Representation and participation in formulating Nepal’s REDD+ approach

ABSTRACT

REDD+ is an international policy aimed at incentivizing forest conservation and management and improving forest governance. In this article, we interrogate how newly articulated REDD+ governance processes established to guide the formulation of Nepal’s REDD+ approach address issues of participation for different social groups. Specifically, we analyse available forums of participation for different social groups, as well as the nature of their representation and degree of participation during the country’s REDD+ preparedness phase. We find that spaces for participation and decision-making in REDD+ have been to date defined and dominated by government actors and influential civil society groups, whereas the influence of other actors, particularly marginalized groups such as Dalits and women’s organizations, have remained limited. REDD+ has also resulted in a reduction of influence for some hitherto powerful actors (e.g. community forestry activists) and constrained their critical voice. These governance weaknesses related to misrepresentation and uneven power relations in Nepal cast doubt on the extent to which procedural justice has been promoted through REDD+ and imply that implementation may, as a consequence, lack the required social legitimacy and support. We discuss possible ways to address these shortcomings, such as granting greater prominence to neglected civil society forums within the REDD+ process, allowing for an increase in their influence on policy design, enhancing capacity and leadership of marginalized groups and institutionalizing participation through continued forest governance reform.

Key policy insights

• Participation is a critical asset in public policy design.

• Ensuring wide and meaningful participation can enhance policy legitimacy and thus its endorsement and potential effective implementation.

• Fostering inclusive processes through dedicated forums such as multi-stakeholder groups can help overcome power dynamics.

• While REDD+ is open to participation by different actors through a variety of formal means, many countries lack a clear framework for participation in national policy processes.

• Nepal’s experience with representation and participation of non-state actors in its REDD+ preparedness programme provides useful insights for similar social and policy contexts.

     

A physical interpretation of the deterministic fractal–multifractal method as a realization of a generalized multiplicative cascade

In this study, we attempt to offer a solid physical basis for the deterministic fractal–multifractal (FM) approach in geophysics (Puente, Phys Let A 161:441–447, 1992; J Hydrol 187:65–80, 1996). We show how the geometric construction of derived measures, as Platonic projections of fractal interpolating functions transforming multinomial multifractal measures, naturally defines a non-trivial cascade process that may be interpreted as a particular realization of a random multiplicative cascade. In such a light, we argue that the FM approach is as “physical” as any other phenomenological approach based on Richardson’s eddies splitting, which indeed lead to well-accepted models of the intermittencies of nature, as it happens, for instance, when rainfall is interpreted as a quasi-passive tracer in a turbulent flow. Although neither a fractal interpolating function nor the specific multipliers of a random multiplicative cascade can be measured physically, we show how a fractal transformation “cuts through” plausible scenarios to produce a suitable realization that reflects specific arrangements of energies (masses) as seen in nature. This explains why the FM approach properly captures the spectrum of singularities and other statistical features of given data sets. As the FM approach faithfully encodes data sets with compression ratios typically exceeding 100:1, such a property further enhances its “physical simplicity.” We also provide a connection between the FM approach and advection–diffusion processes.     

Sediment related impacts of climate change and reservoir development in the Lower Mekong River Basin: a case study of the Nam Ou Basin,Lao PDR

This study applies the soil and water assessment tool (SWAT), with climate (precipitation and temperature) outputs from four general circulation models (GCMs) and a regional circulation model (PRECIS), to evaluate (1) the impacts of climate change on reservoir sedimentation and (2) the impacts of climate change and reservoir development on sediment outflow in the Nam Ou River Basin located in northern Laos. Three reservoir–density scenarios, namely one reservoir (1R), three reservoirs in series (3R), and five reservoirs in series (5R), were evaluated for both no climate change and climate change conditions. The results show that under no climate change conditions, by 2070, around 17, 14, and 15% of the existing reservoir storage volume in the basin will be lost for 1R, 3R, and 5R scenarios, respectively. Notably, under climate change scenario with highest changes in erosion and sediment outflux from the basin, the additional reduction in reservoir storage capacity due to sedimentation is estimated to be nearly 26% for 1R, 21% for 3R, and 23% for 5R. Climate change alone is projected to change annual sediment outflux from the basin by ?20 to 151%. In contrast, the development of reservoirs in the basin will reduce the annual sediment outflux from the basin varying from 44 to 80% for 1R, 44–81% for 3R, and 66–89% for 5R, considering climate change. In conclusion, climate change is expected to increase the sediment yield of the Nam Ou Basin, resulting in faster reduction of the reservoir’s storage capacity. Sediment yield from the Nam Ou River Basin is likely to decrease significantly due to the trapping of sediment by planned reservoirs. The impact of reservoirs is much more significant than the impact of climate change on the sediment outflow of the basin. Hence, it is necessary to investigate appropriate reservoir sediment management strategies.     

Talkoot: software tool to create collaboratories for earth science

“Open science,” where researchers share and publish every element of their research process in addition to the final results, can foster novel ways of collaboration among researchers and has the potential to spontaneously create new virtual research collaborations. Based on scientific interest, these new virtual research collaborations can cut across traditional boundaries such as institutions and organizations. Advances in technology allow for software tools that can be used by different research groups and institutions to build and support virtual collaborations and infuse open science. This paper describes Talkoot, a software toolkit designed and developed by the authors to provide Earth Science researchers a ready-to-use knowledge management environment and an online platform for collaboration. Talkoot allows Earth Science researchers a means to systematically gather, tag and share their data, analysis workflows and research notes. These Talkoot features are designed to foster rapid knowledge sharing within a virtual community. Talkoot can be utilized by small to medium sized groups and research centers, as well as large enterprises such a national laboratories and federal agencies.     

Downscaling daily precipitation over the Yellow River source region in China: a comparison of three statistical downscaling methods

Three statistical downscaling methods are compared with regard to their ability to downscale summer (June–September) daily precipitation at a network of 14 stations over the Yellow River source region from the NCEP/NCAR reanalysis data with the aim of constructing high-resolution regional precipitation scenarios for impact studies. The methods used are the Statistical Downscaling Model (SDSM), the Generalized LInear Model for daily CLIMate (GLIMCLIM), and the non-homogeneous Hidden Markov Model (NHMM). The methods are compared in terms of several statistics including spatial dependence, wet- and dry spell length distributions and inter-annual variability. In comparison with other two models, NHMM shows better performance in reproducing the spatial correlation structure, inter-annual variability and magnitude of the observed precipitation. However, it shows difficulty in reproducing observed wet- and dry spell length distributions at some stations. SDSM and GLIMCLIM showed better performance in reproducing the temporal dependence than NHMM. These models are also applied to derive future scenarios for six precipitation indices for the period 2046–2065 using the predictors from two global climate models (GCMs; CGCM3 and ECHAM5) under the IPCC SRES A2, A1B and B1scenarios. There is a strong consensus among two GCMs, three downscaling methods and three emission scenarios in the precipitation change signal. Under the future climate scenarios considered, all parts of the study region would experience increases in rainfall totals and extremes that are statistically significant at most stations. The magnitude of the projected changes is more intense for the SDSM than for other two models, which indicates that climate projection based on results from only one downscaling method should be interpreted with caution. The increase in the magnitude of rainfall totals and extremes is also accompanied by an increase in their inter-annual variability.     

Deterministic simulation of highly intermittent hydrologic time series

Application of a deterministic geometric approach for the simulation of highly intermittent hydrologic data is presented. Specifically, adaptations of the fractal-multifractal (FM) method and a Cantorian extension are advanced in order to simulate rainfall records measured at the daily scale and encompassing a water year. It is shown, using as case studies 2 years of rainfall sets gathered in Laikakota, Bolivia and Tinkham, Washington, USA, that the FM approach, relying on only at most 8 parameters, is capable of closely preserving either the whole record’s histogram (therefore including moments), the whole data’s Rényi entropy function and/or the maximum number of consecutive zero values present in the sets, resulting in suitable rainfall simulations, whose overall features and textures are similar to those of the observed sets. The study hence establishes the possibility of simulating highly intermittent sets in time in a deterministic and holistic way as a novel parsimonious methodology to supplement available stochastic frameworks.     

Streamflow trends and climate linkages in the Zagros Mountains,Iran

This paper examines trends in streamflow and their links with local climate in the Karkheh River and its major tributaries, which originate from the Zagros Mountains, Iran. Streamflow records from five mainstream stations for the period 1961–2001 were used to examine trends in a number of streamflow variables. The studied variables were mean annual and monthly flows, 1 and 7 days maximum and minimum flows, timing of the 1-day maxima and minima, and the number and duration of high and low flow pulses. Similarly, the precipitation and temperature data from seven climate stations for the period from 1950s to 2003 were used to examine trends in climatic variables and their correlation with the streamflow. The Spearman Rank test was used for the detection of trends and the correlation analysis was based on the Pearson method. The results reveal a number of significant trends in streamflow variables both increasing (e.g. December flows) and decreasing (e.g. May flows) for all stations. However, some trends were not spatially uniform. For example, decline in low flow characteristics were more significant in the upper parts of the basin, whereas increasing trends in floods and winter flows were noteworthy in the middle parts of the basin. Most of these trends could be attributed to precipitation changes. The results show that the decline in April and May precipitation causes the decline in the low flows while the increase in winter (particularly March) precipitation coupled with temperature changes lead to increase in the flood regime. The observed trends at the Jelogir station on the Karkheh River reflect the combined effect of the upstream catchments. The significant trends observed in a number of streamflow variables at Jelogir, 1-day maximum, December flow and low pulse count and duration, point to the changes in hydrological regime of the entire Karkheh River system and are attributed to the changes in climatic variables.     

Instance‐based learning compared to other data‐driven methods in hydrological forecasting

Data‐driven techniques based on machine learning algorithms are becoming popular in hydrological modelling, in particular for forecasting. Artificial neural networks (ANNs) are often the first choice. The so‐called instance‐based learning (IBL) has received relatively little attention, and the present paper explores the applicability of these methods in the field of hydrological forecasting. Their performance is compared with that of ANNs, M5 model trees and conceptual hydrological models. Four short‐term flow forecasting problems were solved for two catchments. Results showed that the IBL methods often produce better results than ANNs and M5 model trees, especially if used with the Gaussian kernel function. The study showed that IBL is an effective data‐driven method that can be successfully used in hydrological forecasting. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessment of drought hazard,exposure, vulnerability,and risk for rice cultivation in the Mun River Basin in Thailand

Natural Hazards - When assessing drought risk, most studies focus on hazard and vulnerability, paying less attention to exposure. Here, we propose a comprehensive drought risk assessment scheme...     

Trends in temperature and rainfall extremes in the Yellow River source region, China

Spatial and temporal changes in daily temperature and rainfall indices are analyzed for the source region of Yellow River. Three periods are examined: 1960–1990, 1960–2000 and 1960–2006. Significant warming trends have been observed for the whole study region over all the three periods, particularly over the period 1960–2006. This warming is mainly attributed to a significant increase in the minimum temperature, and characterized by pronounced changes in the low temperature events composing a significant increase in the magnitude and a significant decrease in the frequency. In contrast to the temperature indices, no significant changes have been observed in the rainfall indices at the majority of stations. However, the rainfall shows noticeable increasing trends during winter and spring from a basin-wide point of view. Conversely, the frequency and contribution of moderately heavy rainfall events to total rainfall show a significant decreasing trend in summer. To conclude, this study shows that over the past 40–45 years the source region of the Yellow River has become warmer and experienced some seasonally varying changes in rainfall, which also supports an emerging global picture of warming and the prevailing positive trends in winter rainfall extremes over the mid-latitudinal land areas of the Northern Hemisphere.