the potential range of climate change impacts on aridity in Türkiye. Therefore, in this study, we aimed to determine the changes in aridity conditions in Türkiye until the end of the 21st century. We used three aridity indices: the Pinna combinative index, the Erinç aridity index and the UNEP aridity index. These indices were calculated for the baseline period of 1981–2010 using gridded data (CHELSA) and for the periods of 2011–2040, 2041–2070 and 2071–2100 using three climate models (GFDL‐ESM4, MRI‐ESM2‐0 and IPSL‐CM6A‐LR) and multi‐model means with three SSPs to represent different future scenarios. The results showed that all three indices indicate an increase in dry climate conditions in Türkiye after 2041, with particularly notable increases expected in Central Anatolia, Southeastern Anatolia and parts of the Eastern Mediterranean, as well as eastern parts of Eastern Anatolia and the inner Aegean region. Under the SSP3‐7.0 scenario, the expansion of semi‐arid and arid areas is predicted to cover more than 30% of the country by the end of the century (2071–2100). This increase in aridity could increase the region's vulnerability to climate change and the risk of desertification, which should be taken into consideration in national water management and planning.

This study introduces a new global climate model—the Integrated Climate Model (ICM)—developed for the seasonal prediction of East Asian-western North Pacific (EA-WNP) climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics (CMSR, IAP), Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of El Nino as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature (SST) and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate—El Nino and the East Asia-Pacific Pattern—are also well simulated in ICM, with realistic spatial pattern and period. The simulated El Nino has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.

Hydrologic response to climate change in the Densu River Basin in Ghana

The decrease in freshwater input to the coastal system of the Southern Andes (40–45°S) during the last decades has altered the physicochemical characteristics of the coastal water column, causing significant environmental, social and economic consequences. Considering these impacts, the objectives were to analyze historical severe droughts and their climate drivers, and to evaluate the hydrological impacts of climate change in the intermediate future (2040–2070). Hydrological modelling was performed in the Puelo River basin (41°S) using the Water Evaluation and Planning (WEAP) model. The hydrological response and its uncertainty were compared using different combinations of CMIP projects (n = 2), climate models (n = 5), scenarios (n = 3) and univariate statistical downscaling methods (n = 3). The 90 scenarios projected increases in the duration, hydrological deficit and frequency of severe droughts of varying duration (1 to 6 months). The three downscaling methodologies converged to similar results, with no significant differences between them. In contrast, the hydroclimatic projections obtained with the CMIP6 and CMIP5 models found significant climatic (greater trends in summer and autumn) and hydrological (longer droughts) differences. It is recommended that future climate impact assessments adapt the new simulations as more CMIP6 models become available.

The upper Bandama basin at Badikaha in the North of Côte d'Ivoire, subject to climate change, has recorded a rapid population growth that significantly affects water availability. This study applies the water evaluation and planning (WEAP) system model to explore how the water resources available currently can meet people's needs in the future, mainly for irrigation, mining activities, rural and urban water supply and cattle breeding. The outputs from two regional climate models RACMO 22T and CCLM 4-8-17 under representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios were used for the climate change impact assessment. Results predict an increase in mean annual temperature by 1.5°C while precipitation could decrease by 21% by 2090. The climate model outputs coupled with the WEAP model show that unmet water demand estimated to 50 million m3 in 2020 could reach 115 million m3 in 2050. Nevertheless, climate change mitigation scenarios by the WEAP model, including the implementation of dams, boreholes and the hydraulics infrastructure improvement reveal that water scarcity could be reduced significantly in the catchment.

Büyük Menderes Basin is one of the largest basins in Turkey, with almost half of the basin area utilized for agricultural purposes. The amount of water allocated to the agricultural areas in the basin corresponds to 80% of water use in the watershed. Hence, the impact of climate change on the water supply in the Büyük Menderes Basin will be significant for the basin. In this study, we model the effects of climate change on the water budget (water supply and demand balance) of the Büyük Menderes Basin using the Water and Evaluation and Planning (WEAP) tool. Future precipitation, temperature, and evaporation data for the basin are attained from outputs of the HadGEM2-ES global circulation model (GCM), along with CNRM-CM5.1 and GFDL-ESM2M regional circulation models (RCM) for RCP 4.5 and RCP 8.5 scenarios. Subsequently, the study applies different statistical bias correction methods (Linear Scaling (LS), Distribution Mapping (DM), Local Precipitation Scaling (PLIS), and Power Transformation of Precipitation (PTP) for raw outputs of GCMs and RCMs and analyzes the changes in outcomes of projected climate data and the impact of changes on the hydrology of the basin using the WEAP model. For this analysis, calibrated and validated WEAP model for the 12 reservoirs of Büyük Menderes Basin is used to understand the impact of different bias correction methods on reservoir levels.