کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5744419 1618222 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The value and skill of seasonal forecasts for water resources management in the Upper Santa Cruz River basin, southern Arizona
ترجمه فارسی عنوان
ارزش و مهارت پیش بینی های فصلی برای مدیریت منابع آب در حوضه رودخانه سانتا کروز، جنوب آریزونا
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Seasonal forecasts can benefit water resources management and southern Arizona.
- Only extreme ENSO conditions have forecasting skill for winter and summer rainfall.
- CFS forecast skill extends up to four months lead-time during the winter.
- CFS forecast skill of summer rain was found only for July.
- Adaptive management requires considerations of large uncertainties in the forecasts.

The potential for adaptive water resources management based on seasonal forecasts in the arid Upper Santa Cruz River, southern Arizona was examined. We demonstrated that seasonal forecasts can be used to optimize water resources management and increase supply. Using El Nino Southern Oscillation (ENSO) to forecast the wet seasons (winter and summer) can provide information during extreme ENSO. We found that ENSO is a better indicator for dryer than normal winters during La Nina and dryer than normal summers during El Nino. As in indicator of wetter than normal seasons (i.e. El Nino and La Nina in the winter and summer, respectively) ENSO is often not a consistent predictor and moreover, on several occasions the wetter than normal rainfall did not yield above normal seasonal flows. We also examined the seasonal precipitation forecasts for the region from the Climate Forecast System (CFS). The CFS showed reasonable predictive skill for the winter that extends up to four months lead-time. The only CFS skill for forecasting summer rainfall was observed for predicting above normal rainfall in July with one-month lead-time. Seasonal forecasts can substantially improve water resources management but currently requires considerations of large uncertainties in the operationally available forecasts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Arid Environments - Volume 137, February 2017, Pages 35-45
نویسندگان
,